Kok Annette M, van der Lugt Aad, Verhagen Hence J M, van der Steen Antonius F W, Wentzel Jolanda J, Gijsen Frank J H
Department of Biomedical Engineering, Thorax Center, Erasmus Medical Center, Rotterdam, The Netherlands.
Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands.
J Biomech. 2017 Jul 26;60:175-180. doi: 10.1016/j.jbiomech.2017.06.034. Epub 2017 Jul 5.
A rupture-prone carotid plaque can potentially be identified by calculating the peak cap stress (PCS). For these calculations, plaque geometry from MRI is often used. Unfortunately, MRI is hampered by a low resolution, leading to an overestimation of cap thickness and an underestimation of PCS. We developed a model to reconstruct the cap based on plaque geometry to better predict cap thickness and PCS. We used histological stained plaques from 34 patients. These plaques were segmented and served as the ground truth. Sections of these plaques contained 93 necrotic cores with a cap thickness <0.62mm which were used to generate a geometry-based model. The histological data was used to simulate in vivo MRI images, which were manually delineated by three experienced MRI readers. Caps below the MRI resolution (n=31) were (digitally removed and) reconstructed according to the geometry-based model. Cap thickness and PCS were determined for the ground truth, readers, and reconstructed geometries. Cap thickness was 0.07mm for the ground truth, 0.23mm for the readers, and 0.12mm for the reconstructed geometries. The model predicts cap thickness significantly better than the readers. PCS was 464kPa for the ground truth, 262kPa for the readers and 384kPa for the reconstructed geometries. The model did not predict the PCS significantly better than the readers. The geometry-based model provided a significant improvement for cap thickness estimation and can potentially help in rupture-risk prediction, solely based on cap thickness. Estimation of PCS estimation did not improve, probably due to the complex shape of the plaques.
通过计算峰值帽应力（PCS），有可能识别出易破裂的颈动脉斑块。对于这些计算，通常使用来自MRI的斑块几何形状。不幸的是，MRI受分辨率低的影响，导致帽厚度被高估而PCS被低估。我们开发了一个基于斑块几何形状重建帽的模型，以更好地预测帽厚度和PCS。我们使用了34名患者的组织学染色斑块。这些斑块被分割并作为真实数据。这些斑块的切片包含93个帽厚度<0.62mm的坏死核心，用于生成基于几何形状的模型。组织学数据用于模拟体内MRI图像，由三位经验丰富的MRI阅片者手动勾勒。低于MRI分辨率的帽（n = 31）被（数字移除并）根据基于几何形状的模型重建。确定了真实数据、阅片者和重建几何形状的帽厚度和PCS。真实数据的帽厚度为0.07mm，阅片者为0.23mm，重建几何形状为0.12mm。该模型预测帽厚度比阅片者显著更好。真实数据的PCS为464kPa，阅片者为262kPa，重建几何形状为384kPa。该模型预测PCS并不比阅片者显著更好。基于几何形状的模型在帽厚度估计方面有显著改进，并且仅基于帽厚度就有可能帮助进行破裂风险预测。PCS估计没有改善，可能是由于斑块形状复杂。
