Diese Seite wurde automatisch übersetzt und die Genauigkeit der Übersetzung wird nicht garantiert. Bitte wende dich an die englische Version für einen Quelltext.

Validation of AI-Based Detection of Idiopathic Pulmonary Fibrosis in Serial Chest Radiographs: A Retrospective Longitudinal Study

13. Juli 2026 aktualisiert von: Kyoungmin Moon, Chung-Ang University Hospital

Retrospective Evaluation of AI-Based Early Detection of Reticular Opacity in Longitudinal Chest Radiograph Sequences in Patients With Idiopathic Pulmonary Fibrosis

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.

Studienübersicht

Status

Abgeschlossen

Bedingungen

Intervention / Behandlung

Detaillierte Beschreibung

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:

  1. 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.
  2. Compare the proportion of early detections (greater than 180 days before diagnosis) between AI and radiologists.
  3. 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).
  4. Examine whether longitudinal AI IO-score trajectory patterns (progressive, oscillating, persistently high) are associated with mortality using Cox proportional-hazards modeling.

Design and methods:

Retrospective, single-center, observational cohort study conducted at Chung-Ang University Hospital (Seoul, Republic of Korea), reported in accordance with STROBE reporting guidelines. The cohort was identified via an April 2025 registry screening of patients carrying an IPF diagnosis at Chung-Ang University Hospital. All available frontal (PA or AP) chest radiographs obtained before each patient's IPF diagnosis date, within a 15-year retrospective imaging window anchored to the April 2025 screening date (January 2010-April 2025), are analyzed with VUNO Med-Chest X-ray (interstitial opacity, consolidation, nodule/mass) and compared against the corresponding radiology reports. Vital status (mortality) was ascertained as of the April 2025 screening date, with no follow-up beyond that cutoff.

Index test: VUNO Med-Chest X-ray interstitial opacity (IO) score, using a pre-specified cutoff (0.35). The AI-detected date is defined as the date of the earliest pre-diagnosis CXR meeting this cutoff.

Comparator: The radiologist-detected date is defined as the earliest chest-radiograph report date containing terminology consistent with reticular pattern / interstitial opacity(reticular opacity) / IO. A sensitivity analysis separately accounts for reports where a chest CT was obtained within +/- 3 months, given the potential influence of CT findings on radiologist reporting. Of 175 enrolled patients with a confirmed IPF diagnosis and an available pre-diagnosis CXR series, 166 comprise the primary paired analysis cohort (AI and radiologist detection dates both available before diagnosis).

Studientyp

Beobachtungs

Einschreibung (Tatsächlich)

175

Kontakte und Standorte

Dieser Abschnitt enthält die Kontaktdaten derjenigen, die die Studie durchführen, und Informationen darüber, wo diese Studie durchgeführt wird.

Studienorte

  • Südkorea
      • Seoul, Südkorea
        • Chung-Ang University Hospital

Teilnahmekriterien

Forscher suchen nach Personen, die einer bestimmten Beschreibung entsprechen, die als Auswahlkriterien bezeichnet werden. Einige Beispiele für diese Kriterien sind der allgemeine Gesundheitszustand einer Person oder frühere Behandlungen.

Zulassungskriterien

Studienberechtigtes Alter

  • Erwachsene
  • Älterer Erwachsener

Akzeptiert gesunde Freiwillige

Nein

Probenahmeverfahren

Nicht-Wahrscheinlichkeitsprobe

Studienpopulation

Adults aged 19 years or older carrying a final diagnosis of idiopathic pulmonary fibrosis (IPF; ICD-10 J84.1 or clinical diagnosis) at Chung-Ang University Hospital, identified via an April 2025 registry screening, with a digital chest radiograph series available before the diagnosis date within the 15-year retrospective imaging window (January 2010-April 2025).

Beschreibung

Inclusion Criteria:

  • 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

Exclusion Criteria:

  • 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

Studienplan

Dieser Abschnitt enthält Einzelheiten zum Studienplan, einschließlich des Studiendesigns und der Messung der Studieninhalte.

Wie ist die Studie aufgebaut?

Designdetails

Kohorten und Interventionen

Gruppe / Kohorte
Intervention / Behandlung
IPF-diagnosed cohort
Patients with a final diagnosis of idiopathic pulmonary fibrosis at Chung-Ang University Hospital, identified via an April 2025 registry screening, whose historical chest radiograph series obtained before diagnosis (within a 15-year retrospective window, January 2010-April 2025) were retrospectively analyzed by both the AI algorithm and radiology reports.
Gerät: VUNO Med-Chest X-ray
Retrospective, offline application of the AI-based chest radiograph analysis software VUNO Med-Chest X-ray (VUNO Inc., Seoul, Korea) to archival chest radiographs obtained before each patient's IPF diagnosis. The software outputs scores for interstitial opacity(reticular opacity), consolidation, and nodule/mass; interstitial opacity(reticular opacity) score, applying a pre-specified cutoff, is used for the primary and secondary analyses. The AI analysis is performed solely for research purposes and does not inform clinical care.

Was misst die Studie?

Primäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Paired lead-time difference (radiologist first-mention date minus AI first-detection date, days)
Zeitfenster: 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, %).
From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)

Sekundäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Proportion with AI-earlier detection among discordant pairs
Zeitfenster: From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)
Exact binomial sign test (null hypothesis p=0.5, two-sided); reported as the AI-earlier proportion (n/N, %) and p-value, assessed among the subset of the paired cohort with a non-zero lead-time difference (n=73).
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
Zeitfenster: From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)
Exact McNemar test plus continuity-corrected asymptotic McNemar test on a 2x2 paired table; reported measures: each proportion (n, %, 95% CI), number of discordant pairs, and p-value. Assessed in the full enrolled cohort (n=175).
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
Zeitfenster: From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)
Exact McNemar test plus continuity-corrected asymptotic McNemar test on a 2x2 paired table; reported measures: each proportion (n, %, 95% CI), number of discordant pairs, and p-value. Assessed in the full enrolled cohort (n=175).
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
Zeitfenster: From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)
Wilcoxon signed-rank test repeated with three zero-handling methods (wilcox: zeros excluded; pratt: zeros included in ranking then removed; zsplit: zero ranks split); statistic and p-value reported for each method. Assessed in the primary paired analysis cohort (n=166).
From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)

Andere Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Kaplan-Meier Time-to-Detection Curves for AI versus Radiologist
Zeitfenster: From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)
Kaplan-Meier curves comparing time from first available chest radiograph to first detection, separately for AI and radiologist, with log-rank test comparing the two curves.
From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)
Time From AI First Detection to Eventual IPF Diagnosis
Zeitfenster: From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)
Descriptive Kaplan-Meier analysis of the time elapsed between the AI's first positive detection and the patient's pulmonology/allergy-confirmed IPF diagnosis.
From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)
Predictors of the Primary Lead-Time Difference (Regression Coefficients)
Zeitfenster: From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)
Exploratory, hypothesis-generating analysis of candidate patient-level and process-level variables potentially associated with the primary lead-time difference (e.g., patient demographics, follow-up duration, CXR imaging frequency, comorbidity history, and specialist visit patterns), using univariable and multivariable OLS regression with HC3 robust standard errors as the primary model, with quantile regression (median, tau=0.5) as a robustness check. The final covariate set will be determined based on pre-specified clinical rationale at the time of analysis. Reported measures: regression coefficients (β, days), 95% CI, and p-value for each retained predictor.
From first available chest radiograph to IPF diagnosis date (retrospective, up to 15 years, anchored to April 2025 registry screening)

Mitarbeiter und Ermittler

Hier finden Sie Personen und Organisationen, die an dieser Studie beteiligt sind.

Sponsor

Chung-Ang University Hospital

Mitarbeiter

VUNO Inc.

Ermittler

  • Hauptermittler: Kyoungmin Moon, Chung-Ang University Hospital
  • Hauptermittler: Yoona Hwang, VUNO Inc.

Studienaufzeichnungsdaten

Diese Daten verfolgen den Fortschritt der Übermittlung von Studienaufzeichnungen und zusammenfassenden Ergebnissen an ClinicalTrials.gov. Studienaufzeichnungen und gemeldete Ergebnisse werden von der National Library of Medicine (NLM) überprüft, um sicherzustellen, dass sie bestimmten Qualitätskontrollstandards entsprechen, bevor sie auf der öffentlichen Website veröffentlicht werden.

Haupttermine studieren

Studienbeginn (Tatsächlich)

30. April 2025

Primärer Abschluss (Tatsächlich)

30. April 2025

Studienabschluss (Tatsächlich)

30. April 2025

Studienanmeldedaten

Zuerst eingereicht

2. Juli 2026

Zuerst eingereicht, das die QC-Kriterien erfüllt hat

13. Juli 2026

Zuerst gepostet (Tatsächlich)

20. Juli 2026

Studienaufzeichnungsaktualisierungen

Letztes Update gepostet (Tatsächlich)

20. Juli 2026

Letztes eingereichtes Update, das die QC-Kriterien erfüllt

13. Juli 2026

Zuletzt verifiziert

1. Juli 2026

Mehr Informationen

Begriffe im Zusammenhang mit dieser Studie

Schlüsselwörter

Zusätzliche relevante MeSH-Bedingungen

Andere Studien-ID-Nummern

  • 2507-022-19585

Plan für individuelle Teilnehmerdaten (IPD)

Planen Sie, individuelle Teilnehmerdaten (IPD) zu teilen?

NEIN

Beschreibung des IPD-Plans

This is a retrospective study using data collected under an IRB-approved waiver of informed consent. Individual participant data were not collected with participant consent for sharing with third parties, and no data-sharing infrastructure or de-identification protocol for external release has been established.

Arzneimittel- und Geräteinformationen, Studienunterlagen

Studiert ein von der US-amerikanischen FDA reguliertes Arzneimittelprodukt

Nein

Studiert ein von der US-amerikanischen FDA reguliertes Geräteprodukt

Nein

Diese Informationen wurden ohne Änderungen direkt von der Website clinicaltrials.gov abgerufen. Wenn Sie Ihre Studiendaten ändern, entfernen oder aktualisieren möchten, wenden Sie sich bitte an register@clinicaltrials.gov. Sobald eine Änderung auf clinicaltrials.gov implementiert wird, wird diese automatisch auch auf unserer Website aktualisiert .

Klinische Studien zur VUNO Med-Chest X-ray

Suchen Sie nach ähnlichen Studien

Sponsoren und Mitarbeiter

Krankheiten

Drogeninterventionen

CROs by country

CROs in Denmark

Bedingungen

Seltene Krankheiten

Drogeninterventionen

Nahrungsergänzungsmittel

Sponsor / Mitarbeiter

Standorte

3
Abonnieren