Using Gaussian process for velocity reconstruction after coronary stenosis applicable in positron emission particle tracking: An in-silico study

• Published in: PloS one Vol. 18; no. 12; p. e0295789
• Main Authors: Keramati, Hamed, de Vecchi, Adelaide, Rajani, Ronak, Niederer, Steven A
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 14.12.2023; Public Library of Science (PLoS)
• Subjects: Algorithms; Analysis; Bifurcations; Biology and Life Sciences; Blood flow; Cardiovascular disease; Care and treatment; Computational fluid dynamics; Coronary artery disease; Coronary heart disease; Design optimization; Diagnosis; Emissions; Error analysis; Evaluation; Flow velocity; Fluid dynamics; Fluid flow; Gaussian process; Gaussian processes; Heart diseases; Hydrodynamics; Medical research; Medicine and Health Sciences; Methods; Occlusion; Particle tracking; Physical Sciences; Positron emission; Reconstruction; Research and Analysis Methods; Reynolds number; Scanners; Stenosis; Tomography; Tracer particles; Tracers; Velocity; Velocity distribution; United Kingdom
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0295789

Accurate velocity reconstruction is essential for assessing coronary artery disease. We propose a Gaussian process method to reconstruct the velocity profile using the sparse data of the positron emission particle tracking (PEPT) in a biological environment, which allows the measurement of tracer particle velocity to infer fluid velocity fields. We investigated the influence of tracer particle quantity and detection time interval on flow reconstruction accuracy. Three models were used to represent different levels of stenosis and anatomical complexity: a narrowed straight tube, an idealized coronary bifurcation with stenosis, and patient-specific coronary arteries with a stenotic left circumflex artery. Computational fluid dynamics (CFD), particle tracking, and the Gaussian process of kriging were employed to simulate and reconstruct the pulsatile flow field. The study examined the error and uncertainty in velocity profile reconstruction after stenosis by comparing particle-derived flow velocity with the CFD solution. Using 600 particles (15 batches of 40 particles) released in the main coronary artery, the time-averaged error in velocity reconstruction ranged from 13.4% (no occlusion) to 161% (70% occlusion) in patient-specific anatomy. The error in maximum cross-sectional velocity at peak flow was consistently below 10% in all cases. PEPT and kriging tended to overestimate area-averaged velocity in higher occlusion cases but accurately predicted maximum cross-sectional velocity, particularly at peak flow. Kriging was shown to be useful to estimate the maximum velocity after the stenosis in the absence of negative near-wall velocity.