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Order-Aware 2.5D Multiple Instance Learning for Preoperative MRI-Based Perineural Invasion Risk Assessment in Intrahepatic Cholangiocarcinoma

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The paper introduces Order-Aware Slab Multiple Instance Learning (OAS‑MIL) for predicting perineural invasion (PNI) in intrahepatic cholangiocarcinoma using preoperative T2‑weighted MRI. It treats each tumor‑centered MRI crop as an ordered sequence of overlapping 2.5D slabs, extracting slab‑level features with a shared encoder and aggregating them through both permutation‑invariant set‑attention and bidirectional sequence‑attention branches. In five‑fold patient‑level cross‑validation, OAS‑MIL achieved a mean AUROC of 0.770, outperforming volumetric and MIL baselines, indicating that axial order provides a useful inductive bias for weakly supervised PNI prediction.

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