The use of analytical techniques is important and critical in all areas of REE research such as exploration, mining, extraction, and metallurgical activities at different stages. At every stage of these activities, rock, ore, mineral, and other related materials have to be analysed for their REE contents in terms of elemental, isotopic, and mineralogical concentrations using different analytical techniques. Spectacular developments have taken place in the area of analytical instrumentations during the last four decades, with some of them having shrunk in size and become hand-held. Among laboratory-based techniques, F-AAS, GF-AAS, ICP-OES, and MP-AES have become very popular. Because of high sensitivity, less interference effects, and ease of use. ICP-MS techniques such as quadrupole-ICP-MS, ICP-MS/MS, ICP-TOF-MS, MH-ICP-MS, HR-ICP-MS, and MC-ICP-MS, with both solution nebulisation as well as direct solid analysis using laser ablation sample introduction methods, have become extremely popular for REE analysis. For direct analysis of solids INAA, XRF, and LIBS techniques besides LA-based ICP-MS techniques are being extensively utilised. LIBS technique in particular requires little to no sample preparation. TIMS, SIMS, and SHRIMP techniques are being used for isotopic as well as dating REE depots. Portable analytical techniques such as pXRF, pLIBS, and Raman spectrometers are able to do in situ analysis even in the field helping to take fast decisions during exploration studies. At present hyperspectral remote sensing techniques including hand-held, drone, and satellite-based techniques have become very popular in REE exploration studies because of their ability to cover larger areas in a limited time and thus became very cost-effective. Deployment of microanalytical devices/sensors mounted in remotely operated vehicles (ROV) is being successfully utilized in detecting REE-rich deposits in the deep oceans. Providing updated in-depth information on all these important aspects with suitable examples, especially from the point of view of REE research studies is the focal point of this review article.

This paper presents a combined optical imaging/artificial intelligence (OI/AI) technique for real-time analysis of tissue morphology at the tip of the biopsy needle, prior collecting a biopsy specimen. This is an important clinical problem as up to 40% of the collected biopsy cores provide low diagnostic value due to high adipose or necrotic content. Micron-scale resolution optical coherence tomography (OCT) images can be collected with a minimally invasive needle probe and automatically analyzed by a computer neural network (CNN)-based AI software. The results can be conveyed to the clinician in real-time and used to select the biopsy location more adequately. This technology was evaluated on a rabbit model of cancer. OCT images were collected with a hand-held custom-made OCT probe. Annotated OCT images were used as ground truth for AI algorithm training. The overall performance of the AI model was very close to that of the humans performing the same classification tasks. Specifically, tissue segmentation was excellent (~99% accuracy) and provided segmentation that closely mimicked ground truth provided by the human annotations, while over 83% correlation accuracy was obtained for tumor and non-tumor classification.

(1) Background: Artificial intelligence (AI) has existed in some form for decades, but recent rapid advances in a subset called machine learning (ML) — and more specifically deep learning (DL), a neural network-based approach — have made headlines for the potential to revolutionize and automate multiple large sectors of society, including scientific research and the healthcare field. Furthermore, large language models (LLMs) — which are built on DL — could lead to a more seamless, natural interaction between humans and computers. (2) Methods: We reviewed numerous publications on this subject from recent years. (3) Results: We found these studies collectively show that AI is positively disrupting both biomedical research and medical practice, such as optical imaging in surgery guidance. (4) Conclusions: However, we recommend caution in over-reliance on AI in the laboratory or the clinic due to anticipated risks and current limitations.

Classifying spinal tumors can be challenging due to nonspecific clinical and radiological qualities, and a precise biopsy is crucial for an accurate diagnosis and treatment planning. This study aimed to enhance the accuracy and efficiency of spinal biopsies integrating Cone Beam Computed Tomography (CBCT) and magnetic resonance imaging (MRI) modalities using an O-arm CT navigation system. Eighteen patients with diverse spinal lesions underwent 18 biopsies following the Stealth Station navigation system Spine 8 protocol. Preoperative MRI scans were merged with intraoperative CT navigation systems for continuous monitoring during the biopsy process. The combined imaging technique accurately identified the diseased lesion type in all biopsies, demonstrating 100% sensitivity and specificity. In conclusion, combining MRI and CT imaging modalities significantly improved spinal biopsy accuracy and efficiency, differentiating between pathological entities. However, large-scale studies are desired to validate these findings and investigate potential benefits in different clinical scenarios. Although this method requires general anesthesia, its potential profits in avoiding misdiagnosed lesions and decreasing the need for further invasive procedures make it a promising approach for improving spinal biopsy accuracy and efficiency.

Advanced MRI methods and PET using radiolabeled amino acids provide valuable information in addition to conventional MR imaging for brain tumor diagnostics. These methods are particularly helpful in challenging situations such as the differentiation of malignant processes from benign lesions, the identification of non-enhancing glioma subregions, the differentiation of tumor progression from treatment-related changes, and the early assessment of response to anticancer therapy. The debate over which of the methods is preferable in which situation is ongoing and has been addressed in numerous studies. Currently, most radiology and nuclear medicine departments perform these examinations independently of each other leading to multiple examinations for the patient. The advent of hybrid PET/MRI allowed a convergence of the methods but to date simultaneous imaging has reached little relevance in clinical neuro-oncology. This is partly due to the limited availability of hybrid PET/MRI scanners, but is also due to the fact that PET is a second-line examination in brain tumors. PET is only required in equivocal situations, and spatial co-registration of PET examinations of the brain to previous MRI is possible without disadvantage. A key factor for the benefit of PET/MRI in neuro-oncology is a multimodal approach that provides decisive improvements in the diagnostics of brain tumors compared with a single modality. This systematic review focuses on studies that were able to demonstrate the additive value of amino acid PET and ‘advanced’ MRI in the diagnosis of brain tumors. Available studies suggest that the combination of amino acid PET and advanced MRI improves grading and the histomolecular characterization of newly diagnosed tumors. However, data concerning the delineation of tumor extent and biopsy guidance are of limited value. A clear additive diagnostic value of amino acid PET and advanced MRI can be achieved regarding the differentiation of tumor recurrence from treatment-related changes. Here, PET-guided evaluation of advanced MR methods seems to be helpful. In summary, there is growing evidence that a multimodal approach can achieve decisive improvements in the diagnostics of brain tumors, for which hybrid PET/MRI offers optimal conditions.

CT scans are currently the most common imaging modality used for suspected stroke patients due to their short acquisition time and wide availability. However, MRI offers superior tissue contrast and image quality. In this study, eight deep learning models are developed, trained, and tested using a dataset of 181 CT/MR pairs from stroke patients. The resultant synthetic MRIs generated by these models are compared through a variety of qualitative and quantitative methods. The synthetic MRIs generated by a 3D UNet model consistently demonstrated superior performance across all methods of evaluation. Overall, the generation of synthetic MRIs from CT scans using the methods described in this paper produces realistic MRIs that can guide the registration of CT scans to MRI atlases. The synthetic MRIs enable the segmentation of white matter, gray matter, and cerebrospinal fluid using algorithms designed for MRIs, exhibiting a high degree of similarity to true MRIs.

Our aim was to compare the inter-rater agreement of Transvaginal ultrasonography (TVS) with Magnetic Resonance Imaging (MRI) regarding diagnosing adenomyosis and for various predefined imaging features of adenomyosis in the same set of women. MRIs were assessed by four experienced radiologists and 2D TVS videoclips and 3D ultrasound volumes were assessed by five experienced sonographers. Each rater subjectively evaluated the presence or absence of adenomyosis, assessed various imaging. Fleiss kappa (κ) was used to reflect inter-rater agreement for categorical data and the Intraclass correlation coefficient (ICC) to reflect the reliability of quantitative data. Agreement between raters for diagnosing adenomyosis was higher for TVS than for MRI (κ =0.42 vs.0.28). MRI had a higher inter-rater agreement in assessing wall asymmetry irregular Junctional Zone (JZ) presence of myometrial cysts, while TVU had a better agreement for globular shape. MRI showed a moderate-good reliability for measuring the JZ (ICC=0.57-0.82). For TVS, JZ was unmeasurable in > 50% of cases and the remaining cases had a low reliability (ICC=-0.31-0.08). We found that Inter-rater agreement for diagnosing adenomyosis was higher for TVS than for MRI, despite that MRI showed a higher inter-rater agreement in most specific features. Measurements of JZ in the coronal plane with 3D TVS were unreliable and thus unlikely to be useful for diagnosing adenomyosis.

In the context of autosomal dominant polycystic kidney disease (ADPKD), total kidney volume (TKV) plays a key role as biomarker of disease progression and response to therapy and has been recently recognized as enrichment biomarker and possible surrogate endpoint. Several imaging modalities and methods are available to calculate TKV, and the choice depends on the purpose of use. Technological advancements have made it possible to accurately assess cyst burden, that can be crucial to assess the disease state and help identifying rapid progressors. Moreover, the development of automated algorithms has increased the efficiency of total kidney and cyst volume measurements. Beyond total kidney and cyst volume, the quantification and characterization of non-cystic kidney tissue show potential to early stratify ADPKD patients, monitor disease progression, and possibly predict renal function loss. A broad spectrum of kid-ney MRI techniques are available to characterize kidney tissue, showing promise to non-invasively pick up early signs of ADPKD progression. Radiomics has been used to extract tex-tural features from ADPKD images, providing valuable information about the heterogeneity of the cystic and non-cystic components. This review provides an overview of ADPKD imaging bi-omarkers, focusing on quantification methods, potential, and necessary steps towards successful translation to clinical practice.

This paper aimed to describe an atlas of the head of the crested porcupine (Hystrix cristata), applying advanced imaging techniques such as MRI. Furthermore, by combining the images acquired through these techniques with anatomical gross sections, we obtained an adequate description of the structures that form the CNS and associated structures of this species. This anatomical information could serve as a valuable diagnostic tool for the clinical evaluation of different pathological processes in porcupines such as abscesses, skull malformations, fractures, and neoplasia.

This study aims at better understanding the damage and fracture kinetics in flax fibres elements at both the unitary and bundle scales using an experimental setup allowing optical observation at high recording rate in the course of tensile loading. Defects issues from flax unitary fibre extraction are quantitated using polarized light microscopy. Tensile loading is conducted according to a particular setup adapted to fibres of 10 to 20 µm in diameter and 10 mm in length. Optical recording using high speed camera is performed during loading up to the failure at acquisition speed ranging from 108,000 to 270,000 frames per second. Crack initiation in polymer layers of fibre elements, propagation as well as damage mechanisms are captured. The results show different failure scenarios depending on the fibre element nature. In particular, fractured fibres underline either a fully transverse failure propagation or a combination of transverse and longitudinal cracking with different balances. Image recordings with high time resolution down to 3.7 μs suggest unstable system and transverse crack speed higher than 4 m/s and a slower propagation for longitudinal crack deviation.

Multiple sclerosis (MS) is a heterogeneous disease of the central nervous system that is governed by neural tissue loss and dystrophy during its progressive phase, with complex reactive pathological cellular changes. The immune-mediated mechanisms that promulgate the demyelinating lesions during the relapses of acute episodes are not characteristic of chronic lesions during progressive MS. This has limited our capacity to target the disease effectively as it evolves within the central nervous system white and gray matter, thereby leaving neurologists without effective options to manage individuals as they transition to a secondary progressive phase. The current review highlights the molecular and cellular sequelae that have been identified to cooperate and/or contribute to neurodegeneration that identifies individuals with progressive forms of MS. We emphasize the need for appropriate monitoring via known and novel molecular and imaging biomarkers that can accurately detect and predict progression for the purposes of newly designed clinical trials that may demonstrate efficacy of neuroprotection and potentially neurorepair. To achieve neurorepair, we focus on the modifications required in the reactive cellular and extracellular milieu, in order to enable endogenous cell growth as well as transplanted cells that can integrate and/or renew the degenerative MS plaque.

Nonconventional luminescent materials (NLMs) that do not contain traditional aromatic chromophores are of great interest due to their unique chemical structures, optical properties and their potential applications in various areas such as cellular imaging and chemical sensing. However, most reported NLMs show weak or no emission in dilute solutions, severely limiting their applications. In this work, the dynamic hydrogen bonds were utilized to design NLMs with efficient emission in dilute solutions. To further validate the results, polymers P1 and P2 were successfully prepared and investigated. It was found that luminescence quantum efficiency of P1 and P2 at concentration of 0.1 mg/mL in water solution is 8.9 and 0.6%, respectively. The high efficiency can be attributed to the fact that polymer P1 has more intra- or intermolecular dynamic hydrogen bonds and other short interactions than P2 in dilute solutions, allowing P1 to achieve the through-space conjugation effect to increase the degree of system conjugation, restrict molecular motion, and decrease non-radiative transitions, which can effectively improve luminescence. In addition, polymer P2 exhibits the characteristics of clustering-triggered emission, excitation wavelength-dependent and concentration-dependent fluorescence properties, excellent photobleaching resistance, low cytotoxicity and selective recognition of Fe3+. This work is a preliminary study of the luminescence properties of NLMs in dilute solutions via modulating dynamic hydrogen bonds, which can be used as a semi-empirical method to design and construct novel NLMs in future.

Background: Thoracic endovascular aortic repair (TEVAR) has become the standard treatment for blunt thoracic aortic injury (BTAI). Some small observational studies revealed aortic morphological changes after TEVAR in patients with BTAI. However, these studies were limited by the rarity of the condition and small sample sizes. To address this gap, the current study aims to conduct a systematic review and meta-analysis of existing literature to provide evidence on the degree of immediate and long-term aortic diameter change following TEVAR for BTAI. Methods: This systematic review and meta-analysis of studies published up to March 2023, was conducted in accordance with the PRISMA statement. Studies eligible for inclusion were studies evaluating aortic diameter change post-TEVAR in BTAI patients. Results: 14 articles, including 353 patients, were included after review. Treatment and measurement protocols varied among individual studies resulting in high heterogeneity of the results. Our meta-analysis demonstrated an immediate post-intervention dilation 2.41 mm and 2.63 mm of the proximal and distal aortic necks’, respectively, as well as continuous dilation of the respective regions at a rate of 0.35 mm/year and 0.49 mm/year. Conclusion: TEVAR in BTAI leads to immediate post-intervention and continuous aortic dilation and morphological changes with possible future important clinical consequences.

