AI Article Synopsis

  • This study aimed to assess how different coronary artery bypass graft (CABG) configurations impact blood flow and graft success, using computational fluid dynamics (CFD) models to aid surgical decision-making.
  • Sixteen surgeons evaluated preferred grafting strategies for patients with severe coronary artery disease, comparing standard 'aortic' approaches to 'anaortic' techniques that minimize aortic manipulation.
  • Results showed that 'anaortic' configurations were more likely to result in unsatisfactory grafts without CFD guidance, but the use of predictive models significantly improved surgeon decisions, particularly for 'anaortic' approaches.

Article Abstract

Objectives: Flow competition between coronary artery bypass grafts (CABG) and native coronary arteries is a significant problem affecting arterial graft patency. The objectives of this study were to compare the predictive hemodynamic flow resulting from various total arterial grafting configurations and to evaluate whether the use of computational fluid dynamics (CFD) models capable of predicting flow can assist surgeons to make better decisions for individual patients by avoiding poorly functioning grafts.

Methods: Sixteen cardiac surgeons declared their preferred CABG configuration using bilateral internal mammary and radial arteries for each of 5 patients who had differing degrees of severe triple vessel coronary disease. Surgeons selected both a preferred 'aortic' strategy, with at least one graft arising from the ascending aorta, and a preferred "anaortic" strategy which could be performed as a "no-aortic touch" operation. CT coronary angiograms of the 5 patients were coupled to CFD models using a novel flow solver "COMCAB." Twelve different CABG configurations were compared for each patient of which 4 were "aortic" and 8 were "anaortic." Surgeons then selected their preferred grafting configurations after being shown predictive hemodynamic metrics including functional assessment of stenoses (instantaneous wave-free ratio; fractional flow reserve), transit time flowmetry graft parameters (mean graft flow; pulsatility index) and myocardial perfusion.

Results: A total of 87.5% (7/8) of "anaortic" configurations compared to 25% (1/4) of "aortic" configurations led to unsatisfactory grafts in at least 1 of the 5 patients ( = 0.038). The use of the computational models led to a significant decrease in the selection of unsatisfactory grafting configurations when surgeons employed "anaortic" (21.25% (17/80) vs. 1.25% (1/80), < 0.001) but not "aortic" techniques (5% (4/80) vs. 0% (0/80), = 0.64). Similarly, there was an increase in the selection of ideal configurations for "anaortic" (6.25% (5/80) vs. 28.75% (23/80), < 0.001) but not "aortic" techniques (65% (52/80) vs. 61.25% (49/80), = 0.74). Furthermore, surgeons who planned to use more than one unique "anaortic" configuration across all 5 patients increased (12.5% (2/16) vs. 87.5% (14/16), <0.001).

Conclusions: "COMCAB" is a promising tool to improve personalized surgical planning particularly for CABG configurations involving composite or sequential grafts which are used more frequently in anaortic operations.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9940318PMC
http://dx.doi.org/10.3389/fcvm.2023.1095678DOI Listing

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