Toward individualized medicine in stroke—The TiMeS project: Protocol of longitudinal, multi-modal, multi-domain study in stroke

This I think is invalidly putting the cart before the horse. First you solve stroke recovery for all the common and similar damage diagnosis, then you work on tweaking that to individuals.  

1. Cure spasticity, that would solve major problems in motor recovery.

2. Recover all the cognitive decline, that would then get the survivor fully understanding the work required to recover.

3. Cure stroke fatigue, that would solve all the reps needed to get to recovery.

4. Understand EXACTLY  how neuroplasticity can be made repeatable on demand, that could be applied to huge portions of damage from stroke.

Toward individualized medicine in stroke—The TiMeS project: Protocol of longitudinal, multi-modal, multi-domain study in stroke

Lisa Fleury^1,2†, Philipp J. Koch^1,2,3†, Maximilian J. Wessel^1,2,4†, Christophe Bonvin⁵, Diego San Millan⁵, Christophe Constantin⁵, Philippe Vuadens⁶, Jan Adolphsen⁷, Andéol Cadic Melchior^1,2, Julia Brügger^1,2, Elena Beanato^1,2, Martino Ceroni^1,2, Pauline Menoud^1,2, Diego De Leon Rodriguez², Valérie Zufferey², Nathalie H. Meyer⁸, Philip Egger^1,2, Sylvain Harquel^1,2, Traian Popa^1,2, Estelle Raffin^1,2, Gabriel Girard^9,10,11, Jean-Philippe Thiran^9,10,11, Claude Vaney⁷, Vincent Alvarez⁵, Jean-Luc Turlan⁶, Andreas Mühl⁶, Bertrand Léger⁶, Takuya Morishita^1,2, Silvestro Micera^12,13, Olaf Blanke^8,14, Dimitri Van De Ville^9,15,16 and Friedhelm C. Hummel^1,2,17*

• ¹Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), EPFL, Campus Biotech, Geneva, Switzerland
• ²Defitech Chair of Clinical Neuroengineering, INX and BMI, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
• ³Department of Neurology, University of Lübeck, Lübeck, Germany
• ⁴Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
• ⁵Hôpital du Valais, Sion, Switzerland
• ⁶Clinique Romande de Réadaptation, Sion, Switzerland
• ⁷Berner Klinik, Crans-Montana, Switzerland
• ⁸Laboratory of Cognitive Neuroscience, INX and BMI, EPFL, Campus Biotech, Geneva, Switzerland
• ⁹CIBM Center for Biomedical Imaging, Lausanne, Switzerland
• ¹⁰Department of Radiology, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
• ¹¹Signal Processing Laboratory (LTS5), EPFL, Lausanne, Switzerland
• ¹²The Biorobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
• ¹³Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, EPFL, Lausanne, Switzerland
• ¹⁴Department of Clinical Neurosciences, University of Geneva (UNIGE), Geneva, Switzerland
• ¹⁵Medical Image Processing Lab, Center for Neuroprosthetics, Institute of Bioengineering, EPFL, Lausanne, Switzerland
• ¹⁶Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland
• ¹⁷Clinical Neuroscience, Geneva University Hospital, Geneva, Switzerland

Despite recent improvements, complete motor recovery occurs in <15% of stroke patients. To improve the therapeutic outcomes, there is a strong need to tailor treatments to each individual patient. However, there is a lack of knowledge concerning the precise neuronal mechanisms underlying the degree and course of motor recovery and its individual differences, especially in the view of brain network properties despite the fact that it became more and more clear that stroke is a network disorder. The TiMeS project is a longitudinal exploratory study aiming at characterizing stroke phenotypes of a large, representative stroke cohort through an extensive, multi-modal and multi-domain evaluation. The ultimate goal of the study is to identify prognostic biomarkers allowing to predict the individual degree and course of motor recovery and its underlying neuronal mechanisms paving the way for novel interventions and treatment stratification for the individual patients. A total of up to 100 patients will be assessed at 4 timepoints over the first year after the stroke: during the first (T1) and third (T2) week, then three (T3) and twelve (T4) months after stroke onset. To assess underlying mechanisms of recovery with a focus on network analyses and brain connectivity, we will apply synergistic state-of-the-art systems neuroscience methods including functional, diffusion, and structural magnetic resonance imaging (MRI), and electrophysiological evaluation based on transcranial magnetic stimulation (TMS) coupled with electroencephalography (EEG) and electromyography (EMG). In addition, an extensive, multi-domain neuropsychological evaluation will be performed at each timepoint, covering all sensorimotor and cognitive domains. This project will significantly add to the understanding of underlying mechanisms of motor recovery with a strong focus on the interactions between the motor and other cognitive domains and multimodal network analyses. The population-based, multi-dimensional dataset will serve as a basis to develop biomarkers to predict outcome and promote personalized stratification toward individually tailored treatment concepts using neuro-technologies, thus paving the way toward personalized precision medicine approaches in stroke rehabilitation.