SMARCA4-deficient non-small cell lung cancer (NSCLC) is a more recently recognized subset of NSCLC. We describe the 18F-fluorodeoxyglucose (FDG) PET/CT findings in a rare case of SMARCA4-deficient NSCLC and response to therapy. A 45-year-old male patient with a history of heavy smoking (10 years) underwent an 18F-fluorodeoxyglucose (FDG) PET/CT dynamic (chest) + static (whole-body) scan for diagnosis and pre-treatment staging. 18F-FDG PET/CT showed an FDG-avid mass in the upper lobe of the left lung (SUVmax of 22.4) and FDG-avid lymph nodes (LN) in the left pulmonary hilar region (SUVmax of 5.7). In addition, there are multiple metastases throughout the body, including distant LNs, adrenal glands, bone, and brain. Pathological findings confirmed SMARCA-4 deficient NSCLC. After 4 cycles of chemotherapy and immune checkpoint inhibitors（ICI）, the patient underwent again an 18F-FDG PET/CT scan (including dynamic scan) for efficacy evaluation. We report cases that deepen the understanding of the 18F-FDG PET/CT presentation of SMARCA4-deficient NSCLC as well as dynamic imaging features and parametric characteristics.

Background: Current prostate cancer evaluation can be inaccurate and burdensome. Quantitative evaluation of MRI sequences non-invasively helps prostate tumor assessment. However, including Dynamic Contrast Enhancement in the examined MRI sequence set can add complications, inducing possible side effects from the IV placement or injected contrast material, and prolongs scanning time. Purpose: Predict the risk of developing Clinically Significant (Insignificant) prostate cancer CsPCa (CiPCa) and International Society of Urologic Pathology (ISUP) grade using processed Signal to Clutter Ratio (SCR) derived from spatially registered bi-parametric MRI (SRBP-MRI) and thereby enhance non-invasively management of prostate cancer. Methods: This pilot study retrospectively analyzed 42 consecutive prostate cancer patients from the PI-CAI data collection. BP-MRI (Apparent Diffusion Coefficient, High B-value, T2) were resized, translated, cropped, and stitched to form spatially registered SRBP-MRI. Efficacy of noise reduction was tested by regularizing, eliminating principal components (PC), and minimizing elliptical volume from the covariance matrix to optimize the SCR. MRI guided biopsy (MRBx), Systematic Biopsy (SysBx), combination (MRBx+SysBx), or radical prostatectomy determined the ISUP grade for each patient. ISUP grade >=2 (<2) was judged as CsPCa (CiPCa). Linear and Logistic regression were fitted to ISUP grade and CsPCa/CiPCa SCR. Correlation Coefficients (R) and Area Under the Curves (AUC) for Receiver Operator Curves (ROC) evaluated the performance. Results: High correlation coefficients (R) (>0.55) and high AUC (=1.0) for linear and/or logistic fit from processed SCR and z-score for SRBP-MRI greatly exceed fits using prostate serum antigen, prostate volume, and patient age (R~0.17). Patients assessed with combined MRBx+SysBx and from individual MRI scanners achieved higher R (R=0.207+/-0.118) than using all patients in the fits. Conclusions: In the first study to date to apply and test hyperspectral approaches for assessing tumor aggressiveness on SRBP-MRI, high values of R and exceptional AUC to fit the ISUP grade and CsPCA/CiPCA were comparable or better than those from artificial intelligence in other studies.

In this work, we obtained three new phosphorescent iridium complexes (Ir1-Ir3) of general stoichiometry [Ir(N^C)2(N^N)]Cl decorated with oligo(ethylene glycol) fragments to make them water soluble and biocompatible, as well as to protect them from aggregation with biomolecules such as albumin. The major photophysical characteristics of these phosphorescent complexes are determined by the nature of two cyclometallating ligands (N^C) based on 2-pyridine-benzothiophene, since quantum chemical calculations revealed that the electronic transitions responsible for the excitation and emission are localized mainly at these fragments. However, the use of various diimine ligands (N^N) proved to affect the quantum yield of phosphorescence and allows for changing the complexes sensitivity to oxygen, due to the variations in the steric accessibility of the chromophore center for O2 molecules. It was also found that the N^N ligands made possible to tune the biocompatibility of the resulting compounds. The wavelengths of the Ir1-Ir3 emission maxima fall in the range of 630-650 nm, the quantum yields reach 17% (Ir1) in deaerated solution and sensitivity to molecular oxygen, estimated as ratio of emission lifetime in deaerated and aerated water solution, displays the highest value 8.2 for Ir1. The obtained complexes feature low toxicity, good water solubility and the absence of a significant effect of biological environment components on the parameters of their emission. Of the studied compounds Ir1 and Ir2 have been chosen for in vitro and in vivo biological experiments aimed at estimation of oxygen concentration in cell lines and tumors. These sensors have demonstrated their effectiveness for mapping the distribution of oxygen and for monitoring hypoxia in biological objects studied.

Osteoarthritis of the hand (HOA) is one of the most common musculoskeletal diseases affecting health. Osteophytes, documented by imaging procedures are often used as diagnostic criteria. The gold standard is the radiographic image, however, more sensitive and saver methods such as ultrasound are gaining in importance. We investigated the prevalence, grade and pattern of osteophytes by high resolution ultrasound investigation (US) in a population-based cross-sectional study. Factory workers were recruited at work. 26 finger joints of each participant were examined with US with grading the occurrence of osteophytes in a semiquantitative score ranging 0-3, increasing scores indicated larger osteophytes. 427 participants (mean age 53.5 years, range. 20-79 years) were investigated, resulting in 11,000 scored joints. At least one osteophyte was found in 4,546/11,000 (41.3%) joints or 426/427 (99.8%) participants but grade 2 or 3 osteophytes were seen in only 553 (5.0%) joints. The number of os-teophyte sum score increased with age (0.18/year of age increase, p<0.001). Distal interphalange-al joints (DIP) were predominantly affected with 61%, followed by proximal interphalangeal joints (PIP) with 48%, carpometacarpal joint 1 (CMC1) with 39% and metacarpophalangeal joints (MCP) with 16%. In conclusion, US is a feasible screening tool for osteophytes and HOA. Grade 1 osteophytes are a common finding in the working population when assessed by ultrasound and their prevalence is increasing with age. Prevalence of grade 2 or 3 osteophytes is less common and reflects clini-cal presence of HOA. Follow up investigations are necessary to recognize the predictive rele-vance of early osteophytes.

Panoramic and periapical radiograph tools help dentists diagnose the most common dental diseases. Generally, dentists identify dental caries manually by inspecting X-ray images. However, due to their heavy workload, or poor image quality, dentists may sometimes overlook some unnoticeable dental caries, which may ultimately hinder the patient treatment. The purpose of this study was to develop an algorithm that classifies the teeth X-Ray images into three categories of “Normal”, “Caries”, and “Filled”. Our study used a dataset of 116 patients and 3712 single teeth images for training, validation and testing. Images were pre-processed using a sharpening filter and an intensity color map. We used a pre-trained transfer learning model, the NASNetMobile, which served as the feature extractor and the Convolutional Neural Network (CNN) model served as the classifier. The training dataset had a “Recall” of 0.92, 0.90 and 0.91 for “Normal”, “Caries” and “Filled” respectively and the test dataset had a “Recall” of 0.86, 0.81 and 0.85 for “Normal”, “Caries” and “Filled” respectively. The classification of the teeth X-Rays was successful and can be valuable for dentist as the artificial intelligence algorithm can serve as a decision support tool to aid dentists when they need to diagnose dental treatment.

The main objective of this work was to evaluate the application of individual and ensemble machine learning models to classify malignant and benign breast masses using features from two-dimensional (2D) correlated spectroscopy spectra extracted from five-dimensional Echo Planar-Correlated Spectroscopic Imaging (5D EP-COSI) and Diffusion-weighted imaging (DWI). Twenty-four different metabolite and lipid ratios with respect to 2D diagonal peaks at 1.4ppm and 5.4ppm, and water from one-dimensional non-water-suppressed (NWS) spectra were used as the features. Additionally, water fraction, fat fraction and water-to-fat ratios from NWS spectra and apparent diffusion coefficients (ADC) from DWI were included. Nine most important features were identified using recursive feature elimination. XGBoost (AUC:93.0%, Accuracy:85.7%, F1-score:87.6%), GradientBoost (AUC:94.4%, Accuracy:87.0%, F1-score:89.4%), CatBoost (AUC:95.2%, Accuracy:86.9%, F1-score:88.4%) and RandomForest (AUC:92.2%, Accuracy:85.3%, F1-score:87.6%) were the best performing models. While the conventional biomarkers like choline, myo-Inositol, and glycine were statistically significant predictors, the key features contributing to the classification were ADC, 2D diagonal peaks at 0.9ppm, 2.1ppm and 2.3ppm, cross peaks between 1.4 and 0.9ppm, 4.3 and 4.1ppm, 2.1 and 1.4ppm and the triglyceryl-fat cross peak. The results highlight the contribution of the 2D spectral peaks to the model, and they demonstrate the potential of 5D EP-COSI for early breast cancer detection.

Alzheimer’s disease has become a major concern in the healthcare domain as it is growing rapidly. Many researches have been conducted to detect it from MRI images through various deep-learning approaches. However, the problem of the availability of medical data and the privacy of the patients still exists. To mitigate this issue in Alzheimer’s disease detection, we have implemented the federated approach which is found to be more efficient, robust, and consistent compared to the conventional approach. For this, we needed deep excavation on various orientations of MRI images and transfer learning architectures. Then, we utilized the publicly available two datasets (OASIS, and ADNI), and designed various cases to evaluate the performance of the federated approach. In almost all of them, the federated approach achieved better accuracy and sensitivity. In distinguishing between two classes equally, the capability of the models was better in the found model when trained with federated approach compared to the conventional approach. In this approach. MobileNet, which is a low-cost transfer learning architecture, achieved the highest 95.24%, 81.94%, and 83.97% accuracy in OASIS, ADNI, and merged (ADNI+OASIS) test set, which was way higher than the achieved performance in Conventional approach. Moreover, in this approach, only the weights of the model were shared which keeps the original MRI images in their respective hospital or institutions, mitigating the privacy concern in the healthcare domain.

This study aimed to evaluate contrast-enhanced mammography (CEM) and compare breast lesions on CEM and breast magnetic resonance imaging (MRI) using 5 features. We propose to create a flowchart for BI-RADS classification of breast lesions on CEM based on the Kaiser score (KS) flowchart for breast MRI. Included were 68 subjects (women and men; median age 61.4 ± 11.6 years) who were suspected of having a malignant process in the breast based on digital mammography (MG) findings. The patients underwent breast ultrasound (US), CEM, MRI, and biopsy of the suspicious lesion. There were 47 patients with malignant lesions confirmed by biopsy and 21 patients with benign lesions, for each of which a KS was calculated. In the patients with malignant lesions, the MRI-derived KS was 9 (IQR 8-9), its CEM equivalent was 9 (IQR 8-9), and BI-RADS was 5 (IQR 4-5). In patients with benign lesions, MRI-derived KS was 3 (IQR 2-3), its CEM equivalent was 3 (IQR 1.7-5), and BI-RADS was 3 (IQR 0-4). There was no significant difference between the ROC-AUC of CEM and MRI (P=0.749). In conclusion, there were no significant differences in KS results between CEM and breast MRI. The KS flowchart is useful for evaluating breast lesions on CEM.

Fibroblast activation protein (FAP) is a membrane-tethered serine protease overexpressed in the reactive stromal fibroblasts of &gt; 90% human carcinomas, which makes it a promising target for developing radiopharmaceuticals for imaging and therapy of carcinomas. Here, we synthesized two novel (R)-pyrrolidin-2-yl-boronic acid-based FAP-targeted ligands; SB02055 (DOTA-conjugated (R)-(1-((6-(3-(piperazin-1-yl)propoxy)quinoline-4-carbonyl)glycyl)pyrrolidin-2-yl)boronic acid) and SB04028 (DOTA-conjugated ((R)-1-((6-(3-(piperazin-1-yl)propoxy)quinoline-4-carbonyl)-D-alanyl)pyrrolidin-2-yl)boronic acid). natGa- and 68Ga-complexes of both ligands were evaluated in preclinical studies and compared to previously reported natGa/68Ga-complexed PNT6555. Enzymatic assays showed that FAP binding affinities (IC50) of natGa-SB02055, natGa-SB04028 and natGa-PNT6555 were 0.41±0.06, 13.9±1.29 and 78.1±4.59 nM, respectively. PET imaging and biodistribution studies in HEK293T:hFAP tumor-bearing mice showed that while [68Ga]Ga-SB02055 presented with a nominal tumor uptake (1.08±0.37 %ID/g), [68Ga]Ga-SB04028 demonstrated clear tumor visualization with ~1.5-fold higher tumor uptake (10.1±0.42 %ID/g) compared to [68Ga]Ga-PNT6555 (6.38±0.45 %ID/g). High accumulation in the bladder indicated renal excretion of all three tracers. [68Ga]Ga-SB04028 displayed low background level uptake in most normal organs, and comparable to [68Ga]Ga-PNT6555. However, since its tumor uptake was considerably higher than [68Ga]Ga-PNT6555, the corresponding tumor-to-organ uptake ratios for [68Ga]Ga-SB04028 were also significantly greater than [68Ga]Ga-PNT6555. Our data demonstrate that (R)-(((quinoline-4-carbonyl)-D-alanyl)pyrrolidin-2-yl)boronic acid is a promising pharmacophore for the design of FAP-targeted radiopharmaceuticals for cancer imaging and radioligand therapy.

