Time-efficient patient-specific quantification of regional carotid artery fluid dynamics and spatial correlation with plaque burden

Abstract

Purpose: Low wall shear stress (WSS) and high oscillatory shear index (OSI) influence plaque formation, yet little is known about their role in progression/regression of established plaques because of lack of practical means to calculate them in individual patients. Our aim was to use computational fluid dynamics (CFD) models of patients with carotid plaque undergoing statin treatment to calculate WSS and OSI in a time-efficient manner, and determine their relationship to plaque thickness (PT), plaque composition (PC), and regression.

Methods: Eight patients (68 +/- 9 yr, one female) underwent multicontrast 3 T MRI at baseline and six-month post statin treatment. PT and PC were measured in carotid segments (common-CC, bifurcation-B, internal-IC) and circumferentially in nonoverlapping 600 angles and correlated with CFD models created from MRI, ultrasound, and blood pressure.

Results: PT was highest in B (2.42 +/- 0.98 versus CC: 1.60 +/- 0.47, IC: 1.62 +/- 0.52 mm, p < 0.01). Circumferentially, plaque was greatest opposite the flow divider (p < 0.01), where the lowest WSS and highest OSI were observed. In B and IC, PT was inversely related to WSS (R = -0.28 and -0.37, p < 0.01) and directly related to OSI (R = 0.22 and 0.52, p < 0.05). The total plaque volume changed from 1140 +/- 437 to 974 +/- 587 mm3 at six months (p = 0.1). Baseline WSS, but not OSI, correlated with changes in PT, necrotic tissue, and hemorrhage in B and IC, but not CC. CFD modeling took 49 +/- 18 h per patient.

Conclusions: PT and PC correspond to adverse WSS and OSI in B and IC, and WSS is modestly but significantly related to changes in PT after short-term statin treatment. Regional hemodynamics from CFD can feasibly augment routine clinical imaging for comprehensive plaque evaluation.

Figure 1

Plaque analysis. (a) Representative TOF, T1, T2, and PD-weighted images. (b) Carotid lumen and wall segments traced (middle row) and plaque components delineated by the software. (c) Lumen thickness as a function of image slice and circumferential location.

Figure 2

CFD modeling. The process involves (a) finding the centerline path, (b) performing segmentation to delineate the wall, (c) connecting these segments to form a representative model, and (d) discretizing the model using an automatic mesh generation program.

Figure 3

Simulation timing. Summary of the time required to complete each portion of the simulation process. Values represent averages from 16 simulations conducted on a computing cluster constructed from standard commercially available components.

Figure 4

WSS and OSI. Time-averaged wall shear stress (top half) and oscillatory shear index distributions (bottom half) for each patient at baseline and after six months.

Figure 5

Regional segmental and circumferential distribution of plaque, WSS, and OSI. There is regional segmental and circumferential variability in (a) plaque thickness, (c) time-averaged WSS, and (d) OSI. In the bifurcation region, the circumferential variability in WSS and OSI closely follows plaque distribution. The regional segmental and circumferential designations are depicted in (b).