MRI Biomarkers for Hand-Motor Outcome Prediction and Therapy Monitoring following Stroke

• Published in: Neural plasticity Vol. 2016; no. 2016; pp. 1 - 12
• Main Authors: Horn, U., Lotze, M., Grothe, M.
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01-01-2016; Hindawi Limited
• Subjects: Biomarkers; Female; Hand - physiology; Humans; Magnetic resonance imaging; Magnetic Resonance Imaging - trends; Male; Motor ability; Motor Cortex - diagnostic imaging; Motor Cortex - physiopathology; Motor Skills - physiology; Patients; Predictive Value of Tests; Psychomotor Performance - physiology; Recovery of Function - physiology; Review; Stroke; Stroke - diagnostic imaging; Stroke - physiopathology; Stroke - therapy; Treatment Outcome
• ISSN: 2090-5904; 1687-5443
• DOI: 10.1155/2016/9265621

Several biomarkers have been identified which enable a considerable prediction of hand-motor outcome after cerebral damage already in the subacute stage after stroke. We here review the value of MRI biomarkers in the evaluation of corticospinal integrity and functional recruitment of motor resources. Many of the functional imaging parameters are not feasible early after stroke or for patients with high impairment and low compliance. Whereas functional connectivity parameters have demonstrated varying results on their predictive value for hand-motor outcome, corticospinal integrity evaluation using structural imaging showed robust and high predictive power for patients with different levels of impairment. Although this is indicative of an overall higher value of structural imaging for prediction, we suggest that this variation be explained by structure and function relationships. To gain more insight into the recovering brain, not only one biomarker is needed. We rather argue for a combination of different measures in an algorithm to classify fine-graded subgroups of patients. Approaches to determining biomarkers have to take into account the established markers to provide further information on certain subgroups. Assessing the best therapy approaches for individual patients will become more feasible as these subgroups become specified in more detail. This procedure will help to considerably save resources and optimize neurorehabilitative therapy.