Through the arrow decomposition of the Mueller matrix, respective sets of sixteen independent polarimetric images of biological tissues are obtained for enpolarizing, retarding and depolariz-ing descriptors. In addition to the mean intensity coefficient and the three indices of polarimetric purity, the absolute values and Poincaré orientations of diattenuation, polarizance, entrance re-tardance and exit retardance vectors are considered. In this work we use for the first time this set of polarimetric observables for the visualization of biological structures, both of animal and vege-tal origin. Results show images with enhanced visualization derived from the spatial variation of such significant polarimetric properties. The experimental results are discussed, showing the suit-ability of such set of observables for applications in biophotonics imaging, providing not only ex-cellent visualization of biological tissues, but also showing structures not visible in non-polarimetric images.

The organic coating of bridge steel girders is subjected to physical scratches, corrosion, and aging in natural weathering. The breakdown of the coating may cause serviceability and safety problems if left unnoticed. A hyperspectral imaging method is proposed to detect the condition of steel coatings based on coating-responsive features in reflectance spectra. A field test was conducted on the real-world bridge which shows obvious signs of degradation. The hyperspectral signature enables an assessment of the coating health and defect severity. The results indicated that the coating scratch can be effectively located in the domain of a hyperspectral image and the scratch depth can be determined by mapping a scratch depth indicator (SDI=R532nm / R641nm). Rust sources and products in steel girders can be identified by the unique spectral signatures and the rust stains (and thus stain areas) scattered on the coating can be pinpointed at pixel level by the corrosion rust indicators. The chemical integrity of a topcoat is demonstrated by the short-wave infrared spectroscopy and the topcoat degradation can be evaluated by the absorption at 8000 cm-1 and 5850 cm-1.

Background & Aims: Non-alcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) have been linked to changes in amino acid (ΑΑ) levels. The current observational study sought to investigate the relationship between plasma AA concentrations in a NAFLD population and MRI parameters reflecting inflammation and fibrosis, inflammatory and oxidative stress markers, and disease-related anthropometric and biochemical indicators. Approach & Results: Plasma AA levels were quantified with liquid chromatography in 97 NAFLD patients from the MAST4HEALTH study. Medical, anthropometric and lifestyle characteristics were collected and biochemical parameters, as well as inflammatory and oxidative stress biomarkers were measured. In total, males and subjects with higher MRI-proton density fat fraction (MRI-PDFF) exhibited higher plasma AA levels compared to females and subjects with lower PDFF respectively. Several associations of AAs with disease related markers were revealed, with the more prominent ones being those of aromatic amino acids with log-PDFF (beta: 1.190E-02, p-Value: 0.001) and log-ALT (beta: 7.55E-03, p-Value: 0.001), of branched amino acids with log-insulin (beta: 1.97E-03, p-Value: 1.16E-04) and of ethanolamine (beta: 0.036, p-Value: 3.65E-04) and L-ornithine (beta: 5.4E-04, p-Value: 0.021) with log-total antioxidant status (TAS). Conclusions: Plasma AA levels varied according to sex, BMI, and several MRI clinical factors. Furthermore, significant relationships were demonstrated between AA and several disease indicators, such as MRI parameters, biochemical and oxidative stress indices, showing the potential utility of AAs as diagnostic dis-ease-related indicators activity.

Introduction: Austere environments include the wilderness and many lower-and-middle-income countries, many of these facing unrest and war. The access to advanced diagnostic equipment is often unaffordable even if available and is often liable to breakdown. This short review paper examines the options available to medical professionals to undertake clinical and point of care diagnostic testing in resource constrained environments and also illustrates the development of mobile advanced diagnostic equipment. The aim is to provide an overview of the spectrum and functionality of these devices beyond clinical acumen.

Abstract: Background: Trauma is the leading cause of morbidity and mortality in young patients, acute surgical conditions cause morbidity and mortality in patients of all ages. Computed tomography scan (CT) assist greatly in the investigation and management of these patients with blunt and penetrating trauma, facilitating early diagnosis and expedites early appropriate treatment of these patients. Acute non-traumatic surgical conditions also mimic non-surgical pathologies and differentiating the two is important because management is different and any delay in surgical intervention results in high morbidity and some may even result in mortality. Method: Literature review of the role of multidetector CT scan (MDCT) in managing acute surgical emergencies and trauma-diagnosis in the trauma patient and patients presenting with acute surgical emergencies. The focus is on the role of the MDCT in the management of these patients. Results highlight that the use of MDCT expedites management of these patients, allowing early surgical intervention and preventing unnecessary surgical interventions where the intervention is not indicated, based on the MDCT results. Conclusion: This paper emphasizes the important role that is played by the MDCT in the management of the above patients.

Attempts to use computers to aid in the detection of breast malignancies date back more than 20 years. Despite significant interest and investment, this has historically led to minimal or no significant improvement in performance and outcomes with traditional computer aided detection. However, recent advances in artificial intelligence and machine learning are now starting to deliver on the promise of improved performance. There are at present more than 20 FDA approved AI applications for breast imaging, but adoption and utilization are widely variable and overall low. Breast imaging is unique and has aspects that create both opportunities and challenges for AI development and implementation. Breast cancer screening programs worldwide rely on screening mammography to reduce the morbidity and mortality of breast cancer and many of the most exciting research and available AI applications focus on cancer detection for mammography. There are however multiple additional potential applications for AI in breast imaging including decision support, risk assessment, breast density quantitation, workflow and triage, quality evaluation, response to neoadjuvant chemotherapy assessment, and image enhancement. In this review the current status, availability, and future directions of investigation of these applications are discussed, as well as the opportunities and barriers to more widespread utilization.

Quantification of bone loss for follow-up comparisons has not been routinely performed in patients with parietal thinning so far. This study compares different methodological approaches including both 2- and 3-dimensional methods in computerized tomographies of a single patient. The 2-dimensional method provides accurate measurements of bone thickness, while the 3-dimensional method allows for a more comprehensive view of the bone's structure, including parameters like shape, size, and thickness. The techniques provided valuable data for the treating physician and suggest a possible effect of corticosteroids in this individual patient. The study concludes that 3-dimensional reconstruction of computerized tomographies with subsequent 2-dimensional analyses appears justified for routine radiological practice to increase clinical awareness of the size of the parietal bone defects and allow for quantification of bone loss during long-term follow-ups. Further validation of the proposed analytical approaches is warranted in larger studies to investigate patterns of bone thinning across the skull and changes in bone volumes over time, with specialized software to be approved for such analyses.

For the replacement of lost contractile elements in the treatment of coronary heart disease, the most promising approaches to obtain cardiomyocytes by cardiac differentiation of pluripotent cells. The aim of this work is to develop a technology for the formation of a functional layer of cardiomyocytes differentiated from iPSCs, capable of generating rhythmic activity and synchronous contractions. To accelerate cardiomyocyte maturation, the renal subcapsular transplantation model was used in SCID mice. After explantation, the formation of cardiomyocyte contractile apparatus was assessed by fluorescence and electron microscopy, and calcium ion oscillation in the cytoplasm was assessed by visualization of the fluorescent calcium binding dye Fluo-8. It was shown that human iPSC-derived cardiomyocyte cell layers transplanted (for up to 6 weeks) under SCID mouse kidney fibrous capsules begin to form an ordered contractile apparatus and retain functional activity and the ability to oscillate calcium ion fluxes after explantation from the body.

Background. To prospectively evaluate the reliability of a portable optical scanner compared to the water displacement technique for volumetric measurements of the foot and ankle, and to compare the acquisition time associated with these two methods. Methods. Foot volume was measured in 29 healthy volunteers (58 feet, 24 female/5 male) by a 3D scanner (UPOD-S 3D Laser Full-Foot Scanner ®) and by water-displacement volumetry. Measurements were performed on both feet, up to a height of 10 cm above the ground. The acquisition time for each method was evaluated. Kolmogorov-Smirnov test, Lin's Concordance Correlation Coefficient, and a Student’s t-test were performed. Results: Mean foot volume was 869.7+/-165.1cm3 (3D scanner) versus 867.9+/-155.4cm3 (water-displacement volumetry) (p <10-5). Concordance of measurements was 0.93, indicative of a high correlation between the two techniques. Volumes were 47.8 cm3 lower when using the 3D scanner versus water volumetry. After statistically correcting this underestimation, the concordance was improved (0.98, residual bias = -0.03 +/- 35.1 cm3). Mean examination time was 4.2 +/-1.7 min (3D optical scanner) versus 11.1 +/-2.9 min (water volumeter) (p<10-4). Conclusion: Ankle/foot volumetric measurements performed using this portable 3D scanner are reliable and fast, and can be used in clinical practice and research.

The Neurovascular Unit (NVU), comprised of glia (astrocytes, oligodendrocytes, microglia), neurons, pericytes and endothelial cells, is a dynamic interface ensuring physiological functioning of the central nervous system (CNS), that gets affected and contributes to the pathology of several neurodegenerative diseases. Neuroinflammation is a common feature of neurodegenerative diseases and is primarily related to the activation state of perivascular microglia and astrocytes, which constitute two of its major cellular components. Our studies focus on monitoring in real time the morphological changes of perivascular astrocytes and microglia, as well as their dynamic interactions with the brain vasculature, under physiological conditions and following systemic neuroinflammation triggering both microgliosis and astrogliosis. To this end, we performed 2-photon laser scanning microscopy (2P-LSM) for intravital imaging of the cortex of transgenic mice visualizing the dynamics of microglia and astroglia following neuroinflammation induced by systemic administration of the endotoxin lipopolysaccharide (LPS). Our results indicate that following neuroinflammation the end-feet of activated perivascular astrocytes lose their close proximity and physiological crosstalk with vasculature, an event that most possibly contributes to a loss of blood-brain-barrier (BBB) integrity. At the same time, microglial cells get activated with more frequent contacts of the blood vessels. These dynamic responses of perivascular astrocytes and microglial are peaking at 4 days following LPS administration, however they still persist at a lower level 8 days after LPS, revealing incomplete reversal of inflammation affecting the glial properties and interactions with the NVU.

Reservoir in the Central Structural Zone of the Xihu Sag is the Huagang Formation, dominated by natural gas reservoirs, and the reservoir in the Western Slope Zone is the Pinghu Formation, dominated by light oil and wet gas. In this paper, the Gas Drive Water Displacement- Magnetic Resonance Imaging (GWD-MRI) experiments are used to simulate the charging characteristics of the sandstone migration layer. The centrifugal- Magnetic Resonance (Cen-NMR) experiments simulate the short-term fast trap charging process, and the Semi-Permeable Baffle (SPB) charging experiment simulates the slow trap accumulation process. Studies have shown that there is a start-up pressure for the migration layer charging, and the start-up pressure of the core with a permeability of 0.3mD is about 0.6MPa. Experimental simulations have confirmed that there is a front zone with changed water saturation, with a width of about 1-1.5cm. The migration layer charging mainly has two actions, drive effect and carry effect. The drive effect reduces the water saturation to 70%-80%, and the carry effect can still reduce the water saturation by 5%-10%. The water saturation of rapid charging is mainly affected by the petro-physical. The porosity is high, the water saturation is low. The water saturation decreased significantly with the increase of centrifugal force when the centrifugal force is smaller. If the centrifugal force is greater than 0.8 MPa, the water saturation decreases slowly. The water saturation of the trap slowly charging is basically maintained at 40%-50%, which matches the water saturation of the airtight coring from 40%-55%, the petro-physical do not affect the final water saturation.

The winged bean is an underutilized legume that has the potential to contribute to nutrition and food security globally, especially in sub-Saharan Africa (SSA). However, very little research attention is paid to exploiting its full potential due to a lack of adequate knowledge of the existing genetic diversity in the available winged bean germplasm. To bridge this gap, seed morphometric and selected agro-morphological traits which are crucial for yield and seed quality determination in crop plants were used to assess the genetic diversity of thirty accessions of winged bean sourced from the Gene bank of the International Institute of Tropical Agriculture (IITA), Ibadan. The thirty winged accessions were evaluated under field trials at three agro-ecological zones in Nigeria. The agro-morphological data as well as the seed morphometric dataset obtained from a Multi-Spectral Imaging (MSI) system were subjected to Analysis of Variance (ANOVA), Principal Component (PC) analysis, cluster analysis, and correlation analysis. Significant differences (p &lt; 0.05) were observed among the accessions for all measured traits. The first three PCs accounted for 93% of the variation observed among the accessions for all measured traits. Accessions were grouped into three clusters based on the agro- morphological traits and three clusters under the MSI system. Seed yield per plant had the highest estimates of significant positive correlation with hundred seed weight, pod weight per plant, etc. at both phenotypic and genotypic levels. TPt-31 had the highest seed yield per plant, pod weight per plant, and early maturity while TPt-7 had an extended flowering and maturity period, the highest number of pods per peduncle and pods per plant as well as the lowest seed yield. These accessions could serve as a good resource for future winged bean improvement programs. The result also confirmed that the MSI system is an invaluable tool for discriminating among accessions of the same crop species.

Owing to the advantages of cost-effectiveness, compactness, and the avoidance of complicated camera synchronization, single-camera three-dimensional (3D) digital image correlation (DIC) techniques have gained increasing attention for deformation measurement of materials and structures. In the traditional single-camera 3D-DIC system, the left and right view images can be recorded by a single camera using a diffraction grating, a bi-prism or a set of planar mirrors. To further improve the measurement accuracy of single-camera 3D-DIC, this paper introduces a single-camera four-view imaging technique by installing a pyramidal prism in front of the camera. The 3D reconstruction of the measured points before and after deformation is realized with eight governing equations induced by four views, and the strong geometric constraints of four views can help to improve the measurement accuracy. A static experiment, a rigid body translation experiment and a four-point bending experiment show that the proposed single-camera 3D-DIC method can achieve higher measurement accuracy than the dual-view single-camera 3D-DIC techniques and has advantages in reducing both random error and systematic error.

