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Evaluation on the Effectiveness and Safety of RuiXin-CoronaryAI for Diagnosis of Coronary Artery Stenosis

Coronary Artery Disease Clinical Trial

Official title:
Evaluation on the Effectiveness and Safety of AI-based Coronary CT Angiographic Analysis Software (RuiXin-CoronaryAI) for Diagnosis of Coronary Artery Stenosis

Clinical Trial Summary

With the emergence of advanced technology to date in the artificial intelligence (AI), computer aided diagnosis has gradually gained its popularity in the field of healthcare. Particularly, in the clinical practice of coronary artery disease diagnosis, the application of AI could be of great implication in alleviating the shortage of medical sources. To evaluate the effectiveness and safety of the AI-based coronary CT angiographic analysis software (RuiXin-CoronaryAI) for diagnosis of coronary artery stenosis, a retrospective, multi-center, cross-over designed, blinded, sensitivity superiority and specificity non-inferiority clinical trial will be conducted.

Clinical Trial Description

Patients ≥18 years old with suspected or known coronary artery disease who underwent CCTA will be included. CCTA images of subjects should be of good quality up to the DICOM 3.0 standards, obtained by CT scan with ≥64-slices. The subjects with unqualified CTA will be excluded. CCTA images will be analyzed in three methods (3 groups). Control group: CCTA images will be visually evaluated by physicians. Experiment group: CCTA images will be evaluated by physicians using RuiXin-CoronaryAI. Reference group: CCTA images will be visually evaluated by cardiologists with at least 10 years experiences, and the conclusions they offer will be used as golden standard. Primary outcomes are diagnostic sensitivity and specificity of RuiXin-CoronaryAI and coronary CTA for diagnosis of ischemia on a per-vessel basis. The effectiveness of RuiXin-CoronaryAI for diagnosis of coronary artery stenosis will be conducted by testing superiority of diagnostic sensitivity and non-inferiority of specificity. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT05320185
Study type Observational
Source Shenzhen Raysight Intelligent Medical Technology Co., Ltd.
Contact Liming Xia
Phone 13607176908
Email lmxia@tjh.tjmu.edu.cn
Status Recruiting
Phase
Start date July 28, 2021
Completion date December 30, 2022
View Details
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