Banff 2022 Liver Group Meeting report: Monitoring long-term allograft health.

The Banff Working Group on Liver Allograft Pathology met in September 2022. Participants included hepatologists, surgeons, pathologists, immunologists, and histocompatibility specialists. Presentations and discussions focused on the evaluation of long-term allograft health, including noninvasive and tissue monitoring, immunosuppression optimization, and long-term structural changes. Potential revision of the rejection classification scheme to better accommodate and communicate late T cell-mediated rejection patterns and related structural changes, such as nodular regenerative hyperplasia, were discussed. Improved stratification of long-term maintenance immunosuppression to match the heterogeneity of patient settings will be central to improving long-term patient survival. Such personalized therapeutics are in turn contingent on a better understanding and monitoring of allograft status within a rational decision-making approach, likely to be facilitated in implementation with emerging decision-support tools. Proposed revisions to rejection classification emerging from the meeting include the incorporation of interface hepatitis and fibrosis staging. These will be opened to online testing, modified accordingly, and subject to consensus discussion leading up to the next Banff conference.

Endomyocardial biopsy in clinical practice: the diagnostic yield and insights from a 5-year single-center experience.

OBJECTIVES: Endomyocardial biopsy (EMB) is a diagnostic tool for evaluating various cardiac conditions, such as myocarditis and myocardial infiltrative diseases. It is also the gold standard screening technique for detecting allograft rejection after heart transplantation. Despite advances in noninvasive imaging modalities for myocardial tissue characterization, EMB is still necessary for making a definitive diagnosis and determining treatment for certain conditions. Herein, we report our recent experience using EMB and its diagnostic yield. METHODS AND RESULTS: We retrospectively reviewed EMBs performed at our institution from March 2018 through March 2023. Clinical data, including patient characteristics, indication and diagnostic yield of EMB, and procedure-related complications, were collected. Histopathological findings of the biopsies were recorded and classified based on the degree to which they matched the clinical diagnosis and cardiac magnetic resonance imaging (CMR) findings. A total of 212 EMBs obtained in 178 consecutive patients were retrospectively analyzed, with 42 biopsies performed for allograft rejection surveillance (10 patients) and the remaining performed for presumptive diagnosis of acute myocarditis or unexplained cardiomyopathy. Among the non-heart transplant cases, 54.7% of EMBs provided a clear diagnosis. The most common diagnosis was myocarditis (69%), followed by cardiac amyloidosis (CA) (26%). EMB was also helpful in detecting several rare cardiac conditions, such as eosinophilic granulomatosis with polyangiitis (EGPA), Fabry disease, and cardiac sarcoidosis. In a cohort of 101 patients who underwent both CMR and EMB, the results were concordant in 66% of cases. However, in 24.7% of patients, EMB was able to identify pathological conditions where CMR results were inconclusive, highlighting its complementary role in determining an accurate diagnosis. No complications were reported in any of the 212 EMBs performed. CONCLUSIONS: With advances in cardiac imaging modalities, EMB is not routinely indicated for the diagnosis of cardiomyopathy. However, EMB is still an important tool for diagnosing specific cardiac diseases and could be crucial for confirming the diagnosis. EMB is generally safe if performed at experienced centers.

Incorporating artificial intelligence in portable infrared thermal imaging for the diagnosis and staging of nonalcoholic fatty liver disease.

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is one of the most prevalent chronic liver diseases worldwide. Thermal imaging combined with advanced image-processing and machine learning analysis accurately classified disease status in a study on mice; this study aimed to develop this tool for humans. This prospective study included 46 patients who underwent liver biopsy. Liver thermal imaging was performed on the same day as liver biopsy. We developed an image-processing algorithm that measured the relative spatial thermal variation across the skin covering the liver. The texture parameters obtained from the thermal images were input into the machine learning algorithm. Patients were diagnosed with MASLD and stratified according to nonalcoholic fatty liver disease activity score (NAS) and fibrosis stage using the METAVIR score. Twenty-one of 46 patients were diagnosed with MASLD. Using thermal imaging followed by processing, detection accuracy for patients with NAS >4 was 0.72.