Episcopic imaging using techniques such as High Resolution Episcopic Microscopy (HREM) and its variants, allows biological samples to be visualized in three dimensions over a large field of view. Quantitative analysis of episcopic image data is undertaken using a range of methods. In this systematic review, we look at trends in quantitative analysis of episcopic images and discuss avenues for further research. Papers published between 2011 and 2022 were analyzed for details about quantitative analysis approaches, methods of image annotation and choice of image processing software. It is shown that quantitative processing is becoming more common in episcopic microscopy and that manual annotation is the predominant method of image analysis. Our meta-analysis highlights where tools and methods require further development in this field, and we discuss what this means for the future of quantitative episcopic imaging, as well as how annotation and quantification may be automated and standardized across the field.

The aim of study was to investigate epidemiology aspects of magnetic resonance imaging (MRI) during COVID-19 pandemic. The study comprised depersonalized residents of Tomsk and Tomsk Region (n = 1714). Invitations to take online survey were sent to 50,000 residents by target SMS with response rate of 1.2% (n = 727, Cohort 1). Cohort 2 comprised retrospective patients (n = 987) who underwent contrast-enhanced cardiac MRI (CMR) in 2019-2022. Referrals, clinical characteristics, diagnosis, gender, age, past COVID-19, MRI study protocols, and MRI data were analyzed. 29% of respondents in cohort 1 received MRI examination within past two years; 26% of respondents considered MRI the most informative imaging modality for detecting COVID-19 pneumonia; 12% of respondents reported MRI unavailable. Proportion of CMR among MRI studies increased during COVID-19 pandemic, and maximum incidence of cardiac diseases detected by MRI was in 2021. Incidence of myocardial fibrosis increased from ~67% in 2019 to ~84% in 2022. The rate of outpatient MRI studies significantly increased in 2020, but returned to pre-pandemic level in 2021. COVID-19 pandemic increased the need for MRI and CMR. Patients with history of COVID-19 had persistent and newly occurring symptoms of myocardial damage suggesting chronic cardiac involvement requiring continuous follow-up.

Pattern recognition techniques form the heart of most, if not all, incoherent linear shift-invariant systems. When an object is recorded using a camera, the object information gets sampled by the point spread function (PSF) of the system, replacing every object point with the PSF in the sensor. The PSF is a sharp Kronecker Delta-like function when the numerical aperture (NA) is large with no aberrations. When the NA is small, and the system has aberrations, the PSF appears blurred. In the above case, if the PSF is known, then the object information can be obtained by scanning the PSF over the recorded object intensity pattern and looking for pattern matching conditions through a mathematical process called correlation. In this study, a recently developed deconvolution method, the Lucy-Richardson-Rosen algorithm (LR2A), has been implemented to computationally refocus images recorded in the presence of spatio-spectral aberrations. The performance of LR2A was compared against the Lucy-Richardson algorithm and non-linear reconstruction. LR2A exhibits a superior deconvolution capability even in extreme cases of spatio-spectral aberrations and blur. Experimental results of deblurring a picture captured using high-resolution smartphone cameras are presented. LR2A was implemented to significantly improve the performances of the widely used deep convolutional neural networks for image classification.

About 50% of colorectal cancer patients develop liver metastases. Patients with metastatic colorectal cancer have 5-year survival rates below 20% despite new therapeutic regimens. Tumor heterogeneity has been linked with poor treatment response and clinical outcome, but was so far mainly studied via bulk genomic analyses. In this study we performed spatial proteomics via MALDI mass spectrometry imaging on six patient-matched CRC primary tumor and liver metastases to characterize interpatient, intertumor and intratumor hetereogeneity. We found several peptide features that were enriched in vital tumor areas of primary tumors and liver metastasis and tentatively derived from tumor cell specific proteins such as annexin A4 and prelamin A/C. Liver metastases of colorectal cancer showed higher heterogeneity between patients than primary tumors while within patients both entities show similar intratumor heterogeneity sometimes organized in zonal pattern. Together our findings give new insights into the spatial proteomic heterogeneity of primary CRC and patient-matched liver metastases.

OCTA is an imaging modality used in the assessment of the retinal vasculature. It operates on the principle of coherence tomography used in standard OCT with the addition of delineating the retinal vascular. This provides a modern non-invasive retinal vascular imaging method compared to conventional dye-based imaging. High quality depth resolution of the superficial and deep capillary networks is possible on OCTA whereas this was not possible prior. OCTA may be limited by image quality degradation from factors such as motion artefact or media opacities, and therefore may not be the investigation of choice for all patient groups. There are multiple potential clinical applications for OCTA in retinal and choroidal vascular disease. Ongoing research is necessary to substantiate the more widespread use of OCTA due to its significant cost burden compared to current modalities.

Accurate retroperitoneal lymph node metastasis (LNM) prediction in early-stage testicular germ cell tumours (TGCT) harbours the potential to significantly reduce over- or undertreatment and treatment-related morbidity in this group of young patients as an important survivorship imperative. We investigated the role of computed tomography (CT) radiomics models integrating clinical predictors for the individualized prediction of LNM in early-stage TGCT. Ninety-one patients with surgically proven testicular germ cell tumours and contrast-enhanced CT were included in this retrospective study. Dedicated radiomics software was used to segment 273 retroperitoneal lymph nodes and extract features. After feature selection, radiomics-based machine learning models were developed to predict LN metastasis. The robustness of the procedure was controlled by 10-fold cross-validation. Using multivariable logistic regression modelling, we developed three prediction models: A radiomics-only model, a clinical-only model and a combined radiomics-clinical model. The models' performance was evaluated using the area under the receiver operating characteristic curve (AUC). Finally, decision curve analysis was performed to estimate the clinical usefulness of the predictive model. The radiomics-only model for predicting lymph node metastasis reached a greater discrimination power than the clinical-only model, with an AUC of 0.84 (± 0.17; 95% CI ) vs 0.60 (± 0.22; 95% CI) in our study cohort. The combined model integrating clinical risk factors and selected radiomics features outperformed the clinical-only and the radiomics-only prediction models and showed good discrimination with an area under the curve of 0.94 ( ± 0.10; 95% CI). The decision curve analysis demonstrated the clinical usefulness of our proposed combined model. The presented combined CT-based radiomics-clinical model represents an exciting non-invasive prediction tool for individualized prediction of LN metastasis in testicular germ cell tumours. Multi-centre validation is required to generate high-quality evidence for its clinical application.

The series of papers, 'Re-Visiting Viking Vinland', encompasses a re-evaluation of the Viking voyages from Greenland to North America, from about 985 to 1026 A.D. Searching for their American landfalls used multiple approaches: clues from Norse sagas, logic, creative imagination, and advanced imaging technology. Paper I described locating 'Keelness', a Viking shipwreck site in Newfoundland, Canada, but Covid-19 prevented professional, on-site follow-up. Paper II describes our alternative, a 'virtual excavation', using only remote imaging via drone, plus advanced data-processing of both visible and thermal (infrared) data. Starting with the 'stocks', a support structure for Viking ship repair, other features were accidentally found, identified, and interpreted. These included damaged hull planks ('strakes'), parts of the broken keel, a pit-house for shelter, and the hole where a keel-piece was erected as a navigational marker; with the site named (Norse, 'Kjalarnes') ('Keelness' or Keel Point). Results of this non-contact, non-destructive 'virtual excavation' supported our hypothesis that this site is the 'Keelness' mentioned in the Norse sagas. Fragments of Leif Eriksson's original ship may still be preserved in a sphagnum moss bog after 1000 years, accessible for further study, and perhaps providing valuable information on both provenience (origin) and provenance (history) of these iconic artifacts.

Diffuse optical tomography (DOT) is a medical imaging procedure using light to measure the geometric and working properties of cells, for instance, oxygen consumption, water content, and fat percentage in the tissue by performing three-dimensional visualization of the tissue. This paper aims to explain the theory behind diffuse optical tomography imaging and how the technology works. The paper explains how photon migration techniques based on diffusion theory can be used to image the optical properties of tissue. There are several reasons why near-infrared (NIR) imaging is the most effective method in terms of recovering optical parameters quantitatively in the near-infrared region. The author discusses the methods in detail. This research also presents various advantages, practical uses, and potential problems that have been related to DOT in this work. There is also a brief discussion of current research developments in medical imaging using near-infrared wavelengths, and what the future holds for that area.

Chemotherapy for lung cancer has made remarkable progress, and its selection has been subdivided by genetic analysis. Although response evaluation criteria in solid tumors (RECIST) is a simple and highly objective evaluation method, it has been pointed out that it has the disadvantage of not being able to accurately evaluate the therapeutic effect of molecularly targeted drugs and immune checkpoint inhibitors. The purpose of this study is to determine whether quantitative evaluation of DWIBS is useful in determining the effectiveness of treatment for lung cancer. There were 31 patients with lung cancer and 56 patterns were obtained. First, the determination of treatment effect (PD, SD, PR) based on RECIST was performed on CT. Second, tDV and ADC (median) were measured using BD score from DWI images taken at the same time, and the rate of change was calculated. Then, we compared and examined the correlation between RECIST and the rate of change in tDV. There were correlations between RECIST and the rate of change in tDV in PD and PR cases respectively. Compared RECIST on CT, DWIBS using BD score would be more accurate for response evaluation of treatment. There was a tendency that tDV decreased with increasing ADC values, but some of the cases had a dissociated response with increasing ADC values and increasing tDV. Thus, since the color display of ADC values allows us to infer their contents, it would be useful for the evaluation of cases such as dissociated response and pseudoprogression, which are suspected to be atypical responses that are difficult to evaluate with RECIST and other methods.

Advances in nanomedicine bring the attention of researchers to the molecular targets which can play a major role in the development of novel therapeutic and diagnostic modalities for cancer management. The choice of a proper molecular target can decide on the efficacy of the treatment and endorse the personalized medicine approach. Gastrin-releasing peptide receptor (GRPR) is a G-protein-coupled membrane receptor, well known to be overexpressed in numerous malignancies including pancreatic, prostate, breast, lung, colon, cervical and gastrointestinal cancers. Therefore, many research groups express a deep interest in targeting GRPR with their nanoformulations. A broad spectrum of the GRPR ligands has been described in the literature, which allows tuning of the properties of the final formulation, particularly in the field of the ligand affinity to the receptor and internalization possibilities. Hereby the recent advances in the field of applications of various nanoplatforms which are able to reach the GRPR expressing cells are reviewed.

Diffuse optical tomography (DOT) is an optical medical imaging method that can assess the structural properties of tissues and their functional characteristics, such as hemoglobin concentration, water content, as well as lipid concentration, via three-dimensional image reconstruction. This paper presents the theoretical basis and working principle of diffuse optical tomography. The paper explains how the optical properties of tissue can be imaged by photon migration techniques based on diffusion theory. The author presents the reasoning for near-infrared (NIR) imaging as the most effective technique in terms of quantitative recovery of spectroscopic optical parameters. This work also listed various advantages, applications, and challenges of DOT. The paper also briefly discusses current progress in near-infrared medical imaging and its future direction.

This paper presents an overview of tomography and different tomographic imaging modalities. The goal of this paper is to provide an understanding of various imaging modalities; in particular, how the imaging is performed, working principles, and applications. It was not intended to provide the in-depth mathematical principles of these imaging modalities, rather this paper focuses on providing the knowledge in an easy-to-grasp manner for the readers' benefit. Imaging modalities are categorized based on the physics behind image generation. First, the paper explains the general tomography principle. Then explains Ultrasound Imaging, Electrical Impedance Tomography, Computed Tomography, Magnetic Resonance Imaging (MRI), Photoacoustic Tomography (PAT), and Positron Emission Tomography (PET). In the end, the paper provides the fundamentals and review of two relatively new imagining modalities, Diffuse Optical Tomography (DOT) and functional Near-infrared Spectroscopy (fNIRS).

The optical properties and physiology of biological tissue, as well as how near-infrared (NIR) light interacts with the tissue, both play a significant role in interpreting the tissue probing optical measurements, and in solving the inverse problem of near-infrared spectroscopy (NIRS)-based medical imaging modalities such as diffuse optical tomography and functional near-infrared spectroscopy. This paper discusses the optical properties of tissue, specifically in the NIR wavelength range, which influence NIRS measurements in NIRS-based medical imaging. There is an easy-to-understand explanation given in this paper of the NIR light-tissue interaction phenomenon. The mathematical explanation, the processes involved in the interaction, and the rationale for a few approximations are described. Various types of chromophores present in the tissue, their composition in the tissue, and how these chromophores overall affect the scattering and absorption of NIR light are presented. The absorption spectra of these chromophores are shown. Finally, the paper concludes with the author’s perspective on two NIRS-based medical imaging modalities, diffuse optical tomography, and functional near-infrared spectroscopy.

The series 'Re-Visiting Viking Vinland' describe re-evaluation of Viking voyages from Greenland to North America, from about 985 to 1026 A.D. American landfalls were located using clues from Norse sagas, logic, creative imagination, and advanced imaging technology. Paper I describes a dramatic voyage of Leif Eriksson's brother, Thorvald, during the second of four successful 'Vinland' voyages. Thorvald borrowed Leif's ship for further exploration, was caught in a storm, "shattering" the keel, and disabling the ship. In Greenlanders' Saga: "They had to stay there for a long time while they repaired the ship. Thorvald said to his companions, 'I want to erect the old keel here on the headland and call the place Kjalarnes (Keelness)". Where was Keelness? Re-imagining the voyage, the search led from 'Leif's Booths', Leif's original 'Vinland' site in New Brunswick, Canada, to the north coast of Newfoundland. Using logic, a single satellite image, and follow-up drone scans, the Keelness site was found, very near L'Anse aux Meadows, the first authenticated Viking site in North America. Covid-19 restrictions, and lack of certified professionals, precluded site-visits or excavation. Advanced data-processing of drone data was used to confirm the site, while unexpectedly revealing several distinctive ship-repair features; with visible and thermal imaging supporting this site as 'Keelness'; perhaps the first Viking site unequivocally named in the Vinland sagas.

