Can MRI Predict Perforator Stroke Progression?

Investigators evaluate multisequence imaging for its ability to identify patients at risk for neurologic progression.

By
Kathryn Wighton
February 24, 2026
3 min

MDSpire News

Objective:

To evaluate the predictive performance of a multiparameter MRI-based radiomics model for progressive neurologic deterioration in patients with subacute ischemic perforator artery cerebral infarction.

Approach:

Key Findings:

The combined model achieved an AUC of 0.844 in the training cohort and 0.824 in the validation cohort.
Sensitivity, specificity, and accuracy for the combined model were approximately 76%, 75%, and 76% in the training cohort, and 65%, 73%, and 70% in the validation cohort.
Single-sequence models had lower AUC values ranging from 0.769 to 0.820 in the training cohort.

Interpretation:

The multiparameter MRI-based radiomics model outperforms single-sequence models in predicting progressive cerebral infarction, indicating its potential utility in clinical settings.

Limitations:

Modest sample size and restriction to single perforating artery infarctions.
Heterogeneity in infarct location and lack of external validation.
Retrospective design and potential partial volume effects.

Conclusion:

A radiomics-based model using multiple MRI sequences can effectively predict clinical symptom progression in patients with subacute ischemic perforator artery cerebral infarction.