The XVIIth Banff Conference on Allograft Pathology, held in Paris in 2024 in collaboration with the Paris Institute for Transplantation and Organ Regeneration of Université de Paris Cité, convened the heart transplant working group to discuss 2 main topics: (1) the microvascular inflammatory burden on endomyocardial biopsy (EMB), with a focus on new advancements in inflammation-endothelium interactions within the allograft; and (2) the impact of molecular and noninvasive diagnostic tools in rejection monitoring. The discussions addressed the implications of molecular pathology performed on formalin-fixed paraffin-embedded tissue in the context of the inflammatory burden on EMBs, and explored the emerging characteristics of the endothelium in the microvasculature and its relationship with alloantibodies. The integration of tissue and blood molecular analyses has enhanced the reliability and accuracy of EMB interpretation by pathologists, while highlighting the complexity of inflammatory mechanisms occurring in the allograft. The high negative predictive value of noninvasive biomarkers and novel imaging modalities suggests their potential applicability in clinical practice and their capacity to modify follow-up strategies in heart transplant recipients.

CONTEXT.—:The adoption of digital pathology may enable pathologists to perform primary diagnosis in both local and remote whole slide image viewing settings, improving logistics and convenience. OBJECTIVE.—:To test the performance of a new whole slide imaging system (Aperio GT 450 DX), both local intranet-based and remote internet-based viewing were compared with manual glass slide light microscopy. DESIGN.—:A total of 1161 curated cases, enriched with difficult clinical diagnoses, were enrolled in this accuracy study and digitally scanned on 3 Aperio GT 450 DX instruments at 3 clinical sites. Ten reading pathologists across the 3 study sites viewed images either locally (directly connected to the image server) or remotely (viewed over an internet connection). Each diagnosis was scored (concordant, minor discrepancy, or major discrepancy) by a separate team of 3 adjudication pathologists. The diagnostic accuracy of the Aperio GT 450 DX was tested by comparing the whole slide image review diagnosis with the conventional light microscope manual slide review diagnosis. RESULTS.—:The difference in the major discrepancy rate between whole slide image review diagnosis and manual slide review diagnosis was 2.40% (95% CI, 1.40%-3.39%), meeting the predefined acceptance criterion of the 95% CI upper bound of 4% or less. Secondary end points were also met, including an upper bound of 7% or less and both local-only and remote-only upper-bound discrepancy rates of 4% or less. Major discrepancies were slightly lower for the remotely viewed cases (2.17%) compared with local direct server connection (2.61%), and time per read was not different. CONCLUSIONS.—:The diagnoses made using the Aperio GT 450 DX, using both local and remote access image data, were noninferior to the diagnoses made using conventional light microscopy.

Iatrogenic damage to the cardiac conduction system (CCS) remains a significant risk during congenital heart surgery. Current surgical best practice involves using superficial anatomical landmarks to locate and avoid damaging the CCS. Prior work indicates inherent variability in the anatomy of the CCS and supporting tissues. This study introduces high-resolution, 3D models of the CCS in normal pediatric human hearts to evaluate variability in the nodes and surrounding structures. Human pediatric hearts were obtained with an average donor age of 2.7 days. A pipeline was developed to excise, section, stain, and image atrioventricular (AVN) and sinus nodal (SN) tissue regions. A convolutional neural network was trained to enable precise multi-class segmentation of whole-slide images, which were subsequently used to generate high- resolution 3D tissue models. Nodal tissue region models were created. All models (10 AVN, 8 SN) contain tissue composition of neural tissue, vasculature, and nodal tissues at micrometer resolution. We describe novel nodal anatomical variations. We found that the depth of the His bundle in females was on average 304 μm shallower than those of male patients. These models provide surgeons with insight into the heterogeneity of the nodal regions and the intricate relationships between the CCS and surrounding structures.

