Multimodal Radiomics Model Combining HR‐VWI and Clinical Features for Identifying Symptomatic Basilar Atherosclerotic Plaques.
Objective: This study is aimed at exploring the value of a high‐resolution vessel wall imaging (HR‐VWI)–based radiomics approach for identifying symptomatic basilar atherosclerotic plaques. Materials and Methods: This retrospective study included 154 patients, hospitalized at Shanxi Cardiovascular H...
| Publicado en: | BioMed Research International Vol. 2026; pp. 1 - 13 |
|---|---|
| Autores principales: | , , , , , , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
6/2/2026
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=194234144&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 194234144 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 6/2/2026 vid: 2026 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 194234144 194234144 194234144 10.1155/bmri/7319324 194234144 ppf: 1 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Multimodal Radiomics Model Combining HR‐VWI and Clinical Features for Identifying Symptomatic Basilar Atherosclerotic Plaques. aug: au: Bai, Juan Yang, Caixian Li, Ning Hao, Xiaoyong Zhu, Lina Yan, Jingxi Wu, Jiang Wang, Mengzhu Gurumallesh Prabu, Poorani affil: Magnetic Resonance Room,, Shanxi Cardiovascular Hospital,, Shanxi Key Laboratory of Heart Failure Precision Medicine,, Cardiovascular Hospital Affiliated to Shanxi Medical University,, Taiyuan, China, sxmu.edu.cn sug: subj: Radiomics Magnetic Resonance Imaging Methods Basilar Artery Pathology Atherosclerosis Diagnosis Human China Funding Source Male Female Adult Middle Age Aged Aged, 80 and Over Retrospective Design Record Review Hospitals, Public Descriptive Statistics Data Analysis Software T-Tests Fisher's Exact Test Algorithms Univariate Statistics Multivariate Statistics Logistic Regression ROC Curve Age Factors Sensitivity and Specificity Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Aged, 80 & over Male Female ab: Objective: This study is aimed at exploring the value of a high‐resolution vessel wall imaging (HR‐VWI)–based radiomics approach for identifying symptomatic basilar atherosclerotic plaques. Materials and Methods: This retrospective study included 154 patients, hospitalized at Shanxi Cardiovascular Hospital for cerebrovascular disease, who had basilar artery stenosis and underwent HR‐VWI examinations between July 2020 and December 2023. The patients were randomly divided into training and validation sets in a 7:3 ratio and further classified into symptomatic and asymptomatic groups based on the presence or absence of acute infarction lesions in the basilar artery supply area, respectively. Clinical and traditional imaging features were collected for all patients. Manual plaque segmentation and radiomics feature extraction were performed on the layers of basilar artery plaques identified in the plain‐scanning and enhanced HR‐VWI images. Feature denoising was performed using minimum redundancy maximum correlation, and the least absolute shrinkage and selection operator (LASSO) algorithm was applied to reduce feature variables. The most suitable features were selected through univariate and multivariate logistic regression analyses. The plain‐scanning, enhanced, and plain − scanning + enhanced models were established. Finally, a combined model was constructed by integrating selected clinical and traditional imaging features (intraplaque hemorrhage [IPH], enhanced plaque signal) with the plain − scanning + enhanced HR − VWI radiomics features. The recognition efficiency of each model for symptomatic basilar atherosclerotic plaques was evaluated using the receiver operating characteristic (ROC) curve and the area under the receiver operating characteristic curve (AUC). Results: A statistically significant difference in age was observed between symptomatic and asymptomatic groups (p < 0.05). Conventional imaging features, including IPH, vessel diameter at stenosis, lumen area at stenosis, enhanced plaque signal, stenosis rate, and plaque load, also demonstrated statistically significant differences between the two groups (p < 0.05). Firth‐penalized logistic regression analysis identified IPH and enhanced plaque signal as risk factors for symptomatic basilar artery plaques. In the training set, the AUC values for detecting symptomatic plaques were 0.813, 0.853, and 0.898 for plain‐scanning, enhanced, and plain − scanning + enhanced models, respectively. In the validation set, the AUC values were 0.786, 0.848, and 0.880, respectively. The efficacy of models was in the order of plain − scanning + enhanced model > enhanced model > plain − scanning model. The combined model, integrating IPH and enhanced plaque signal with the plain − scanning + enhanced HR − VWI radiomics features, achieved an AUC of 0.916 in the training set, with sensitivity, specificity, and accuracy of 0.821, 0.941, and 0.879, respectively, for predicting symptomatic basilar artery plaques. In the validation set, the AUC value was 0.891, with sensitivity, specificity, and accuracy of 0.792, 0.870, and 0.830, respectively. The combined model demonstrated superior performance compared with the plain − scanning + enhanced model. Conclusion: Our HR‐VWI–based radiomics models can accurately distinguish symptomatic from asymptomatic basilar atherosclerotic plaques. It is superior to the traditional model in the identification of high‐risk plaques. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|