Imaging techniques such as computed tomographies (CT) play a major role in clinical imaging and diagnosis of malignant lesions. In recent years, spectral CT has emerged in the field of computed tomographies, utilizing detailed information from extracted spectral parameters of the specimen. Metal nanoparticle platforms enable effective payload delivery for this technique. Due to the possibility of surface modification, metal nanoparticles are predestined to facilitate molecular tumor targeting. In this work, we demonstrate the feasibility of anti-plasma membrane Heat shock protein 70 functionalized gold nanoparticles (AuNPs) for tumor specific multimodal imaging. Membrane-associated Hsp70 is exclusively presented on the plasma membrane of malignant cells of multiple tumor entities, but not on corresponding normal tissue cells, predestining this target epitope for tumor-selective in vivo targeting. In vitro microscopical analysis revealed the presence of cmHsp70.1-AuNP in the cytosol of tumor cell lines, being internalized via the endosomal-lysosomal pathway. In tumor bearing mice the biodistribution as well as the intratumorally enrichment of AuNP were examined 24h after i.v. application, in vivo. In parallel to spectral CT analysis, histological analysis confirmed the presence of tumor cells. In contrast to control NP, a significant enrichment of cmHsp70.1-AuNPs has been detected selectively in tumors of different preclinical mouse models. Furthermore, the biodistribution of AuNP, following i.v. injection, was analyzed by a machine-learning approach on digitalized slides. In summary, utilizing mHsp70 on tumor cells for guidance of cmHsp70.1 antibody functionalized nanoparticles enables sufficient enrichment and uniform distribution of AuNPs in mHsp70-expressing tumor cells, adequate for various microscopical imaging techniques and spectral-CT-based tumor delineation, in vivo.

Summarizing radiological characteristics between primary lung adenocarcinoma subtypes and correlate them with FDG uptake on PET-CT are important for further treatment. A PET-CT examination was performed on some of the patients and the values of SUV-max were also correlated with the histological and morphological characteristics of masses in the lungs. Results of this analysis showed that the mean size of AIS-MIA cancer was significantly lower than for all other cancer types, while mean size of the acinar cancer was smaller than in solid type of cancer. Metastases were significantly more frequent in solid adenocarcinoma than in acinar, lepidic and AIS-MIA cancer subtypes. The maximum standardized FDG uptake was significantly lower in AIS-MIA than in all other cancer types, and in acinar compared to solid cancer. Papillary adenocarcinoma had higher odds to develop contralateral lymph node involvement compared to other types. Solid adenocarcinoma was associated with higher odds of having metastases and with higher SUVmax. AIS-MIA was associated with lower odds of one unit increase in tumour size, ipsilateral lymph node involvement. Radiology has a significant role in the diagnosis and monitoring of the disease, and in determining its prognosis, and influence on the decision on the method of treatment.

Objective: to evaluate the feasibility of the intra-operative application of a specimen PET/CT imager in a clinical setting. Materials and methods: this is a pilot analysis performed in three patients who received an intra-operative administration of 68Ga-PSMA-11 (n=2) and 68Ga-DOTA-TOC (n=1), respectively. Patients were administrated with PET radiopharmaceuticals to perform radio-guided surgery with a beta-probe detector during radical prostatectomy for prostate cancer (PCa) and salvage lymphadenectomy for recurrent neuroendocrine tumor (NET) of the ileum, respectively. All procedures have been performed within two ongoing clinical trials in our Institute (NCT05596851 and NCT05448157). Pathologic assessment with immunohistochemistry (PSMA-staining and SSA immunoreactivity) was considered as standard of truth. Specimen images were compared with baseline PET/CT images and histopathological analysis. Results: Patients received 1 MBq/Kg of 68Ga-PSMA-11 (PCa) or 1.2 MBq/Kg of 68Ga-DOTA-TOC (NET) prior to surgery. Specimens were collected, positioned in the dedicated specimen container, and scanned to obtain high resolution PET/CT images. In all cases a perfect match was observed between the findings detected by the specimen imager and histopathology. Overall, the PET spatial resolution was sensibly higher for the specimen images compared to the baseline whole-body PET/CT images. Furthermore, the use of the PET/CT specimen imager did not significantly interfere with any procedures, and the overall length of the surgery was not affected using the PET/CT specimen imager. Finally, the radiation exposure of the operating theater staff was lower than 40 µSv per procedure (range 26 – 40 Sv). Conclusion: the image acquisition of specimens obtained by patients who received intra-surgery injection of 68Ga-PSMA-11 and 68Ga-DOTA-TOC was feasible and reliable also in a live-experience session and has been easily adapted to surgery daily-practice. The high sensitivity, together with the evaluation of intra-lesion tumor heterogeneity, were the most relevant results since the data derived from specimen PET/CT imaging matched perfectly with the histopathological analysis.

Following the European Society of Gynaecological Oncology (ESGO), the European Society for Radiotherapy and Oncology (ESTRO), and the European Society of Pathology (ESP) joint guide-lines (2018) for the management of patients with cervical cancer, treatment decisions should be guided by modern imaging techniques. After five years (2023), an update of the ES-GO-ESTRO-ESP recommendations was performed furtherly confirming this statement. Trans-vaginal/transrectal ultrasound (TRS/TVS) or pelvic magnetic resonance (MRI) enables tumour delineation and precise assessment of its local extent, including the evaluation of the depth of infiltration in the bladder- or rectal wall. Additionally, both techniques have very high specificity to confirm the presence of metastatic pelvic lymph nodes but fail to exclude them due to insuffi-cient sensitivity to detect small-volume metastases, as any other currently available imaging modality. In early-stage disease (T1a to T2a1, except T1b3) with negative lymph nodes on TVS/TRS or MRI, surgicopathological staging should be performed. In all other situations, con-trast-enhanced computed tomography (CECT) or 18F-fluorodeoxyglucose positron emission tomography in combination with CT (PET-CT) are recommended to assess extrapelvic spread. The aim of this paper is to review the evidence supporting the implementation of diagnostic imaging with a focus on ultrasound at primary diagnostic workup of cervical cancer.

Background: Appendicitis is a common cause of emergency department visits and appendectomies in the US, with 250,000 appendectomies performed annually. Current diagnostic methods, such as clinical findings, lead to inaccuracies and missed diagnoses, increasing morbidity and mortality. The only solution is surgery, but current hematological tests are not reliable and may lead to unnecessary surgery if the underlying etiology is self-limiting or requires medical treatment. This study explores the role of MRI as a diagnostic modality that can replace US/CT and supplement traditional clinical diagnostic signs while avoiding ionizing radiation and intravenous contrast medium. The purpose of this meta-analysis is to determine the accuracy of MRI as a diagnostic modality in diagnosing appendicitis, addressing concerns about diagnostic modalities and their adverse effects, and addressing the necessity and success of relevant interventions. Methods: Medical literature was comprehensively searched and reviewed without restrictions to particular study designs, or publication dates using PubMed, Cochrane Library, and Google Scholar databases for all relevant literature formulated in English. The extraction of necessary data proceeded after specific inclusion and exclusion criteria were applied. Meta Analysis was performed for 5206 patients, with 35 RCTs being selected. Analysis was done using the QualSyst tool, wherein two writers independently assessed the caliber of each study as well as the use of the Cochrane tool for bias risk apprehension. The statistical software packages RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20), and Excel in Stata 14 were used to perform the statistical analyses along with other analytical software. Results: MRI had an overall sensitivity of over 95%, an overall specificity of 94.2% with a PPV of 0.875 in comparison to CT scan in the diagnosis and intervention regarding appendicitis. Conclusion: These findings strongly suggest that MRI is a reasonable alternative to CT for the diagnosis of appendicitis in hospitals with appropriate access to this technology for reasons about accuracy, reliability, and reproducibility as well as addressing safety concerns.

Cancer/testis (CT) antigens exhibit selective expression predominantly in immunoprivileged tissues in non-pathological contexts but are aberrantly expressed in diverse cancers. Because of their expression pattern, they have historically been attractive targets for immunotherapies. The investigation of mechanistic roles of CT antigens in promoting oncogenesis has historically been a prominent research question, and a growing number of studies implicate CT antigens in promoting almost all the hallmarks of cancer. This suggests that CT antigens may act as cancer drivers. CT antigens are expressed in head and neck squamous cell carcinomas, although their role in the pathogenesis, prognostication, and treatment for this family of cancers remains poorly studied. Given that CT antigens hold intriguing potential as therapeutic targets and as biomarkers for prognosis and therapeutic response and that they can provide novel insights into oncogenic mechanisms, their further study in the context of head and squamous cell carcinoma is warranted.

Computed tomography (CT) is a widely employed imaging modality with diverse clinical applications in pediatric and adult populations, offering numerous advantages. Despite several alternatives to imaging modalities with ionising radiation, CT scans have demonstrated persistent global popularity, contributing to a substantial amount of effective radiation doses for patients. This exposure results in hazards, including stochastic effects that amplify the radiation-induced cancer risk proportionally to the radiation dose received. CT-related radiation comprises a substantial portion of cumulative effective doses within diagnostic radiology, specifically impacting younger patient cohorts undergoing repeated investigations for chronic diseases over time. Scientific literature over recent decades has explored various methods to mitigate radiation doses during medical imaging. One notable strategy involves implementing low-dose and ultralow-dose CT protocols, maintaining diagnostic efficacy in acute and non-acute medical and surgical conditions. Utilising innovative image reconstruction algorithms, such as iterative reconstruction and emerging deep-learning algorithms based on artificial intelligence, plays a pivotal role in achieving an approximately 80% reduction in patient radiation compared to standard doses. This review article discusses the significance of low-dose protocols across a spectrum of acute and chronic medical conditions affecting different body systems.

Coronary artery disease (CAD) represents a modern pandemic associated with significant morbidity and mortality. The multi-faceted pathogenesis of this entity has long been investigated, highlighting the contribution of systemic factors such as hyperlipidemia and hypertension. Nevertheless, recent research has drawn light to the importance of geometrical features of coronary vasculature on the complexity and vulnerability of coronary atherosclerosis. Various parameters have been investigated so far, including vessel-length, cross-sectional area, curvature, and tortuosity, using primarily invasive angiography and recently non-invasive cardiac computed tomography angiography (CCTA). It is clear that there is correlation between geometrical parameters and both the haemodynamic alterations augmenting the atherosclerosis-prone environment and the extent of plaque burden. The purpose of this review is to discuss the currently available literature regarding this issue and propose a potential non-invasive imaging biomarker, the geometric risk score, which could be of importance to allow early detection of individuals at increased risk of developing CAD.

Obturator herniæ are a quite rare type of abdominal hernia, accounting for less then 1% of all abdominal wall hernias and for 0.2-1.6% of patient with a small bowel obstruction. The obturator canal is the only portion of the obturator foramen that is not obliterated by the membrane of the same name and hosts the obturator neurovascular bundle; it is, for this reason, a locus minoris resistentiae, through which obturator hernias are formed, generally in elderly, multiparous women. Despite the fact that Computed Tomography offers the possibility of a quick, correct preoperative diagnosis, often signs and symptoms of obturator herniæ are quite unspecific; considering that, at the same time, patients with an obturator hernia are generally elderly, with concurrent conditions, this might cause delays in the diagnosis and treatment and produces the high postoperative mortality rates that obturator herniæ yield

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.

Continuous water resources monitoring is needed for sustainable urban water supply. Remote sensing techniques have proven useful for monitoring some water qualitative parameters with optical characteristics. The study area was the Marateca reservoir in central inland Portugal. The aims were the following: (1) to explore the water quality parameters at the monitoring points of the Marateca reservoir that may explain the event; (2) to validate optical water quality parameters with the monitoring points data; and (3) to model the reservoir water characteristics regarding its deepness, trophic state, and turbidity. The parameters total phosphorus, total nitrogen, and chlorophyll-a were used to compute a trophic level index. The Sentinel-2 imagery was used to compute spectral indices and bands image ratio; to obtain spectral signatures for the monitoring points, and to model water characteristics. The water parameters were above the recommended values at the reservoir entry point from the Ocreza River. The reservoir trophic level was Hypereutrophic and Eutrophic. The spectral signatures confirmed a Hypereutrophic pattern in the entry point. The Marateca reservoir’s water characteristics modeling forecasted problematic zones by contamination. The methodological approach developed can be easily applied to other reservoirs and is a key support tool for decision-makers.

