Multimodal Assessment of the Motor System in Patients With Chronic Ischemic Stroke.


Journal

Stroke
ISSN: 1524-4628
Titre abrégé: Stroke
Pays: United States
ID NLM: 0235266

Informations de publication

Date de publication:
01 2021
Historique:
pubmed: 16 12 2020
medline: 20 4 2021
entrez: 15 12 2020
Statut: ppublish

Résumé

Despite continuing efforts in the multimodal assessment of the motor system after stroke, conclusive findings on the complementarity of functional and structural metrics of the ipsilesional corticospinal tract integrity and the role of the contralesional hemisphere are still lacking. This research aimed to find the best combination of motor system metrics, allowing the classification of patients into 3 predefined groups of upper limb motor recovery. We enrolled 35 chronic ischemic stroke patients (mean 47 [26-66] years old, 29 [6-58] months poststroke) with a single supratentorial lesion and unilateral upper extremity weakness. Patients were divided into 3 groups, depending on upper limb motor recovery: good, moderate, and bad. Nonparametric statistical tests and regression analysis were used to investigate the relationships among microstructural (fractional anisotropy (FA) ratio of the corticospinal tracts at the internal capsule (IC) level (classic method) and along the length of the tracts (Fréchet distance), and of the corpus callosum) and functional (motor evoked potentials [MEPs] for 2 hand muscles) motor system metrics. Stratification rules were also tested using a decision tree classifier. IC FA ratio in the IC and MEP absence were both equally discriminative of the bad motor outcome (96% accuracy). For the 3 recovery groups' classification, the best parameter combination was IC FA ratio and the Fréchet distance between the contralesional and ipsilesional corticospinal tract FA profiles (91% accuracy). No other metrics had any additional value for patients' classification. MEP presence differed for 2 investigated muscles. This study demonstrates that better separation between 3 motor recovery groups may be achieved when considering the similarity between corticospinal tract FA profiles along its length in addition to region of interest-based assessment and lesion load calculation. Additionally, IC FA ratio and MEP absence are equally important markers for poor recovery, while for MEP probing it may be important to investigate more than one hand muscle.

Sections du résumé

BACKGROUND AND PURPOSE
Despite continuing efforts in the multimodal assessment of the motor system after stroke, conclusive findings on the complementarity of functional and structural metrics of the ipsilesional corticospinal tract integrity and the role of the contralesional hemisphere are still lacking. This research aimed to find the best combination of motor system metrics, allowing the classification of patients into 3 predefined groups of upper limb motor recovery.
METHODS
We enrolled 35 chronic ischemic stroke patients (mean 47 [26-66] years old, 29 [6-58] months poststroke) with a single supratentorial lesion and unilateral upper extremity weakness. Patients were divided into 3 groups, depending on upper limb motor recovery: good, moderate, and bad. Nonparametric statistical tests and regression analysis were used to investigate the relationships among microstructural (fractional anisotropy (FA) ratio of the corticospinal tracts at the internal capsule (IC) level (classic method) and along the length of the tracts (Fréchet distance), and of the corpus callosum) and functional (motor evoked potentials [MEPs] for 2 hand muscles) motor system metrics. Stratification rules were also tested using a decision tree classifier.
RESULTS
IC FA ratio in the IC and MEP absence were both equally discriminative of the bad motor outcome (96% accuracy). For the 3 recovery groups' classification, the best parameter combination was IC FA ratio and the Fréchet distance between the contralesional and ipsilesional corticospinal tract FA profiles (91% accuracy). No other metrics had any additional value for patients' classification. MEP presence differed for 2 investigated muscles.
CONCLUSIONS
This study demonstrates that better separation between 3 motor recovery groups may be achieved when considering the similarity between corticospinal tract FA profiles along its length in addition to region of interest-based assessment and lesion load calculation. Additionally, IC FA ratio and MEP absence are equally important markers for poor recovery, while for MEP probing it may be important to investigate more than one hand muscle.

Identifiants

pubmed: 33317414
doi: 10.1161/STROKEAHA.119.028832
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

241-249

Commentaires et corrections

Type : CommentIn

Auteurs

Maria Nazarova (M)

Centre for Cognition and Decision making, ICN, HSE University, Moscow, Russia (M.N., A.L., P.N., V.N.).
FSBI «Federal center of brain and neurotechnologies» of the Federal Medical Biological Agency, Moscow, Russia (M.N.).

Sofya Kulikova (S)

HSE University, Perm, Russia (S.K., A.S.).

Michael A Piradov (MA)

Research Center of Neurology, Moscow, Russia (M.P., L.D., R.K.).

Alena S Limonova (AS)

Laboratory of Clinomics, National Medical Research Center for Therapy & Preventive Medicine, Moscow, Russia (A.L.).

Larisa A Dobrynina (LA)

Research Center of Neurology, Moscow, Russia (M.P., L.D., R.K.).

Rodion N Konovalov (RN)

Research Center of Neurology, Moscow, Russia (M.P., L.D., R.K.).

Pavel A Novikov (PA)

Centre for Cognition and Decision making, ICN, HSE University, Moscow, Russia (M.N., A.L., P.N., V.N.).

Bernhard Sehm (B)

Department of Neurology, Martin Luther University of Halle-Wittenberg, Germany (B.S.).
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (B.S., A.V., V.N.).

Arno Villringer (A)

Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (B.S., A.V., V.N.).
Clinic for Cognitive Neurology, University Hospital Leipzig, Germany (A.V.).

Anastasia Saltykova (A)

HSE University, Perm, Russia (S.K., A.S.).

Vadim V Nikulin (VV)

Centre for Cognition and Decision making, ICN, HSE University, Moscow, Russia (M.N., A.L., P.N., V.N.).
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (B.S., A.V., V.N.).

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