Coronarybypassgraftsurgery(CABG)improvesthelivesofpatientswithcoronarydisease(CAD)asagroup, but20%ofpatientsremainsymptomaticoneyearaftersurgery.InclinicalpracticeCABGdecisionsarelargely drivenbystenosisseveritydeterminedfrominvasiveangiographydespitetheknownrelevanceoffunctional CAD parameters. This practical impasse will continue to exist without clinically available, high-resolution, quantitativefunctionalimaging,andabetterunderstandingoftheclinicaloutcomesinrelationtoanatomical (angiography) and functional (ischemia, scar tissue) factors. The long-term goal is to improve outcome of CABG through personalized imaging-guided care. The overall objective of this proposal is to identify determinants of myocardial flow restoration (ischemia reduction), and develop integrated imaging tools for individualized, lesion-specific CABG decision-making, and computational flow simulations based on the patient?s anatomy and function to predict the hemodynamic outcome. Supported by studies using invasive FFR-guided CABG, the rationale for the proposed research is that integration of anatomical (angiography) andfunctionalinformation(ischemia,scartissue)willidentifyindividualcoronaryvesselsthatwillbenefitfrom revascularization,andindividualoptimizationofsurgicalproceduresbyflowsimulationswillmaximizeclinical benefit of CABG for patients with CAD. Supported by promising preliminary data, three specific aims are proposed: 1) Prospectively identify angiographic, functional and clinical baseline determinants of outcome afterCABG,definedasimprovementofmyocardialperfusion(ischemiareduction)andanginasymptoms;?2) Develop and validate a comprehensive imaging strategy and clinically applicable tool that integrate high- resolution angiographic and quantitative functional information (ischemia, viability) for per-vessel/lesion revascularization decisions;? 3) Develop and validate new multi-parametric computational flow simulations, withincorporationoffunctionalimagingdata,whichallowsforpredictionofindividualhemodynamicoutcome and ultimately surgical optimization based on virtual hemodynamic results. This approach is innovative because new imaging techniques will advance the field?s understanding of CABG physiology, and new clinicallyapplicabletoolswillbedevelopedforcomprehensiveclinicaldecision-makingandoptimizedsurgical planning.Theacquiredknowledgeanddevelopedtoolsareapplicabletoothervascularcontexts,andmay also be instrumental for new therapeutic innovations. The proposed research is significant because identification of CABG outcome determinants, and new solutions for comprehensive decision-making and procedural guidance, have the potential to improve the effectiveness (by complete functional revascularization) and efficiency of CABG (by avoiding futile grafts). For a large group of patients, these innovations willimprove thepatient-valued benefit of CABG(complications,symptoms), andalsodecrease costbyimprovedefficiencyofcare.

Public Health Relevance

TheproposedresearchisrelevanttothepublichealthbecauseidentificationofCABGoutcomedeterminants, and development of diagnostic solutions for comprehensive decision-making and procedural guidance of CABG surgery, can help achieve complete functional revascularization and restoration of myocardial blood flow in more patients. Thus, the proposed research is relevant to the NIH?s mission that pertains to the discoveryoffundamentalknowledgeaboutthenatureandbehavioroflivingsystemsandtheapplicationof thatknowledgetoenhancehealth,lengthenlife,andreduceillnessanddisability.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL141712-02
Application #
9869041
Study Section
Clinical and Integrative Cardiovascular Sciences Study Section (CICS)
Program Officer
Lee, Albert
Project Start
2019-02-15
Project End
2024-01-31
Budget Start
2020-02-01
Budget End
2021-01-31
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Stanford University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305