With the development of hyperspectral technology, to establish an effective spectral data compressive reconstruction method that can improving data storage, transmission and maintaining spectral information is critical for quantitative remote sensing research and application in vegetation. By introducing the idea of compressive sensing in compressed reconstruction, the spectral adaptive grouping distributed compressive sensing algorithm is proposed, which enables a distributed compressed sensing reconstruction of plant hyperspectral data. The experimental results showed that comparing with orthogonal matching pursuit(OMP) and gradient projection reconstruction(GPSR), the proposed algorithm can significantly improve the visual effect of image reconstruction in the spatial domain. The PSNR in low sampling rate(sampling rate is lower than 0.2) increases by 13.72dB than OMP and 1.66dB than GPSR. In the spectral domain, the average normalized root mean square error、the mean absolute percentage error and the mean absolute error of the proposed algorithm is35.38%，31.83% and 33.33% lower than GPSR respectively.. Therefore, the proposed algorithm can achieve relatively high reconstructed efficiency.

This paper provides a comprehensive overview of the potential applications of dual energy CT (DECT) in improving image quality and diagnostic capabilities of CT arthrography (CTA) in clinical practice. The paper covers the use of virtual non contrast (VNC) images, in which the injected contrast medium is reduced from the articular cavity, in order to better analyze 2D and 3D images of the bone. Moreover , virtual monoenergetic imaging (VMI) applications and their potential use for the reduction of metal artifacts and improving image contrast are reviewed. The role of virtual non calcium (VNCa) in detecting bone marrow edema surrounding the imaged joint will be discussed. Furthermore , the role of iodine map to enhance the contrast between soft tissues, optimizing the visualization of contrast material, and to distinguish contrast material from calcifications is described. Finally, a case series including different joints is provided to underline the additional advantages of high spatial resolution dual energy CT reconstructed images.

Introduction: CT scan of the skull in patients with head trauma play an important role in identifying patients' injuries; In moderate to severe brain injury; CT scans are arguably the best way to get information about the intracranial complications of a head injury. Researchers have cited a number of reasons for why doctors are increasingly asking for CT scans of patients. In this study; pathological findings in CT scan of patients with mild cranial trauma and level of consciousness 13-15 are examined. Method: In this study, the treatment process of 445 patients who had referred to the emergency department due to skull trauma was examined as research units; and samples were taken by simple random sampling among patients for whom CT scan of the brain was requested. In this study; the reasons for requesting a CT scan of the skull from the requesting physician were questioned through an interview at the time of request. Results: According to the tables; it can be seen that most of the patients referred to the hospital due to skull trauma for CT scan were men and were discharged in less than the first 24 hours. The age group of 21 to 30 years had the highest and the age group over 70 years had the lowest frequency and the highest percentage of request for CT scan was by doctor and the biggest injury that caused patients with mild cranial trauma to go to hospital was fall. Conclusion Based on the findings of this study, cranial trauma is one of the life-threatening factors that can cause minor or severe injuries Its range varies from superficial injuries to hematoma and intracranial hemorrhage, which is a reason to perform CT scans of patients with skull trauma. In order to carefully examine the extent of the damage to the patient and to avoid possible risks and to take the necessary measures for treatment. On the other hand, the lack of clear protocols as well as the lack of clarity and certainty of physicians in their diagnoses to perform graphs of qualified people has increased the number of unnecessary CT scans

An outbreak of novel coronavirus(2019-nCoV) that began in Wuhan, China, is rapidly spreading to all over China, and gradually to multiple countries. Regarding to put the epidemic prevention and spread under the control, early identification and diagnosis play a critical role. Patients with initially no or mild symptoms of Novel Coronavirus Pneumonia (2019-nCoV), namely “stealth” infection, often lack of typical clinical evidence to establish the diagnosis. Based on the clinical analysis of 4 cases in stealth infection, the results of this study highlight that early diagnosis requires a combination of epidemiological history, clinical manifestations, early chest CT examination, and 2019-nCoV RNA test (nucleic acid test), with particular emphasis on definite epidemiological history and early chest CT findings when positive nucleic acid tests lag behind.

Early detection of pancreatic ductal adenocarcinoma (PDAC) requires further examination after selecting cases with risk factors for the condition, such as family history, hereditary pancreatic carcinoma syndrome, intraductal papillary mucinous neoplasms, or chronic pancreatitis. The Japan Study Group on the Early Detection of Pancreatic Cancer has investigated and clarified the clinicopathological features for the early diagnosis of PDAC. Further approaches for the early diagnosis of PDAC are warranted.

The identification of bloodstain is one of the most important approaches in obtaining evidence in criminalistics. A threshold method based on spectral co-efficient and interclass variance is proposed in this paper, it is a non-contact, non-destructive method for quickly identifying bloodstains. The spectra of bloodstains and other suspected substances were all extracted from their hyper-spectral image. Then calculate the correlation coefficients of these spectral and interclass variances, analyze the differences between substances. The best blood recognition threshold was determined as 0.9. After preprocessing for eliminating systematic errors, experiments with the threshold 0.9 are carried out to identify bloodstains on the calico and red T-shirt. The method can remarkably identify the bloodstain from other non-blood substances both quickly and efficiently. The blood extraction rate can reach to 93.35% and 89.19%, respectively. It is an important step toward the implementation of bloodstain non-contact and non-destructive identification in forensic casework.

Purpose: Prostate cancer is the most common male prevalent malignancy in Europe. Biological recurrence occurs in 20-40% of patients within 10 years following treatment. [18F]F-Choline PET/CT is the most used technique for detecting recurrent disease but is rarely positive for low PSA levels. [18F]PSMA-1007 PET/CT allows early detection of recurrence sites. Methods: We conducted a prospective multicenter study. Each patient had access to a [18F]F-Choline and [18F]PSMA PET/CT. The primary endpoint was to determine the therapeutic impact of the [18F]PSMA comparative to [18F]F-Choline PET/CT. Secondary endpoints were the diagnostic performance and the correlation between PET/CT parameters and prognostic factors of prostate disease. Results: 47 patients were included. A therapeutic modification was observed in 36% of them between what the clinicians expected after the [18F]F-Choline PET/CT and what they finally decided after the [18F]PSMA PET/CT. Diagnostic performance of [18F]F-Choline was 28% versus 70% for [18F]PSMA with a significant difference. With [18F]PSMA PET/CT, there was a significative correlation between PSA level of biological recurrence and SUVmax but not between ISUP score and SUVmax of the selected lesion. Conclusion: This study found a modification in therapeutic management following [18F]PSMA PET/CT in one third of patients. This change could result in earlier and better management with detection of lesions at a lower PSA level than is possible with [18F]F-Choline.

Total-body PET/CT scanners provide increased sensitivity, enabling the adjustment of imaging parameters by reducing injected activity or shortening acquisition time. This study aimed to evaluate the limitations of reduced [18F]FDG activity doses on image quality, lesion detectabil-ity, and quantification of lesion uptake in the Biograph Vision Quadra, as well as to assess the benefits of the recently introduced ultra-high sensitivity mode in a clinical setting. A number of 26 patients who underwent [18F]FDG-PET/CT (3.0 MBq/kg, 5 min. scan time) were included in this analysis. PET raw data was rebinned for shorter frame durations to simulate 5 min. scans with lower activities in high sensitivity (HS) and ultra-high sensitivity (UHS) modes. Image quality, noise, and lesion detectability (n=82) were assessed using a 5-point Likert scale. The co-efficient of variation (CoV), signal-to-noise ratio (SNR), tumor-to-background ratio (TBR), and standardized uptake values (SUV) including SUVmean, SUVmax, and SUVpeak were evaluated. Sub-jective image ratings were generally superior in UHS compared to HS mode. At 0.5 MBq/kg, le-sion detectability decreased to 95% (HS) and 98% (UHS). SNR was comparable at 1.0 MBq/kg in HS (5.7±0.6) and 0.5 MBq/kg in UHS (5.5±0.5). With lower doses, there were negligible reductions in SUVmean and SUVpeak, whereas SUVmax increased steadily. Reducing [18F]FDG activity to 1.0 MBq/kg (HS/UHS) in a total-body PET/CT provides diagnostic image quality without statistical-ly significant changes in uptake parameters. UHS mode improves image quality, noise, and le-sion detectability compared to HS mode.

Perilla frutescens leaves are expected to exhibit antioxidant activity and amyloid-β (Aβ) aggregation inhibitory activity due to the presence of polyphenol-type compounds, etc. These activities fluctuate daily; however, measuring the contents of constituents and functionalities is cumbersome and unsuitable for instantaneous measurements in the field. In this study, we developed a facile method to analyze the activity and content of the components in leaves on-site based on the fluorescence spectra obtained by irradiating the perilla leaves with excitation light. The constituent contents (Chlorophyl (Chl), Total polyphenol content (TPC), Total flavonoid content (TFC), rosmarinic acid (RA) and functional properties DPPH radical scavenging activity, ferric reducing antioxidant power (FRAP), oxygen radical absorbance capacity (ORAC), Aβ aggregation inhibitory activity) were evaluated using established analytical techniques. The correlation between the fluorescence spectrum and the contents and activities was calculated using normalized difference spectral index (NDSI), ratio spectral index (RSI), and difference spectral index (DSI) analyses. We identified a predictive model with a high coefficient of determination R² ≥ 0.57 for content of the constituents, and R² ≥ 0.49 for functional properties. This allows convenient, simultaneous, and non-destructive monitoring of the constituent contents and the functionalities of perilla leave and a simple harvest-time diagnosis. The model established using this method is simple and suggesting that it can simultaneously infer the constituents and functionalities of perilla leaves.

Atmospheric correction is a necessary step in image processing data and spectra recorded by spaceborne sensors for pure cloudless atmosphere, primarily in the visible and near-IR spectral range. We have present a fast and sufficiently accurate method of atmospheric correction based on the proposed analytical solutions describing with high accuracy the spectrum of outgoing radiation at the top boundary of the cloudless atmosphere. This technique includes the model of the atmosphere and its optical parameters that are important in terms of radiation transfer. The solution of the inverse problem for finding unknown parameters of the model is carried out by the method of non-linear least squares (Levenberg-Marquardt algorithm) for an individual selected pixel of the image (its spectrum), taking into account the adjacency effects. Using the found parameters of the atmosphere and the average surface albedo, assuming homogeneity of the atmosphere within a certain area of the hyperspectral image (or the whole frame), the spectral albedo at the Earth's surface is calculated for all other pixels. It is essential that the procedure of the numerical simulation with non-linear least squares of the direct transfer problem is based on using analytical solutions, which provides a very short calculation time of the atmospheric parameters (seconds or less) and the ability to perform atmospheric correction "on-fly." Testing methods of atmospheric correction was performed using the synthetic outgoing radiation spectra at the top of the atmosphere (TOA), obtained by numerical simulation in the LibRadTran code, as well as spectra of real space images of the Hyperion hyperspectrometer. A comparison with the results of atmospheric correction in module FLAASH of ENVI package has been performed. Finally, to validate our data obtained by the SHARK method, a comparative analysis with ground-based measurements of Radiometric Calibration Network (RadCalNet) was carried out.

Spectral calibration consists of the calibration of wavelengths and the measurement of the instrument's spectral response function (SRF). Unlike conventional slits, the absorbed aerosol sensors (AAS) are used as a slit homogenizer, in which the spectral response function (SRF) is not a conventional Gaussian curve. To be more precise, the SRF is the convolution of the slit function of the spectrometer, the line spread function of the optical system, and the detector response function. The SRF of the slit homogenizer is a flat-topped multi-Gaussian function. Considering the convenience of fitting, a super-Gaussian function, which looks like a similar distribution to the flat-topped multi-Gaussian function, is used to fit the measured data in a spectral calibration. According to the results, the SRF’s shapes, due to the Earth port, resemble a Gaussian curve with a flatted top could be concluded, which contains an FWHM of 1.78–1.82 nm for the AAS. The results show that the correlation coefficients are about 0.99, which proves that the fitting function could better characterize the SRF of the instrument.

Recent technological advances, including capsule endoscopy (CE) and balloon-assisted endoscopy (BAE), have revealed that small intestinal disease is more common than previously thought. CE has advantages including, high diagnostic yield, discom-fort-free, outpatient basis, and physiological images. BAE enabled endoscopic diagnosis and treatment in the deep small bowel. Computed tomography (CT) enterography with negative oral contrast can evaluate masses, wall thickening, and narrowing of the small intestine. In addition, Enhanced CT can detect abnormalities outside the gastrointestinal tract that endoscopy cannot evalu-ate. Each modality has its advantages and disadvantages, and a good combination of multiple modalities leads to an accurate diagnosis. As a first-line modality, three-phase enhanced CT is preferred. If CT shows a mass, stenosis, or wall thickening, a BAE should be selected. If there are no abnormal findings on CT and no obstructive symptoms, CE should be selected. If there are sig-nificant findings in the CE, determine the indication for BAE and its insertion route based on these findings. Early diagnosis of small intestinal tumors is essential for favorable outcomes. For early diagnosis, the possibility of small bowel lesions should be considered in patients with unexplained symptoms and signs after examination of the upper and lower gastro-intestinal tract.

