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Image Patch-Based Net Water Uptake and Radiomics Models Predict Malignant Cerebral Edema After Ischemic Stroke
Bowen Fu1, Shouliang Qi1,2, Lin Tao3
1College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China.
Frontiers in Neurology
|January 11, 2021
Summary
A new method, Image Patch-based Net Water Uptake (IP-NWU), accurately predicts malignant cerebral edema (MCE) after ischemic stroke using non-enhanced CT scans. This approach simplifies MCE prediction, aiding early intervention decisions.
Area of Science:
- Neurology
- Radiology
- Medical Imaging Analysis
Background:
- Malignant cerebral edema (MCE) following ischemic stroke is a critical determinant of patient outcomes, often necessitating surgical intervention.
- Accurate and early prediction of MCE is crucial for timely treatment decisions, such as decompressive craniectomy.
- Current methods for predicting MCE, like CT perfusion and lesion segmentation, are resource-intensive and require follow-up imaging.
Purpose of the Study:
- To introduce and validate a novel Image Patch-based Net Water Uptake (IP-NWU) method for predicting MCE.
- To assess the performance of IP-NWU using only non-enhanced admission CT scans, eliminating the need for lesion segmentation.
- To compare IP-NWU with existing Segmented Region-based NWU (SR-NWU) methods and develop radiomics models for enhanced MCE prediction.
Main Methods:
- Developed the IP-NWU procedure by comparing densities of ischemic and contralateral normal patches from non-enhanced admission CT scans.
- Compared IP-NWU with SR-NWU, which requires segmented lesion data from follow-up CT.
- Constructed radiomics predictive models for MCE by integrating IP-NWU and other imaging features using a random forest classifier.
Main Results:
- IP-NWU was significantly higher in patients with MCE compared to those without (p < 0.05).
- IP-NWU demonstrated strong predictive capability for MCE with an Area Under the Curve (AUC) of 0.86.
- No significant difference was observed between IP-NWU and SR-NWU in predicting MCE, with exceptional inter-reader and inter-operation agreement for IP-NWU (ICC = 0.92 and 0.95, respectively).
- The radiomics model combining IP-NWU with imaging features achieved the highest predictive performance with an AUC of 0.96.
Conclusions:
- IP-NWU is a reliable and efficient method for predicting MCE using readily available non-enhanced admission CT scans.
- The IP-NWU method offers comparable predictive accuracy to more complex segmentation-based approaches.
- Radiomics models incorporating IP-NWU show significant potential for precise MCE prediction, facilitating earlier clinical management of ischemic stroke patients.

