Task 1 Definition

Overview

Hidden-RAD2 Task 1 evaluates whether an AI system can reproduce the structured reasoning process used by radiologists when interpreting chest X-ray images. Rather than generating only a final diagnosis or a free-text report, the system must describe the intermediate observations, locations, diagnostic decisions, and supporting evidence that lead to each final impression.

Background

During dataset construction, a radiologist examines a chest X-ray image, referred to as Source 1 (S1), and completes a structured interpretation consisting of five components:

1. A1 — Initial Impressions: All possible impressions considered during the initial image review

2. A2 — Thoracic Level: The relevant thoracic spine level or lung zone

3. A3 — Anatomical Location: The anatomical location of each finding

4. A4 — Final Impressions: The final diagnostic decisions after reviewing the available evidence

5. A5 — Confirmation Checklist: An ABCDE-based checklist identifying the evidence that supports each final impression

The corresponding medical report, referred to as Source 2 (S2), is used as a reference during annotation. However, some diagnostic evidence or causal relationships may not be explicitly documented in the report. The A5 checklist captures this supporting information and makes the reasoning behind each final impression more explicit.

NTCIR-18 Hidden-RAD Task 1 required participants to generate a causal exploration section from an existing radiology report, with optional use of the corresponding chest X-ray image. The objective was to recover the hidden causal relationships connecting the findings described in the report to its diagnostic impressions.

Hidden-RAD2 extends this task by moving from report-based explanation generation to image-based reconstruction of the radiologist’s complete reasoning process.

Task 1 Definition

Given a chest X-ray image, a participating system must generate a structured A1–A5 interpretation that represents the progression from initial observations to final diagnostic impressions and their supporting evidence.

The system must:

• identify all reasonable initial impressions;

• determine the relevant thoracic levels or lung zones;

• identify the anatomical locations of the findings;

• decide the final impressions, including a normal conclusion when appropriate; and

• provide an ABCDE-based confirmation checklist supporting each final impression.

Input 

Each test case provides:

• A chest X-ray image from the MIMIC-CXR source dataset

Access to MIMIC-CXR images requires the appropriate PhysioNet credentials and data-use authorization.

Participants may optionally use external medical knowledge resources, pretrained models, or other supporting information, subject to the task rules.

Required Output

For each test image, participants must submit the following structured output:

A1 — Initial Impressions

List all possible impressions considered during the initial image review. These are preliminary candidates and do not necessarily need to appear in the final impressions.

A2 — Thoracic Level

Specify the relevant thoracic spine level or lung zone associated with each observation.

A3 — Anatomical Location

Identify the anatomical location and, when applicable, the laterality of each finding.

A4 — Final Impressions

Provide the final diagnostic impressions supported by the image evidence. A case may be classified as normal even when some preliminary observations were considered in A1.

A5 — Confirmation Checklist

Complete the ABCDE-based checklist for each final impression. The checklist must identify the findings and clinical evidence that confirm or support the diagnostic decision.

Training Data

Each training case contains:

• a chest X-ray image; and

• a radiologist-validated A1–A5 structured interpretation.

The structured annotations capture both the final diagnostic conclusions and the intermediate reasoning used to reach them.

Objective

The primary objective is to generate a transparent and clinically meaningful representation of radiological reasoning. A successful system should not merely predict the correct final impression; it should also explain how image findings, anatomical information, and confirmation evidence support that impression.