The influence of inaccuracies in carotid MRI segmentation on atherosclerotic plaque stress computations

\u3cp\u3eBiomechanical finite element analysis (FEA) based on in vivo carotid magnetic resonance imaging (MRI) can be used to assess carotid plaque vulnerability noninvasively by computing peak cap stress. However, the accuracy of MRI plaque segmentation and the influence this has on FEA has remained unreported due to the lack of a reliable submillimeter ground truth. In this study, we quantify this influence using novel numerical simulations of carotid MRI. Histological sections from carotid plaques from 12 patients were used to create 33 ground truth plaque models. These models were subjected to numerical computer simulations of a currently used clinically applied 3.0 T T1-weighted black-blood carotid MRI protocol (in-plane acquisition voxel size of 0.62 × 0.62 mm2) to generate simulated in vivo MR images from a known underlying ground truth. The simulated images were manually segmented by three MRI readers. FEA models based on the MRI segmentations were compared with the FEA models based on the ground truth. MRI-based FEA model peak cap stress was consistently underestimated, but still correlated (R) moderately with the ground truth stress: R = 0.71, R = 0.47, and R = 0.76 for the three MRI readers respectively (p <0.01). Peak plaque stretch was underestimated as well. The peak cap stress in thick-cap, low stress plaques was substantially more accurately and precisely predicted (error of-12 ± 44 kPa) than the peak cap stress in plaques with caps thinner than the acquisition voxel size (error of-177 ± 168 kPa). For reliable MRI-based FEA to compute the peak cap stress of carotid plaques with thin caps, the current clinically used in-plane acquisition voxel size (∼0.6 mm) is inadequate. FEA plaque stress computations would be considerably more reliable if they would be used to identify thick-cap carotid plaques with low stresses instead.\u3c/p\u3