Retrospective Evaluation of AI-Based Early Detection of Reticular Opacity in Longitudinal Chest Radiograph Sequences in Patients With Idiopathic Pulmonary Fibrosis
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 175
- 试验地点
- 1
- 主要终点
- Paired lead-time difference (radiologist first-mention date minus AI first-detection date, days)
研究概览
简要总结
Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive fibrotic lung disease of unknown cause with a median survival of only 3-5 years after diagnosis. Early detection and timely initiation of antifibrotic therapy may improve outcomes, but diagnosis is frequently delayed. Chest radiography (CXR) is widely accessible and cost-effective but has limited sensitivity for early interstitial opacity (IO), so radiologists may miss or delay documentation of relevant findings.
This retrospective, single-center, observational cohort study evaluates whether an artificial-intelligence algorithm (VUNO Med-Chest X-ray) can detect interstitial opacity earlier than radiologists in the historical chest radiograph series of patients who were diagnosed with IPF. The cohort was identified via a April 2025 registry screening of patients carrying an IPF diagnosis at Chung-Ang University Hospital. For each patient, the date of the first AI-detected IO (using a pre-specified score cutoff) is compared with the date of the first radiologist-reported mention of interstitial/reticular opacity, across all chest radiographs obtained before the IPF diagnosis date, within a 15-year retrospective imaging window anchored to the April 2025 screening date (January 2010-April 2025). The study also explores patient characteristics that modify this lead-time difference and whether longitudinal AI IO-score trajectories are associated with mortality.
详细描述
Background:
IPF is an interstitial lung disease with a median survival of 3-5 years following diagnosis. Because interstitial opacity on CXR is subtle in early disease, opportunistic AI-based detection during CXR obtained for unrelated indications (emergency, gastroenterology, cardiology, etc.) could substantially shorten the time to diagnosis. Prior AI-CXR research has largely validated single-timepoint detection performance for findings such as pneumothorax, nodules, and pleural effusion; few studies have quantified how much earlier an AI system can detect interstitial opacity compared with radiologist reporting across a patient's full longitudinal CXR history.
Objectives:
- Quantify the lead-time advantage of AI (VUNO Med-Chest X-ray) versus radiologist reporting for first detection of interstitial opacity in the retrospective CXR series of IPF patients.
- Compare the proportion of early detections (greater than 180 days before diagnosis) between AI and radiologists.
- Explore patient-level effect modifiers of the AI-radiologist lead-time difference (follow-up duration, number of CXRs, prior emphysema/pneumonia history, prior CT availability, CPFE/COPD mention, pulmonology/allergy visit history).
- Examine whether longitudinal AI IO-score trajectory patterns (progressive, oscillating, persistently high) are associated with mortality using Cox proportional-hazards modeling.
Design and methods:
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 19 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •IPF diagnosis on record at Chung-Ang University Hospital as of the April 30, 2025 registry screening, based on imaging findings, pathology results, and clinical information as determined by a pulmonology specialist
- •Age greater than or equal to 19 years at IPF diagnosis
- •Confirmed diagnosis of IPF (by clinician or multidisciplinary discussion, including CT and/or biopsy)
- •Two or more frontal (PA or AP) chest radiographs obtained before the diagnosis date
- •DICOM images available and analyzable by VUNO Med-Chest X-ray
- •Date of initial IPF diagnosis available
排除标准
- •Only non-frontal chest radiograph views available (e.g., lateral view only)
- •One or fewer analyzable chest radiographs
- •Missing initial diagnosis date
- •No radiology report data available for comparison
结局指标
主要结局
Paired lead-time difference (radiologist first-mention date minus AI first-detection date, days)
时间窗: From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)
Delta = radiologist\_detected\_date - ai\_detected\_date, in days. Delta greater than 0 indicates AI detected interstitial opacity earlier than the radiologist; Delta = 0 indicates same-day detection; Delta less than 0 indicates the radiologist detected it earlier. Analyzed in the paired cohort (n=166) using the Wilcoxon signed-rank test (zero differences excluded, two-sided), with effect size reported as the Hodges-Lehmann estimate and bootstrap 95% CI (4,000 resamples). Reported measures: median Delta (IQR), Hodges-Lehmann estimate (95% CI), p-value, and the proportional breakdown of AI-earlier / same-day / radiologist-earlier pairs (n, %).
次要结局
- Proportion with AI-earlier detection among discordant pairs(From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening))
- Proportion detecting more than 180 days before diagnosis - AI vs. Radiologist(From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening))
- Proportion detecting within 180 days before diagnosis - AI vs. Radiologist(From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening))
- Sensitivity analysis of the primary lead-time comparison using alternative zero-handling methods(From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening))
研究者
Kyoungmin Moon
Associate professor of Pulmonary and Allergy Medicine
Chung-Ang University Hospital