Motor evoked potential of upper-limbs is predictive of aphasia recovery. Issue 1 (2nd January 2019)

• Record Type: Journal Article
• Authors: Glize, Bertrand; Bigourdan, Antoine; Villain, Marie; Munsch, Fanny; Tourdias, Thomas; de Gabory, Isabelle; Dehail, Patrick; Dousset, Vincent; Guehl, Dominique; Joseph, Pierre-Alain; Laganaro, Marina; Sibon, Igor
• Is Part Of: Aphasiology. Volume 33:Issue 1(2019)
• Page Start: 105
• Page End: 120
• Publication Date: 2019-01-02
• Subjects: Aphasia recovery -- motor evoked potential -- stroke -- prognosis -- diffusion tensor imaging tractography; Aphasia -- Periodicals; Aphasia; 616.8552
• DOI: 10.1080/02687038.2018.1444137
• Languages: English
• ISSNs: 0268-7038

Abstract

ABSTRACT: Background : Recovery from aphasia impacts the quality of life in stroke patients but remains difficult to predict. Some neuroanatomical factors combined with anagraphical factors contribute to the prediction of longitudinal outcomes, but still fail to predict changes in severity of symptoms. Among the language features predicting recovery from aphasia, production scores such as repetition or phonology seem to be more relevant predictors than only severity. As motor cortex is strongly involved in language processes, both production and perception, the present study builds on the hypothesis that assessment of the anatomo-functional motor pathways could improve predictive models on top of factors based on neuroanatomy. Aim : In this prospective longitudinal study, we aimed to determine whether the integration of an electrophysiological measure of the motor network using Motor Evoked Potentials (MEPs) with an anatomical approach—diffusion-weighted MRI— in the acute phase of stroke can improve the prediction of recovery from post-stroke aphasia. Methods and Procedures : Fifteen aphasic patients were included in the post-stroke acute phase. Electrophysiological assessment exploring resting motor threshold ratio (rMTr) of the two upper-limbs and neuroanatomy exploration using MRI and diffusion tensor imaging were performed in the acute phase. Language impairment was assessed at the same stage and six months after the stroke. Multivariate regression analyses were carried out on aphasia severity score at M6, on recovery rates (change of severity) and on speech and language features as the dependent variables. Outcomes and Results : A first-level model, including only clinical variables (i.e., the initial severity) predicted severity at six months. When the rMTr of upper limbs was added in a second-level model, the predictive power significantly increased from 51% to 79%, as well as adding in a third-level model rMTr of upper limbs and the initial fibers number ratio (iFNr) of the corticospinal tracts (51% to 80%). With the changes in severity as the dependent variable, the same factors made a significant contribution and the predictive power of a second-level model increased from 23% to 50% to the same extent as in a third-level model (23% to 51%). A similar improvement when adding MEPs was noted for the prediction of articulatory agility and naming skills. Conclusions : Our results suggest that MEPs of upper limbs measured within 15days post-stroke are strong determinants of the prediction of longitudinal severity of post-stroke aphasia as well as of changes in symptoms and that the combination of electrophysiological and anatomical biomarkers improve this prediction.