OBJECTIVES:To describe mismatch repair (MMR) and microsatellite instability (MSI) testing practices in laboratories using the College of American Pathologists (CAP) MSI/MMR proficiency testing programs prior to the 2022 publication of the MSI/MMR practice guidelines copublished by CAP and the Association of Molecular Pathology (AMP). METHODS:Data from supplemental questionnaires provided with the 2020-B MSI/MMR programs to 542 laboratories across different practice settings were reviewed. Questionnaires contained 21 questions regarding the type of testing performed, specimen/tumor types used for testing, and clinical practices for checkpoint blockade therapy. RESULTS:Domestic laboratories test for MSI/MMR more often than international laboratories (P = .04) and academic hospitals/medical centers test more frequently than nonhospital sites/clinics (P = .03). The most commonly used testing modality is immunohistochemistry, followed by polymerase chain reaction, then next-generation sequencing. Most laboratories (72.6%; 347/478) reported awareness of the use of immune checkpoint inhibitor therapy for patients with high MSI or MMR-deficient results. CONCLUSIONS:The results demonstrate the state of MMR and MSI testing in laboratories prior to the publication of the CAP/AMP best practice guidelines, highlighting differences between various laboratory types. The findings indicate the importance of consensus guidelines and provide a baseline for comparison after their implementation.

Background Pathologic antibody mediated rejection (pAMR) remains a major driver of graft failure in cardiac transplant patients. The endomyocardial biopsy remains the primary diagnostic tool but presents with challenges, particularly in distinguishing the histologic component (pAMR-H) defined by 1) intravascular macrophage accumulation in capillaries and 2) activated endothelial cells that expand the cytoplasm to narrow or occlude the vascular lumen. Frequently, pAMR-H is difficult to distinguish from acute cellular rejection (ACR) and healing injury. With the advent of digital slide scanning and advances in machine deep learning, artificial intelligence technology is widely under investigation in the areas of oncologic pathology, but in its infancy in transplant pathology. For the first time, we determined if a machine learning algorithm could distinguish pAMR-H from normal myocardium, healing injury and ACR. Materials and Methods A total of 4,212 annotations (1,053 regions of normal, 1,053 pAMR-H, 1,053 healing injury and 1,053 ACR) were completed from 300 hematoxylin and eosin slides scanned using a Leica Aperio GT450 digital whole slide scanner at 40X magnification. All regions of pAMR-H were annotated from patients confirmed with a previous diagnosis of pAMR2 (>50% positive C4d immunofluorescence and/or >10% CD68 positive intravascular macrophages). Annotations were imported into a Python 3.7 development environment using the OpenSlide™ package and a convolutional neural network approach utilizing transfer learning was performed. Results The machine learning algorithm showed 98% overall validation accuracy and pAMR-H was correctly distinguished from specific categories with the following accuracies: normal myocardium (99.2%), healing injury (99.5%) and ACR (99.5%). Conclusion Our novel deep learning algorithm can reach acceptable, and possibly surpass, performance of current diagnostic standards of identifying pAMR-H. Such a tool may serve as an adjunct diagnostic aid for improving the pathologist's accuracy and reproducibility, especially in difficult cases with high inter-observer variability. This is one of the first studies that provides evidence that an artificial intelligence machine learning algorithm can be trained and validated to diagnose pAMR-H in cardiac transplant patients. Ongoing studies include multi-institutional verification testing to ensure generalizability.

The Banff Heart Concurrent Session, held as part of the 16th Banff Foundation for Allograft Pathology Conference at Banff, Alberta, Canada, on September 21, 2022, focused on 2 major topics: non-human leukocyte antigen (HLA) antibodies and mixed rejection. Each topic was addressed in a multidisciplinary fashion with clinical, immunological, and pathology perspectives and future developments and prospectives. Following the Banff organization model and principles, the collective aim of the speakers on each topic was to • Determine current knowledge gaps in heart transplant pathology • Identify limitations of current pathology classification systems • Discuss next steps in addressing gaps and refining classification system.

Emerging evidence suggests that the higher prevalence of autism in individuals who are assigned male than assigned female at birth results from both biological factors and identification biases. Autistic individuals who are assigned female at birth (AFAB) and those who are gender diverse experience health disparities and clinical inequity, including late or missed diagnosis and inadequate support. In this Viewpoint, an international panel of clinicians, scientists, and community members with lived experiences of autism reviewed the challenges in identifying autism in individuals who are AFAB and proposed clinical and research directions to promote the health, development, and wellbeing of autistic AFAB individuals. The recognition challenges stem from the interplay between cognitive differences and nuanced or different presentations of autism in some AFAB individuals; expectancy, gender-related, and autism-related biases held by clinicians; and social determinants. We recommend that professional development for clinicians be supported by health-care systems, professional societies, and governing bodies to improve equitable access to assessment and earlier identification of autism in AFAB individuals. Autistic AFAB individuals should receive tailored support in education, identity development, health care, and social and professional sense of belonging.

