Predicting periprocedural complications risk in intracranial angioplasty and stenting from integrated high-resolution vessel wall imaging radiomics and clinical characteristics.

Purpose: To develop and validate an integrated model based on MR high-resolution vessel wall imaging (HR-VWI) radiomics and clinical features to preoperatively assess periprocedural complications (PC) risk in patients with intracranial atherosclerotic disease (ICAD) undergoing percutaneous translumi...

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Publicado en:Neuroradiology Vol. 67; no. 9; pp. 2459 - 2470
Autores principales: Guo, Yu, Yuan, Chengxiu, Su, Yuwen, Wang, Zhe, Li, Songchuan, Wang, Bao, Hu, Chunhong
Formato: research tables/charts Journal Article
Publicado: Springer Nature Sep2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Sep2025
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s00234-025-03757-0
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        atl: Predicting periprocedural complications risk in intracranial angioplasty and stenting from integrated high-resolution vessel wall imaging radiomics and clinical characteristics.
      aug:
        au:
          Guo, Yu
          Yuan, Chengxiu
          Su, Yuwen
          Wang, Zhe
          Li, Songchuan
          Wang, Bao
          Hu, Chunhong
        affil: https://ror.org/051jg5p78 Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
      sug:
        subj:
          Intracranial Arteriosclerosis Radiography
          Intracranial Arteriosclerosis Surgery
          Intracranial Arteriosclerosis Diagnosis
          Angioplasty, Transluminal, Percutaneous Coronary Adverse Effects
          Stents Adverse Effects
          Radiomics
          Magnetic Resonance Imaging
          Postoperative Complications Risk Factors
          Risk Assessment
          Human
          Male
          Female
          Middle Age
          Multicenter Studies
          Retrospective Design
          Record Review
          Multivariate Analysis
          Multiple Logistic Regression
          Odds Ratio
          Confidence Intervals
          Image Interpretation, Computer Assisted
          Decision Support Techniques
          Predictive Value of Tests
          ROC Curve
          Validation Studies
          One-Way Analysis of Variance
          Kruskal-Wallis Test
          Chi Square Test
          Fisher's Exact Test
          Univariate Statistics
          Statistical Significance
          Data Analysis Software
          Descriptive Statistics
          Middle Aged: 45-64 years
          Male
          Female
      ab: Purpose: To develop and validate an integrated model based on MR high-resolution vessel wall imaging (HR-VWI) radiomics and clinical features to preoperatively assess periprocedural complications (PC) risk in patients with intracranial atherosclerotic disease (ICAD) undergoing percutaneous transluminal angioplasty and stenting (PTAS). Methods: This multicenter retrospective study enrolled 601 PTAS patients (PC+, n = 84; PC −, n = 517) from three centers. Patients were divided into training (n = 336), validation (n = 144), and test (n = 121) cohorts. All patients underwent preoperative HR-VWI (precontrast T1-weighted [T1] and postcontrast T1-weighted [T1CE] sequences). We extracted 2,396 radiomic features and selected clinical variables via multivariate logistic regression. Radiomics, clinical and integrated model were developed. Model performance was evaluated using areas under the curve (AUC) and DeLong test. Decision Curve Analysis (DCA) was used to evaluate the net benefit of each model. Results: Age was the sole independent clinical predictor (OR = 1.06, p = 0.001). The integrated model demonstrated favorable predictive performance in the training cohort (AUC: 0.93, 95% CI [0.88, 0.96]), validation cohort (AUC: 0.87, 95% CI [0.74, 0.99]), and test cohort (AUC: 0.87, 95% CI [0.78, 0.95]). It significantly outperformed all clinical models (AUC range: 0.59–0.73; all p < 0.05) and showed performance comparable to the optimal radiomics model (T1-T1CE model; AUC range: 0.80–0.91; all p > 0.05).Notably, the DCA curve indicated that the integrated model achieved the optimal clinical net benefit across the 0–90% threshold range in the test cohort. Conclusion: The integrated model demonstrates clinical utility for preoperative PC risk stratification in PTAS patients.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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