Albadri, Sam

ABSTRACT Background Diagnostic interpretation of kidney allograft biopsies using the Banff classification remains variable, but the determinants of this variability are not fully defined. We performed a global, fully digital multi-reader study to identify the principal drivers of disagreement in Banff-based assessment. Methods Thirty-six kidney transplant biopsies were independently scored by 67 renal pathologists on a standardized digital platform. Readers assessed Banff lesions on hematoxylin and eosin, periodic acid–Schiff, and Jones’ silver stains; final diagnostic categories were assigned using prespecified Banff-based decision rules. Interobserver agreement was quantified with Gwet’s agreement coefficient (AC) statistics. Determinants of diagnostic agreement were evaluated using pairwise mixed-effects logistic regression, and reader similarity was examined by principal component analysis (PCA) with post hoc molecular annotation. Results Agreement for final diagnostic categories was moderate (Gwet’s AC1, 0.55; 95% CI, 0.47–0.63). Lesion-level agreement varied substantially, with lowest agreement for selected threshold-dependent inflammatory or semi-quantitative lesions, including interstitial inflammation in areas of IFTA, peritubular capillaritis and arteriolar hyalinosis. Diagnostic concordance differed markedly across biopsies, indicating strong case-level heterogeneity. In pairwise models, differences in active inflammatory and vascular lesion scoring were the strongest correlates of diagnostic disagreement; reader experience and geography contributed minimally. Principal component analysis showed reader variation was organized along two dominant axes: a rejection-calling threshold axis linked mainly to tubulointerstitial inflammatory injury, and a T cell-mediated (TCMR/TI) and antibody-mediated/microvascular (AMR/MVI) inflammation-oriented phenotypic classification axis. Conclusion Interobserver variation in Banff-based kidney transplant biopsy assessment is structured rather than random and driven mainly by how readers threshold and integrate key inflammatory lesion compartments rather than experience or geographic location.

Transplant pathology plays a critical role in ensuring that transplanted organs function properly and the immune systems of the recipients do not reject them. To improve outcomes for transplant recipients, accurate diagnosis and timely treatment are essential. Recent advances in artificial intelligence (AI)-empowered digital pathology could help monitor allograft rejection and weaning of immunosuppressive drugs. To explore the role of AI in transplant pathology, we conducted a systematic search of electronic databases from January 2010 to April 2023. The PRISMA checklist was used as a guide for screening article titles, abstracts, and full texts, and we selected articles that met our inclusion criteria. Through this search, we identified 68 articles from multiple databases. After careful screening, only 14 articles were included based on title and abstract. Our review focuses on the AI approaches applied to four transplant organs: heart, lungs, liver, and kidneys. Specifically, we found that several deep learning-based AI models have been developed to analyze digital pathology slides of biopsy specimens from transplant organs. The use of AI models could improve clinicians’ decision-making capabilities and reduce diagnostic variability. In conclusion, our review highlights the advancements and limitations of AI in transplant pathology. We believe that these AI technologies have the potential to significantly improve transplant outcomes and pave the way for future advancements in this field.

Hydralazine is a vasodilator used for the management of hypertension, heart failure, and hypertensive emergencies in pregnancy. It has been implicated in the causation of drug-induced lupus erythematosus (DLE) and rarely with ANCA-associated vasculitis (AAV), which may present as a pulmonary-renal syndrome and be rapidly fatal. Herein, we describe a case of hydralazine-associated AAV presenting as acute kidney injury with the use of early bronchoalveolar lavage (BAL) with serial aliquots to aid with diagnosis. Our case highlights how, in the correct clinical setting, BAL can act as a rapid diagnostic test to help guide quicker treatment to allow for better patient outcomes.

Purpose: We aimed to describe the clinical and histologic findings in a few enucleation cases with intraocular lymphoma. Methods: Retrospective review of pathology files from a 22-year period identified cases with intraocular lymphoma among all enucleation specimens. Patient demographics, clinical findings, laboratory results, radiographic studies, and indication for enucleation were abstracted from electronic health records; slides were reviewed. Results: Four patients (three women and one man; age range, sixth through eighth decades of life) underwent enucleation with a final diagnosis of intraocular lymphoma. Two patients with primary vitreoretinal large B-cell lymphomas had been treated for refractory uveitis. Specimens showed retinal and subretinal infiltrates by atypical large B-lymphocytes and rare neoplastic cells in the vitreous. The remaining two patients had systemic lymphoproliferative disorders. One patient had chronic lymphocytic leukemia and floaters in his eye; vitreoretinal lymphoma developed, consistent with intraocular Richter transformation. The other had diffuse large B-cell lymphoma in remission; however, blurred vision developed, she was treated for panuveitis without improvement, and was later found to have ocular involvement by diffuse large B-cell lymphoma. Conclusion: Our series details the unusual circumstances when an eye is removed for intraocular lymphoma. Different patterns of ocular tissue involvement were observed when we compared primary and secondary lymphomas.

AbstractObjectivesLong-term follow-up is important for determining performance characteristics of thyroid fine-needle aspiration (FNA).MethodsHistologic or 3 or more years of clinical follow-up was used to calculate performance characteristics of thyroid FNA before and after implementation of The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC). The impact of noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) classification was also investigated.ResultsFollow-up was obtained for 1,277/1,134 and 1,616/1,393 aspirates/patients (median clinical follow-up, 9.9 and 4.4 years, pre- and post-TBSRTC, respectively). Nondiagnostic, suspicious for follicular neoplasm, and suspicious for malignancy (SFM) diagnoses decreased and benign diagnoses increased post-TBSRTC, while atypical rate remained less than 1%. Negative predictive value for benign nodules and positive predictive value (PPV) for SFM increased significantly. Eleven nodules were reclassified as NIFTP, slightly decreasing PPV/risk of malignancy (ROM).ConclusionsAppropriate ROM for thyroid FNA can be achieved through application of TBSRTC terminology with minimal use of atypical category.