Abstract
LI-RADS categorises focal liver lesions in at-risk patients on an ordinal scale from definitely benign to definitely hepatocellular carcinoma, and the assigned category informs clinical management. The AMPLIFAI challenge benchmarks automating this on multi-phase CT, scoring a composite of adjusted quadratic weighted kappa (QWK) and special-category recognition. Cross-validation scores on its public corpus far exceed private-test performance—a gap usually blamed on distribution shift. We show that two non-transferable shortcuts account for much of it. First, slice thickness identifies the source cohort, whose label mixes are near-disjoint—the 0.8 mm stratum is 52% special-category, the 2.5 mm stratum 79% LR-5—so acquisition alone recognises the special categories well above chance, but carries no ordinal signal. Second, 70 lesion-free examinations are scored as LR-1 and 69 ship no segmentation, so lesion diameter—zero exactly when the mask is absent—identifies the anchoring benign class: that scalar alone reaches QWK 0.888, and 0.871 composite with acquisition added—within 0.04 of a full 3D CNN on the same folds, without reading a voxel. Every private case supplies a mask, so none of this transfers. Our cohort-grouped, masked-only protocol addresses both and discriminates where the public one cannot: a baseline scoring QWK 0.943 publicly has no ordinal agreement at all, QWK 0.000. Under it, a method built from the LI-RADS definitions—peri-lesional relative normalisation, region-structured pooling, dense feature supervision and phase-difference channels—scores 0.41 on 174 private cases from three unseen centres, where error analysis localises the residual deficit to small-volume LR-TIV read as LR-M. Both diagnostics are inexpensive and worth running on any harmonised benchmark.
Links to Paper and Supplementary Materials
Main Paper (Open Access Version): https://papers.miccai.org/miccai-2026-sat/paper/AMPLIFAI_004.pdf
SharedIt Link: Not yet available
SpringerLink (DOI): Not yet available
Supplementary Material: Not Submitted
Link to Open Review
Open Review Page: https://openreview.net/forum?id=5DZQnMbNkq
BibTex
@InProceedings{VarHar_ShortcutAware_MICCAISAT2026,
author = { Vardhan, Harsh AND Suryawanshi, Sakshi AND Mandal, Subhamoy},
title = { { Shortcut-Aware Validation for LI-RADS Categorisation on Multi-Phase CT } },
booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2026 Workshops and Challenges},
year = {2026},
publisher = {Springer Nature Switzerland},
volume = {LNCS 17271},
month = {pending},
page = {pending}
}