Direct imaging systems that create an image of an object directly on the sensor in a single step are prone to many constraints as a perfect image is required to be recorded within this step. In designing high resolution direct imaging systems with a diffractive lens, the outermost zone width either reaches the lithography limit or the diffraction limit itself imposing challenges in fabrication. However, if the imaging mode is switched to an indirect one consisting of multiple steps to complete imaging, then different possibilities open up. One such methods is the widely used indirect imaging method with Golay configuration telescopes. In this study, a Golay-like configuration has been adapted to realize a large area diffractive lens with three sub-aperture diffractive lenses. The sub-aperture diffractive lenses are not required to collect light and focus them to a single point as in a direct imaging system but to focus independently on different points within the sensor area. This approach of Large Area Diffractive lens with Integrated Sub-Apertures (LADISA) relaxes the fabrication constraints and allows the sub-aperture diffractive elements to have a larger outermost zone width and smaller area. The diffractive sub-apertures were manufactured using photolithography. The fabricated diffractive element has been implemented in indirect imaging mode using non-linear reconstruction and Lucy-Richardson-Rosen algorithm with synthesized point spread functions. The computational optical experiments revealed an improved optical and computational imaging resolutions compared to previous studies.

Lung cancer is the leading cause of cancer mortality worldwide, and it is urgently necessary to diagnose it as early as possible. Usually, the diagnostic process begins with a radiological examination which, when a possible tumour is present, is followed by a biopsy to extract tissue samples from the patient's lungs. Therefore, the purpose of this study is the development of an artificial intelligence algorithm that will analyse the Whole Slide Image (WSI) generated by the digitisation of the glass slides obtained from the extracted samples and detect if there is a tumour. The developed learning algorithms as well as the tested neural networks (NNs) were trained on a dataset composed of previously annotated WSI tiles, classified as Tumour or Non-Tumour. From these, four developed convolutional neural networks stood out and were selected to be compared with each other and with the tested NNs. When the best result of each of the developed architectures was compared to the highest result of the tested NNs, it was possible to denote that version 4 of CancerDetecNN achieved an average accuracy of 89.749 \% and an average loss of 0.220. Furthermore, the results for the four selected versions are in agreement with the results reported in the literature, however, the limited size of the given dataset must be considered. Given the results obtained, the fourth version has the potential to optimise the lung cancer diagnosis process.

Non-invasive radionuclide molecular visualization of human epidermal growth factor receptor type 2 (HER2) can provide stratifcation of patients for HER2-targeting therapy. This method can also enable monitoring of the response to such therapies and thereby the treatment will be more personalized and efficient. Phase I clinical evaluation of two scaffold protein-based imaging probes, [99mTc]Tc-(HE)3-G3 and [99mTc]Tc-ADAPT6, demonstrated that their injections are safe, well-tolerated and cause low level of absorbed and equivalent doses. The goal of this preclinical study was to select the best probe for patients’ stratification and for response monitoring. Biodis-tribution of both tracers was compared in mice bearing SKOV-3 xenografts with high HER2 ex-pression and MDA-MB-468 xenografts with very low expression. Changes in accumulation of both probes in SKOV-3 tumors 24 h after injection of trastuzumab were evaluated. Both [99mTc]Tc-ADAPT6 and [99mTc]Tc-(HE)3-G3 permitted high contrast imaging of HER2-expressing tumors and clear discrimination between tumors with high and low HER2 expression. However, [99mTc]Tc-ADAPT6 has better preconditions for higher sensitivity and specificity of stratification. On the other hand, [99mTc]Tc-(HE)3-G3 is capable to sense the decrease of HER2 expression on re-sponse to trastuzumab therapy only 24 h after injection of loading dose. This indicates that this tracer would be better for monitoring early response to such treatment. Results of this study should be considered in planning of further clinical development of HER2 imaging probes.

Neck circumference (NC), neck circumference to height ratio (NHtR) and neck circumference to weight ratio (NWtR) appear to be good candidates for the non-invasive management of non-alcoholic fatty liver disease (NAFLD). This study aimed to evaluate the ability of routine variables to assess and manage NAFLD in participants with obesity and NAFLD included in a 2-year nutritional intervention program. Anthropometric measurements, biochemical variables and imaging techniques were performed at different study time-points (baseline, 6, 12 and 24 months). The nutritional intervention significantly improved all anthropometric measurements as well as the glucose profile and the hepatic enzymes. NC and neck ratios combined with ALT levels and HOMA-IR showed good prediction ability for the hepatic fat content and hepatic steatosis at all the study time-points in a ROC analysis. The prediction ability of the combination panels improved when the weight loss variable was also considered. NC and neck ratios are easy anthropometric measurements that in combination with routine biochemical variables (ALT and HOMA-IR) showed good prediction ability of NAFLD. More research studies are necessary to validate the utility of these simple and easy variables as surrogate markers of NAFLD since their application could improve the prevention and management of this prevalent disease.

Phase imaging of biochemical samples has been demonstrated for the first time at the Infrared Microspectroscopy (IRM) beamline of the Australian Synchrotron using the usually discarded Near-IR (NIR) region of the synchrotron-IR beam. The synchrotron-IR beam at the Australian Synchrotron IRM beamline has a unique fork shaped intensity distribution as a result of the gold coated extraction mirror shape, which includes a central slit for rejection of the intense X-ray beam. The resulting beam configuration makes any imaging task challenging. For intensity imaging, the fork shaped beam is usually tightly focused to a point on the sample plane followed by a pixel-by-pixel scanning approach to record the image. In this study, a pinhole was aligned with one of the lobes of the fork shaped beam and the Airy diffraction pattern was used to illuminate biochemical samples. The diffracted light from the samples was captured using a NIR sensitive lensless camera. A rapid phase-retrieval algorithm was applied to the recorded intensity distributions to reconstruct the phase information corresponding to different planes. The preliminary results are promising to develop multimodal imaging capabilities at the IRM beamline of the Australian Synchrotron.

Breast cancer is among the most common and fatal diseases for women, and no permanent treatment has been discovered. Thus, early detection is a crucial step to control and cure breast cancer that can save the lives of millions of women. For example, in 2020, more than 65% of breast cancer patients were diagnosed in early-stage of cancer, from whom all survived cancer. Although early detection is the most effective approach for cancer treatment, breast cancer screening conducted by radiologists is very expensive and time-consuming. More importantly, conventional methods of analyzing breast cancer images suffer from high false detection rates. Different breast cancer imaging modalities are used to extract and analyze the key features affecting diagnosis and treatment of breast cancer. These imaging modalities can be divided into subgroups such as mammograms, ultrasound, magnetic resonance imaging, histopathological images, or any combination of them. Radiologists or pathologists analyze images produced by these methods manually that leads to increase the risk of wrong decisions for cancer detection. Thus, utilization of new automatic methods to analyze all kinds of breast screening images to assist radiologists to interpret images is required. Recently, artificial intelligence (AI) has been widely utilized to automatically improve the early detection and treatment of different types of cancer, specifically breast cancer, thereby enhancing the survival chance of patients. Advances in AI algorithms, such as deep learning, and availability of datasets obtained from various imaging modalities have opened an opportunity to surpass limitations of current breast cancer analysis methods. In this article, we first review breast cancer imaging modalities, and their strengths and limitations. Then, we explore and summarize the most recent studies that employed AI in breast cancer detection using various breast imaging modalities. In addition, we report available datasets on the breast cancer imaging modalities which are important in developing AI-based algorithms and training deep learning models. In conclusion, this review paper tries to provide a comprehensive resource to help researchers working in breast cancer imaging analysis.

Non-invasive radionuclide imaging of human epidermal growth factor receptor type 2 (HER2) expression in breast, gastroesopha-geal and ovarian cancers may stratify patients for treatment using HER2-targeted therapeutics. Designed ankyrin repeat proteins (DARPins) are a promising type of targeting probes for radionuclide imaging. In clinical studies, the DARPin [99mTc]Tc-(HE)3-G3, labeled using a peptide-based chelator His-Glu-His-Glu-His-Glu ((HE)3), provided clear imaging of HER2 expressing breast cancer 2-4 h after injection. The goal of this study was to evaluate if the use of cysteine-containing peptide-based chelators Glu-Glu-Glu-Cys (E3C), Gly-Gly-Gly-Cys (G3C), and Gly-Gly-Gly-Ser-Cys connected via a (Gly-Gly-Gly-Ser)3-linker (designated as G3-(G3S)3C) would further improve the contrast of imaging using 99mTc-labeled derivatives of G3. The labeling of the new variants of G3 provided a radiochemical yield over 95%. Labeled G3 variants bound specifically to human HER2-expressing cancer cell lines with affinity in the range 1.9-5 nM. Biodistribution of [99mTc]Tc-G3-G3C, [99mTc]Tc-G3-(G3S)3C, and [99mTc]Tc-G3-E3C in mice was compared with the biodistribution of [99mTc]Tc-(HE)3-G3. It was found that the novel variants provide specific accumulation in HER2-expressing human xenografts and enable discrimination between tumors with high and low HER2 expression. However, [99mTc]Tc-(HE)3-G3 provided better contrast between tumors and the most frequent metastatic sites of HER2-expressing cancers and is therefore more suitable for clinical applications.

18F-fluorodeoxyglucose positron emission tomography and computed tomography (18F-FDG PET-CT) is increasingly used in the diagnosis, prognosis, staging, and treatment monitoring of many tumor types. However, only a small number of studies have reported the use of 18F-FDG PET-CT in intrahepatic cholangiocarcinoma (ICC). This study aimed to examine the accuracy of tumor staging in ICC by using 18F-FDG PET-CT. Between January 2009 and December 2020, patients with suspected ICC were retrospectively enrolled in the study and underwent imaging. The sensitivity and specificity of 18F-FDG PET-CT, CT, and magnetic resonance imaging (MRI) in detecting tumors, satellite focus, vascular invasion, and lymph node metastases were analyzed. The efficacy of 18F-FDG PET-CT for tumor staging was evaluated. Of the 110 patients who were enrolled in the study, 52 underwent surgical treatment and 45 were histologically diagnosed with ICC. When compared with CT or MRI, 18F-FDG PET-CT had similar sensitivity and specificity values for diagnosing satellite focus and vascular and bile duct invasion; however, PET-CT showed higher accuracy in diagnosing regional lymph node metastases. The accuracy of tumor staging by 18F-FDG PET-CT was higher than that by CT/MRI. Thus, 18FDG PET-CT may support tumor staging in ICC.

Real-time closed-loop control of metallurgical processes is still in its infancy, mostly based on simple models and limited sensor data, challenged by extreme temperature, harsh process conditions. Contact-free thermal imaging-based measurement approaches thus appear to be particularly suitable for process monitoring. With the potential to generate vast amounts of accurate data in real-time, combined with artificial intelligence methods to enable real-time analysis and integration of expert knowledge, thermal spectral imaging is identified as a promising method offering more robust and accurate identification of key parameters, such as surface temperature, morphology, composition and flow rate.

Aim. In the current study, we aimed at identifying resting-state brain networks, which are different in patients with depression compared to healthy individuals. Moreover, we analyzed the potential for clinical use of different network measures that could discriminate the two groups and thus help the diagnostic process. Method and subjects. We recruited 90 subjects: 49 healthy controls (HC) and 41 patients with a major depressive episode (MDE). All subjects underwent clinical evaluation and functional resting-state MRI. The data were processed to investigate functional connectivity network measures across the two groups using Brain Connectivity Toolbox. The statistical inferences were made at the functional networks level, using false discovery rate method. Independent samples t-test was performed on the network measures mean values to reveal differences between HC and MDE groups. Permutation-based statistical testing was used to test the significance of the difference between the distributions of the network measures by nodes for HC and MDE groups. Linear discriminant analysis was used to differentiate between the groups. Results and discussion. Significant differences in FC between depressed patients and healthy controls were found with the most prominent changes encompassing within-region as well as between-region connectivity of occipital lobe areas such as precuneus (PreCu), cuneus (Cu), superior occipital gyrus (SOG), lingual gyrus (LG), fusiform gyrus (FG), cerebellum, along with limbic structures including the hippocampus (Hipp) and cingulate gyrus. Linear discriminant analysis demonstrated that the full connectivity matrices, as well as those with only the significant connections identified in advance, were the most precise in differentiating between depression and health. These measures reached precision levels of 97% and 94%, respectively. Conclusion. Our study delivered further evidence about impairment of functional connectivity networks in MDE that may contribute to differentiate patients with depression from healthy subjects.

Background: The thoracolumbar fascia (TLF) is thought to play a role in the development of LBP, but it is not yet clear which factor of TLF changes is a cause and which is an effect. Therefore, some studies used the cross-correlation function (CCR) to reveal time-dependent relationships between biomechanical and neuromotor factors. Methods: Ten patients with acute low back pain (aLBP) were matched to healthy controls. Simultaneous recording of surface electromyography (sEMG) of the erector spinae muscle (ES) and dynamic ultrasound (US) images of TLF deformation were performed during trunk extension. CCR functions and Granger causality were used to describe the relationship between the two measures. Results: CCR time lags were significant higher in the aLBP group (p = 0.04). Granger causality (GC) showed a direct effect of TLF deformation on ES activation only in the aLBP group (p &lt; 0.03). Conclusions: The results suggest that in aLBP, ES activity is significantly affected by TLF, whereas this relation-ship is completely random in healthy subjects studied with CCR and GC comparisons of dynamic US imaging and sEMG data signals. Fascia-related disturbances in neuromotor control, particularly due to altered muscle spindle functions, are suspected as a possible mechanism behind this.

Since 2007, at the Electron Science Research Institute (ESRI) nano-fabrication laboratories, Edith Cowan University, Australia, we have devoted research efforts to the synthesis and characterization of bismuth-containing ferrite-garnet-type thin-film magneto-optic (MO) materials of different compositions. We report on the development and properties of highly bismuth-substituted iron-garnet thin films prepared by using radio frequency (RF) magnetron sputtering. We study the process parameters associated with the RF magnetron sputter deposition technique and investigate the results of optimizing process parameters and implementing several special techniques including the fabrication of co-sputtered nanocomposite films, all-garnet multilayer structures, applying oxygen plasma treatment on amorphous garnet layers just after the deposition process, and designing modifications of the annealing crystallization process and regimes for achieving the best MO properties. We demonstrated significant improvement in MO properties of Bi-containing ferrite-type garnet thin-film materials, including record-high MO figures of merit and improved conventional and un-conventional hysteresis loops of Faraday rotation. The attractive optical, magnetic, and magneto-optic properties obtained in highly bismuth-substituted iron garnet thin-film materials of multiple composition types are relevant in the context of manufacturing next-generation ultra-fast optoelectronic devices, such as light intensity switches and modulators, high-speed flat panel displays, and high-sensitivity sensors.

