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Relation of Carotid Plaque Features Detected with Ultrasonography-Based Radiomics to Clinical Symptoms

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Abstract

Carotid plaque is one of the predominant causes of stroke. We sought to build a nomogram using ultrasonography (US)-based radiomics and clinical features for identification of symptomatic carotid plaques. We prospectively enrolled 548 patients (mean age ± standard deviation, 63 ± 10 years; 373 men) were randomly divided into training and test cohorts. Clinical and conventional US features of carotid plaques were used to generate a clinical and conventional US model. US-based radiomics model was constructed by extracting radiomics features from grayscale and strain elasticity images. Multivariate logistic regression was performed using the radiomics scores together with clinical and conventional US data, and a final nomogram was subsequently developed. The performance of the final nomogram was assessed with respect to discrimination and clinical usefulness in the training of the test cohorts and contrast-enhanced US test cohort. All the radiomics scores were significantly higher in patients with symptomatic carotid plaques. The US-based radiomics model [area under the curve (AUC) = 0.930 and 0.922 for training and test cohorts, respectively] and final nomogram (AUC = 0.927 and 0.919, respectively) outperformed the clinical and conventional US model (AUC = 0.723 and 0.580, respectively). The decision curve analysis indicated that the final nomogram was clinically useful. In patients undergoing the contrast-enhanced US, the prevalence of plaque enhancement was higher in high-risk patients than in low-risk patients based on the final nomogram-score (P = 0.008). Nomogram has a high diagnostic performance for identification of symptomatic carotid plaques.

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Abbreviations

US:

Ultrasonography

SE:

Strain elastography

ROC:

Receiver operating characteristic

AUC:

Area under the curve

ICC:

Interclass correlation coefficients

LASSO:

Least absolute shrinkage and selection operator

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Funding

This study was funded by Science, Technology and Innovation Seed Fund from Zhongnan Hospital of Wuhan University (znpy2019089), Wuhan, China.

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Authors and Affiliations

  1. Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Dadao, Wuhan, 430030, China

    Zhe Huang, Xue-Qing Cheng, Hong-Yun Liu, Xiao-Jun Bi, Ya-Ni Liu & You-Bin Deng

  2. Department of Artificial Intelligence, Julei Technology Company, 13 Daxueyuan Road, Wuhan, 430030, China

    Wen-Zhi Lv

  3. Department of Cardiovascular Ultrasound, Zhongnan Hospital, Wuhan University, 169 East Lake Road, Wuhan, 430071, China

    Li Xiong

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  1. Zhe Huang
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Correspondence to Li Xiong or You-Bin Deng.

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All procedures performed in this study were in accordance with the ethical standards of the Institutional Review Board of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

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Huang, Z., Cheng, XQ., Liu, HY. et al. Relation of Carotid Plaque Features Detected with Ultrasonography-Based Radiomics to Clinical Symptoms. Transl. Stroke Res. 13, 970–982 (2022). https://doi.org/10.1007/s12975-021-00963-9

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