To investigate whether high body mass index (BMI) increases the risk of recurrence and corre-lates with higher glucose uptake in recurrent lesions in post-menopausal female patients with breast cancer. The hospital database was searched to retrieve breast cancer patients, who had undergone an [18F]FDG PET/CT scan before neoadjuvant chemotherapy and curative-intent sur-gery. BMI was calculated at the baseline [18F]FDG PET/CT scan. There was a median follow-up of 5 years after the baseline PET/CT scan to identify: recurrence in the breast (T_rec); lymph nodes (N_rec); distant locations (M_rec). Furthermore, SUVmax was measured in the sites of recur-rence. A chi-square test was used to investigate any difference in the frequency of any recur-rence, T_rec, N_rec, and M_rec between overweight women (BMI≥25 kg/m2) and women with a BMI<25 kg/m2 (p<0.05). SUVmax, was compared using a t-test (p<0.05) between the two groups. A total of post-menopausal 142 women (BMI: 26.84±5.59; 84 overweight and 58 with normal weight) were retrieved. There were 48 recurrences at the follow-up. The chi-square test demon-strated in overweight women an increased frequency of any recurrence (35 vs. 13; p=0.025) and T_rec (15 vs. 2; p=0.018) and a higher T_rec SUVmax (4.74±2.90 vs. 1.85 ± 0.63; p=0.09) compared to women with a BMI<25 kg/m2. BMI seems to correlate with an increased rate of recurrence, espe-cially in the breast, and a higher glucose uptake in post-menopausal patients with recurrent breast cancer.

Pneumatosis intestinalis is the presence of air within the two layers of the wall of the gastrointestinal tract, specifically in the small and large intestines. This accumulation of gas can cause thicker walls of the intestines in X-ray or CT scans. Superior Mesenteric Artery (SMA) Thrombosis occurs due to the formation of blood clots within the SMA. As it supplies from the ampulla in the second part of the duodenum to the splenic flexure of the large intestine its thrombosis can cause ischemia in any part depending upon its branch. A 67-year-old male patient presented to the hospital with the complaint of generalized abdominal pain for 5 days along with fever, nausea, vomiting, obstipation, and postprandial fullness. On further investigation with the help of an MDCT scan and X-ray, proximal jejunal loops showed circumferential air within the walls giving the diagnosis of Pneumatosis Intestinalis along with Superior Mesenteric Artery Thrombosis causing jejunal infarct.

The 3D reconstruction of vermiculite-based sealing material was carried out based on CT scanning experiments and Avizo software. The precision and representation of the reconstructed digital core were tested by calculating the pore structure parameters and comparing them with the experimental results of mercury compression. Avizo is a perfect interface with Fluent software to perform micro-scale seepage simulation to explore the distribution of pressure and velocity fields during fluid transport. In this paper, a new approach is proposed to study the penetration leakage of non-metallic gaskets by using equivalent pore networks.

Imaging-based biomarkers have developed as an effective tool in neurology, providing vital understandings of the structural, functional, and molecular changes associated with neurological disorders. Imaging techniques such as magnetic resonance imaging (MRI), positron emission tomography (PET), single-photon emission computed tomography (SPECT), and computed tomography (CT) have been widely employed to record disease-related alterations in the brain. These techniques provide a wide range of biomarkers, such as functional connectivity patterns, volumetric measurements, molecular imaging agents, and perfusion parameters, enabling the correct identification of neurological disorders. These biomarkers have proven useful in early diagnosis, disease progression tracking, therapy response prediction, and surgical planning. This review emphasizes the various obstacles and limitations that are associated with imaging-based biomarkers. Technical constraints, standardization obstacles, ethical concerns, regulatory challenges, and cost-effectiveness concerns all offer substantial barriers to wider use. It is vital to overcome these challenges if imaging biomarkers are to be successfully integrated into routine clinical practice. Imaging technology advancements like high-resolution imaging, multimodal imaging, and artificial intelligence-based analysis hold immense promise for imaging-based biomarkers in the future. While more study and standardization are needed, their ongoing development and integration into clinical practice have the potential to revolutionize the diagnosis, treatment, and management of neurological disorders, resulting in better patient care and outcomes.

Background The acknowledgment of computed tomography (CT) defined diagnosis in high prevalence northern Italy may identify more patients with Coronavirus Disease-2019 (COVID 19) infection, than RT-PCR alone. Methods We retrospectively reviewed 148 chest CT scans of oncological patients who were referred to the Radiological Unit of Policlinico S. Marco from 1st of February 2020 to 30th of April 2020, during the Covid-19 outbreak in Bergamo area. Therefore, we analyzed RT-PCR tests of these 148 patients. Results Among 32 patients with diagnosis of COVID-19 infection: 17 patients were asymptomatic or had mild symptoms (53.1%), while 15 developed severe disease (46.8%). The incidence of COVID-19 infection is 22.9%, the mortality rate is 18.8%. Severe COVID-19 disease is associated with higher median age. We did not find any correlation between disease severity and sex, smoke or cardiovascular comorbidities. Remarkably, patients who were on treatment developed milder disease than cancer patients who were not on treatment. Conclusions The acceptance of CT-defined diagnosis in high prevalence area like Bergamo highlighted a larger number of COVID-19 oncological population than RT-PCR alone, in particular asymptomatic and mild symptomatic patients. We observed that actively treated patients had milder disease, according to previous studies that suggested a protective role of immunosuppression.

Introduction: Clinicians have been struggling with the optimal diagnostic approach of patients with suspected COVID-19. We evaluated the added value of chest CT over RT-PCR alone. Methods: Consecutive adult patients with suspected COVID-19 presenting to the emergency department (Academic Medical Center, Amsterdam University Medical Centers, the Netherlands) from March 16^th to April 16^th were retrospectively included if they required hospital admission and underwent chest CT and RT-PCR testing for SARS-CoV-2 infection. The CO-RADS classification was used to assess the radiological probability of COVID-19, where a score of 1-2 was considered as negative, 3 as indeterminate, and 4-5 as positive. CT results were stratified by initial RT-PCR results. For patients with a negative RT-PCR but a positive CT, serology or multidisciplinary discussion after clinical follow-up constituted the final diagnosis. Results: 258 patients with suspected COVID-19 were admitted, of which 239 were included because they had both CT and RT-PCR testing upon admission. Overall, 112 patients (46.9%) had a positive initial RT-PCR, and 14 (5.9%) had a positive repeat RT-PCR. Of 127 patients with a negative or indeterminate initial RT-PCR, 38 (29.9% [95%CI 21.3-39.3%]) had a positive CT. Of these, 13 had a positive RT-PCR upon repeat testing, and 5 had positive serology. The remaining 20 patients were assessed in a multidisciplinary consensus meeting, and for 13 it was concluded that COVID-19 was ‘very likely’. Of 112 patients with a positive initial RT-PCR result, CT was positive in 104 (92.9% [95%CI 89.3-97.5%]). Conclusion: In a high-prevalence emergency department setting, chest CT showed high probability of COVID-19 (CO-RADS 4-5) in 29.9% of patients with a negative or indeterminate initial RT-PCR result. As the majority of these patients had proven or ‘very likely’ COVID-19 after follow-up, we believe that CT helps in the identification of patients who should be admitted in isolation.

In gravitational theory and astrophysical dynamics, singular initial value problems (IVPs) are frequently encountered. Finding the solutions to this class of IVPs can be challenging due to their complex nature. This study strives to circumvent the complexity by proposing a numerical method for solving such problems. The approach proposed in the current research seeks solutions to the IVP by partitioning the domain [0,L] of the problem into two intervals and solving the problem on each domain. The study seeks a closed-form solution to the IVP in the interval containing the singular point. A linearization technique and piecewise partitioning of the domain not containing the singularity are applied to the nonlinear IVP. The resulting linearized differential equation is solved using the Chebyshev spectral collocation method. Some examples are presented to illustrate the efficiency of the proposed method. Numerical analysis of the solution and residual errors are shown to ascertain convergence and accuracy. The results suggest that the technique gives accurate convergent solutions using a few collocation points.

Over the past 30 years, the use of field spectroscopy has risen in importance in remote sensing studies for the characterization of the surface reflectance of materials in situ within a broad range of applications. Potential uses range from measurements of individual targets of interest (e.g. vegetation, soils, validation targets etc.), to characterizing the contributions of different materials within larger spatially-mixed areas as would be representative of the spatial resolution captured by a sensor pixel (UAV to satellite scale). As such, it is essential that a complete and rigorous assessment of both the data-acquisition procedures, and the suitability of the derived data product be carried out. The measured energy from solar-reflected range spectroradiometers is influenced by the viewing and illumination geometries and the illumination conditions which vary due to changes in solar position and atmospheric conditions. By applying corrections, the estimated absolute reflectance (Rabs) of targets can be calculated. This property is independent of illumination intensity or conditions and is the metric commonly suggested to be used to compare spectra even when data are collected by different sensors or acquired under different conditions. By standardizing the process of estimated Rabs, as is provided in the described toolkit, consistency and repeatability in processing are ensured and the otherwise labor intensive and error-prone processing steps are streamlined. The resultant end data product (Rabs) represents our best current effort to generate consistent and comparable ground spectra which have been corrected for viewing and illumination geometries as well as other factors such as the individual characteristics of the reference panel used during acquisition.

The Geostationary Environment Monitoring Spectrometer (GEMS) onboard the Geostationary Korean Multi-Purpose Satellite 2B was successfully launched in February 2020. GEMS is a hyperspectral spectrometer measuring solar irradiance and Earth radiance in the range of 300 to 500 nm. This paper introduces the spectral calibration algorithm for GEMS, which uses a nonlinear least-squares approach. To assess the performance of the algorithm, sensitivity tests for a series of spectral parameters such as shift, spectral range for fitting, signal-to-noise ratio, spectral response function (SRF), and reference spectrum have been conducted. To improve the assessment, a synthetic GEMS spectrum using the prelaunch GEMS SRF is adopted here. The test results show that the required accuracy (0.002 nm) is achievable for the expected uncertainties of the parameters except for the SRF and the choice of high-resolution reference spectrum, which degrade the algorithm performance by an order magnitude. To mitigate the sensitivity to SRF, retrieval of in-orbit SRF using an analytic function is suggested. Finally, a few candidates for the high-resolution solar reference spectrum are prepared for testing by the instrument during in-orbit tests.

In this paper, we identify issues and possible solutions in the key area of large-scale antenna systems, also know as Massive Multiple Input Multiple Output (MIMO) systems. Additionally, we propose the use of Massive MIMO technology as a means to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel (PNSCH), the capacity of the MTC network and, in turn, that of the whole system, can be increased by grouping Machine-Type Communication (MTC) devices into clusters and letting each cluster share the same time-frequency physical resource blocks. We study the feasibility of applying sub-optimal linear detection to the problem of detecting a large number of MTC devices sharing the same time-frequency resources at the uplink of a base station (BS) equipped with a large number of antennas, M. In our study, we derive the achievable lower-bound rates for the studied sub-optimal linear detectors and show that the transmitted power of each MTC device can be reduced as M increases, which is a very important result for powerconstrained MTC devices running on batteries. Our simulation results suggest that, as M is made progressively larger, the performance of sub-optimal linear detection methods approach the matched filter bound, also known as perfect interference-cancellation bound.

This paper presents a novel CNN-based architecture, referred to as Q-Net, to learn local feature descriptors that are useful for matching image patches from two different spectral bands. Given correctly matched and non-matching cross-spectral image pairs, a quadruplet network is trained to map input image patches to a common Euclidean space, regardless of the input spectral band. Our approach is inspired by the recent success of triplet networks in the visible spectrum, but adapted for cross-spectral scenarios, where for each matching pair there are always two possible non-matching patches; one for each spectrum. Experimental evaluations on a public cross-spectral VIS-NIR dataset shows that the proposed approach improves the state-of-the-art. Moreover, the proposed technique can also be used in mono-spectral settings, obtaining a similar performance to triplet network descriptors, but requiring less training data.

ABSTRACT: Iodixanol is an iso-osmolar nonionic dimeric hydrophilic contrast agent with a higher viscosity than the monomeric agents. It is the only Food and Drug Administration (FDA)approved isoosmolar agent in the United States, and it is the only contrast agent with an FDA-approved indication for use in cardiac computed tomographic angiography (CCTA), to assist in the diagnostic evaluation of patients with suspected coronary artery disease. In clinical studies, it has been noted to have fewer side effects and similar image quality when compared to low osmolar contrast media. This can be attributed to the pharmacological properties of iodixanol. In the field of cardiology, iodixanol among other intravenous contrast media is used for coronary computed tomography angiography and cardiac catheterization. In this article, the use, tolerability and efficacy of iodixanol in the field of cardiology are reviewed, specifically evaluating the use for CCTA and coronary angiography, including outcome studies, randomized trials and comparisons to other contrast agents.

