Artificial Intelligence, Coronary Artery Disease, Coronary Artery Stenosis, CT Angiography
Conditions
Brief 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.
Detailed 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.
Interventions
DEVICERuiXin-CoronaryAI software
RuiXin-CoronaryAI, based on Computed Tomography Angiography (CTA) and was independently designed by RaysightMed Inc., which has been already authorized by National Medical Products Administration (NMPA).
Sponsors
Tongji Hospital
Beijing Hospital
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Shenzhen Raysight Intelligent Medical Technology Co., Ltd.
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
1. layer thickness of CCTA images should be less than 1mm, image quality should be up to DICOM 3.0 standards; 2. vessels should be clearly developed, contrast medium ought to be well filled, the average of CT value of aortic root cavity should be between 325-600HU in CCTA image; 3. remodeling of vessels should be intact, including coronary artery and branches, without missed or inaccurate slices; 4. CCTA image should be obtained from single- or dual-source computed tomography (CT) scanners with a minimum of 64 detector rows.
Exclusion criteria
1. CCTA image is of poor quality due to motion artifact, severe calcification, metal coverage, noise, poor contrast medium injection and other variables influencing the diagnosis of stenosis; 2. previous percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG); 3. anomalous origin of coronary artery; 4. other non-atherosclerosis-related coronary diseases like coronary artery fistula, aneurysm, coronary artery ectasia, arteritis coronaria, etc.; 5. repeated enrollment; 6. other conditions not suitable for enrollment.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Per-vessel diagnostic sensitivity of RuiXin-CoronaryAI for diagnosis of coronary artery stenosis | 1 day; Incident time for CTA examination was dependent on the length of time on the CT scaner. RuiXin-CoronaryAI examination was done remotely at Raysight's processing center in Shenzhen with a turnaround time of 24 hours from CT scan. | Outcome measures were comparing RuiXin-CoronaryAI to CTA on a per-vessel basis |
| Per-vessel diagnostic specificity of RuiXin-CoronaryAI for diagnosis of coronary artery stenosis | 1 day; Incident time for CTA examination was dependent on the length of time on the CT scaner. RuiXin-CoronaryAI examination was done remotely at Raysight's processing center in Shenzhen with a turnaround time of 24 hours from CT scan. | Outcome measures were comparing RuiXin-CoronaryAI to CTA on a per-vessel basis |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Per-patient diagnostic sensitivity of RuiXin-CoronaryAI for diagnosis of coronary artery stenosis | 1 day; Incident time for CTA examination was dependent on the length of time on the CT scaner. RuiXin-CoronaryAI examination was done remotely at Raysight's processing center in Shenzhen with a turnaround time of 24 hours from CT scan. | Outcome measures were comparing RuiXin-CoronaryAI to CTA on a per-patient basis |
| Per-patient diagnostic specificity of RuiXin-CoronaryAI for diagnosis of coronary artery stenosis | 1 day; Incident time for CTA examination was dependent on the length of time on the CT scaner. RuiXin-CoronaryAI examination was done remotely at Raysight's processing center in Shenzhen with a turnaround time of 24 hours from CT scan. | Outcome measures were comparing RuiXin-CoronaryAI to CTA on a per-patient basis |
Countries
China
Contacts
Primary ContactLiming Xia
Backup ContactLihui Li
Outcome results
None listed