Patil, Ameya

Submucosal lesions of the esophagus and stomach are commonly discovered as incidental findings during routine endoscopy. These lesions arise from varying layers of the gastrointestinal wall, primarily from the submucosa or the muscularis propria, and can range from benign to malignant. This review provides an overview of common submucosal lesions including gastrointestinal stromal tumors (GIST), leiomyomas, duplication cysts, varices, glomus tumors, lipomas, granular cell tumors, neuroendocrine tumors, pancreatic rest, and schwannomas. We focus on their clinical presentation, endoscopic characteristics, radiologic features, and histopathologic findings to aid in diagnosis.

Metabolic dysfunction-associated steatohepatitis (MASH) is a global health care burden. Appropriate large animal models mimicking the main MASH characteristics of steatosis, inflammation, and hepatocyte damage alongside progression of fibrosis are imperative for robust preclinical studies, especially in the field of hepatobiliary surgery. The present study aimed to characterize a novel model of steatohepatitis in fumarylacetoacetate hydroxylase-deficient ( FAH -/- ) pigs. FAH -/- pigs were generated using a CRISPR/Cas9 system. The animals received a choline-deficient, L-amino acid-defined high-fat diet and subtherapeutic doses of nitisinone and were followed for 3 months. Liver biopsies were obtained at baseline and every month during treatment. Steatosis, inflammation, and fibrosis were assessed by conventional histological scoring systems and by an artificial intelligence (AI) model. Serum liver parameters were analyzed every 2 weeks. Steatosis increased significantly throughout the study, with severe steatosis observed as early as 2 months into treatment. The inflammation score was increased in all animals after 3 months of treatment, whereas the AI-based CD45+ cell count showed region-specific trends in the portal and lobular areas. Collagen content and the corresponding fibrosis stage showed an increase over the 3-month period; however, the difference was not significant. Serum liver parameters did not show any relevant elevations during the study. In summary, we successfully developed and characterized a novel model of steatohepatitis in the FAH -/- pig within 3 months. Further studies with prolonged observation time and/or cycling of nitisinone administration are needed to evaluate whether progressive fibrosis and cirrhosis could be achieved with this model.

AimsThere is a lack of published literature on the diagnostic reproducibility of oesophageal squamous dysplasia using a two‐tiered grading system.Methods and resultsWe identified 75 oesophageal biopsies, which were reviewed by 10 international pathologists twice (1500 total observations) with a > 4‐week washout period. Between rounds, a consensus meeting refining diagnostic criteria was held and an atlas was created to provide illustrations. Overall agreement was fair with kappa of 0.35 and 0.32 in round 1 and 2, respectively. Agreement was moderate to fair for negative for dysplasia (ND) (round 1 = 0.41 and round 2 = 0.34) and poor for indefinite for dysplasia (IND) and low‐grade dysplasia (LGD) (kappa <0.2). Agreement for high‐grade dysplasia (HGD) was good in both rounds (round 1 = 0.64; round 2 = 0.61). In round 1, majority diagnosis (MDx, ≥6 of 10 raters agreeing) was seen in 51 (68%) cases with the majority classified as ND (N = 27) or HGD (N = 18). MDx was rarely achieved for LGD (N = 6). In round 2, MDx was seen in 49 (65%) cases (20 ND, 1 IND, 11 LGD and 17 HGD). Of the 40 cases with MDx for both rounds, 39 were concordant (15 HGD, 6 LGD and 18 ND).ConclusionsOverall agreement among pathologists in diagnosing squamous lesions is fair; however, HGD had good agreement. This study fills an important gap in our knowledge of the inter‐rater variability in the diagnosis of oesophageal squamous dysplasia.

Aims Reticulin stain is used routinely in the histological evaluation of hepatocellular carcinoma (HCC). The goal of this study was to assess whether the histological reticulin proportionate area (RPA) in HCCs predicts tumour‐related outcomes. Methods and results We developed and validated a supervised artificial intelligence (AI) model that utilises a cloud‐based, deep‐learning AI platform (Aiforia Technologies, Helsinki, Finland) to specifically recognise and quantify the reticulin framework in normal livers and HCCs using routine reticulin staining. We applied this reticulin AI model to a cohort of consecutive HCC cases from patients undergoing curative resection between 2005 and 2015. A total of 101 HCC resections were included (median age = 68 years, 64 males, median follow‐up time = 49.9 months). AI model RPA reduction of > 50% (compared to normal liver tissue) was predictive of metastasis [hazard ratio (HR) = 3.76, P = 0.004, disease‐free survival (DFS, HR = 2.48, P < 0.001) and overall survival (OS), HR = 2.80, P = 0.001]. In a Cox regression model, which included clinical and pathological variables, RPA decrease was an independent predictor of DFS and OS and the only independent predictor of metastasis. Similar results were found in the moderately differentiated HCC subgroup (WHO grade 2), in which reticulin quantitative analysis was an independent predictor of metastasis, DFS and OS. Conclusion Our data indicate that decreased RPA is a strong predictor of various HCC‐related outcomes, including within the moderately differentiated subgroup. Reticulin, therefore, may represent a novel and important prognostic HCC marker, to be further explored and validated.