Nieuwstadt Harm A, Speelman Lambert, Breeuwer Marcel, van der Lugt Aad, van der Steen Anton F W, Wentzel Jolanda J, Gijsen Frank J H
J Biomech Eng. 2014 Feb;136(2):021015. doi: 10.1115/1.4026178.
Biomechanical 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.
基于体内颈动脉磁共振成像（MRI）的生物力学有限元分析（FEA）可通过计算帽状峰值应力来无创评估颈动脉斑块易损性。然而，由于缺乏可靠的亚毫米级真实对照，MRI斑块分割的准确性及其对有限元分析的影响尚未见报道。在本研究中，我们使用新型颈动脉MRI数值模拟来量化这种影响。来自12例患者颈动脉斑块的组织学切片用于创建33个真实斑块模型。这些模型接受了当前临床应用的3.0 T T1加权黑血颈动脉MRI协议（平面采集体素大小为0.62×0.62 mm2）的数值计算机模拟，以从已知的真实对照生成模拟体内MR图像。模拟图像由三位MRI阅片者进行手动分割。将基于MRI分割的有限元分析模型与基于真实对照的有限元分析模型进行比较。基于MRI的有限元分析模型帽状峰值应力一直被低估，但仍与真实对照应力呈中度相关（R）：三位MRI阅片者的R分别为0.71、0.47和0.76（p<0.01）。斑块峰值拉伸也被低估。厚帽、低应力斑块的帽状峰值应力预测比帽厚度小于采集体素大小的斑块的帽状峰值应力（误差为-177±168 kPa）更准确、精确（误差为-12±44 kPa）。对于基于MRI的可靠有限元分析以计算薄帽颈动脉斑块的帽状峰值应力，当前临床使用的平面采集体素大小（约0.6 mm）是不够的。如果将有限元分析斑块应力计算用于识别低应力的厚帽颈动脉斑块，其可靠性将大大提高。
