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L'essai clinique NCT07497243 pour Chest X-ray for Clinical Evaluation est pas encore en recrutement. Consultez la vue en carte du Radar des Essais Cliniques et les outils de découverte par IA pour tous les détails, ou posez vos questions ici.
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X-ray Assisted Diagnostic System 16 000

Pas encore en recrutement
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L'essai clinique NCT07497243 est une étude observationnel pour Chest X-ray for Clinical Evaluation. Son statut actuel est : pas encore en recrutement. Le recrutement est prévu pour commencer le 1 mai 2026, avec un objectif de 16 000 participants. Dirigée par Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, l'étude devrait être terminée d'ici le 30 novembre 2026. Les données du site ClinicalTrials.gov ont été mises à jour pour la dernière fois le 27 mars 2026.
Résumé succinct
X-ray examination is one of the most commonly used imaging modalities, especially chest X-ray, which is routinely performed for hospitalized patients. However, due to the low density resolution of X-ray images, radiologists' ability to diagnose diseases-particularly small lesions-is often affected. Studies have shown that the diagnostic accuracy of radiologists using chest X-rays is only around 70%, which does not me...Afficher plus
Titre officiel

Construction and Clinical Application of an X-ray AI-Aided Diagnosis System: A Randomized Controlled Trial

Pathologies
Chest X-ray for Clinical Evaluation
Autres identifiants de l'étude
  • X-Ray-001
Numéro NCT
NCT07497243
Date de début (réel)
2026-05-01
Dernière mise à jour publiée
2026-03-27
Date de fin (estimée)
2026-11-30
Inscription (estimée)
16 000
Type d'étude
Observationnel
Statut
Pas encore en recrutement
Mots clés
X-Ray
AI
Chest diseases
Accuracy
Bras / Interventions
Groupe de participants/BrasIntervention/Traitement
Radiologist diagnostic group
After the patient undergoes an X-ray examination, a radiologist generates the report and makes the diagnosis.
Radiologist diagnostic group
After the patient undergoes an X-ray examination, a radiologist generates the report and makes the diagnosis.
AI-assisted radiologist diagnostic group
After the patient undergoes an X-ray examination, an AI-assisted radiologist generates the report and makes the diagnosis.
AI-assisted radiologist diagnostic group
Based on the previously developed X-ray image diagnosis and report generation model, radiologists are assisted in interpreting X-ray images and generating reports.
Critère principal d'évaluation
Critères d'évaluationDescription de la mesurePériode
Area Under the Curve
The primary outcome was the AUC to evaluate diagnostic performance, comparing radiologists with and without AI assistance.
From enrollment to the end of X-ray image acquisition at 1 week
Critère secondaire d'évaluation
Critères d'évaluationDescription de la mesurePériode
X-ray report generation time
X-ray report generation time refers to the amount of time required to produce a diagnostic report after an X-ray examination has been performed. It typically measures the interval from when the X-ray images are acquired to when the radiologist (with or without AI assistance) completes and finalizes the report.
From enrollment to the end of X-ray image acquisition at 1 week
Assistant à la participation
Critères d'éligibilité

Âges éligibles
Enfant, Adulte, Adulte âgé
Sexes éligibles
Tous
Accepte les volontaires en bonne santé
Oui
  • Clinically suspected thoracic diseases (such as pneumonia, tuberculosis, or lung cancer) requiring X-ray diagnosis；
  • Patients providing written informed consent for research data use；
  • Complete clinical records (including chief complaints, medical history, and laboratory test results)

  • Substandard X-ray image quality (including severe motion artifacts, over-/underexposure, or missing anatomical structures)
  • Pregnant or lactating women
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology logoUnion Hospital, Tongji Medical College, Huazhong University of Science and Technology
Contact central de l'étude
Contact: Huangxuan Zhao, PhD, 18971676985, [email protected]
4 Centres de l'étude dans 1 pays

Hubei

Wuhan Union Hospital, Wuhan, Hubei, 430022, China
Lei Chen, MD, Contact, 15971480677, [email protected]
Wuhan Union Jinyin Lake Hospital, Wuhan, Hubei, 430022, China
Lei Chen, Contact, 15971480677, [email protected]
Wuhan Union West Hospital, Wuhan, Hubei, 430022, China
Huangxuan Zhao, Contact, 18971676985, [email protected]
The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
Huangxuan Duan, Contact, 13209867189, [email protected]