Aim To perform a comprehensive analysis of discordances between contrast-enhanced CT (ceCT) and 18F-FDG PET/CT in the evaluation of the extra-cerebral treatment monitoring in patients with stage IV melanoma. Materials and methods We conducted a retrospective monocentric observational study over a 3 years period in patients referred for 18F-FDG PET/CT and ceCT in the framework of therapy monitoring of immune checkpoint or tyrosine kinase inhibitors (ICIs or TKIs) as of January-2017. Imaging reports were analysed by two physicians in consensus. Anatomical site responsible for discordances, as well as induced changes in treatment were noted. Results Eighty patients were included and 195 couples of scans analysed. Overall, discordances occurred in 65 cases (33%). Eighty percent of the discordances (52/65) were due to 18F-FDG PET/CT scans upstaging the patient. Amongst these discordances, 17/52 (33%) led to change in patient’s management, the most frequent being radiotherapy of a progressing site. ceCT represented 13/65 (20%) of discordances and induced changes in patients’ management in 2/13 cases (15%). The more frequent anatomical site involved was subcutaneous for 18F-FDG PET/CT findings and lung or liver for ceCT. Conclusions Treatment monitoring with 18F-FDG

Aim To perform a comprehensive analysis of discordances between contrast-enhanced CT (ceCT) and 18F-FDG PET/CT in the evaluation of the extra-cerebral treatment monitoring in patients with stage IV melanoma. Materials and methods We conducted a retrospective monocentric observational study over a 3 years period in patients referred for 18F-FDG PET/CT and ceCT in the framework of therapy monitoring of immune checkpoint or tyrosine kinase inhibitors (ICIs or TKIs) as of January-2017. Imaging reports were analysed by two physicians in consensus. Anatomical site responsible for discordances, as well as induced changes in treatment were noted. Results Eighty patients were included and 195 couples of scans analysed. Overall, discordances occurred in 65 cases (33%). Eighty percent of the discordances (52/65) were due to 18F-FDG PET/CT scans upstaging the patient. Amongst these discordances, 17/52 (33%) led to change in patient’s management, the most frequent being radiotherapy of a progressing site. ceCT represented 13/65 (20%) of discordances and induced changes in patients’ management in 2/13 cases (15%). The more frequent anatomical site involved was subcutaneous for 18F-FDG PET/CT findings and lung or liver for ceCT. Conclusions Treatment monitoring with 18F-FDG

In this work, we propose simple and robust technique for the retrieval of underlying surface spectral albedo using spaceborne observations. It can be used to process both multispectral moderate resolution satellite data and also multi - zone high spatial resolution data. The technique can work automatically for different types of land surfaces without using huge databases accumulated in advance. The new cloud discrimination and retrieval of the water vapor content in atmosphere procedures are presented. The key point of the proposed atmospheric correction technique is the suggested single-wavelength method for determining the atmospheric aerosol optical thickness without reference to a specific type of underlying surface spectrum. The retrievals of spectral albedo for various land surfaces with developed technique, performed using computer simulation and experimental data, have demonstrated a high retrieval accuracy.

Presenting a case report about an occurrence of duodeno-duodenal intussusception in a 17-year-old female patient. Intussusception is typically observed in children. The patient has a history of recurrent pain and vomiting for four days. During the examination tenderness in the epigastric area worsened when the legs were elevated. An initial X-ray of the abdomen was done and the findings were normal. Subsequent ultrasound and abdominal CECT scans of the abdomen revealed intussusception involving the 2^nd, 3^rd, and 4^th part of the duodenum ampulla of Vater and pancreas without any identifiable cause for this condition. There was no abnormal thickening of the wall. This case shows how using radiological imaging and surgical management helps to prevent severe complications in cases like duodeno-duodenal intussusception in adults.

This study evaluated the efficacy of experimental TEGDMA-functionalized dicalcium phosphate dihydrate (T-DCPD) filler-based resin-based composites (RBC) in preventing caries lesions around the restoration margins (secondary caries”, SC). Standardized Class-II cavities were made in sound molars having the cervical margin in dentin. Cavities were filled with a commercial resin-modified glass-ionomer cement (RMGIC) or experimental RBCs containing a BisGMA-TEGDMA resin blend and one of the following inorganic fractions: 60 wt.% Ba glass (RBC-0); 40 wt.% Ba glass, 20 wt.% T-DCPD (RBC-20); 20 wt.% Ba glass, 40 wt.% T-DCPD (RBC-40). An open-system bioreactor produced S. mutans biofilm-driven SC. Specimens were scanned using micro-CT to evaluate demineralization depths. Scanning Electron Microscopy and Energy-dispersive X-ray Spectroscopy characterized the specimens’ surfaces, while antimicrobial activity, buffering effect, and ion uptake by the biofilms were also evaluated. ANOVA and Tukey’s test were applied at p<0.05. RBC-0 and RBC-20 showed SC development in dentin, while RBC-40 and RMGIC significantly reduced the lesion depth at the restoration margin (p<0.0001). Initial enamel demineralization could be observed only around RBC-0 and RBC-20 restorations. A direct antibiofilm activity could explain SC reduction by RMGIC, while a buffering effect on biofilm’s acidogenicity explained the behavior of RBC-40. Experimental RBC with CaP-releasing functionalized T-DCPD filler could prevent SC with the same efficacy as F-releasing materials.

Some COVID-19 patients develop interstitial pneumonia that can evolve into Acute Respiratory Distress Syndrome (ARDS). This is accompanied by an inflammatory cytokine storm. SarS-CoV has proteins capable of promoting cytokine storm, especially in patients with comorbidities, including obesity. Since there is currently no resolutive therapy for ARDS and given the scientific literature regarding the use of adenosine, its application has been hypothesized. Adenosine through its receptors is able to inhibit the acute inflammatory process, increase the protection capacity of the epithelial barrier and reduce the damage due to an overactivation of the immune system, such as in cytokine storms. These features are known in ischemia / reperfusion models and could also be exploited in acute lung injury, with hypoxia. In light of these hypotheses, for compassionate use, a COVID-19 patient, with unresponsive respiratory failure, was treated with adenosine. The results showed a rapid and clear improvement in clinical conditions, with the negative effect of detection of SarS-CoV2.

Background: Lung CT provides an effective modality to evaluate patients with suspected COVID-19. However, overlapping imaging findings with cardiogenic pulmonary oedema have been reported. Reports comparing lung CT features of these diseases have not been elaborated. Thus, we aimed to investigate these gaps in the knowledge regarding low-dose lung CT features of patients with COVID-19 pneumonia with those with acute heart failure (HF). Methods: This retrospective analysis enrolled hospitalized patients with COVID-19 (n=10) and acute heart failure (n=9) that exclusively underwent low-dose lung CT scans within 24-hours of admission. Clinical and lung CT characteristics were collected and analysed. Results: Ground-glass-opacities (GGO) appearance has been recorded in all subjects in HF and COVID-19 group. There was no significant statistical difference between the two groups for rounded morphology, consolidation, crazy paving pattern, lesion distribution, parenchymal band (P> 0.05). However, diffuse lesions were more frequent in HF cases (55.6% vs. 0%) than in COVID-19 pneumonia, which had predominantly multifocal pattern. Notably, CT images in HF patients were more likely to have signs of interstitial tissue thickening such as the interlobular septums, fissures and peribronchovascular interstitium (55.6% vs 0%, 88.9% vs 20% and 44.4% vs 0%,respectively), as well as cardiomegaly (77.8% vs 0%), increased artery to bronchus ratio (55.6% vs 0%), and pleural effusions (77.8% vs 0%). Conclusions: Major overlaps of lung CT imaging features existed between COVID-19 pneumonia and acute HF cases. However, signs of fluid redistribution are clues that favour HF over COVID-19 pneumonia.

Forward-bias hole injection from 10 nm-thick p-type Nickel Oxide layers into 10 um-thick n-type Gallium Oxide in a vertical NiO/Ga2O3 p-n heterojunction leads to more than a factor of 2 enhancement of photoresponse measured from this junction. While it takes only 600 seconds to obtain such a pronounced increase in photoresponse, it persists for hours, indicating feasibility of photovoltaic device performance control. The effect is ascribed to charge injection-induced increase of minority carrier (hole) diffusion length (resulting in improved collection of photogenerated non-equilibrium carriers) in n-type beta-Ga2O3 epitaxial layers, due to trapping of injected charge (holes) on deep meta-stable levels in the material and subsequent blocking of non-equilibrium carrier recombination through these levels. Suppressed recombination leads to increased non-equilibrium carrier lifetime, in turn determining a longer diffusion length and being the root-cause for the effect of charge injection.

This study aims to assess the feasibility of delineating and identifying mineral ores from hyperspectral images of tin-tungsten mine excavation faces using machine-learning classification. We compiled a set of hand samples of minerals of interest from a tin-tungsten mine and analyzed two types of hyperspectral images: 1) images acquired with a laboratory set-up under close-to-optimal conditions; and 2) scan of a simulated mine face using a field set-up, under conditions closer to those in the gallery. We have analyzed the following minerals: cassiterite (tin ore), wolframite (tungsten ore), chalcopyrite, malachite, muscovite, and quartz. Classification (Linear Discriminant Analysis, Singular Vector Machines and Random Forest) of laboratory spectra had a very high overall accuracy rate (98%), slightly lower if the 450 – 950 nm and 950 – 1780 nm ranges are considered independently, and much lower (74.5%) for simulated conventional RGB imagery. Classification accuracy for the simulation was lower than in the laboratory but still high (85%), likely a consequence of the lower spatial resolution. All three classification methods performed similarly in this case, with Random Forest producing results of slightly higher accuracy. The user’s accuracy for wolframite was 85%, but cassiterite was often confused with wolframite (user’s accuracy: 70%). A lumped ore category achieved 94.9% user’s accuracy. Our study confirms the suitability of hyperspectral imaging to record the spatial distribution of ore mineralization in progressing tungsten-tin mine faces.

We review the state of dynamical downscaling with scale-constrained regional and global models. The methodology, in particular spectral nudging, has become a routine and well-researched tool for hindcasting climatologies of sub-synoptic atmospheric disturbances in coastal regions. At present, the spectrum of applications is expanding to other phenomena, but also to ocean dynamics and to extended forecasting. Also new diagnostic challenges are appearing such as spatial characteristics of small-scale phenomena such as Low Level Jets.

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.

COVID-19 is a severe global problem, and AI can play a significant role in preventing losses by monitoring and detecting infected persons in early-stage. This paper aims to propose a high-speed and accurate fully-automated method to detect COVID-19 from the patient's CT scan images. We introduce a new dataset that contains 48260 CT scan images from 282 normal persons and 15589 images from 95 patients with COVID-19 infections. At the first stage, this system runs our proposed image processing algorithm to discard those CT images that inside the lung is not properly visible in them. This action helps to reduce the processing time and false detections. At the next stage, we introduce a novel method for increasing the classification accuracy of convolutional networks. We implemented our method using the ResNet50V2 network and a modified feature pyramid network alongside our designed architecture for classifying the selected CT images into COVID-19 or normal with higher accuracy than other models. After running these two phases, the system determines the condition of the patient using a selected threshold. We are the first to evaluate our system in two different ways. In the single image classification stage, our model achieved 98.49% accuracy on more than 7996 test images. At the patient identification phase, the system correctly identified almost 234 of 245 patients with high speed. We also investigate the classified images with the Grad-CAM algorithm to indicate the area of infections in images and evaluate our model classification correctness.

Previous research has shown that the effectiveness of selecting filter set from a large set of commercial broadband filters by vector analyzing method based on maximum linear independence (MLI). However, the traditional MLI is suboptimal due to predefining the first filter of the selected filter set being the maximum ℓ2 norm among all those of the filters. An exhaustive imaging simulation is conducted to investigate the features of the most competent filter set. In the simulation, every filter in a subset of all the filters is selected serving as the first filter in turn. From the results of the simulation, we found there are remarkable characteristics for the most competent filter set. Besides smaller condition number, the geometric features of the best-performed filter set comprise the distinct peak of the transmittance of the first filter, the generally uniform distributing of the peaks of the transmittance curve of the filters, the substantial overlapping of the transmittance curves with those of the adjacent filer sets. Therefore, the best-performed filter sets can be decided intuitively by simple vector analyzing and just a few experimental verifications. This work would be useful for optimizing spectral sensitivity of broadband multispectral imaging sensors or SFA sensors.

