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• Clinical Article •
The study of MRI perfusion imaging global and local radiomics in the prediction of outcome in acute stroke
ZHOU Xiaohu  PENG Mingyang  WANG Tongxing  CHEN Guozhong  YIN Xindao  REN Jun 

Cite this article as: ZHOU X H, PENG M Y, WANG T X, et al. The study of MRI perfusion imaging global and local radiomics in the prediction of outcome in acute stroke[J]. Chin J Magn Reson Imaging, 2024, 15(10): 98-102, 135. DOI:10.12015/issn.1674-8034.2024.10.017.


[Abstract] Objective To investigate the predicting value of local and global brain radiomics of MR perfusion weighted imaging (PWI) in the outcome of acute stroke after endovascular.Materials and Methods A total of 180 acute stroke patients with PWI images in our hospital were retrospectively enrolled. The ITK-SNAP software was used to segment the regions of interest of abnormal perfusion areas in Tmax. The SPM software was used to automatically segment the global brain in Tmax. The AK software was used to extract the local and global brain radiomics and reduce the dimensionality. The support vector machine classifier was used to construct the models for predicting the outcome of acute stroke, and further searching for the optimal prediction model.Results After least absolute shrinkage and selection operator (LASSO) dimensionality reduction, there are 6 local features, 5 global brain features, and 10 combined local and global brain features that are highly related to outcome. Receiver operating characteristic (ROC) analysis showed that area under the curve (AUC) of the outcome prediction model based on both local and global brain features was 0.900, with the sensitivity and specificity were 82.3% and 89.1% respectively, which is significantly better than the local features model (AUC=0.706; Z=-3.248; P=0.001) and the global brain features (AUC=0.711; Z=-3.393; P<0.001).Conclusions Combining local and global PWI features can more accurately predict the outcome of acute stroke patients and provide personalized guidance for early clinical intervention.
[Keywords] stroke；outcome；perfusion weighted imaging；magnetic resonance imaging；radiomics；machine learning

ZHOU Xiaohu   PENG Mingyang   WANG Tongxing   CHEN Guozhong   YIN Xindao   REN Jun*  

Department of Medical Imaging, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China

Corresponding author: REN J, E-mail: renjun1203@163.com

Conflicts of interest   None.

Received  2024-04-24
Accepted  2024-10-10
DOI: 10.12015/issn.1674-8034.2024.10.017
Cite this article as: ZHOU X H, PENG M Y, WANG T X, et al. The study of MRI perfusion imaging global and local radiomics in the prediction of outcome in acute stroke[J]. Chin J Magn Reson Imaging, 2024, 15(10): 98-102, 135. DOI:10.12015/issn.1674-8034.2024.10.017.

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