Key result
A combined 3D carotid plaque radiomics and traditional radiological model based on high-resolution MRI significantly improved the identification of vulnerable plaques compared to the traditional model alone in the testing cohort (AUC 0.864 vs 0.778, p=0.037).
Why the study?
Carotid plaque vulnerability had previously been assessed qualitatively, motivating development of a 3D carotid plaque radiomics model based on HRMRI to quantitatively identify vulnerable plaques.
Does a 3D carotid plaque radiomics model based on HRMRI improve the identification of vulnerable plaques compared to a traditional model in patients with carotid stenosis?
Observational (n=90)
Single-blind
No
Does a 3D carotid plaque radiomics model based on HRMRI improve the identification of vulnerable plaques compared to a traditional model in patients with carotid stenosis?
An HRMRI-based 3D carotid radiomics model significantly improves the precision of detecting vulnerable carotid plaques compared to traditional qualitative radiological assessment.
May support quantitative vulnerable plaque identification on HRMRI; hypothesis-generating pending prospective validation.
Background: Identification of vulnerable carotid plaque is important for the treatment and prevention of stroke. In previous studies, plaque vulnerability was assessed qualitatively. We aimed to develop a 3D carotid plaque radiomics model based on high-resolution magnetic resonance imaging (HRMRI) to quantitatively identify vulnerable plaques. A combined model was constructed using radiological and radiomics characteristics. Nomogram was generated based on the combined models, and ROC curves were utilized to assess the performance of each model. Results: 48 patients (53.33%) were symptomatic and 42 (46.67%) were asymptomatic. The traditional model was constructed using intraplaque hemorrhage, plaque enhancement, wall remodeling pattern, and lumen stenosis, and it provided an area under the curve (AUC) of 0.816 vs. 0.778 in the training and testing sets. In the two cohorts, the 3D carotid plaque radiomics model and the combined model had an AUC of 0.915 vs. 0.835 and 0.957 vs. 0.864, respectively. In the training set, both the radiomics model and the combination model outperformed the traditional model, but there was no significant difference between the radiomics model and the combined model. Conclusions: HRMRI-based 3D carotid radiomics models can improve the precision of detecting vulnerable carotid plaques, consequently improving risk classification and clinical decision-making in patients with carotid stenosis.
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Zhang et al. (2023) conducted an observational in Carotid artery stenosis (n=90). Combined 3D HRMRI radiomics and traditional radiological model vs. Traditional radiological model was evaluated on Area under the ROC curve (AUC) for identifying vulnerable carotid plaques in the testing cohort (95% CI 0.721-1.000, p=0.037). A combined 3D carotid plaque radiomics and traditional radiological model based on high-resolution MRI significantly improved the identification of vulnerable plaques compared to the traditional model alone in the testing cohort (AUC 0.864 vs 0.778, p=0.037).
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