ABSTRACT Objectives: Typical Diagnostic Reference Levels (DRL) in terms of Computed Tomography Dose Index (CTDI) and patient dose in terms of Effective Dose (ED ) and Size Specific Dose Estimate (SSDE) were estimated in Computed Tomography (CT) guided biopsy procedures. Materials and Methods: A total of 226 CT biopsy procedures - Iliac bone, liver, lung, mediastinum and para-aortic tissue - were retrospectively analyzed and Typical DRL extracted based on ICRP 135 instructions. Results: For helical mode acquisitions, DRLs in terms of CTDIvol were 9.7 mGy for Iliac bone, 8.9 mGy for liver, 8.8 mGy for lung, 7.9 mGy for mediastinal mass and 9 mGy for para-aortic lymph nodes biopsy procedures. For biopsy acquisitions, DRL values were 7.3 mGy, 7.7 mGy, 5.6 mGy, 5.6 mGy and 7.4 mGy respectively. Also, SSDE median values ranged from 7.6 mGy to 10 mGy for biopsy acquisitions and 11,3 mGy to 12,6 mGy for helical acquisitions, as well as the median values for effective dose ranged from 1.6 mSv to 5,7 mSv for biopsy scans and 3.9 to 9.3 mSv for helical scans. Conclusions: The use of DLR as an optimization tool for CT-guided biopsy procedures revealed that helical scans across the entire anatomical region greatly affect radiation dose compared to biopsy acquisitions.

Severe respiratory syncytial virus (RSV) infections in early life have been linked to the development of chronic airway disease. RSV is a potent inducer of reactive oxygen species (ROS) which contributes to inflammation and enhanced clinical disease. NF-E2-related factor 2 (Nrf2) is an evolutionary conserved redox-responsive protein that helps to protect cells and whole organisms from oxidative stress and injury. The role of Nrf2 in the context of viral-mediated chronic lung injury is not known. Herein, we show that RSV experimental infection of adult Nrf2 deficient BALB/c mice (Nrf2-/-; Nrf2 KO) is characterized by enhanced disease, increased inflammatory cell recruitment to the bronchoalveolar compartment, and a more robust upregulation of innate and inflammatory genes and proteins, compared to wild type Nrf2+/+ competent mice (WT). These events that occur at very early time points, lead to increased peak RSV replication in Nrf2 KO compared to WT mice (day 5). To evaluate longitudinal changes of the lung architecture, mice were scanned weekly by high-resolution micro-computed tomography (micro-CT) imaging up to 28 days after initial viral inoculation. Based on micro-CT qualitative 2D imaging and quantitative reconstructed histogram-based analysis of lung volume and density, we found that RSV infected Nrf2 KO mice developed significantly greater and prolonged fibrosis compared to WT mice. Results of this study underscore the critical role of Nrf2-mediated protection from oxidative injury not only in acute pathogenesis of RSV infection, but also in its long-term consequences of chronic airway injury.

The COVID-19 pandemic caused an unprecedented effect on national radiological investigations. Since the World Health Organization officially declared the COVID-19 as a global pandemic, health policies have been rapidly organized to limit the spread of the virus and decrease the risk of exposure. These restrictions, in combination with home-stay arrangements and the onset of economic recession. As a result of public policies, financial difficulties and patient fear, many radiology departments have suffered a significant reduction in diagnostic examinations with important implications for their economic stability. The aim of this work is to evaluate the economic impact of the COVID-19 pandemic in the Radiology Department of an infectious disease hospital.

Epilepsy is a common neurological condition, typically diagnosed using Electroencephalogram (EEG). Large scale EEG datasets have recently been made publicly available, allowing the use of advanced Machine Learning (ML) algorithms to analyze EEG patterns associated with epilepsy. While most existing studies focus on identifying seizures in the EEG, few have tried to identify preictal EEG segments. Identifying preictal EEG segments are not only useful in developing early warning systems but also helps inform the course of treatment for the patient. In this study, we propose to represent EEG segments as images, instead of time-series data, and identify preictal EEG segments using a preexisting ML algorithm (YOLOv8) designed for image processing. Multiplexed images (containing the original EEG signal represented on a 2D grid, kurtosis, and spectral entropy) achieve the best accuracy of 95.75% on the dataset while images just containing the EEG signal result in an accuracy of 91.25%. Using only spectrograms, generated from the original EEG signal, results in an accuracy of 90.15%.

With the changing climate, there is an increasing emphasis on drought-resistant varieties including the ability to maintain quality production. As there is also interest in ancient wheat varieties, the aim of this study was to evaluate the ancient Khorasan (Kamut ®) with the modern Kabot spring wheat variety using remote sensing data. Images from unmanned aerial vehicles during four growing seasons were processed. Based on vegetation indices, the growth of these varieties and their response to meteorological conditions were evaluated, as well as the ability to resist drought and higher temperatures with respect to specific soil conditions under conventional (CT), minimum (MTC) and minimization (MTD) tillage. It was found that the Khorasan had the lowest values of the vegetation indices on the CT variant in the dry years 2022 and 2023. On the contrary, in the previous wet years 2020 and 2021, both varieties showed similar results. Regarding to water stress, the CT variant was also the least suitable for ancient Khorasan (average CWSI = 0.38). On the contrary, this variant seems to be suitable for the modern Kabot variety (CWSI = 0.29), while no significant difference between tillage variants was found for this variety. In general, water stress was easily detectable by the observed parameters in the growth phase of stem elongation (R2 up to 0.88).

Wastewater (WW) analysis is a critical step in various operations such as control of a WW treatment facility, and speeding-up the analysis of WW quality can significantly improve such operations. This work demonstrates the capability of neural network (NN) regression models to estimate WW characteristic properties such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), ammonia (NH3-N), total dissolved substances (TDS), total alkalinity (TA), and total hardness (TH) by training on WW spectral reflectance in the visible to near-infrared spectrum (400nm-2000nm). The dataset contains samples of spectral reflectance intensity, which were the inputs, and the WW parameter levels (BOD, COD, NH3-N, TDS, TA, and TH), which were the outputs. Various NN model configurations were evaluated in terms of regression model fitness. The mean-absolute-error (MAE) was used as the metric for training and testing the NN models, and the coefficient of determination (R2) between the model predictions and true values was also computed to measure how well the NN models predict the true values. With online spectral measurements, the trained neural network model can provide non-contact and real-time estimation of WW quality at minimum estimation error.

In this study, we define the concept of pseudo-prime subhypermodules of hypermodules as a generalization of the prime hyperideal of commutative hyperrings in [17]. Firstly we examine the spectrum of the Zariski topology, which we built on the element of the pseudo-prime subhypermodules of a class of hyper-modules, then we give some relevant properties of the hypermodule in this topological hyperspace.

We present the results of direct numerical simulations of power spectral densities for kinetic energy, convective entropy and heat flux for unsteady Rayleigh-Bénard magnetoconvection in the frequency space. For larger values of frequency, the power spectral densities for all the global quantities vary with frequency f as f⁻². The scaling exponent is independent of Rayleigh number, Chandrasekhar’s number and thermal Prandtl number.

ATLID (ATmospheric LIDar) is the atmospheric backscatter LIDAR (Light Detection and Ranging) on board of the EarthCARE (Earth Cloud, Aerosol and Radiation Explorer) mission, the sixth Earth Explorer Mission of the ESA (European Space Agency) Living Planet Programme [1-5]. ATLID’s purpose is to provide vertical profiles of optically thin cloud and aerosol layers, as well as the altitude of cloud boundaries [6-10]. In order to achieve this objective ATLID emits short duration laser pulses in the UV, at a repetition rate of 51 Hz, while pointing in a near nadir direction along track of the satellite trajectory. The atmospheric backscatter signal is then collected by its 620 mm aperture telescope, filtered through the optics of the instrument focal plane assembly, in order to separate and measure the atmospheric Mie and Rayleigh scattering signals. With the completion of the full instrument assembly in 2019, ATLID has been subjected to an ambient performance test campaign, followed by a successful environmental qualification test campaign, including performance calibration and characterization in thermal vacuum conditions. In this paper the design and operational principle of ATLID is recalled and the major performance test results are presented, addressing the main key receiver and emitter characteristics. Finally, the estimated instrument, in-orbit, flight predictions are presented; these indicate compliance of the ALTID instrument performance against its specification and that it will meet its mission science objectives for the EarthCARE mission, to be launched in 2023.

A long standing problem in paleontology is the presence of giant arthropods during the so-called carboniferous era. The same difficulty occurs for the size of plants at the same period. We devise a possible answer to this question entirely different from the theories developed until now, based on the hypothesis that the size of atoms is decaying for very large times and the dimensions of polymers such as chitin and cellulose, containing expansible holes, are decreasing more slowly than rigid materials such as metals, alloys, composite materials and stone. Incidentally, this hypothesis might also give an alternative statement to the expansion of space.

The emission of mercury (II) from coal combustion and other industrial processes continues to be a concern and have local impact on water resources. The detection of these ions in water with sensitive but rapid testing methods is desirable for environmental screening and fieldwork. Nanoparticles of various chemistries have shown promise for this purpose, as they can be used in simple colorimetric analyses. Silver nanoprisms were chemically synthesized resulting in a blue reagent solution, that transitioned towards yellow and colorless solutions when exposed to Hg²⁺ ions at various concentrations. A rapid galvanic reduction of Hg²⁺ onto the nanoprism surfaces is apparently responsible for a change in shape towards spherical nanoparticles, leading to the change in color. There were no interferences by other metal ions in solution, and pH had minimal effect in the range of 6.5 to 9.8. The silver nanoprism reagent provided a detection limit of approximately 0.5 µM (100 µg/L) for mercury (II), which compares favorably with other nanoparticle-based techniques. Further optimization may reduce this detection limit.

The assessment of biomass carbon stocks was conducted at plot scale as a sample to estimate for all vegetation areas by using destructive sampling and or allometric equation method. Remote sensing is one of the techniques can be used to estimate and mapping biomass carbon stock for the entire areas. The objectives of the study are the identification and determine the range of electromagnetic wave of Landsat 8 satellite data that most suitable for assessing and mapping biomass carbon stock distribution. This research analyses exponential regression equation between spectral radiance values (Lλi) for with biomass measurement results on the field to find the best correlation based on the coefficient of determination value (R2). It also analyses the relationship between field biomass and NDVI value (Normal Differences Vegetation Index) from satellite data. The study area consists of 54.9% bush (Bs), 24.5% scrub (Sc), 16.8% secondary forest (Sf), while the rest (3.8%) is a water body. The with average biomass carbon stock value 4.11 tons.ha-1, 64.43 tons.ha-1, and 85.36 tons.ha-1, for strata Sc, Bs, and Sf respectively. Spectral radiance of SWIR (Shortwave Infra-Red) band 6 is determined as a spectral characteristic that can be used to estimating carbon stock with following the equation Y= 12657(EXP(-0.642(Lλband6)) with r2 = 0.75. Correlation NDVI and field biomass showed the low r2 value (0.08), so in this study, NDVI cannot be used to estimate the biomass carbon stock.

Three patients with multi-year histories of relapsing and remitting Lyme disease and associated co-infections despite extended antibiotic therapy were each given double dose dapsone combination therapy (DDD CT) for a total of 7-8 weeks. At the completion of therapy, all three patients major Lyme symptoms remained in remission for a period of 25-30 months. In conclusion, Double dose dapsone therapy could represent a novel and effective anti-infective strategy in chronic Lyme disease/PTLDS, especially in those individuals who have failed regular dose dapsone combination therapy (DDS CT) or standard antibiotic protocols. A randomized, blinded, placebo-controlled trial is warranted to evaluate the efficacy of DDD CT in those individuals with chronic Lyme disease/PTLDS.

With the rapid advancements in remote sensing technology, the spectral information from hyperspectral remote sensing images has become increasingly rich, facilitating detailed spectral analysis of the Earth's surface objects. However, this abundance of spectral data poses significant challenges in data processing, such as the curse of dimensionality leading to the “Hughes” phenomenon, "strong correlation" due to high resolution, and "non-linear characteristics" caused by varied surface reflectance rates. Therefore, dimensionality reduction of hyperspectral data has become a crucial task. This paper, grounded in manifold theory and manifold learning techniques, and considering the non-linear structures and features in hyperspectral remote sensing data, elucidates the principles and processes of dimensionality reduction in hyperspectral remote sensing images using manifold learning, with a formalized expression of the process. This article introduces spectral information divergence (SID) into the nearest neighbor graph computation of manifold learning algorithms. The principles and computational processes of nearest neighbor graph algorithms based on Euclidean distance (ED), spectral angle mapping (SAM), and SID are studied, and a comparative analysis of the dimensionality reduction effects under these three metrics in hyperspectral data is conducted. Experiments on feature extraction under different metrics were performed using the publicly available Indian Pines hyperspectral dataset. The intrinsic features obtained post-dimensionality reduction were used as inputs for classification algorithms in ground objects classification experiments, with algorithm runtime, overall accuracy, and Kappa coefficient as evaluation metrics for dimensionality reduction quality. The results demonstrate that nearest neighbor graph computation based on SAM and SID outperforms traditional ED methods; SAM-based computation has the lowest time complexity, while SID-based manifold learning yields the highest accuracy in ground objects classification. Thus, manifold learning based on SAM and SID metrics proves to be an effective method for feature extraction in hyperspectral remote sensing data, underscoring the potential of manifold learning techniques in the dimensionality reduction of hyperspectral remote sensing images.

