Apply CT angiography, CT perfusion imaging and advanced image processing techniques to improve revascularization decision-making and surgical strategies in patients undergoing coronary artery bypass graft surgery.
The objective of this study is to integrate noninvasively acquired anatomical and functional information to develop clinically applicable tools for meaningful per-vessel revascularization decisions. The decisions will be based on quantitative lesion-specific ischemia and viability and flow simulations. These will be based on CT anatomy enhanced with a function for prediction of hemodynamic improvement after CABG.
Aim 1: Predict restoration of myocardial perfusion from coronary artery bypass graft surgery. The investigators will perform cardiac CT before and after CABG and measure absolute changes in myocardial perfusion as the functional outcome of CABG. The investigators will investigate clinical, surgical and imaging variables in association with post-CABG perfusion improvement on a per-vessel and per-patient level.
Aim 2: Non-invasively quantify vessel-specific ischemia for meaningful CABG decisions.
The investigators will develop and validate tools for assessment of vessel-specific ischemia and viability. The investigators will assess the potential impact of CT guided CABG by comparing the per-vessel need for grafting with standard care.
Aim 3: Predict CABG benefit through multi-parameter flow simulations Hypothesis: Integration of myocardial perfusion and viability can improve flow simulation models to predict CABG outcome. The investigators will develop new computational fluid dynamics models enriched with functional parameters and explore the potential of virtual grafting to improve hemodynamic outcomes.
Condition | Coronary Artery Disease, Coronary artery bypass graft, Coronary heart disease, Computer Assisted Diagnosis, CT scan, coronary disease, cabg, coronary artery bypass, coronary bypass, coronary artery bypass surgery, cytarabine/daunorubicin, disease, coronary, coronary heart diseases, ct scans, computed tomography, computerized tomography, ct scanning |
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Clinical Study Identifier | NCT03894423 |
Sponsor | Stanford University |
Last Modified on | 26 March 2021 |
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