The recent COVID-19 pandemic has caused tremendous damage to social economy and people’s health. Some major issues fighting COVID-19 include early and accurate diagnosis and the shortage of ventilator machines for critical patients. In this work, we propose a closed-loop solution to deal with COVID-19: portable biosensing and wearable photoacoustic imaging for early and accurate diagnosis of infection and magnetically neuromodulation or minimally invasive electrical stimulation to replace the traditional ventilation. Proposed technique can guarantee ubiquitous and onsite detection, and electrical hypoglossal stimulator can be more effective in helping severe patients as well as reducing complications caused by ventilators.

There is an increasing need for effective anxiety and pain reduction during medical imaging procedures in children. This is a complex issue, addressed by both non-pharmacological or pharmacological approaches. Dexmedetomidine is a fairly recently marketed, selective α2-adrenergic agonist, and can be administered intranasally. To develop an evidence-guided clinical protocol, we investigated its (side)-effects, preconditions and safety aspects following intranasal dexmedetomidine in children (1 month-5 years) for procedural sedation during medical imaging. To do so, a systematic search (PubMed, Embase, CINAHL (12/2021)) was performed to identify clinical studies on intranasal dexmedetomidine for procedural sedation for medical imaging (Computer Tomography, Magnetic Resonance Imaging). Following screening and quality assessment, 8 studies were retained. Nasal nebulization was considered the best administration method, dosing varied between 2 to 4 µg/kg (age-dependent) 30-45 minutes prior to imaging, and contra-indications or restrictions on oral intake were somewhat consistent across studies. Valid sedation scores were routinely used to assess sedation and the need for rescue dosing, while discharge was generally based on the Aldrete score (score ≥9). Heart rate, blood pressure and saturation were routinely monitored, with commonly observed bradycardia or hypotension (decrease by 20%). Based on these findings, a roadmap for evidence-guided clinical protocol was generated.

Cancer invasion through basement membranes represents the initial step of tumor dissemination and metastasis. However, little is known about how human cancer cells breach basement membranes. Here, we used a 3-dimensional in vitro invasion model consisting of cancer spheroids encapsulated by a basement membrane and embedded in 3D collagen gels to visualize the early events of cancer invasion by confocal microscopy and live-cell imaging. Human breast cancer cells generated large numbers of basement membrane perforations, or holes, of varying sizes that expanded over time during cell invasion. We used a wide variety of small molecule inhibitors to probe the mechanisms of basement membrane perforation and hole expansion. Protease inhibitor treatment (BB94), led to a 63% decrease in perforation size. After myosin II inhibition (blebbistatin), basement membrane perforation area decreased by only 15%. These treatments produced correspondingly decreased cellular breaching events. Interestingly, inhibition of actin polymerization dramatically decreased basement membrane perforation by 80% and blocked invasion. Our findings suggest that human cancer cells can primarily use proteolysis and actin polymerization to perforate the BM and to expand perforations for basement membrane breaching, with a relatively small contribution from myosin II contractility.

Growing interest surrounds the assessment of perivascular spaces (PVS) on magnetic resonance imaging (MRI) and their validation as a clinical biomarker of adverse brain health. Nonetheless, the limits of validity of current state-of-the-art segmentation methods are still unclear. Here, we propose an open-source three-dimensional computational framework comprising 3D digital reference objects and evaluate the performance of three PVS filtering methods under various spatiotemporal imaging considerations (including sampling, motion artefacts, and Rician noise). Specifically, we study the performance of the Frangi, Jerman and RORPO filters in enhancing PVS-like structures to facilitate segmentation. Our findings were three-fold. First, as long as voxels are isotropic, RORPO outperforms the other two filters, regardless of imaging quality. Unlike the Frangi and Jerman filters, RORPO’s performance does not deteriorate as PVS volume increases. Second, the performance of all “vesselness” filters is heavily influenced by imaging quality, with sampling and motion artefacts being the most damaging for these types of analyses. Third, none of the filters can distinguish PVS from other hyperintense structures (e.g. white matter hyperintensities, stroke lesions, or lacunes) effectively, the area under precision-recall curve dropped substantially (Frangi: from 94.21 [IQR 91.60, 96.16] to 43.76 [IQR 25.19, 63.38]; Jerman: from 94.51 [IQR 91.90, 95.37] to 58.00 [IQR 35.68, 64.87]; RORPO: from 98.72 [IQR 95.37, 98.96] to 71.87 [IQR 57.21, 76.63] without and with other hyperintense structures, respectively). The use of our computational model enables comparing segmentation methods and identifying their advantages and disadvantages, thereby providing means for testing and optimising pipelines for ongoing and future studies.

Visualization of deep biological structures in human and animal bodies is not possible through the naked eye due to the scattering of visible light by tissues in tolerable intensities. Different types of imaging modalities based on electromagnetic and pressure waves have been developed that help us image deep biological tissues with varying resolution and contrast. Some of the most widely used modalities are X-ray imaging, ultrasound imaging, MRI imaging, fluorescence imaging, and photoacoustic imaging. Although these techniques have significantly helped the advancement of our understanding of deep biological tissues and functions, they often require the use of exogenous contrast agents to improve their image quality for better investigation. Nanoparticle-based contrast agents have captivated scientists because of multiple advantages associated with them such as their excellent photophysical and chemical properties, ability to be precisely delivered at the target, and superlative tunability. This article is aimed to give a brief outlook on the recent state of art advances in the usage of nanoparticles for preclinical and clinical bioimaging through fluorescence, photoacoustic, and MRI imaging modalities.

A refractive lens is one of the simplest, cost-effective and easily available imaging elements. With a spatially incoherent illumination, a refractive lens can faithfully map every object point to an image point in the sensor plane, when the object and image distances satisfy the imaging conditions. However, static imaging is limited to the depth of focus, beyond which the point-to-point mapping can be only obtained by changing either the location of the lens or the imaging sensor. In this study, the depth of focus of a refractive lens in static mode has been expanded using a recently developed computational reconstruction method, Lucy-Richardson-Rosen algorithm (LRRA). The technique consists of three steps. In this first step, the point spread functions (PSFs) were recorded along different depths and stored in the computer as PSF library. In the next step, the object intensity distribution was recorded. The LRRA was then applied to deconvolve the object information from the recorded intensity distributions in the final step. The results of LRRA were compared against two well-known reconstruction methods namely Lucy-Richardson algorithm and non-linear reconstruction.

It is one of the central goals of cognitive neuroscience to understand how structure and function relate in the brain. We review how cognitive function characterization has been approached in the past. In addition, we examine the ongoing efforts, as well as the implications for the future. Clinical studies on patients with lesions have provided key insights into the relationship between brain areas and behavior over the past century. We describe cognitive function according to localization considering these early efforts for characterization. We chose a perceptual-cognitive function, namely body perception, to describe our current efforts. Using body perception as an example, we summarize contemporary techniques. Finally, we outline the trajectory of current progress into the future and discuss the implications for clinical and basic neuroscience.

Speckle patterns are formed by random interferences of mutually coherent beams. While speckles are often considered as an unwanted noise in many areas, they also formed the foundation for the development of numerous speckle-based imaging, holography and sensing technologies. In the recent years, artificial speckle patterns have been generated with spatially incoherent sources using static and dynamic optical modulators for advanced imaging applications. In this report, a fundamental study has been carried out with Bessel distribution as the fundamental building block of the speckle pattern: speckle patterns formed by randomly interfering Bessel beams. Indirect computational imaging framework has been applied to study the imaging characteristics. In general, Bessel beams have a long focal depth, which in this scenario is counteracted by the increase in randomness enabling tunability of the axial resolution between the limits of Bessel beam and a Gaussian beam. Three-dimensional computational imaging has been synthetically demonstrated. The presented study will lead to a new generation of incoherent imaging technologies.

Background. To describe the characteristics of anterior mediastinal masses on conventional magnetic resonance imaging (MRI) and to assess the role of the Apparent Diffusion Coefficient (ADC) value in distinguishing benign from malignant mediastinal lesions. Methods. We conducted a retrospective cross-sectional study on 55 patients with anterior mediastinal mass who performed MRI before treatment. Biopsy and histopathological assessments were done after that. A radiologist evaluates the changes of signal intensity on these sequences: T1- weighted VIBE DIXON pre and post-contrast with Gadolinium, T2 HASTE, T2 TIRM, DWI/ADC, to determine the size, margin of the lesion, the presence of fat, cystic in it. ADCs values were calculated from the ADC maps which were constructed from b = 0 and b = 2000 Results. The study was composed of 55 patients, with 5 benign lesions and 50 malignant lesions. The ADCmean, ADCmedian, ADC10, and ADC90 in the histogram-based approach and hot-spot-ROI-based mean ADC for the malignant lesions was significantly lower than those found in benign lesions (P-value <0.05). The hot-spot-ROI-based mean ADC had the highest value in differentiation between benign and malignant mediastinal lesions, between group A (benign lesions, thymoma A, AB, B1) and group B (thymoma B2, B3 and other malignant lesions). The cut-off point of the ADC value differentiating malignant from benign mediastinal lesions was 1,17x10-3mm2/s with sensitivity of 80%, and specificity of 80%. The cut off point of the ADC value differentiating group A from group B was 0.99 x10-3mm2/s with sensitivity of 78,4%, and specificity of 88.9%. The cut-off point of the ADC value differentiating lymphoma from other malignant lesions was 0,91 x10-3mm2/s with sensitivity of 100%, and specificity of 60.5%. Conclusion. Diffusion-weighted MRI and measurement of ADC value in histogram-based approach and hot-spot-ROI-based mean ADC are very helpful in the differentiation between benign and malignant anterior mediastinal lesions.

This study assesses the efficacy of a microwave colonoscopy algorithm to detect colorectal cancer precursors or polyps in an ex-vivo human colon model. The algorithm works with a device composed of a cylindrical ring-shaped switchable antenna array, which can be attached to the tip of a conventional colonoscope as an accessory. The accessory is connected to an external processing unit that generates an acoustic signal when a polyp is detected. Nowadays, 22% of polyps go undetected with conventional colonoscopy and the risk of cancer after a negative colonoscopy can be up to 7.9%. Fifteen ex-vivo freshly excised human colons with cancer (n=12) or polyps (n=3) were examined with the microwave-assisted colonoscopy system simulating a real colonoscopy exploration. Successive measurements of the colon were taken with the microwave-based colonoscopy device and processed with a microwave imaging algorithm. After the experiment, the dielectric properties of the specimens were measured with a coaxial probe and finally the samples underwent a pathology analysis. The results show that all the neoplasms were detected with a sensitivity of 100% and specificity of 87.4%.

Scattering has been always considered a problem in most of the imaging and holography systems. In this project, a 3D imaging system has been developed based on scattering against common beliefs. The 3D imaging system consists of only two components namely a scattering lens, fabricated by grinding the surface of a convex lens using sandpaper and a web camera. The point spread function (PSF) in the form of speckle distribution was recorded using a laser source in the first step. A synthetic object was selected which was convolved with the PSF in a computer to generate the object intensity distribution. The image of the object was reconstructed by processing the PSF and object intensity distribution using a computational reconstruction method called non-linear reconstruction. The recorded PSF was scaled and the process was repeated for a different synthetic object. The concept was extended to 3D by summing the object intensity distributions generated using PSFs with different scaling factors. The image at different planes can be reconstructed using the PSFs corresponding to that plane.

Indirect imaging methods involve at least two steps, namely optical recording, and computational reconstruction. The optical recording process uses an optical modulator that transforms the light from the object into a typical intensity distribution. This distribution is numerically processed to reconstruct the object’s image corresponding to different spatial and spectral dimensions. There have been numerous optical modulation functions and reconstruction methods developed in the past years for different applications. In most cases, a compatible pair of optical modulation function and reconstruction method gives optimal performance. A new reconstruction method termed non-linear reconstruction (NLR) was developed in 2017 to reconstruct the object image in the case of optical scattering modulators. During the years, it was revealed that the NLR could reconstruct an object’s image modulated by an axicons, bifocal lenses and even exotic spiral diffractive elements, which generate deterministic optical fields. Apparently, NLR seems to be a universal reconstruction method for indirect imaging. In this review, the performance of NLR has been investigated for many deterministic and stochastic optical fields. Simulation and experimental results for different cases are presented and discussed.

Artificial intelligence is dramatically transforming medical imaging. We assessed the levels of artificial intelligence use among radiology trainees and explored their perceived impact of artifi-cial intelligence on the radiology workflow and radiology profession, in correlation with the perceived ease of use and behavioral intention to use artificial intelligence. This cross-sectional study enrolled radiology trainees from Saudi Arabia, and an online 5-part-structured question-naire was disseminated via online networks to trainee in July 2021. We included 98 participants (51 male; age 27.59±2.02 years). Level of use was low; few used it in routine practice (7%). The impact of artificial intelligence on the radiology workflow was positively perceived in all radi-ology workflow steps (3.64–3.97 out of 5). A positive impact on the radiology profession was more frequently perceived for technical and performance aspects (81%–85%) compared with prestige and legal aspects (64%–71%). Perceived ease of use and behavioral intention to use arti-ficial intelligence was associated with the current professional activity, level of use artificial in-telligence use, and perceived impact on the profession as well as on radiology workflow (p<0.05). Levels of artificial intelligence use in radiology are very low. The perceived positive impact of ar-tificial intelligence on radiology workflow and profession is correlated with an increase in be-havioral intention to use artificial intelligence. Thus, increasing awareness about the favorable impact can improve the behavioral use.