TAFRO syndrome (TS) is a rare variant of idiopathic multicentric Castleman's disease (iMCD) characterized by a confluence of symptoms: thrombocytopenia (T), anasarca (A), fever (F), reticulin myelofibrosis (R), and organomegaly (O). First described in Japan in 2010, the pathogenesis of the disease remains unclear. Due to its heterogeneous presentation and potential life-threatening delays in diagnosis, precise diagnosis is essential. According to the literature, no specific imaging modality has been recommended for the work-up of patients with suspected TS. Here, we report a case of TS and its management using 18F-FDG-PET/CT imaging as an attractive complementary diagnostic tool.

Background: A careful work-up before Transcatheter aortic valve replacement (TAVR) consists not only of measuring anatomical conditions but also assessment of frailty. Previous studies have evaluated body composition parameters, primarily fat and muscle mass. Few data are available on other frailty parameters, which, however, can be easily determined by pre-TAVR computed tomography (CT). Objectives: The primary objective was to investigate the impact of total muscle area (TMA) and visceral adipose tissue (VAT), as frailty parameters, on 5-year all-cause mortality in patients undergoing TAVR. Methods: Between 01/2017 and 12/2018, consecutive TAVR patients undergoing CT-angiography scan enabling TMA and VAT measurement were included. A single axial image was acquired at the level of the middle third lumbar vertebra to perform TMA and VAT measurements using dedicated slicing software (Sliceomatic, TomoVision). Results: A total of 500 patients qualified for TMA analysis. Age was not associated with a higher risk of 5-year mortality HR 1.02 (95% CI: 0.998 - 1.049; p=0.069). Body surface area normalized TMA (nTMA) was significantly associated with 5-year all-cause mortality (HR 0.927, 95% CI: 0.927-0.997; p= 0.033), while VAT had no effect (HR 1.002, 95% CI: 0.99-1.015; p= 0.7). The effect of nTMA on 5- year all-cause mortality was gender-dependent: the protective effect of higher nTMA was found in male patients (pinteraction: sex * nTMA = 0.007). The combination of normalized TMA and VAT was not associated with higher mortality rates. Conclusion: Normalized TMA derived from routine CT before TAVR complements frailty assessment in patients undergoing TAVR.

Breast cancer has become the most diagnosed cancer in women globally with 2.3 million new diagnosis each year. Accurate early staging is essential for improving survival rates with metastatic spread from loco regional to distant metastasis decreasing rates by 50%. Current guidelines do not advice the routine use of Positron Emission Tomography (PET)-Computed Tomography (CT) in staging of early breast cancer in the absence of symptoms. However, there is a growing body of evidence to suggest that PET-CT used in this early stage can benefit the patient by improving staging and as a result treatment and outcome as well as psychological burden without increasing costs to the health service. Ongoing research in PET radiomics and artificial intelligence is showing promising future prospects in its use in diagnosis, staging, prognosticatication and assessing response to treatment in breast cancer. Furthermore ongoing research to address current limitations of PET-CT by improving techniques and tracers is encouraging.

Some bispecific radiotracers have been developed to overcome the limitations of monospecific tracers and improve detection sensitivity for heterogeneous tumor lesions. Here we aim to synthesize two bispecific tracers targeting prostate-specific membrane antigen (PSMA) and fibroblast activation protein (FAP), which are key markers expressed in prostate cancer. A pyridine-based FAP-targeted ligand was synthesized through multi-step organic synthesis, and then connected to the 2-Nal-containing PSMA-targeted motif. Ki(PSMA) values of Ga-complexed bispecific ligands, Ga-AV01084 and Ga-AV01088, were 11.6 ± 3.25 and 28.7 ± 6.05 nM, respectively, and the IC50(FAP) values of Ga-AV01084 and Ga-AV01088 were 10.9 ± 0.67 and 16.7 ± 1.53 nM, respectively. The uptake values for PSMA-expressing LNCaP tumor xenografts were 9.05 ± 1.54 and 8.85 ± 1.25 %ID/g for [68Ga]Ga-AV010184 and [68Ga]Ga-AV01088, respectively, which were lower than the monospecific PSMA-targeted tracer [68Ga]Ga-PSMA-617 (16.7 ± 2.30 %ID/g). The uptake values for FAP-expressing HEK293T:hFAP tumor xenografts were 1.90 ± 0.41 and 1.20 ± 0.25 %ID/g for [68Ga]Ga-AV01084 and [68Ga]Ga-AV01088, respectively, which were also lower than the monospecific FAP-targeted tracer, [68Ga]Ga-AV02070 (7.93 ± 1.88 %ID/g). Further investigations are needed to optimize the selection of linkers and targeted pharmacophores to improve the tumor uptake of PSMA/FAP bispecific tracers for prostate cancer imaging.

The success rate of extracorporeal shock wave lithotripsy (ESWL) is influenced by various factors, including stone density, which is determined through computed tomography scans in Hounsfield Units (HU). Materials and method: This retrospective single-center study was conducted in King Fahad hospital. Sixty-seven adult patients with renal and ureteric stones were selected randomly and enrolled in the study. Their age ranged from 20 to 69 years. The patients were examined with non-contrast enhancement (NCCT) to assess the HU of stones, consequently, treated with ESWL. Results: of the 67 patients, 37.3% of the stones were completely fragmented, while 62.7% were partially fragmented. HU, location of the stone, a multiplicity of the stone, and patient age were significant factors contributing to stone fragility (p-values&lt; 0.05). The HU has a positive significant linear correlation with serum calcium (r= .28, p-value=.036), while serum acid has a negative correlation (r=-.55, p-value= &lt; .001). Thus, the probability of calcium-containing stones formation increased with increased HU. In contrast, uric acid stone formation is likely to develop with decreasing HU with serum uric acid. Renal stones in patients with diabetes mellitus and hypertension were not completely fragmented compared to those without clinical history. Conclusion: Mean HU, location of the stone, laterality, status of stone, and the number of ESWL sessions were the most significant factors affecting stone fragility. CT attenuation values can predict the composition of stones from serum calcium and uric acid examinations. Hypertension and Diabetes mellitus are risk factors for renal stone fragmentation.

This study compared condylar volume, length, and articular eminence (AE) characteristics in normal individuals and those with unilateral and bilateral juvenile idiopathic osteoarthritis (JOA). The 116 patients were divided into four groups: control (n=16), affected condyle of unilateral JOA (Aff-Uni) (n=36), non-affected condyle of JOA (NonAff-uni) (n=36), and bilateral JOA (Bi-JOA) (n=28). Volume and length differences in the condyle and AE were analyzed using ANOVA and Bonferroni post hoc tests. The results showed that Bi-JOA had significantly different condylar volume, especially in the condylar head (p&lt;0.01), specifically the middle, anterior, and medial parts (p&lt;0.05). Condylar length also differed among the groups, with differences observed between the control group and the other three groups, as well as between the bilateral group and the other three groups (p&lt;0.01). AE total volume differed between the control group and Aff-Uni. In the detailed comparison, Aff-Uni and NonAff-Uni were smaller than the control group in the posterior, lateral, and medial sections (p&lt;0.05). In conclusion, depending on the involvement of unilateral or bilateral JOA, there were differences in condylar volume and AE compared to the normal control group. Therefore, prognosis should be evaluated by distinguishing between patients with unilateral and bilateral JOA.

(1) Background: This retrospective study aimed to compare the efficacy and safety of one-stage computed tomography (OSCT)- to that of two-stage computed tomography (TSCT)-guided localization for the surgical removal of small lung nodules. (2) Methods: We collected data from patients with ipsilateral pulmonary nodules who underwent localization before surgical removal at Veteran General Hospital Kaohsiung between October 2017 and January 2022. The patients were divided into the OSCT and TSCT groups. (3) Results: We found that OSCT significantly reduced the localization time and risky time compared to TSCT, and the success rate of localization and incidence of pneumothorax were similar in both groups. However, the time spent under general anesthesia was longer in the OSCT group than in the TSCT group. (4) Conclusions: The OSCT-guided approach to localize pulmonary nodules in hybrid operation room is a safe and effective technique for the surgical removal of small lung nodules.

Deep convolutional neural networks (CNN) are favored methods widely used in medical image processing due to their assured shown performance. Recently, the emergence of new lung diseases and the possibility of early detection of their symptoms has attracted many researchers to classify diseases by training deep CNNs on lung CT images. The trained networks are expected to distinguish between lung indications in different diseases, especially at the early stages of them. With the hope of achieving this purpose, we proposed an efficient deep CNN called AFEX-Net with adaptive feature extraction layers that successfully extract distinguishing features and classify chest CT images. The efficiency of the proposed network has two aspects: it is a lightweight network with low number of parameters and fast training and it has adaptive pooling layers and adaptive activation functions to increase its level of compatibility to the input data. The proposed network has been evaluated on a dataset with more than 10K chest CT slices, while an efficient pre-processing method is developed to remove any bias from the images. Additionally, we evaluated the performance of the proposed model on the public COVID-CTset dataset to prove the generalisability of our model. The obtained results confirm the competence of the proposed network in confronting medical images, where prompt and accurate learning is required.

Purpose: To assess the utility of measurement of the computed tomography (CT) attenuation value (CTav) in predicting tumor necrosis in hepatocellular carcinoma (HCC) patients who achieve a complete response (CR), defined using modified Response Evaluation Criteria in Solid Tumors (mRECIST), after lenvatinib treatment. Method: We compared CTav in arterial phase CT images with postoperative histopathology in four patients who underwent HCC resection after lenvatinib treatment, to determine CTav thresholds indicative of histological necrosis (N-CTav). Next, we confirmed the accuracy of the determined N-CTav in 15 cases with histopathologically proven necrosis in surgical specimens. Furthermore, the percentage of the tumor with N-CTav, i.e. the N-CTav occupancy rate, assessed using Image J software in 30 tumors in 12 patients with CR out of 571 HCC patients treated with lenvatinib, and its correlation with local recurrence following CR were examined. Results: Receiver operating characteristic (ROC) curve analysis revealed an optimal cut-off value of CTav of 30.2 HU, with 90.0% specificity and 65.0% sensitivity in discriminating between pathologically identified necrosis and degeneration, with a CTav of less than 30.2 HU indicating necrosis after lenvatinib treatment (N30-CTav). Furthermore, the optimal cut-off value of 30.6% for the N30-CTav occupancy rate by ROC analysis was a significant indicator of local recurrence following CR with 76.9% specificity and sensitivity (area under the ROC curve; 0.939), with the CR group with high N30-CTav occupancy (&gt;30.6%) after lenvatinib treatment showing significantly lower local recurrence (8.3% at 1 year) compared with the low (&lt;30.6%) N30-CTav group (P&lt;0.001, 61.5% at 1 year). Conclusion: The cut-off value of 30.2 HU for CTav (N30-CTav) might be appropriate for identifying post-lenvatinib necrosis in HCC, and an N30-CTav occupancy rate of &gt;30.6% might be a　predictor of maintenance of CR. Use of these indicators have the potential to impact systemic chemotherapy for HCC.

Uveal melanoma is the most common primary intraocular malignancy in adults characterized by insidious onset and poor prognosis strongly associated with tumor size and the presence of distant metastases, most commonly in the liver. Contrary to most tumor identification, biopsy followed by pathological exam is not recommended in ophthalmic oncology. Therefore, early and non-invasive diagnosis is essential to enhance patients’ chances for early treatment possibilities. We reviewed imaging modalities currently used in the diagnosis of uveal melanoma, i.e., fundus imaging, ultrasonography (US), optical coherence tomography (OCT), single-photon emission computed tomography (SPECT), positron emission tomography/computed tomography (PET/CT), magnetic resonance imaging (MRI), fundus fluorescein angiography (FFA), indocyanine green angiography (ICGA), fundus autofluorescence (FAF). The principle of imaging techniques was briefly explained, along with their role in the diagnostic process and a summary of their advantages and limitations. Further, the experimental data and the advancements in imaging modalities were searched. We described their innovations, showed current usage and research, and explained the possibilities of utilizing them to diagnose uveal melanoma and their potential application in personalized medicine such as theranostics.

