Radiomics model based on dual-energy CT can determine the source of thrombus in strokes with middle cerebral artery occlusion.

Purpose: To develop thrombus radiomics models based on dual-energy CT (DECT) for predicting etiologic cause of stroke. Methods: We retrospectively enrolled patients with occlusion of the middle cerebral artery who underwent computed tomography (NCCT) and DECT angiography (DECTA). 70 keV virtual mono...

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Publicado en:Neuroradiology Vol. 66; no. 10; pp. 1681 - 1692
Autores principales: Ma, Yuzhu, Dai, Yao, Zhao, Ying, Song, Ziyang, Hu, Chunhong, Zhang, Yu
Formato: diagnostic images research tables/charts Journal Article
Publicado: Springer Nature Oct2024
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
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        atl: Radiomics model based on dual-energy CT can determine the source of thrombus in strokes with middle cerebral artery occlusion.
      aug:
        au:
          Ma, Yuzhu
          Dai, Yao
          Zhao, Ying
          Song, Ziyang
          Hu, Chunhong
          Zhang, Yu
        affil: https://ror.org/04n3e7v86 Department of Radiology, The Fourth Affiliated Hospital of Soochow University, 215124, Suzhou, China
      sug:
        subj:
          Embolic Stroke Etiology
          Thrombosis Radiography
          Middle Cerebral Artery Pathology
          Arterial Occlusive Diseases Radiography
          Radiomics
          Tomography, X-Ray Computed
          Human
          Funding Source
          Retrospective Design
          Logistic Regression
          Computed Tomography Angiography
          Comparative Studies
          ROC Curve
          Decision Making, Clinical
          Calibration
          NIH Stroke Scale
          Scales
          Descriptive Statistics
          Atrial Fibrillation Radiography
      ab: Purpose: To develop thrombus radiomics models based on dual-energy CT (DECT) for predicting etiologic cause of stroke. Methods: We retrospectively enrolled patients with occlusion of the middle cerebral artery who underwent computed tomography (NCCT) and DECT angiography (DECTA). 70 keV virtual monoenergetic images (simulate conventional 120kVp CTA images) and iodine overlay maps (IOM) were reconstructed for analysis. Five logistic regression radiomics models for predicting cardioembolism (CE) were built based on the features extracted from NCCT, CTA and IOM images. From these, the best one was selected to integrate with clinical information for further construction of the combined model. The performance of the different models was evaluated and compared using ROC curve analysis, clinical decision curves (DCA), calibration curves and Delong test. Results: Among all the radiomic models, model NCCT+IOM performed the best, with AUC = 0.95 significantly higher than model NCCT, model CTA, model IOM and model NCCT+CTA in the training set (AUC = 0.88, 0.78, 0.90,0.87, respectively, P < 0.05), and AUC = 0.92 in the testing set, significantly higher than model CTA (AUC = 0.71, P < 0.05). Smoking and NIHSS score were independent predictors of CE (P < 0.05). The combined model performed similarly to the model NCCT+IOM, with no statistically significant difference in AUC either in the training or test sets. (0.96 vs. 0.95; 0.94 vs. 0.92, both P > 0.05). Conclusion: Radiomics models constructed based on NCCT and IOM images can effectively determine the source of thrombus in stroke without relying on clinical information.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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