Style–morphology decomposition for disentangling structural and staining effects on MSI prediction changes. A, Representative examples of counterfactual manipulation between MSIH and non-MSIH classes. For each original image x and its counterfactual xcf, style-hybrid (xstyle) and morphology-hybrid (xmorph) images were generated using Vahadane stain transfer. Each hybrid isolates the effect of either stain or morphology while controlling for the other. The right-hand bars show the Shapley-style decomposition of the logit change (Δf) into stain (φstyle) and morphology (φmorph) contributions, demonstrating that morphologic differences dominate the model’s predictions. Grad-CAM visualizations below provide region-level attribution under MIL. In contrast, MoPaDi produces class-directed “what-if” edits that offer a complementary view of candidate morphologic and style changes associated with prediction shifts. Scale bar applies to all images within the panel. B, Decomposition results across test-set patients, showing median contributions of φstyle, φmorph, and total (Δf) for manipulations toward (↑) and away from (↓) each class. C, Scatter plot of morphology versus style contributions per patient, illustrating consistent dominance of morphologic effects across both manipulation directions and classes.
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