Classifications of atherosclerotic plaque components with T1 and T2* mapping in 11.7 T MRI
Research output: Contribution to journal › Article
Background and aims: Histopathology is the gold standard for analysis of atherosclerotic plaques but has drawbacks due to the destructive nature of the method. Ex vivo MRI is a non-destructive method to image whole plaques. Our aim was to use quantitative high field ex vivo MRI to classify plaque components, with histology as gold standard.
Methods: Surgically resected carotid plaques from 12 patients with recent TIA or stroke were imaged at 11.7 T MRI. Quantitative T1/T2* mapping sequences and qualitative T1/T2* gradient echo sequences with voxel size of 30 × 30 × 60 μm3 were obtained prior to histological preparation, sectioning and staining for lipids, inflammation, hemorrhage, and fibrous tissue. Regions of interest (ROI) were selected based on the histological staining at multiple levels matched between histology and MRI. The MRI parameters of each ROI were then analyzed with quadratic discriminant analysis (QDA) for classification.
Results: A total of 965 ROIs, at 70 levels matched between histology and MRI, were registered based on histological staining. In the nine plaques where three or more plaque components were possible to co-localize with MRI, the mean degree of misclassification by QDA was 16.5 %. One of the plaques contained mostly fibrous tissue and lipids and had no misclassifications, and two plaques mostly contained fibrous tissue. QDA generally showed good classification for fibrous tissue and lipids, whereas plaques with hemorrhage and inflammation had more misclassifications.
Conclusion: 11.7 T ex vivo high field MRI shows good visual agreement with histology in carotid plaques. T1/T2* maps analyzed with QDA is a promising non-destructive method to classify plaque components, but with a higher degree of misclassifications in plaques with hemorrhage or inflammation.
|Research areas and keywords||
Subject classification (UKÄ) – MANDATORY
|Journal||European Journal of Radiology Open|
|Publication status||Published - 2021|