Extended Data Fig. 7: Analysis of case with concurrent cellular, antibody-mediated rejection, and Quilty-B lesions.
From: Deep learning-enabled assessment of cardiac allograft rejection from endomyocardial biopsies

a-b. The selected biopsy region and the corresponding H&E stained WSI. Attention heatmaps are computed for each task (c,d,e) and the grade (f). For the cellular task (c.), the high-attention regions correctly identified diffuse, multi-focal interstitial inflammatory infiltrate, predominantly comprised of lymphocytes, and associated myocyte injury. For the antibody heatmap (d.), the high-attention regions identified interstitial edema, endothelial swelling, and mild inflammation, consisting of lymphocytes and macrophages. For the Quilty-B heatmap (e.), the high-attention regions highlighted a focal, dense collection of lymphocytes within the endocardium, with mild crush artifact. For the grade (f.), the high-attention regions identified areas with diffuse, interstitial lymphocytic infiltrate with associated myocyte injury, corresponding to high grade cellular rejection. The high-attention regions for both types of rejection and Quilty-B lesions appear similar at the slide level at low power magnification, since all three tasks assign high-attention to regions with atypical myocardial tissue. However, at higher magnification, the highest attention in each task comes from regions with the task-specific morphology. The image patches with the highest attention scores from each task are shown in the last column. This example also illustrates the potential of CRANE to discriminate between ACR and similarly appearing Quilty-B lesions.