Clarke Sharon E, Hammond Robert R, Mitchell J Ross, Rutt Brian K
Imaging Research Laboratories, Robarts Research Institute, London, Canada.
Magn Reson Med. 2003 Dec;50(6):1199-208. doi: 10.1002/mrm.10618.
MRI is emerging as a promising modality for monitoring carotid atherosclerosis. Multiple MR contrast weightings are required for identification of plaque constituents. In this study, eight MR contrast weightings with proven potential for plaque characterization were used to image carotid endarterectomy specimens. A classification technique was developed to create a tissue-specific map by incorporating information from all MR contrast weightings. The classifier was validated by comparison with micro-CT (calcification only) and with matched histological slices registered to MR images using a nonlinear warping algorithm (other components). A pathologist who was blinded to the classifier results manually segmented digitized histological images. The sensitivity of the classifier, as determined by pixel-by-pixel comparison with the pathologist's segmentation and micro-CT, was 60.4% for fibrous tissue, 83.9% for necrosis, 97.6% for calcification, and 65.2% for loose connective tissue. The corresponding values for specificity were 87.9%, 75.0%, 98.3%, and 94.9%, respectively. In conclusion, multicontrast MRI was successfully used in conjunction with a supervised classification algorithm to identify plaque components in endarterectomy specimens. Furthermore, this methodology will provide a framework for comparing different classification algorithms, and determining which combination of MR contrasts will be most valuable for in vivo plaque imaging.
磁共振成像（MRI）正逐渐成为监测颈动脉粥样硬化的一种有前景的方式。识别斑块成分需要多种磁共振对比加权成像。在本研究中，使用了八种已证实具有斑块特征表征潜力的磁共振对比加权成像来对颈动脉内膜切除术标本进行成像。开发了一种分类技术，通过整合所有磁共振对比加权成像的信息来创建组织特异性图谱。通过与微计算机断层扫描（仅针对钙化）以及使用非线性扭曲算法配准到磁共振图像的匹配组织学切片（其他成分）进行比较，对分类器进行了验证。一位对分类器结果不知情的病理学家手动分割数字化的组织学图像。通过与病理学家的分割结果和微计算机断层扫描进行逐像素比较确定，分类器对纤维组织的敏感性为60.4%，对坏死组织为83.9%，对钙化组织为97.6%，对疏松结缔组织为65.2%。相应的特异性值分别为87.9%、75.0%、98.3%和94.9%。总之，多对比磁共振成像与监督分类算法联合使用，成功地识别了内膜切除术标本中的斑块成分。此外，这种方法将为比较不同的分类算法以及确定哪种磁共振对比组合对体内斑块成像最有价值提供一个框架。
