Pituitary adenomas are benign brain tumors that pose a heavy burden on patients worldwide. However, the local burden of disease is yet to be established due to scarcity of data. In line with this, this study aims to present the challenges and gaps in the treatment of pituitary adenomas in the Philippines. A scoping review of available relevant literature on epidemiology, clinical experience with treatment, health financing, and healthcare delivery system based on the Preferred Reporting Items for Systematic reviews and Meta-analysis guidelines extension for Scoping Reviews was conducted. The scarcity of updated local clinical data, inequity of distribution of resources, inadequate government support, and lack of affordable diagnostic testing, medications and neurosurgical procedures are the factors that hinder provision of adequate care of pituitary adenomas in the Philippines. There are notable treatment gaps in the management of pituitary adenomas in the Philippines, which may be addressed by strengthening universal healthcare. Strategies to address these gaps were proposed, including improving public-private insurance coverage, increasing manpower, enhancing accessibility to resources, and spreading more awareness.

The detection of subtle changes in the pituitary dimensions has relevant implications since this gland is crucial for the endocrine system. In cats, few studies established the cut-offs values of the pituitary gland’s dimensions, but using small and inhomogeneous samples. The aims of this study were: to determine by computed tomography (CT) the pituitary linear dimensions and the pituitary-to-brain (P:B) ratio in a sample of domestic short-haired (DSH) cats; to assess the effects of sex, age and weight on pituitary dimensions; to evaluate the inter- and intra-observer agreement for such measurements. Exclusion criteria were: clinical, laboratory or CT alterations of pituitary gland or brain diseases, fractures of the neurocranium, or diabetes mellitus. Pituitary dimensions and brain area were assessed by two different observers using multiplanar reconstructions and automated segmentation tools. Fifty-one cats were included in the final sample. The intraclass correlation coefficient for intra- and inter-observer reliability showed good/excellent and moderate/good reliability, respectively. No differences between sexes were detected, and negligible correlations were found with age and weight. Findings from the current study provided normal reference values for pituitary height (1.88 – 4.01 mm) and P:B ratio (0.25 – 0.49), useful for assessing abnormally enlarged pituitary gland in DSH cats.

Keywords: Y RNA; Canine hepatocellular carcinoma, canine hepatocellular adenoma

Prediction of tumor consistency is valuable for planning transsphenoidal surgery for pituitary adenoma. A prospective study was conducted involving 49 participants with pituitary adenoma to determine whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of adenoma. Pharmacokinetic parameters in the adenomas including volume of extravascular extracellular space (EES) per unit volume of tissue (ve), blood plasma volume per unit volume of tissue (vp), volume transfer constant between blood plasma and EES (Ktrans), and rate constant between EES and blood plasma (kep) were obtained. The pharmacokinetic parameters and the histologic percentage of collagen content (PCC) were compared between soft and hard adenomas using Mann–Whitney U test. Pearson’s correla-tion coefficient was used to correlate pharmacokinetic parameters with PCC. Hard adenomas showed significantly higher PCC (44.08 ± 15.14% vs. 6.62 ± 3.47%, p < 0.01), ve (0.332 ± 0.124% vs. 0.221 ± 0.104%, p = 0.02), and Ktrans (0.775 ± 0.401/min vs. 0.601 ± 0.612/min, p = 0.02) than soft adenomas. Moreover, a significant positive correlation was found between ve and PCC (r = 0.601, p < 0.01). The ve derived using DCE-MRI may have predictive value for consistency of pituitary adenoma.

“Gray zone” category tumors in thyroid follicular tumors are difficult to diagnose, especially to distinguish between follicular thyroid adenoma (FTA) and follicular thyroid carcinoma (FTC). This study aimed to assess the diagnostic performance of metabolite enzymes using imaging mass spectrometry to distinguish FTA from FTC and determine the association between metabolite enzyme expression with thyroid follicular borderline tumor diagnosis. Air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFAIDESI-MSI) was used to develop a classification model for the characteristics of thyroid follicular tumors among 24 samples. We analyzed the expression of metabolic enzyme markers in an independent validation set of 133 cases and evaluated the potential biological behavior of 19 borderline thyroid lesions. Phospholipids and fatty acids (FAs) were more abundant in FTA than in FTC (P<0.001). The metabolic enzyme panel—including FA synthase and Ca²⁺-independent PLA2, which are closely associated with altered metabolic pathways—was further identified in follicular thyroid tumors. The marker combination showed optimal performance in the validation group (area under the receiver operating characteristic curve, sensitivity, and specificity: 73.6%, 82.1%, 60.6%, respectively). The diagnostic strategy suggested considering a putative role of AFAIDESI-MSI in routine clinical triage for strict follow-up, with low metabolic enzyme expression combined with diagnostic in patients with a thyroid follicular borderline tumor diagnosis.

