Imaging-Enhanced Prediction of Upper Limb Motor Function After Stroke Using Automated Segmentation and Cluster Analysis
Seungwoo Cha, Wi-Sun Ryu, Bokgi Hwang, Dae Yul Kim, Seung Hak Lee · 2026
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Description
Seungwoo Cha and co-authors used brain imaging to predict how well a stroke patient's arm will work, in a 2026 study. Early prediction helps therapists plan personal rehabilitation. The team studied two hundred and forty-two patients with a fresh stroke from a blocked brain artery, all of whom had brain scans and arm function tests. Software measured the damaged area and its overlap with movement paths automatically.
Adding the imaging measures clearly improved prediction of arm scores, and damage to the motor tract stood out as the key factor. A grouping analysis then found three kinds of patients: younger people with mild problems, older people with many other illnesses, and people with severe deficits and large strokes. Outcomes differed sharply across the groups. The authors say the profiles can guide personal care plans.
Catalog record
| CREATOR | Seungwoo Cha, Wi-Sun Ryu, Bokgi Hwang, Dae Yul Kim, Seung Hak Lee |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 31 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |