Joyce L Chen, Timothy K Lam, Melanie C Baniña, Daniele Piscitelli, Mindy F Levin
{"title":"脑卒中后上肢运动障碍的神经影像学和运动学生物标志物。","authors":"Joyce L Chen, Timothy K Lam, Melanie C Baniña, Daniele Piscitelli, Mindy F Levin","doi":"10.1016/j.nicl.2025.103854","DOIUrl":null,"url":null,"abstract":"<p><p>Structural and functional biomarkers derived from magnetic resonance imaging explain some variance in post-stroke motor impairment. The understanding of the nature of impairment and the discrimination between true behavioural motor recovery/restitution and motor compensation may be improved by the addition of kinematic information. The aim of the study was to determine the influence of neuroimaging combined with kinematic biomarkers in explaining the variance in motor impairment of the upper limb. People living with late sub-acute to chronic stroke (n = 25) underwent the Fugl Meyer Assessment - Upper Limb (FMA-UL), magnetic resonance imaging, and completed a reaching task where upper limb and trunk kinematics were recorded. Regression analyses were performed to determine the amount of variability in FMA-UL explained by the following biomarkers: the amount of corticospinal tract impacted by the stroke lesion (CST involvement), interhemispheric and ipsilesional resting state connectivity, and the Trunk-based Index of Performance (IPt) that measures skilled reaching ability while accounting for trunk compensation. CST involvement, interhemispheric connectivity, and the IPt, together explained ∼49 % of the variance in the FMA-UL (F(3,21) = 8.694, p = 0.001, R<sup>2</sup><sub>adj</sub> = 0.49). The IPt explained an additional 14 % of the variance in the FMA-UL compared to CST involvement alone (p = 0.02). The IPt is a relevant kinematic biomarker of post-stroke upper limb motor impairment. Our findings suggest the importance of using multiple categories of biomarkers to better understand the level of post-stroke motor impairment.</p>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"48 ","pages":"103854"},"PeriodicalIF":3.6000,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12356466/pdf/","citationCount":"0","resultStr":"{\"title\":\"Neuroimaging and kinematic biomarkers of post-stroke upper limb motor impairment.\",\"authors\":\"Joyce L Chen, Timothy K Lam, Melanie C Baniña, Daniele Piscitelli, Mindy F Levin\",\"doi\":\"10.1016/j.nicl.2025.103854\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Structural and functional biomarkers derived from magnetic resonance imaging explain some variance in post-stroke motor impairment. The understanding of the nature of impairment and the discrimination between true behavioural motor recovery/restitution and motor compensation may be improved by the addition of kinematic information. The aim of the study was to determine the influence of neuroimaging combined with kinematic biomarkers in explaining the variance in motor impairment of the upper limb. People living with late sub-acute to chronic stroke (n = 25) underwent the Fugl Meyer Assessment - Upper Limb (FMA-UL), magnetic resonance imaging, and completed a reaching task where upper limb and trunk kinematics were recorded. Regression analyses were performed to determine the amount of variability in FMA-UL explained by the following biomarkers: the amount of corticospinal tract impacted by the stroke lesion (CST involvement), interhemispheric and ipsilesional resting state connectivity, and the Trunk-based Index of Performance (IPt) that measures skilled reaching ability while accounting for trunk compensation. CST involvement, interhemispheric connectivity, and the IPt, together explained ∼49 % of the variance in the FMA-UL (F(3,21) = 8.694, p = 0.001, R<sup>2</sup><sub>adj</sub> = 0.49). The IPt explained an additional 14 % of the variance in the FMA-UL compared to CST involvement alone (p = 0.02). The IPt is a relevant kinematic biomarker of post-stroke upper limb motor impairment. 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Neuroimaging and kinematic biomarkers of post-stroke upper limb motor impairment.
Structural and functional biomarkers derived from magnetic resonance imaging explain some variance in post-stroke motor impairment. The understanding of the nature of impairment and the discrimination between true behavioural motor recovery/restitution and motor compensation may be improved by the addition of kinematic information. The aim of the study was to determine the influence of neuroimaging combined with kinematic biomarkers in explaining the variance in motor impairment of the upper limb. People living with late sub-acute to chronic stroke (n = 25) underwent the Fugl Meyer Assessment - Upper Limb (FMA-UL), magnetic resonance imaging, and completed a reaching task where upper limb and trunk kinematics were recorded. Regression analyses were performed to determine the amount of variability in FMA-UL explained by the following biomarkers: the amount of corticospinal tract impacted by the stroke lesion (CST involvement), interhemispheric and ipsilesional resting state connectivity, and the Trunk-based Index of Performance (IPt) that measures skilled reaching ability while accounting for trunk compensation. CST involvement, interhemispheric connectivity, and the IPt, together explained ∼49 % of the variance in the FMA-UL (F(3,21) = 8.694, p = 0.001, R2adj = 0.49). The IPt explained an additional 14 % of the variance in the FMA-UL compared to CST involvement alone (p = 0.02). The IPt is a relevant kinematic biomarker of post-stroke upper limb motor impairment. Our findings suggest the importance of using multiple categories of biomarkers to better understand the level of post-stroke motor impairment.
期刊介绍:
NeuroImage: Clinical, a journal of diseases, disorders and syndromes involving the Nervous System, provides a vehicle for communicating important advances in the study of abnormal structure-function relationships of the human nervous system based on imaging.
The focus of NeuroImage: Clinical is on defining changes to the brain associated with primary neurologic and psychiatric diseases and disorders of the nervous system as well as behavioral syndromes and developmental conditions. The main criterion for judging papers is the extent of scientific advancement in the understanding of the pathophysiologic mechanisms of diseases and disorders, in identification of functional models that link clinical signs and symptoms with brain function and in the creation of image based tools applicable to a broad range of clinical needs including diagnosis, monitoring and tracking of illness, predicting therapeutic response and development of new treatments. Papers dealing with structure and function in animal models will also be considered if they reveal mechanisms that can be readily translated to human conditions.