Predicting Hemorrhagic Transformation in Stroke Patients Using Radiomics
Author Information
Author(s): Gong Chundan, Liu Yun, Ma Wei, Jing Yang, Liu Li, Huang Yan, Yang Jinlin, Feng Chen, Fang Yuan, Fang Weidong
Primary Institution: The First Affiliated Hospital of Chongqing Medical University
Hypothesis
Can a model based on hyperdense middle cerebral artery sign (HMCAS) radiomics features predict hemorrhagic transformation in acute ischemic stroke patients undergoing endovascular treatment?
Conclusion
HMCAS-based radiomics is expected to be a reliable tool for predicting hemorrhagic transformation risk in acute ischemic stroke patients after endovascular treatment.
Supporting Evidence
- 71 out of 118 patients developed hemorrhagic transformation after treatment.
- The combined model showed improved predictive performance with an AUC of 0.911.
- ASPECTS was identified as the only independent predictor among various clinical and radiological variables.
Takeaway
Doctors can use special imaging techniques to better predict if stroke patients will have complications after treatment.
Methodology
A retrospective study was conducted on patients with acute ischemic stroke who underwent endovascular treatment, using radiomics features from non-contrast CT scans to develop predictive models.
Potential Biases
Data selection bias may affect the results due to the retrospective nature of the study.
Limitations
The study is retrospective, has a small sample size, and lacks independent external validation.
Participant Demographics
Patients were adults aged 18 and older with acute anterior circulation large vessel occlusion.
Statistical Information
P-Value
0.039
Confidence Interval
95% CI 0.797–0.935
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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