Background: The aim of this study has been to investigate if inflammatory biomarkers such as the systemic immune-inflammation index (SII), neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) have any correlation with the recurrence of pleomorphic adenomas (PA) in patients afflicted by this disease. Methods: A retrospective multicentre study involving two Italian centres, the Maxillofacial Sur-gery at the Policlinico Federico II in Naples and the ENT and Maxillofacial Surgery at the IRCCS G. Pascale National Cancer Institute in Naples, has been performed. The study, involving 608 pa-tients who had received a diagnosis of PA, was conducted between January 2000 and January 2020. A Receiver Operating Characteristic (ROC) curve was used to calculate the optimal cut-off values for the SII, PLR and NLR. A linear regression model (LRM) and a non-linear logistic re-gression model (NLRM) were realized with respect to the NLR, PLR and SII. Results: The highest performance was achieved by the NLR (cut-off 2.960) with the AUC = 0.91, with an accuracy of 96.1%, sensitivity of 78.4% and specificity of 97.2%, PPV = 64.4% and NPV = 98.6%. The LRM and NLRM including all the haematological parameters did not increase the per-formance in terms of recurrence detection. Conclusion: The NLR is an excellent support tool in predicting the recurrence of PA with a cut-off of 2.960. It can be a good reference point for surgical decision-making and follow-up in clinical practice.

Papillary thyroid carcinoma (PTC) has two main histologic variants: classical-PTC (CL-PTC) and follicular variant PTC (FV-PTC). Recently, due to its similar features to benign lesions, the encapsulated FV-PTC variant was reclassified as noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP). Nonetheless, specific molecular signatures are not yet available. It is well known that telomere-related genome instability is caused by inappropriate DNA repair of dysfunctional telomeres and that mechanisms involved in the damaged telomere repair processing may led to detrimental outcomes, altering the 3D nuclear telomere and genome organization in cancer cells. This pilot study aimed to evaluate whether a specific nuclear telomere architecture might characterize NIFTP, potentially distinguishing it from other PTC histologic variants. Our findings demonstrate that 3D telomere profiles of CL-PTC and FV-PTC were different from NIFTP and that NIFTP more closely resembles follicular thyroid adenoma (FTA). NIFTP has longer telomeres than CL-PTC and FV-PTC samples and telomere length overlaps in NIFTP and FTA. There was no association between BRAF expression and telomere length in all tested samples. Our data showing that 3D nuclear telomere organization is altered differently in thyroid cancer variants, suggest that this parameter might guide clinical management of NIFTP. Although further investigations in a larger cohort of patients are necessary to corroborate our observations, telomere-related genomic instability might be of value in the diagnosis of NIFTP and allow for a more appropriate selection of the correct treatment.

Background: Although endoscopic submucosal dissection (ESD) can provide a high rate of curative resection, remaining gastric mucosa after ESD is at risk of metachronous recurrence. We investigated risk factors for metachronous superficial gastric epithelial neoplasms (MSGENs) following ESD. Methods: We conducted a retrospective cohort study including 369 patients with 382 lesions that underwent ESD for adenoma/early gastric cancer. The primary endpoint was to identify clinicopathological risk factors for the occurrence of MSGENs. The secondary endpoint was to evaluate the association of Helicobacter pylori (Hp) eradication with the MSGENs. Results: Twenty-seven MSGENs were occurred. The subjects were divided into MSGEN and not-MSGEN groups. There was a significantly higher frequency of histological intestinal metaplasia (HIM) and initial neoplasm location in upper or middle part (INUM) in the MSGEN group. The HIM group and INUM group had significantly higher cumulative incidence of MSGENs. We compared the 27 patients of MSGEN group and 27 patients of matched not-MSGEN (Mnot-MSGEN) group that was matched to the MSGEN group for variables including HIM and INUM. There was a significantly higher frequency of Hp spontaneous eradication in the MSGEN group. Conclusion: HIM, INUM and Hp spontaneous eradication may be clinicopathological risk factors for developing MSGENs after ESD.

Background: Processing whole-slide images (WSI) to train neural networks can be intricate and laborious. We developed an open-source library covering recurrent tasks in processing of WSI and in evaluating the performance of the trained networks for classification tasks. Methods: Two histopathology use-cases were selected. First we aimed to train a CNN to distinguish H&amp;E-stained slides obtained from neuropathologically classified low-grade epilepsy-associated dysembryoplastic neuroepithelial tumor (DNET) and ganglioglioma (GG). The second project we trained a convolutional neural network (CNN) to predict the hormone expression of pituitary adenoms only from hematoxylin and eosin (H&amp;E) stained slides. In the same approach, we addressed the issue to also predict clinically silent corticotroph adenoma. We included four clinico-pathological disease conditions in a multilabel approach. Results: Our best performing CNN achieved an area under the curve (AUC) of 0.97 for the receiver operating characteristic (ROC) for corticotroph adenoma, 0.86 for silent corticotroph adenoma and 0.98 for gonadotroph adenoma. Our DNET-GG classifier achieved an AUC of 1.00 for the ROC curve. All scores were calculated with the help of our library on predictions on a case basis. Conclusions: Our comprehensive library is most helpful to standardize the work-flow and minimize the work-burden in training CNN. It is also compatible with fastai. Indeed, our new CNNs reliably extracted neuropathologically relevant information from the H&amp;E staining only. This approach will supplement the clinico-pathological diagnosis of brain tumors, which is currently based on cost-intense microscopic examination and variable panels of immunohistochemical stainings.