Validation of automatically classified magnetic resonance images for carotid plaque compositional analysis

Abstract

Background and purpose: MRI may be used for noninvasive assessment of atherosclerotic lesions; however, MRI evaluation of plaque composition requires validation against an accepted reference standard, such as the American Heart Association (AHA) lesion grade, defined by histopathological examination.

Methods: Forty-eight carotid endarterectomy specimen cross-sections had AHA lesion grade determined histopathologically and were concurrently imaged using combinations of 8 MRI contrast weightings in vitro. A maximum likelihood classification algorithm generated MRI "maps" of plaque components, and an AHA lesion grade was assigned correspondingly. Additional analyses compared classification accuracy obtained with a commonly used set of magnetic resonance contrast weightings [proton density (PDw), T1 (T1w), and partial T2 (T2w)] to accuracy obtained with the combination of PDw, T1w, and diffusion-weighted (Dw) contrast.

Results: For the 8-contrast combination, the sensitivities for fibrous tissue, necrotic core, calcification, and hemorrhage detection were 83%, 67%, 86%, and 77%, respectively. The corresponding specificities were 81%, 78%, 99%, and 97%. Good agreement (79%) between magnetic resonance and histopathology for AHA classification was achieved. For the PDw, T1w, and Dw combination, the overall classification accuracy was insignificantly different at 78%, whereas the overall classification accuracy using PDw, T1w, and partial T2w contrast weightings was significantly lower at 67%.

Conclusions: This study provides proof-of-principle that the composition of atherosclerotic plaques determined by automated classification of high-resolution ex vivo MRI accurately reflects lesion composition defined by histopathological examination.