ST-elevation myocardial infarction (STEMI) remains one of the leading causes of morbidity and mortality worldwide. The identification of novel metabolic and imaging biomarkers could unveil key pathophysiological mechanisms at the molecular level and promote personalized care in patients with acute coronary syndromes. We studied 38 patients with STEMI who underwent primary percutaneous coronary intervention and thrombus aspiration. We sought to correlate serum ceramide levels with micro-CT quantified aspirated thrombus volume and relevant angiographic outcomes, including modified TIMI thrombus grade and pre- or post-procedural TIMI flow. Higher ceramide C16:0 levels were significantly, but weakly correlated with larger aspirated thrombus volume (Spearman r=0.326, p=0.046), larger intracoronary thrombus burden (Nagelkerke R2=0.236, p=0.030) and worse pre- and post-procedural TIMI flow (Nagelkerke R2=0.210; p=0.049 and Nagelkerke R2=0.277; p=0.039, respectively). Ceramides C24:0 and C24:1 were also significantly associated with larger intracoronary thrombus burden (Nagelkerke R2=0.311; p=0.008 and Nagelkerke R2=0.423; p=0.001, respectively). In conclusion, serum ceramide levels (mainly C16:0 and C24:1) were higher among patients with larger intracoronary and aspirated thrombus burden. This suggests that quantification of serum ceramides might improve risk-stratification of patients with STEMI and facilitate a more individualized approach in everyday clinical practice.

The aim of this study was to clarify degradation characteristics in each tissue of the knee complex of a medial meniscectomy (MMx)-induced knee osteoarthritis (KOA) animal model using classical methods and a new comprehensive evaluation method called contrast-enhanced X-ray micro-computed tomography (CEX-μCT), which was developed in the study. Surgical MMx was performed in the right knee joints of five male Wistar rats to induce KOA. At 4 wk post-surgery, the synovitis was evaluated using qPCR. Degradations of the articular cartilage of the tibial plateau were evaluated using classical methods and CEX-μCT. Evaluation of the synovitis demonstrated significantly increased expression levels of inflammation-associated marker genes in MMx-treated knees compared to that in sham-treated knees. Evaluation of the articular cartilage using classical methods showed that MMx fully induced degradation of the cartilage. Evaluation using CEX-μCT showed that local areas of the medial cartilage of the tibial plateau were significantly reduced in MMx-treated knees compared to that in sham-treated knees. On the other hand, total cartilage volumes were significantly increased in MMx-treated knees. Based on the findings of this study, the researchers in KOA research could be helped to select an optimal KOA model to discover new drugs.

The paper highlights the performance of the seismic isolation devices, installed on retrofitted buildings in reducing the seismic response when subjected to earthquakes. Two buildings from the beginning of the XX-th century in Bucharest are chosen from many more, monitored over the city area. We discuss the response of these base-seismic isolated structures, relying on good quality data acquired from the recent strong earthquake (03.11.2022, MW = 5.0). Elastic response spectra computed from recordings at two levels of each structure are used, placed under and right above the isolating layer. At one building the existence of previous recordings and the particularity of the sensors allow a comparison with other two relatively recent medium intensity earthquakes. The assessment is carried out in terms of maximum acceleration amax, measured at certain levels in each structure, spectral acceleration amplitude SAmax and spectral-peak corresponding period. We find that the base-isolation methodology is effective in reducing the response of the building right above the isolating layer, an observation valid for both structures, all components of the recordings, and spectral acceleration values. Moreover, the outcomes from the modal evaluation performed prior to rehabilitation and seismic isolation process are presented, by pointing out a higher newly acquired fundamental period of the isolated structures.

The spectrums of one type of object under different conditions have the same features (up, down, protruding, concave) at the same spectral positions, which can be used as primary parameters to evaluate the difference among remotely sensed pixels. Wavelet-feature correlation ratio Markov clustering algorithm (WFCRMCA) for the remotely sensed data is proposed based on an accurate description of abrupt spectral features and an optimized Markov clustering in the wavelet feather space. The peak points can be captured and identified by applying a wavelet transform to spectral data. The correlation ratio between two samples is a statistical calculation of the matched peak point positions on the wavelet feature within an adjustable spectrum domain or a range of wavelet scales. The evenly sampled data can be used to create class centers, depending on the correlation ratio threshold at each Markov step, accelerating the clustering speed by avoiding the computation of Euclidean distance for traditional clustering algorithms, such as K-means and ISODATA. Markov clustering applies several strategies, such as a simulated annealing method and gradually shrinking the clustering size, to control the clustering convergence. At each clustering tempera-ture, it can obtain the best class centers quickly. The experimental results of the Airborne Visible/ Infrared Imaging Spectrometer (AVIRIS) and Thermal Mapping (TM) data have verified its ac-ceptable clustering accuracy and high convergence velocity.

A multispectral superconducting nanowire single photon detector sensitive to different incident photon wavelength bands, is proposed. The SNSPD consists of a Distributed Bragg Reflector, a gold mirror, and two regions employing four NbN nanowires. Using the DBR both as a filter and a reflector, two distinct detection bands are created. The first detection band has a peak absorbance of > 0.75 at a wavelength of 1143 nm, while the second band has an absorbance of > 0.70 in the wavelength range 1440 to 2000 nm. The design of the device can be tuned to provide sensitivity in different wavelength bands. While SNSPDs do not typically provide photon wavelength sensitivity, the band-selection design proposed in this work opens up potential applications for future quantum communication technology.

The paper deals with applying Artificial Intelligence techniques to examine CHIRP-recorded data in sand and sandstone sea-bottom sites. The provided analysis of the state of the art portrays that actual time series or spectrum backscattered data from a point on the sea bottom were rarely used as the features for machine learning models. The results of the examination indicate that types of sea bottom can be quantitatively characterized by applying logistic regression models to either the backscatter time series of a frequency-modulated signal or the spectrum of that backscatter. The examination accuracy reached 90% for the time series and 94% for the spectra. The application of spectral data as features for more advanced machine learning algorithms, and the advantages of its combination with other types of data have great potential for future research and the enhancement of remote marine soil classification.

In the context of the Atmospheric Observing System (AOS) international program, a new generation spaceborne lidar is expected to be in polar orbit for deriving new observations of aerosol and clouds. In this work, we analyze the added values of these new observations for characterizing aerosol vertical distribution. For this, synthetic observations are simulated using the BLISS lidar simulator in terms of backscatter coefficient at 532 nm. We consider two types of lidar instruments, an elastic backscatter lidar instrument and a high spectral resolution lidar (HSRL). These simulations are performed with atmospheric profiles from a Nature Run (NR) modeled by the MOCAGE Chemical Transport Model. In three case studies involving large events of different aerosol species, the added value of the HSRL channel for measuring aerosol backscatter profiles with respect to simple backscatter measurements is shown. Observations independent from an a-priori lidar Ratio assumption, as done typically for simple backscattering instruments, allows probing the vertical structure of aerosol layers without divergence, even in case of intense episodes. Relative error in the backscatter coefficient profiles are observed to lay between +40% and -40% for low abudancies, with mean biases between +5% and -5%. A 5-day study in the case of desert dust completes the study of the added value of the HSRL channel with relative mean bias from the NR of the order of 1.5%.

We develop the theory of Heyting small spaces and prove a new version of Esakia duality for such spaces. To do this, we notice that spectral spaces may be seen as sober small spaces with all smops compact and introduce the method of the standard spectralification. This helps to understand open continuous definable mappings between definable spaces over o-minimal structures.

Extensive growth in the volume of irregular brain cells is known as brain tumor. Human brain is surrounded by stiff skull. There are various issues that occur due to the growth of any tumor inside this restricted space. The malignant and benign are two main categories of the brain tumor. The skull is pressurized to enlarge from inside in case of growth of any benign or malignant tumor. This tumor leads to harm in brain and it may be dangerous to life also. The brain tumor is divided into two kinds - primary or secondary. The brain tumor detection techniques have various phases. In this paper, comparative study of CNN with GLCM approach and superpixel based spectral clustering is done tumor. This work takes into account metrics like accuracy, sensitivity and specificity for drawing the comparison between both the techniques.

Bistable rhodopsins have two stable forms which can be interconverted by light. Due to their ability to act as photoswitches, these proteins are considered as ideal candidates for applica-tions such as optogenetics. In this work we analyze a recently crystalized bistable rhodopsin, namely the jumping spider rhodopsin-1 (JSR1). This rhodopsin exhibits identical absorption maxima for the parent and the photoproduct form, which impedes its broad application. We have performed hybrid QM/MM simulations to study three isomers of the retinal chromo-phore: the 9-cis, 11-cis and all-trans configurations. The main aim was to gain insight into the specific interactions of each isomer and their impact on the absorption maximum in JSR1. The absorption spectra were computed using sampled snapshots from a QM/MM molecular dy-namics trajectory and compared to experimental counterparts. The chromophore-protein in-teractions were analyzed by visualizing the electrostatic potential of the protein and projecting it onto chromophore. It was found that the distance between a nearby tyrosine (Y126) residue plays a larger role in the predicted absorption maximum than the primary counterion (E194). Geometric differences between the isomers were also noted including a structural change in the polyene chain of the chromophore as well as changes in the nearby hydrogen bond network.

In cotton cultivars, an insect that causes irreversible damage is the Spodoptera frugiperda, known as the fall armyworm. Since the visual detection of plants is a burdensome task for human inspection, the spectral information related to plant damage, registered on a spectral scale, can be useful. These measurements, associated with machine learning techniques, produce useful information for a rapid and non-invasive inspection method development. To contribute to this gap fulfillment, this paper proposes a machine learning framework to model the spectral response of cotton plants under the attack of the fall armyworm. Additionally, a theoretical model is presented, built from the results of the machine learning analysis, to infer this damage with up-to-date orbital sensors. The data was composed of the reflectance measurements collected at a cotton field with control plants and plants submitted to Spodoptera frugiperda damage. Their spectral response was recorded with a hand-held spectroradiometer ranging from 350 to 2,500 nm, for eight consecutive days. Different machine learning models were evaluated and the overall best model was defined by accuracies comparisons on a testing-set. A ranking approach was adopted based on the model accuracy, returning the most contributive wavelengths for the classification. Sequentially, an unsupervised neural network (Self-Organizing Map - SOM) was implemented to reduce data-dimensionality and assist in the definition of important spectral regions. The regions were associated with the spectral bands of the two sensors (OLI and MSI) and a theoretical model using a band simulation process with the overall best machine learning model was proposed. The results indicated that the Random Forest (RF) algorithm is the most suitable to predict cotton-plants damaged by insects and that the last day of analysis (8th day) was better to separate it, with F-measure equals 0.912. The ranking approach combined with the SOM method indicated the spectral regions at the red to near-infrared (650 to 1,350 nm) and shortwave infrared (1,570 to 1,640 nm) as the most important regions to the analysis. The proposed theoretical model simulated with the OLI and MSI sensor-bands returned an F-Measure of 0.865 and 0.886, respectively. In conclusion, this framework can be used to map cotton-plants under insect-attack. The theoretical model presents high accuracy to infer the insect-damaged on cotton plants based on multispectral bands from other sensors, being a useful tool for future research that intends to evaluate it in other areas and at different field scales.

With the dramatic increase in world population, continued advances in modern greenhouse agriculture and plant growth practices are expected to help overcome the global problem of future food shortages. Next generation greenhouse design practices will need to address a range of issues, ranging from energy and land use efficiency to providing plant-optimised growth techniques. In this paper, we focus on investigating the optimum irradiation spectra matched to the lettuce species (Lactuca sativa, L.), which is commonly grown in greenhouse environments, in order to develop low-emissivity glass panes that maximize the biomass productivity of glass greenhouses. This low-emissivity glass passes the solar spectral components needed for crop growth, while rejecting other unwanted radiations, leading to significant energy savings and other beneficial effects related to greenhouse climate control, in a range of climates. This is due to reducing both the solar heat gain and photosaturation, which can raise the temperature of the crops to harmful levels. Experimental results show that substantial biomass productivity improvements in lettuce (up to ~14.7%) can be attained using spectrally optimized illumination, compared with white light irradiation. We also report on the development of advanced metal-dielectric thin-film filters that produce the optimum illumination spectrum when exposed to sunlight.

We calculate the spectral function of a boson ladder in an artificial magnetic field by means of analytic approaches based on bosonization and Bogoliubov theory. We discuss the evolution of the spectral function at increasing effective magnetic flux, from the Meissner to the Vortex phase, focussing on the effects of incommensurations in momentum space. At low flux, in the Meissner phase, the spectral function displays both a gapless branch and a gapped one, while at higher flux, in the Vortex phase, the spectral function displays two gapless branches and the spectral weight is shifted at a wavevector associated to the underlying vortex spatial structure which can indicate a 8 supersolid-like behavior. While the Bogoliubov theory, valid at weak interactions, predicts sharp delta-like features in the spectral function, at stronger interactions we find power-law broadening of 10 the spectral functions due to quantum fluctuations as well as additional spectral weight at higher 11 momenta due to backscattering and incommensuration effects. These features could be accessed in 12 ultracold atom experiments using radio-frequency spectroscopy techniques.

