Computational fluid modeling to understand the role of anatomy in bifurcation lesion disease
Background: Treatment of bifurcation lesion disease is complex with limited studies that describe the influence of lesion anatomy on clinical outcomes. Hypothesis: Computational simulations can be used to understand the interplay between morphological characteristics of lesion and clinical diagnostic metrics. Methods: Geometric modifications along the bifurcation in a patient-derived left coronary artery were made to incorporate unique combination of anatomic features: curvature, length and occlusion severity. The resulting geometries were used to perform CFD simulations using physiological flow parameters. Three diagnostic metrics, resting gradient, instantaneous wave free ratio (iFR) and diastolic-systolic velocity ratio (DSVR), were computed from the simulations. Results: We report occlusion severity to be an independent predictor for lower resting gradient and iFR values, whereas lesion length and curvature did not yield dramatic changes in iFR and resting gradient. Our results suggest that DSVR is more sensitive to nuanced flow disturbances; however, it may be complex to derive direct correspondence to disease severity relative to resting gradient and iFR. Conclusion: Spatial lesion characteristics can be used to determine diseased bifurcation cases that may lead to interventional complications.