Boron Neutron Capture Therapy (BNCT) is a promising binary disease-targeted therapy, as neutrons preferentially kill cells labeled with boron (¹⁰B), which makes it a precision medicine treatment modality that provides a therapeutic effect exclusively on patient-specific tumor spread. Contrary to what is usual in radiotherapy, BNCT proposes cell-tailored treatment planning rather than to the tumor mass. The success of BNCT depends mainly on the sufficient spatial biodistribution of ¹⁰B located around or within neoplastic cells to produce a high-dose gradient between the tumor and healthy tissue. However, it is not yet possible to precisely determine the concentration of ¹⁰B in a specific tissue in real-time using noninvasive methods. Critical issues remain to be resolved if BNCT is to become a valuable, minimally invasive, and efficient treatment. Moreover, functional imaging technologies such as PET can be applied to determine biological information that can be used for the combined-modality radiotherapy protocol for each specific patient. Anyway, not only imaging methods but also proteomics and gene expression methods will facilitate BNCT becoming a modality of personalized medicine. This work provides an overview of the fundamental principles, recent advances, and future directions of BNCT as cell-targeted cancer therapy for personalized radiation treatment.

In plants, water flows are the major driving force behind the growth and play a crucial role in the life cycle. To study hydrodynamics, methods based on tracking small particles inside water flows occupy a special place. Due to these tools, it is possible to get information about the dynamics of the spatial distribution of the fluxes characteristics. In this paper, using contrast-enhanced MRI, we have shown that gadolinium chelate, used as an MRI contrast agent, marks the structural characteristics of xylem bundles of maize stem nodes and internodes. Supplementing MRI data, a high-precision visualization of xylem vessels by laser scanning microscopy was used to reveal structural and dimensional characteristics of the stem vascular system. In addition, we proposed the concept of using the prototype "Y-type xylem vascular bundles" as a model of the elementary connection of vessels within the vascular system. A Reynolds number can match the microchannel model with the real xylem vessels.

Over recent years, the importance of patent literature has become more recognized in the academic setting. In the context of artificial intelligence, deep learning, and data sciences, patents are relevant to not only industry but also academe and other communities. In this article, we focus on deep tomographic imaging and perform a preliminary landscape analysis of the related patent literature. Our search tool is PatSeer . Our patent bibliometric data is summarized in various figures and tables. In particular, we qualitatively analyze key deep tomographic patent literature.

Quantitative differential phase contrast (qDPC) imaging has become an important method of optical measurement and life science research in microscopy because of its high reconstruction resolution and non-invasive, high-contrast and quantitative imaging of biological samples. Despite the continuous development of the principle and algorithm, the frame rate of the existing qDPC algorithm is still much lower than that of camera acquisition, so it is hardly applied to real-time image the fast-moving biological samples. In this paper, based on color-coded multiplexing strategy, a compact real-time quantitative phase imaging system is designed to realize multi-mode imaging. The system employs a programmable LED array to illuminate directly, and the phase reconstruction algorithm is deployed in the graphics processing unit (GPU) of the laptop to accelerate the calculation. The system can achieve high-speed quantitative phase imaging of non-stained biological samples, and the frame rate can reach 60fps. The device has the advantages of compact structure, low cost and portability. Thus, it is suitable for mobile medical applications.

Functional Data Analysis (FDA) is a relatively new field of statistics dealing with data expressed in the form of functions. FDA methodologies can be easily extended to the study of imaging data, an application proposed in Wang et al. (2020), where the authors settle the mathematical groundwork and properties of the proposed estimators. This methodology allows for the estimation of mean functions and simultaneous confidence corridors (SCC), also known as simultaneous confidence bands, for imaging data and for the difference between two groups of images. This is especially relevant for the field of medical imaging, as one of the most extended research setups consists on the comparison between two groups of images, a pathological set against a control set. FDA applied to medical imaging presents at least two advantages compared to previous methodologies: it avoids loss of information in complex data structures and avoids the multiple comparison problem arising from traditional pixel-to-pixel comparisons. Nonetheless, computing times for this technique have only been explored in reduced and simulated setups (Arias-López et al., 2021). In the present article, we apply this procedure to a practical case with data extracted from open neuroimaging databases and then measure computing times for the construction of Delaunay triangulations, and for the computation of mean function and SCC for one-group and two-group approaches. The results suggest that previous researcher has been too conservative in its parameter selection and that computing times for this methodology are reasonable, confirming that this method should be further studied and applied to the field of medical imaging.

Cracking in a wide array of industrial components and structures pose a significant threat to their integrity. Detecting cracks using ultrasonic inspection techniques is a widespread activity for economic reasons but there are limitations to the techniques due to the morphology of cracks, such as fatigue cracks. In addition to detection there is a need to measure the size of the cracks which are often within the volume of the material. Ultrasonic techniques are well-suited to look inside the volume of the material but achieving sufficient sensitivity to the tip of the cracks in particular is practically difficult. Without an accurate knowledge of where the tip of the crack lies there can be significant uncertainty in sizing measurements. Machine Learning (ML) techniques are being developed to aid in the inspection and monitoring tasks but presenting the ultrasonic data in a suitable way for ML is very important. Following on from recent work presenting the development of the snooker algorithm to create images termed parameter-spaces, this paper presents how these images can be input into neural network based ML systems to automatically size these critical cracks.

Cognitive rehabilitation is useful for many after traumatic brain injury (TBI), but we lack critical knowledge about which patients benefit the most from different approaches. Advanced neuroimaging techniques have provided important insight into brain pathology and systems plasticity after TBI and have potential to inform new practices in cognitive rehabilitation. In this study, we aimed to identify candidate structural brain measures with relevance for rehabilitation of cognitive control (executive) function after TBI. Twenty-eight patients (9 female, mean age 40.5 (SD = 13.04) years) with moderate/severe TBI (>21 months since injury) that participated in a randomized controlled cognitive rehabilitation trial (NCT02692352) were included in the analyses. Regional brain volume was extracted from T1-weighted MRI scans before treatment using tensor-based morphometry. Both positive and negative associations between treatment outcome (everyday cognitive control function) and regional brain volume were observed. The most robust structural brain measures with relevance for improvement in function were observed in midline fronto-parietal regions, including the anterior and posterior cingulate cortices. The study pro-vides proof of concept and valuable insight for planning future studies focusing on neuroimaging in cognitive rehabilitation after TBI.

Degenerative spinal cord (SC) compression is a frequent pathological condition with increasing prevalence throughout aging. Initial non-myelopathic cervical SC compression (NMDC) might progress over time into potentially irreversible degenerative cervical myelopathy (DCM). While quantitative MRI (qMRI) techniques demonstrated the ability to depict intrinsic tissue properties, longitudinal in-vivo biomarkers to identify NMDC patients who will eventually develop DCM are still missing. Thus, we aim to review the ability of qMRI techniques (such as diffusion MRI, diffusion tensor imaging (DTI), magnetization transfer (MT) imaging, magnetic resonance spec-troscopy (1H-MRS)) to serve as prognostic markers in NMDC. While DTI in NMDC patients con-sistently detected lower fractional anisotropy and higher mean diffusivity at compressed levels caused by demyelination and axonal injury, MT and 1H-MRS along with advanced and tract-specific diffusion MRI recently revealed microstructural alterations also rostrally pointing to Wallerian degeneration. Recent studies also disclosed significant relationship between micro-structural damage and functional deficits, assessed by qMRI and electrophysiology, respectively. Thus, tract-specific qMRI in combination with electrophysiology critically extend our under-standing of the underlying pathophysiology of degenerative SC compression and may provide predictive markers of DCM development for accurate patient management. However, the prog-nostic value must be validated in longitudinal studies.

Externalizing behavior in its more extreme form is often considered a problem to the individual, their families, teachers and society as a whole. Several brain structures have been linked to externalizing behavior and such associations may arise if the (co)development of externalizing behavior and brain structures share the same genetic and/or environmental factor(s). We assessed externalizing behavior with the Child Behavior Checklist and Youth Self Report, and brain volumes and white matter integrity (FA and MD) with magnetic resonance imaging in the BrainSCALE cohort, consisting of twins and their older siblings from 112 families measured longitudinally at ages 10, 13, and 18 years of the twins. Genes influenced externalizing behavior and changes therein (h2 up to 88%). More pronounced externalizing behavior was associated with higher FA (observed correlation rph up to +0.20) and lower MD (rph up to –0.20); with sizeable genetic correlations (FA ra up to +0.42; MD ra up to –0.33). Cortical gray matter (CGM; rph up to –0.20) and cerebral white matter (CWM; rph up to +0.20) volume were phenotypically but not genotypically associated with externalizing behavior. These results suggest a potential mediating role for global brain structures in the display of externalizing behavior during adolescence that are both partially explained by the influence from the same genetic factor.

Abstract—Low-frequency Fahræus–Lindqvist-driven (not blood pressure-driven) oscillations in the small vessels are crucial because oscillations in small vessels support nutrient supply. Understanding of this is critical in type 2 diabetes mellitus (T2DM) to develop therapeutic measures to prevent Alzheimer's Disease Related Dementias: vascular factors contribute to cerebrovascular disease as well as mild cognitive impairment and dementia, which are predicted to affect 152 million people by 2050 (Alzheimer's Disease International London, UK, 2019). In this clinical study, we performed functional near-infrared spectroscopy (fNIRS) of the forehead to investigate the effect of the Mini-Cog with three-item recall test on the prefrontal cortex (PFC) activation and the relative oscillatory power in the 0.01–0.02-Hz (Fahræus–Lindqvist effect) and 0.021–0.052 Hz (smooth muscle autonomic innervation) frequency bands in elderly (60 years and older) T2DM and age-matched controls. We found a significant (p<0.01) difference in the PFC activation between elderly subjects with T2DM and age-matched elderly controls. Moreover, power spectral density (PSD) analysis revealed a significantly lower relative power in 0.021–0.052 Hz (smooth muscle autonomic innervation) frequency band in elderly subjects with T2DM during the Mini-Cog three-item recall test. Furthermore, a drop in the oscillatory power in the 0.01–0.02-Hz frequency band during Mini-Cog three-item recall test was found more pronounced in the elderly subjects with T2DM. Therefore, our study highlighted portable brain imaging to capture cerebrovascular reactivity to cognitive load that may provide a biomarker of cerebrovascular dysfunction in T2DM.Clinical Relevance— Our study establishes forehead portable brain imaging for monitoring cerebrovascular function in T2DM under cognitive load.

Intratumoral heterogeneity associates with more aggressive disease progression and worse patient outcomes. Understanding the reasons enabling the emergence of such heterogeneity remains incomplete, which restricts our ability to manage it from a therapeutic perspective. Technological advancements such as high-throughput molecular imaging, single-cell omics and spatial transcriptomics now allow recording the patterns of spatiotemporal heterogeneity in a longitudinal manner, thus offering insights into the multi-scale dynamics of its evolution. Here, we review latest technological trends and biological insights from molecular diagnostics as well as spatial transcriptomics, both of which have witnessed a burgeoning growth in recent past in terms of mapping heterogeneity within tumor cell types as well as stromal constitution. We also discuss ongoing challenges, indicating possible ways to integrate insights across these methods to have a systems-level spatiotemporal map of heterogeneity in each tumor, and a more systematic investigation of implications of heterogeneity for the patient outcomes.

Background: Left ventricular noncompaction (LVNC) is a distinct cardiomyopathy characterized by the presence of a two-layer myocardium with prominent trabeculation and deep intertrabecular recesses. The diagnosis of LVNC can be challenging because the diagnostic criteria are not uniform. The aim of our study was to evaluate echocardiographic and CMR findings in a group of children with isolated LVNC. Methods: From February 2008 to July 2021, pediatric patients under 18 years of age at the time of diagnosis with echocardiographic evidence of isolated LVNC were prospectively enrolled. The patients underwent echocardiography and contrast-enhanced cardiovascular magnetic resonance (CMR) with late gadolinium enhancement to assess myocardial noncompaction, ventricular size, and function. Results: A total of 34 patients with a median age of 11.9 years were recruited. Patients were followed prospectively for a median of 5.1 years. Of the 31 patients who met Jenni’s criteria in echocardiography, CMR was performed in 27 (79%). Further comprehensive analysis was performed in the group of 25 patients who met the echocardiographic and CMR criteria for LVNC. In echocardiography, the median NC/C ratio in systole was 2.60 and in diastole 3.40. In 25 out of 27 children (93%), LVNC was confirmed by CMR according to Petersen’s criteria, with a median NC/C ratio of 3.27. Conclusions: 1) Echocardiography precisely identifies patients with LVNC. 2) Echocardiography is a good method for monitoring LV systolic function, but CMR is indicated for the precise assessment of LV remodeling and RV size and function as well as for the detection of myocardial fibrosis.

Phenotypical screening is a widely used approach in drug discovery for the identification of small molecules with cellular activities. However, functional annotation of identified hits often poses a challenge. The development of small molecules with narrow or exclusive target selectivity such as chemical probes and chemogenomic (CG) libraries, greatly diminishes this challenge, but non-specific effects caused by compound toxicity or interference with basic cellular functions still poses a problem to associate phenotypic readouts with molecular targets. Hence, each compound should ideally be comprehensively characterized regarding its effects on general cell functions. Here, we report an optimized live-cell multiplexed assay that classifies cells based on nuclear morphology, presenting an excellent indicator for cellular responses such as early apoptosis and necrosis. This basic readout in combination with the detection of other general cell damaging activities of small molecules such as changes in cytoskeletal morphology, cell cycle and mitochondrial health provides a comprehensive time-dependent characterization of the effect of small molecules on cellular health in a single experiment. The developed high-content assay offers multi-dimensional comprehensive characterization that can be used to delineate generic effects regarding cell functions and cell viability, allowing an assessment of compound suitability for subsequent detailed phenotypic and mechanistic studies.

