Takuya Morishita, Elena Beanato, Philipp J Koch, Gabriel Girard, Philip Egger, Jean-Philippe Thiran, Giacomo Koch, Giorgia Giulia Evangelista, Jung-Soo Lee, Chang-hyun Park, Adrian G. Guggisberg, Yun-Hee Kim, Friedhelm C. Hummel, Maximilian J. Wessel, Charlotte Rosso, Centre d'Etudes Lasers Intenses et Applications (CELIA), Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Bordeaux (UB), Center for Biomedical Imaging [Lausanne] (CIBM), Ecole Polytechnique Fédérale de Lausanne (EPFL), Department of Earth Sciences [Swiss Federal Institute of Technology - ETH Zürich] (D-ERDW), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Samsung Medical Center Sungkyunkwan University School of Medicine, Institute Division of Hematology/Oncology, Clinical and Behavioral Neurology - Neuroscienze e riabilitazione, IRCCS Fondazione Santa Lucia [Roma], Geneva University Hospitals and Geneva University, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université de Bordeaux (UB)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Gestionnaire, HAL Sorbonne Université 5
Stroke patients vary considerably in terms of outcomes: some patients present ‘natural’ recovery proportional to their initial impairment (fitters), while others do not (non-fitters). Thus, a key challenge in stroke rehabilitation is to identify individual recovery potential to make personalized decisions for neuro-rehabilitation, obviating the ‘one-size-fits-all’ approach. This goal requires (i) the prediction of individual courses of recovery in the acute stage; and (ii) an understanding of underlying neuronal network mechanisms. ‘Natural’ recovery is especially variable in severely impaired patients, underscoring the special clinical importance of prediction for this subgroup. Fractional anisotropy connectomes based on individual tractography of 92 patients were analysed 2 weeks after stroke (TA) and their changes to 3 months after stroke (TC − TA). Motor impairment was assessed using the Fugl-Meyer Upper Extremity (FMUE) scale. Support vector machine classifiers were trained to separate patients with natural recovery from patients without natural recovery based on their whole-brain structural connectomes and to define their respective underlying network patterns, focusing on severely impaired patients (FMUE, Koch et al. apply computational approaches to the structural whole brain connectome in stroke to identify (i) features that predict in the acute phase whether individual patients, especially those with severe impairments, will show natural recovery; and (ii) the distributed networks relevant to such recovery.