Giant cell arteritis (GCA) is the most common systemic vasculitis in adults in Europe and North America, typically involving the extra-cranial branches of the carotid arteries and the thoracic aorta. Despite advances in noninvasive imaging, temporal artery biopsy (TAB) remains the gold standard for establishing a GCA diagnosis. The processing of TAB depends largely on individual institutional protocol, and the interpretation and reporting practices vary among pathologists. To address this lack of uniformity, the Society for Cardiovascular Pathology formed a committee tasked with establishing consensus guidelines for the processing, interpretation, and reporting of TAB specimens, based on the existing literature. This consensus statement includes a discussion of the differential diagnoses including other forms of arteritis and noninflammatory changes of the temporal artery.

Diagnosis of myocarditis as the cause of death in the forensic setting at post-mortem is currently determined by a forensic pathologist. There is no systematic method for diagnosis and thus the determination is subject to inter-observer variability and is often non-reproducible. The primary aim of this study was to investigate the differences in the amount of inflammation between cases where myocarditis was deemed the cause of death, compared to cases where myocardial inflammation was incidentally present at autopsy, but not determined to be the cause of death. Participants were sourced from the Victorian Institute of Forensic Medicine (VIFM) database, from full autopsies conducted on reportable death in Victoria, Australia between the years 2011 and 2021.Cases of fatal myocarditis were significantly more likely to experience infection-like symptoms prior to death, and to be in hospital at the time of death. Histopathological examination revealed fatal cases had a significantly higher inflammatory index compared to the incidental group. Lethal cases were also significantly more likely to have myocyte necrosis, and a diffuse pattern of inflammation.There are significant differences between cases where myocardial inflammation has been determined to be the cause of death and cases where inflammation in the myocardium was an incidental finding. These results could be used in the forensic autopsy to help pathologists determine if inflammation should be considered fatal or incidental.

In this report, we showcase diffusible iodine-based contrast-enhanced computed tomography (DICE-CT) as a method for improving soft tissue visualization and reducing beam hardening artifact within a stented vessel. This technique is commonly used in our pathology lab to image soft tissue specimens with dense metal implants and to ensure reliable morphological analysis through clear delineation of tissue structures. For this report, a porcine right coronary artery with an implanted metal stent was scanned using both conventional and DICE-CT methods. Upon reconstruction, DICE-CT produced less beam hardening artifact in comparison to traditional micro-CT; furthermore, DICE-CT produced results with morphometric similarity to histology. Accordingly, these differences illustrated the clear advantage of using DICE-CT over conventional micro-CT when imaging soft tissue specimens with dense metal implants.

Statistical models are commonly used to predict the outcome of events in a wide variety of fields such as health, finance, and business. Evaluation metrics are used to assess the effectiveness of these predictive models. One classification evaluation metric, called the receiver operating characteristics (ROC) curve has several useful properties, such as being threshold agnostic and can manage class imbalance where the outcomes are not equally represented. Despite the usefulness of the ROC curve, there is not a standard approach to extend to curve to multiclass problems. The purpose of this project was to evaluate multivariate ROC curve implementations with various underlying class proportions and degrees of separation. The methods we evaluated include the Macro, Micro, and Weighted average for one versus rest comparisons as well as the Hand and Till (HT) method. We compared the methods on simulated data with balanced, unbalanced and strongly unbalanced class proportions in combination with no separation, small separation, and large separation between classes. We found the methods were significantly different when class proportions were either unbalanced or severely unbalanced and the distributions were either separated or strongly separated (n=100, p<0.01). Pairwise comparisons found that HT and Macro were significantly different than Micro and Weighted (n=100, p<0.01). This study demonstrates that some of the AUC ROC methods differ depending on the class proportions and underlying distributions. The findings from this project may help practitioners select the most appropriate method according to their goals. Department: Computer Science Faculty Mentor: Dr. Wanhua Su