In this study, we investigate spectral structure of conformable Sturm-Liouville problems and with this end, we obtain representation of solutions under different initial conditions and asymptotic formulas for eigenfunctions, eigenvalues, norming constants and normalized eigenfunctions. Consequently, we prove the existence of infinitely many eigenvalues. Also, we compare the solutions with graphics with different orders, different eigenvalues, different potentials and so, we observe the behaviors of eigenfunctions. We give an application to the α-orthogonality of eigenfunctions and reality of eigenvalues for conformable Sturm-Liouville problems defined by [15] in the last section.

UAS-based multi-spectral imagery is becoming increasingly popular for the improved monitoring and managing of various horticultural crops. However, for UAS data to be used as an industry standard for assessing tree structure and condition as well as production parameters, it is imperative that the appropriate data collection and pre-processing protocols are established to enable multi-temporal comparison. There are several UAS-based radiometric correction methods commonly used for precision agricultural purposes. However, their relative accuracies have not been assessed for data acquired in complex horticultural environments. This study assessed the variations in estimated surface reflectance values of different radiometric corrections applied to multi-spectral UAS imagery acquired in both avocado and banana orchards. We found that inaccurate calibration panel measurements, inaccurate signal-to-reflectance conversion, and high variation in geometry between illumination, surface, and sensor viewing produced significant radiometric variations in at-surface reflectance estimates. Potential solutions to address these limitations included appropriate panel deployment, site-specific sensor calibration, and appropriate BRDF correction. Future UAS based horticultural crop monitoring can benefit from the proposed solutions to radiometric corrections to ensure they are using comparable image-based maps of multi-temporal biophysical properties.

This algorithm is designed to perform Discrete Fourier Transforms (DFT) to convert temporal data into spectral data. This algorithm obtains the Fourier Transforms by studying the Coefficient of Determination of a series of artificial sinusoidal functions with the temporal data, and normalizing the variance data into a high-resolution spectral representation of the time-domain data with a finite sampling rate. What is especially beneficial about this DFT algorithm is that it can produce spectral data at any user-defined resolution.

In the present study, field observation wind data from the time of the wind turbine blade damage accident on Shiratakiyama Wind Farm were analyzed in detail. In parallel, high-resolution LES turbulence simulations were performed in order to examine the model’s ability to numerically reproduce terrain-induced turbulence. The comparison of the observed and simulated time series (1 second average values) from a 10 minute period from the time of the accident led to the conclusion that the settings of the horizontal grid resolution and time increment are important to numerically reproduce the terrain-induced turbulence that caused the wind turbine blade damage accident on Shiratakiyama Wind Farm. A spectral analysis of the same set of observed and simulated data revealed that the simulated data reproduced the energy cascade of the actual terrain-induced turbulence well.

LR004 is a novel chimeric (human/mouse) monoclonal antibody developed for the treatment of advanced colorectal carcinoma with detectable epidermal growth factor receptor (EGFR) expression. We aimed to investigate the preclinical pharmacokinetics (PK) and in vivo biodistribution of LR004. The PK profiles of LR004 were initially established in rhesus monkeys. Subsequently, 125I radionuclide-labeled LR004 was developed and its binding activity to the EGFR antigen were evaluated. Furthermore, the biodistribution, autoradiography, and NanoSPECT/CT of 125I-LR004 in xenograft mice bearing A431 tumors were examined. The PK data revealed a prolonged half-life and nonlinear PK characteristics of LR004 within the dose range of 6–54 mg/kg. The radiochemical purity of 125I-LR004 was approximately 98.54%, and iodination of LR004 did not affect its specific binding activity to the EGFR antigen. In a classical biodistribution study, 125I-LR004 exhibited higher uptake in highly perfused organs than in poorly perfused organs. Prolonged retention properties of 125I-LR004 in tumors were observed at 4 and 10 days. Autoradiography and NanoSPECT/CT confirmed the significant accumulation and sustained retention of 125I-LR004 at the tumor site in xenograft mice. These findings demonstrated the adequate tumor targeting capabilities of 125I-LR004 in EGFR-positive tumors, which may improve dosing strategies and future drug development.

Endovascular therapy (EVT) has revolutionized the management of acute ischaemic strokes with large vessel occlusion, with emerging evidence suggesting its benefit also in large infarct core volume strokes. In the last 2 years, 4 randomised controlled trials have been published on this topic - RES-CUE-Japan-LIMIT, ANGEL-ASPECT, SELECT2 and TENSION, with overall results showing that EVT improves functional and neurological outcomes compared to medical management alone. This review seeks to summarise the recent evidence presented by these 4 trials and highlight some of the limitations of our current understanding on this topic.

To prevent CO2 leakage and ensure the safety of long-term CO2 storage, it is essential to investigate the flow mechanism of CO2 in complex pore structures at the pore scale. This study focuses on reviewing the experimental, theoretical, and numerical simulation studies on the microscopic flow of CO2 in complex pore structures during the last decade. For example, advanced imaging techniques, such as X-ray computed tomography (CT) and nuclear magnetic resonance (NMR), are used to reconstruct the complex pore structures of rocks. Mathematical methods, such as Darcy's law, Young–Laplace’s law, and the Navier-Stokes equation, are used to describe the microscopic flow of CO2. Numerical methods, such as the lattice Boltzmann method (LBM) and pore network (PN) model, are used for numerical simulation. The application of these experimental and theoretical models and numerical simulation studies is discussed, considering the effect of complex pore structures. Finally, future research is suggested to focus on: (1) Conducting real-time CT scanning experiments of CO2 displacement combined with the developed real-time CT scanning clamping device to realize real-time visualization and provide quantitative description of the flow behavior of CO2 in complex pore structures; (2) The effect of pore structures change on the CO2 flow mechanism caused by the chemical reaction between CO2 and the pore surface, the flow theory of CO2 considering wettability and damage theory in a complex pore structures; (3) The flow mechanism of multi-phase CO2 in complex pore structures; (4) The flow mechanism of CO2 in the pore structures at multiscale and the scale upgrade from microscopic to mesoscopic to macroscopic. Generally, this study focuses on reviewing the research progress of CO2 flow mechanisms in complex pore structures at the pore scale and affords an overview of potential advanced developments to enhance the current understanding of CO2 microscopic flow mechanisms.

Despite the available literature on traumatic brain injury (TBI) biomarkers elsewhere, data are limited or non-existent in sub-Saharan Africa (SSA). The aim of the study was to analyse associations in acute TBI between admission serum biomarker concentrations and TBI severity, CT-scan findings and outcome as well as explore the influence of concurrent Toxoplasma gondii infection. Concentrations of serum biomarkers (GFAP, NFL Tau, UCH-L1, and S100B) were measured and Toxoplasma gondii detected in samples obtained <24 hours post-injury. The GOSE was used to evaluate 6 months outcome. All biomarkers levels increased with severity of TBI, but this increase was significant only for NFL (P=0.01). GFAP values significantly increased (P=0.026) in those with unfavorable outcome. Tau levels were higher in those who died (P=0.017). GFAP and NFL were sensitive to CT-scan pathology (p values respectively 0.004 and 0.002). S100B levels were higher (P<0.001) in TBI patients seropositive to Toxoplasma gondii. NFL was found to be sensitive to TBI severity while NFL and GFAP were predictive of CT intracranial abnormalities. Increased levels of GFAP and Tau were associated with poorer outcomes 6 months after TBI. S100B levels were significantly higher in T. gondii seropositive TBI patients.

Aim of the study: To draw inferences from a retrospective evaluation of PSMA PET CT scans performed for the evaluation of biochemical recurrence. Material and Methods: Retrospective analysis of 295 PSMA PET CT scans spanning 3 years between 2020 and 2022 was undertaken. Results: Of 295 PET CT scans, 179 were positive, 66 negative and 50 had indeterminate findings. In positive group, 67 had radical prostatectomy and PSMA avid lesions were seen most commonly in pelvic lymph nodes. Remaining 112 positive scans, in non-radical prostatectomy group; 25 had recurrence only in prostate, 17 had recurrence involving prostate bed; 28 had no recurrence in prostate gland, while 42 had recurrence in prostate as well as extra prostatic sites. Overall, in non-prostatectomy group, 75 % population was harbouring a PSMA avid lesion in prostate gland while in remaining 25% population recurrence did not involve prostate gland. Majority of indeterminate findings were seen in small pelvic or retroperitoneal lymph nodes or skeletal regions (ribs/others) and in 9 patients indeterminate focus was seen in the prostate bed only. Follow up PSMA PET CT was helpful in prior indeterminate findings and unexplained PSA rise. Conclusion: A higher recurrence in prostate bed while evaluating biochemical recurrence prompts us to think; whether prostatectomy should be offered more proactively? Follow up PSMA PET CT is helpful for indeterminate findings; a PSA rise of 0.7 ng/ml in 6 months can result in positive PSMA PET CT while negative scan can be seen upto 2ng/ml PSA rise in 6 months.

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.

Expressive clinical terminologies are of utmost importance for achieving an semantically interoperable data exchange and reuse in healthcare. SNOMED CT, widely respected as the most comprehensive terminology in medicine, provides formal concept definitions based on description logic which not only allows for advanced querying of SNOMED CT-coded data but also for flexibly augmenting its 350,000 concepts. This ability for postcoordination largely increases the expressivity of the terminology but correlates with an intrinsic complexity. Complicated by the current lack of tooling support, postcoordination is widely either ignored or applied in an error-prone way. To help facilitate the adoption of postcoordination, we implemented a web application that guides through the creation of Postcoordinated expressions (PCEs) while ensuring the adherence to syntactic and semantic constraints. Our approach was largely facilitated by making use of the extensive SNOMED CT specifications as well as advanced HL7 FHIR Terminology Services. Qualitative evaluations confirmed the usability of the developed application and the correctness of PCEs created with it.

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.

Conventional pervious pavement materials (PPM) consist of cement and aggregate materials and are known for poor durability due to their brittle behavior. Herein, we fabricated polymeric PPMs from durable and abundant polyurethane (PU) to enhance the durability of the material and undertook mechanical and microscopic characterizations. PU-based PPM samples with varying aggregate sizes were produced and the compressive strength and water permeability of each were examined. The pore and tortuosity characteristics of the specimens were analyzed using X-ray micro-computed tomography (micro-CT). Through the micro-CT analysis, the morphological characteristics of the internal structures of PPM were identified and the correlations between the pore size distribution, connectivity, and tortuosity within the specimen were quantitatively analyzed. The microstructures derived from micro-CT were generated as a finite element model and the stress distribution generated inside was numerically determined.

The incidence of cancer in organ transplant patients is higher than in the non-transplanted population. The incidence increases with increasing age. The use of Fludeoxyglucose positron emission tomography/CT (PET/CT) is sensitive and specific to detect PTLD LD compared with conventional CT imaging. We analyzed the medical data of 127 patients aged over 60 years, who underwent heart transplantation in the above period, who have been practicing early CT-PET for diagnostic purposes between February 2007 and October 2018. Of 127 consecutive patients who underwent CT-PET, SUVs up than 4, were found in 84 patients of which 20 were affected by PTLDs, seven patients were affected by chronic non neoplastic inflammatory diseases, the remainder were affected by other neoplasms. The favorable effect of physical activity programs on cardiorespiratory and psychomotor function occur in all patients. In conclusion, CT-PET at the first doubts about the possibility of the development of neoplasms has allowed a diagnosis and then a treatment more quickly. Education in behavioral norms that improve the patient's quality of life is necessary.

This paper investigates the effects of air void topology on hydraulic conductivity in asphalt mixtures with porosity in the range 14%-31%. Virtual asphalt pore networks were generated using the Intersected Stacked Air voids (ISA) method, with its parameters being automatically adjusted by the means of a differential evolution optimisation algorithm, and then 3D printed using transparent resin. Permeability tests were conducted on the resin samples to understand the effects of pore topology on hydraulic conductivity. Moreover, the pore networks generated virtually were compared to real asphalt pore networks captured via X-ray Computed Tomography (CT) scans. The optimised ISA method was able to generate realistic 3D pore networks corresponding to those seen in asphalt mixtures in term of visual, topological, statistical and air void shape properties. It was found that, in the range of porous asphalt materials investigated in this research, the high dispersion in hydraulic conductivity at constant air void content is a function of the average air void diameter. Finally, the relationship between average void diameter and the maximum aggregate size and gradation in porous asphalt materials was investigated.