Role of On-site CT-derived FFR in the Management of Suspect CAD Patients (TARGET)
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|ClinicalTrials.gov Identifier: NCT03901326|
Recruitment Status : Recruiting
First Posted : April 3, 2019
Last Update Posted : August 21, 2019
|Condition or disease||Intervention/treatment||Phase|
|Coronary Artery Disease||Diagnostic Test: CT-FFR||Not Applicable|
|Study Type :||Interventional (Clinical Trial)|
|Estimated Enrollment :||1216 participants|
|Intervention Model:||Parallel Assignment|
|Masking:||None (Open Label)|
|Official Title:||The Effect of On-site CT-derived Fractional Flow Reserve on the Management Making for the Patients With Stable Chest Pain (TARGET Trial)|
|Actual Study Start Date :||May 10, 2019|
|Estimated Primary Completion Date :||December 2020|
|Estimated Study Completion Date :||December 2021|
Experimental: CTA/CT-FFR care group
If the subjects are randomly allocated to CTA/CT-FFR arm, they will be examined by DeepFFR for three major epicardial arteries. If CT-FFR value of one or more major coronary arteries is less than 0.75, ICA will be performed directly; if CT-FFR is 0.75-0.8 (including 0.8), physicians will decide whether to start intensive drug therapy or ICA; if CT-FFR value is more than 0.8, only drug therapy will be needed. The clinical management plan will be suggested including optimal medical therapy, ICA, PCI, CABG and other intervention according to the result of this non-invasive examination.
Diagnostic Test: CT-FFR
When subjects are randomized to the CTA/CT-FFR arm, FFR based on the coronary CTA imaging will be measured. DeepFFR workstation is very dedicated software utilizing the original CTA imaging to meter simulated FFR values in artificial intelligence model.The first step is to extract a 3D coronary artery model and generate coronary centerlines which are similar to the routine reconstruction of coronary CTA. The centerlines are extracted using a minimal path extraction filter. Then a novel path-based deep learning model, referred to DeepFFR, is used to predict the simulated FFR values on the vascular centerlines. Deep learning algorithm is used to establish characteristic sample database of coronary hemodynamics characteristic parameters. When deep training model is proved to be valid, it is applied to a new lesion-specific measurement. Lesion-specific CT-FFR is defined as simulated FFR value 2-3cm downstream of an interest lesion.
No Intervention: routine clinically-indicated diagnostic care group
If the subjects are randomized to CID arm, attending physicians will decide next step of diagnosis and treatment, such as exercise ECG, stress cardiac echo, SPECT. According to the results of examination combined with risk factors assessment and clinical manifestations, physicians should provide recommendation whether the subjects would undergo ICA or not.
- Rate of ICA without obstructive CAD or intervention [ Time Frame: 90 days ]Percentage of those with planned ICA in whom no significant obstructive CAD (no stenosis≥50% by core lab quantitative analysis or invasive FFR≤0.8) is found or interventions (including stent implantation, balloon dilation and bypass graft) are performed during ICA within 90 days.
- Major adverse cardiovascular event [ Time Frame: 90 days，6 months，12 months ]Major adverse cardiovascular event include death, myocardial infarction (MI), major complications from cardiovascular (CV) procedures or testing, and unstable angina hospitalization
- Medical expenditure [ Time Frame: 90 days，12 months ]Medical expenditure by intention to treat at both 90 days and 12 months cumulatively
- Quality of life score [ Time Frame: 12 months ]Quality of life score evaluated as quality of life (QOL), which is measured by Seattle Angina Questionnaire Scale, used 11-item instrument that measures patient reported symptoms, function and QOL for subjects with CAD within 12 months
- Cumulative radiation exposure [ Time Frame: 90 days, 12 months ]Cumulative radiation exposure for any examination within 90 days and 12 months
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03901326
|Contact: Junjie Yang, MD||86-13581662680||Fearlessyang@126.com|
|Contact: Dongkai Shan, MDemail@example.com|
|Chinese PLA General Hospital||Recruiting|
|Beijing, Beijing, China, 100853|
|Contact: Junjie Yang, MD|
|Contact: Dongkai Shan, MD|
|Principal Investigator:||Yundai Chen, Ph.D.||Chinese PLA General Hospital|