Abstract
Reasoning in multimodal large language models (MLLMs) has shown strong promise in medical imaging. However, this reasoning is usually free-form text judged only by its final answer, which makes it hard to interpret and verify, especially in 3D radiology, where a diagnosis should be traceable to the evidence in the scan. Existing chest computed tomography (CT) question-answering datasets make this harder by reducing expert radiology reports to answer-only pairs, dropping the reasoning that links findings to conclusions and omitting the patient history clinicians rely on. As a result, reasoning-capable 3D chest CT MLLMs remain out of reach as neither the structured supervision needed to train them nor the protocol needed to verify their reasoning yet exists. We introduce CORTEX (Clinically Organized Reasoning and sTructured EXplanation), a structured reasoning benchmark for 3D chest CT. For each question, CORTEX restores the missing reasoning as a four-stage diagnostic trace that mirrors a radiologist’s workflow (task understanding, visual observation, diagnostic reasoning, and answer synthesis). We generate these traces using frontier large language models with broad medical and general-domain knowledge, then filter and verify them with a stage-level evaluation protocol that combines automated rubric scoring with expert radiologist review. Crucially, both the reasoning structure and the evaluation rubrics are designed in close collaboration with clin icians. Built on CT-RATE, a large, publicly available chest CT dataset without reasoning annotations, CORTEX comprises 76,177 validated reasoning traces across open-ended VQA, closed-ended VQA, and report generation, providing both the structured supervision and the stage-level evaluation protocol needed to build and evaluate trustworthy reasoning models for 3D chest CT. Our dataset and codebase is publicly available at github.com/aneesurhashmi/cortex
Links to Paper and Supplementary Materials
Main Paper (Open Access Version): https://papers.miccai.org/miccai-2026-sat/paper/SAFER_013.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=JlHzIqLjAQ
BibTex
@InProceedings{MalHas_CORTEX_MICCAISAT2026,
author = { Malik, Hashmat Shadab AND Hashmi, Anees Ur Rehman AND Saeed, Numan AND Naseer, Muzammal AND Khan, Salman AND Lippert, Christoph},
title = { { CORTEX: A Structured Reasoning Benchmark for Trustworthy 3D Chest CT MLLMs } },
booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2026 Workshops and Challenges},
year = {2026},
publisher = {Springer Nature Switzerland},
volume = {LNCS 17262},
month = {pending},
page = {pending}
}