Key result
A multicontrast MRI classification algorithm identified carotid plaque components with sensitivities of 60.4%-97.6% and specificities of 75.0%-98.3% compared to histology and micro-CT.
Why the study?
Does multicontrast MRI with a supervised classification algorithm accurately identify plaque components in carotid endarterectomy specimens compared to histology and micro-CT?
Population
Carotid endarterectomy specimens
Comparison
Multicontrast MRI with a supervised… vs Micro-CT and matched histological slices…
Design
Preclinical, Pathologist blinded to classifier results
Authors
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Hypothesis-generating for MRI plaque classification; requires human validation before clinical translation.
Observational
Single-blind
Does multicontrast MRI with a supervised classification algorithm accurately identify plaque components in carotid endarterectomy specimens compared to histology and micro-CT?
Multicontrast MRI combined with a supervised classification algorithm accurately identifies carotid plaque components in endarterectomy specimens, offering a framework for in vivo plaque imaging.
Clarke et al. (2003) conducted an observational in Carotid atherosclerosis. Multicontrast MRI with supervised classification algorithm vs. Histology and micro-CT was evaluated on Sensitivity and specificity for identifying plaque components (fibrous tissue, necrosis, calcification, loose connective tissue). A multicontrast MRI classification algorithm identified carotid plaque components with sensitivities of 60.4%-97.6% and specificities of 75.0%-98.3% compared to histology and micro-CT.
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