The accuracy of multi-parametric MRI (mpMRI) in pre-operative staging of prostate cancer (PCa) remains controversial. Objective: To evaluate the ability of mpMRI to accurately predict PCa extra-prostatic extension (EPE) on a side-specific basis using a risk-stratified 5-point Likert scale. This study also aimed to assess the influence of mpMRI scan quality on diagnostic accuracy. Patients and Methods: We included 124 men who underwent robot-assisted RP (RARP) as part of the NeuroSAFE PROOF study at our centre. Three radiologists retrospectively reviewed mpMRI blinded to RP pathology and assigned a Likert score (1-5) for EPE on each side of the prostate. Each scan was also ascribed a Prostate Imaging Quality (PI-QUAL) score for assessing the quality of the mpMRI scan, where 1 represents poorest and 5 represents best diagnostic quality. Outcome measurements and statistical analyses: Diagnostic performance is presented for binary classification of EPE including 95% confidence intervals and area under the receiver operating characteristic curve (AUC). Results: A total of 231 lobes from 121 men (mean age 56.9 years) were evaluated. 39 men (32.2%), or 43 lobes (18.6%) had EPE. Likert score ≥3 had sensitivity (SE), specificity (SP), NPV, PPV of 90.4%, 52.3%, 96%, 29.9%, respectively, and AUC was 0.82 (95% CI: 0.77-0.86). AUC was 0.63 (95% CI: 0.37-0.9), 0.77 (0.71-0.84) and 0.92 (0.88-0.96) for biparametric scans, PI-QUAL 1-3 and PI-QUAL 4-5 scans, respectively. Conclusions: MRI can be used effectively by genitourinary radiologists to rule out EPE and help inform surgical planning for men undergoing RARP. EPE prediction was more reliable when the MRI scan was a) multi-parametric and b) of a higher image quality according to the PI-QUAL scoring system.

Genetic code expansion has emerged as an enabling tool to provide insight into functions of understudied proteinogenic species such as small proteins and peptides, and to probe protein biophysics in the cellular context. Here we discuss recent technical advances and applications of genetic code expansion in cellular imaging of complex mammalian protein species, along with considerations and challenges upon using the method.

Hyperspectral reflectance imaging is an emerging method for rapid non-invasive quantitative screening of plant traits. This method is essential for high-throughput phenotyping and hence for accelerated breeding of crop plants as well as for precision agriculture practices. However, extraction of sensible information from reflectance images is hindered by the complexity of plant optical properties, especially when they are measured in the field. We propose using reflectance indices (Plant Senescence Reflectance Index, PSRI; Anthocyanin Reflectance Index, ARI; and spectral deconvolution) previously developed for remote sensing of vegetation and point-based reflectometers to infer the spatially resolved information on plant development and biochemical composition using ripening apple fruit as the model. Specifically, the proposed approach enables capturing data on distribution of chlorophylls and primary carotenoids as well as secondary carotenoids (both linked with fruit ripening and leaf senescence during plant development) as well as the information on spatial distribution of anthocyanins (known as stress pigments) over the plant surface. We argue that the proposed approach would enrich the phenotype assessments made on the base of reflectance image analysis with valuable information on plant physiological condition, stress acclimation state, and the progression of the plant development.

Historically, the evaluation and assessment of the clinical response to treatment for canine back pain is subjective and relies on owner and clinician assessment of pain. This study evaluated the use of sequential infrared thermal images as a measure of the response of canine patients with back pain to a prescribed series of photobiomodulation therapy (PBMT) treatments. Qualifying participants had histories of pain and dysfunction associated with spinal osteoarthritis or intervertebral disk disease, or of non-specific uni- or bilateral back pain along the paravertebral epaxial muscles. Each patient was initially thermally imaged prior to PBMT treatment and then received multiple PBMT treatments delivered to the appropriate spinal area on days 1, 2, 3, and 4. Participants were reimaged on day 7. Thermal images provided an objective measure of superficial temperature changes over the area of PBMT treatment of each patient after the PBMT regimen. The temperature correlated with statistically significant changes in Colorado State University Canine Chronic Pain Scale scoring (CPS) and owner assessment using the Canine Brief Pain Inventory (CBPI), which includes a Pain Severity Score (PSS) and Pain Interference Score (PIS). The correlation of objective thermal imaging data with more subjective outcome measures suggests thermal imaging may be a valuable additional tool in monitoring therapy outcome.

In this study, a new method for synthesizing Au-NaYF4:Yb3+/Er3+-DSPE-PEG2K nanocomposites was introduced. Using a hydrothermal method, the synthesized Yb3+- and Er3+-codoped NaYF4 upconversion luminescent materials and Au nanoparticles were doped into upconversion nanomaterials and modified with DSPE-PEG2k up-conversion nanomaterials. This material is known as Ag-UCNPs-DSPE-PEG2k, it improves both the luminous intensity because of the doped Au nanoparticles and has low cytotoxicity because of the DSPE-PEG2k modified. Exciting UCNPs with a wavelength of 980nm near-infrared light will emit light with a wavelength of 520nm to further excite gold nanoparticles to convert light energy into heat. Successful synthesized gold nanoparticles was confirmed using transmission electron microscopy (TEM). The morphology of UCNPs was observed using scanning electron microscopy (SEM), and the mapping confirmed the successful doping of Au nanoparticles. Fluorescence spectra were used to compare changes in luminescence intensity before and after doping Au nanoparticles. The cytotoxicity of Au-UCNPs-DSPE-PEG2K was tested via the cell counting kit-8 (CCK-8) method, and its imaging ability was characterized using the Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) method.

Simultaneously being a non-radiative and non-invasive technique makes magnetic resonance imaging (MRI) one of the highly sought imaging techniques for the early diagnosis and treatment of diseases. Despite more than four decades of research on finding a suitable imaging agent from fluorine for clinical applications, it still lingers as a challenge to get the regulatory approval compared to its hydrogen counterpart. The pertinent hurdle is the simultaneous intrinsic hydrophobicity and lipophobicity of fluorine and its derivatives that make them insoluble in any liquids, strongly limiting their application in areas such as targeted delivery. A blossoming technique to circumvent the unfavorable physicochemical characteristics of perfluorocarbon compounds (PFCs) and guarantee a high local concentration of fluorine in the desired body part is to encapsulate them in nanosystems. In this review, we will be emphasizing different types of nanocarrier systems studied to encapsulate various PFCs and fluorinated compounds, headway to be applied as a contrast agent (CA) in fluorine-19 MRI (19F MRI). We would also scrutinize the different types of PFCs and their specific applications and limitations concerning the nanoparticle (NP) system used to encapsulate them studied over the last decade. A critical evaluation for future opportunities would be speculated.

In this study, a new method for synthesizing Ag-NaYF4:Yb3+/Er3+ @ SiO2 nanocomposites was introduced. Using a hydrothermal method, the synthesized Yb3+- and Er3+-codoped NaYF4 upconversion luminescent materials and Ag nanoparticles were doped into upconversion nanomaterials and coated with SiO2 up-conversion nanomaterials. This material is known as Ag-UCNPs-SiO2’ it improves both the luminous intensity because of the doped Ag nanoparticles and has low cytotoxicity because of the SiO2 coating. The morphology of UCNPs was observed using scanning electron microscopy (SEM), and the mapping confirmed the successful doping of Ag nanoparticles. Successful coating of SiO2 was confirmed using transmission electron microscopy (TEM). Fluorescence spectra were used to compare changes in luminescence intensity before and after doping Ag nanoparticles. The reason for the increase in luminescence intensity after doping with Ag nanoparticles was simulated using first-principles calculations. The cytotoxicity of Ag-UCNPs-SiO2 was tested via the cell counting kit-8 (CCK-8) method, and its imaging ability was characterized using the micro-CT method.

Systemic sclerosis is an autoimmune disease characterized by organ fibrosis and vasculopathy. Almost all patients suffer from Raynaud’s phenomenon (RP). Currently, several imaging techniques are available; nailfold video capillaroscopy (NVC) is the most widely available, but flow quantification is not possible with NVC. Novel imaging techniques are of interest in this population. We performed a single-center feasibility study using Micro Vascular Imaging (MVI) as a novel imaging technique for flow quantification of small fingertip vessels. We compared a group of 20 healthy controls (HCs) with 20 Systemic Sclerosis (SSc) patients. In HCs, flow measurements assessed with MVI were statistically significantly higher in individual fingers and combined for all fingers (p&lt;0.0001). As a cut-off value to discriminate HCs from SSc, a peak systolic (PS) flow velocity of &lt;6.9 cm/s and an end-diastolic (ED) flow velocity of &lt;2.68 cm/s was determined. Test characteristics for PS flow velocity showed moderate sensitivity (0.69, 95% CI 0.58-0.78) but high specificity (0.88, 95% CI 0.79-0.93). Similar test characteristics for ED flow velocity were obtained. The optimal cut-off point was estimated at &lt;2.68 cm/s, sensitivity was moderate (0.65, 95% CI 0.53-0.75), specificity was 0.80 (95% CI 0.70-0.87). Here, we present the first study on the use of MVI to assess blood flow in the fingertips with high specificity in SSc patients. Future studies need to investigate correlations with the risk for organ complications, such as digital ulcers or pulmonary arterial hypertension.

In this paper, we present a method for detecting and quantifying pathogens in water samples. The method proposes a portable dark field imaging and analysis system for quantifying E. coli concentrations in water after being labeled with magnetic particles. The system utilizes the tracking of moving micro/nano objects close to or below the optical resolution limit confined in small sample volumes (~ 10 µl). In particular, the system analyzes the effect of volumetric changes due to bacteria conjugation to magnetic microparticles (MP) on their Brownian motion while being suspended in liquid buffer solution. The method allows for a simple inexpensive implementation and the possibility to be used as point-of-need testing system. Indeed, a work-ing prototype is demonstrated with the capacity of quantifying E. coli colony forming units (CFU) at a range of 1x10³ - 6x10³ CFU/mL.

A pilot study on laser 3D printing of inorganic free-form micro-optics is experimentally validated. Ultrafast laser nanolithography is employed for structuring hybrid organic-inorganic material SZ2080TM followed by high-temperature calcination post-processing. The combination allows production of 3D architectures and the heat-treatment results in converting the material to inorganic substance. The produced miniature optical elements are characterized and their optical performance demonstrated. Finally, the concept is validated for manufacturing compound optical components such as stacked lenses. This is opening for new directions and applications of laser made microoptics under harsh conditions such as high intensity radiation, temperature, acidic environment, pressure variations, which include open space, astrophotonics, and remote sensing.

Optical properties of the cornea are responsible for correct vision, ultrastructure allows optical transparency and biomechanical properties governs the shape, elasticity or stiffness of the cor-nea affecting ocular integrity and intraocular pressure. Therefore, optical aberrations, corneal transparency, structure and biomechanics play a fundamental role in the optical quality of hu-man vision, ocular health and refractive surgery outcomes. However, the convergence of those properties is not yet reported at macroscopic scale within the hierarchical structure of the cornea. This work explores the relationships between biomechanics, structure and optical properties (corneal aberrations and optical density) at macrostructural level of the cornea through dual Placido-Scheimpflug imaging and air-puff tonometry systems in a healthy young adult popula-tion. Results showed convergence between optical transparency, corneal macrostructure and biomechanics.

At INFN-LNS, and in collaboration with the ATOMKI laboratories, an innovative multi-diagnostic system with advanced analytical methods has been designed and implemented. This is based on several detectors and techniques (Optical Emission Spectroscopy, RF systems, Interfero-polarimetry, X-ray detectors) and here we focus on high resolution spatially-resolved X-ray spectroscopy, performed by means of a X-ray pin-hole camera setup operating in the 0.5−20 keV energy domain. The diagnostic system was installed at a 14 GHz Electron Cyclotron Resonance (ECR) ion source (ATOMKI, Debrecen), enabling high precision X-ray spectrally-resolved imaging of ECR plasmas heated by hundreds of Watts. The achieved spatial and energy resolution were 0.5 mm and 300 eV at 8 keV, respectively. We here present the innovative analysis algorithm that we properly developed for obtaining Single Photon-Counted (SPhC) images providing the local plasma emitted spectrum in a High-Dynamic-Range (HDR) mode, by distinguishing fluorescence lines of the materials of the plasma chamber (Ti, Ta) from plasma (Ar). This method allows a quantitative characterization of warm electrons population in the plasma (and its 2D distribution) which are the most important for ionization, and also to estimate local plasma density and spectral temperatures. The developed post-processing analysis is also able to remove the readout noise, that is often observable at very low exposure times (msec). The setup is now under update including fast shutters and trigger systems in order to allow simultaneously space and time-resolved plasma spectroscopy during transients, stable and turbulent regimes.

There is increasing interest in identifying biological and imaging markers for the early detection of neurocognitive decline. In addition, non-pharmacological strategies including physical exercise and cognitive interventions may be beneficial for those developing cognitive impairment. The Feuerstein Instrumental Enrichment (FIE) Program is a cognitive intervention based on Structural Cognitive Modifiability and the Mediated Learning Experience (MLE) and aims to promote problem-solving strategies and metacognitive abilities. The FIE program uses a variety of instruments to enhance the cognitive capacity of the individual as a result of mediation. A specific version of the FIE program was developed for the cognitive enhancement of older adults, focusing on strengthening orientation skills, categorization skills, deductive reasoning and memory. We performed a prospective interventional pilot observational study on older subjects with MCI who participated in 30 mediated FIE sessions (two sessions weekly for 15 weeks). Of the 21 subjects who completed the study, there was a significant improvement in memory on the Neurotrax battery comparing pre- and post-intervention scores (pre: M=95.3, SD=12.2, post: M=101.2, SD=7.9, p<.05). Complete sets of anatomical MRI data for voxel-based morphometry, taken at the beginning and the end of the study, were obtained from 16 participants (mean age 83.5 years). Voxel-based morphometry showed an unexpected increase in grey matter (GM) in the anterolateral occipital border and the middle cingulate cortex. These initial findings of our pilot study support the design of randomized trials to evaluate the effect of cognitive training using the FIE Program on brain volumes and cognitive function.