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Corpus Callosum Integrity Predicts Functional Outcomes in Acute Stroke: A Probabilistic Structural Connectivity Study
Elena de la Calle1, Carles Biarnés1, Marian Martí-Navas1
1Department of Radiology-Medical Imaging (IDI), Girona Biomedical Research Institute (IdIBGi), Dr. Josep Trueta University Hospital, Girona, Spain.
Journal of Stroke
|February 9, 2026
Summary
Structural disconnection mapping using diffusion tensor imaging can predict stroke recovery. Corpus callosum and somatomotor network connections are key indicators for functional outcomes after ischemic stroke.
Area of Science:
- Neuroimaging
- Neurology
- Biomedical Engineering
Background:
- Stroke significantly impacts cognitive and motor functions.
- Clinical severity and infarct volume offer limited predictive power for functional outcomes.
- Advanced structural and functional connectivity methods are needed to understand patient variability in stroke recovery.
Purpose of the Study:
- To evaluate disconnection markers derived from diffusion tensor imaging for predicting functional outcomes in acute ischemic stroke patients.
- To identify specific white matter (WM) disconnection patterns associated with varying degrees of functional recovery.
- To enhance the accuracy of predicting stroke outcomes beyond traditional clinical measures.
Main Methods:
- A probabilistic approach quantified brain damage by analyzing white matter (WM) disconnections affecting cortical areas.
- Forty-three acute ischemic stroke patients were categorized based on functional improvement at 3-month follow-up.
- Structural disconnection measures, including fractional anisotropy (FA) and radial diffusivity (RD) of WM tracts, were analyzed and combined using principal component analysis for logistic regression modeling.
Main Results:
- Baseline structural disconnections in the corpus callosum predicted poor functional outcomes.
- Increased somatomotor network (SMN) disconnection severity correlated with diminished recovery.
- Logistic regression models incorporating age, NIH Stroke Scale score, and structural disconnections significantly predicted functional outcomes, improving prediction accuracy from 53.8% to 76.9%.
Conclusions:
- Probabilistic structural disconnection mapping identifies key predictive markers for acute stroke outcomes.
- Preservation of interhemispheric corpus callosum and SMN connections is crucial for better functional recovery.
- This method offers a more precise approach to forecasting patient recovery trajectories after stroke.
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