Introduction and rationale

With 80 million survivors in 2016, stroke is the second most common cause of acquired disability in the world (1, 2). This number is still increasing due to the population growth and aging (3). Better acute stroke management results in an improved stroke survival, but implies a higher prevalence of chronic stroke (2). Yet, complete motor recovery still occurs in <15% of patients (4). Moreover, although motor deficits are the most debilitating and investigated (5–7), patients also show consistent long-lasting cognitive deficits (8, 9), with a relevant proportion of patients having multiple domains affected. These long-term impairing behavioral deficits have a strong impact on patients' reintegration, on patients and their relatives' daily life, but also on socioeconomics and health care systems (10, 11). Therefore, the call for effective strategies of neurorehabilitation in order to maximize the rate of recovery is recognized as a priority to substantially reduce the burden of stroke survivors (2, 12). However, the heterogeneity in stroke outcome and in individual recovery potential is an important challenge to address, in order to provide optimal rehabilitative therapies. A crucial aspect to take up this challenge is to deepen our understanding of individual courses of recovery and the underlying neuronal mechanisms through the identification of associated biomarkers (13).

On the behavioral level, stroke is known to yield multiple deficits. The most reported and debilitating ones are the motor impairments, present in 50–80% of stroke survivors (7). In particular, damages to the upper extremity function are common and significantly impact the patients' capacity to retrieve independence, as well as to reintegrate to professional life (14, 15). Besides motor deficits, cognitive impairment is common in stroke survivors although initially less obvious: half of stroke survivors report difficulties in at least one cognitive domain, but this area is much less studied than the motor domain (8, 16). Cognitive impairment could be found in multiple domains most frequently in, e.g., executive functions, attentional functions or memory. Such deficits are significantly persistent after one to several years after the stroke (8, 17). Cognitive deficits also represent an obstacle for patients to go back into a normal daily life (10, 18, 19). Furthermore, these dysfunctions might strongly impact, slow or even prevent proper motor recovery and response to treatment (20). For example, it is known that executive functions, such as information processing and motor planning are essential in the processes of motor (re)learning (21), which is crucial in motor rehabilitation following stroke. However, despite few investigations of the relationships between these domains [e.g., 17, 22], research mainly focused so far on deficits in only one domain, e.g., motor (22), language (23) or attention (24) and neglected largely the interaction between them. Thus, there is a strong lack of knowledge about how deficits in different domains depend on and influence each other in regard of impairment, residual functions and the process of regaining lost functions after a stroke.

Recovery is often incomplete among stroke survivors, and the potential of restoring lost functions is crucially highly heterogeneous between patients (25, 26). For example, spontaneous natural recovery in motor domain occurs in roughly 2/3 of patients (13) who recover about ~70% in average of their maximum recovery potential given their initial impairment (27). In contrast, roughly 1/3 of patients presents altered or insufficient intrinsic plasticity after stroke leading to a poor natural recovery (13). Such heterogeneity has also been reported in other cognitive deficits e.g., neglect and aphasia (28). In addition, stroke survivors act highly heterogeneous in the view of the response toward specific treatment strategies, resulting in the distinction between responders and non-responders (29–31). For instance, patients with cortical lesions specifically demonstrated low responsiveness to repetitive Transcranial Magnetic Stimulation (rTMS) protocols (32, 33). Therefore, a key challenging aspect for enhancing neuro-rehabilitation efficacy might be to shed light on the heterogeneity of stroke patients and leverage this information to determine and predict the degree of impairment and potential for individual functional recovery (33, 34). This heterogeneity in stroke ranges from brain reorganization to behavioral outcomes and needs to be accounted for when planning rehabilitation strategies (31, 34).

The identification of specific individual patterns of recovery through a multi-domain perspective during the first weeks/months post-stroke, and crucially the uncovering of the underlying brain reorganization mechanisms would be a massive step toward the optimization of treatment strategies for each patient. However, there is a lack of understanding concerning the detailed neuronal mechanisms following a stroke lesion and during the course of recovery. Accumulating evidence suggests that stroke is not a focal disorder, but a brain network disorder (35, 36). In addition to local brain tissue damage, stroke also impacts the functioning of connected areas (close or remote from the lesion) as a result of alterations in brain networks (37). In addition, functional reorganization associated with recovery is also not restricted to a focal area. For instance, cortical plasticity associated with motor recovery is not restricted to the primary motor cortex (M1), but rather embraces the complete motor network, including primary and secondary motor cortical areas in both hemispheres, subcortical areas like the basal ganglia and the cerebellum (34, 37, 38). Factors such as lesion size and location [e.g., (39, 40)], as well as structural and functional prerequisites and dynamics (41) might relevantly influence recovery-associated plasticity processes in the brain leading to heterogeneous, widespread and time-dependent changes of brain reorganization and connectivity between patients. To improve rehabilitative strategies, it is therefore crucial to take this heterogeneity into account and understand how it relates to the pattern of network reorganization and the range of behavioral outcomes following a stroke.

On the basis of this reasoning, there is a strong need for an exact phenotyping of patients that would consider stroke heterogeneity in order to predict outcome and course of recovery and to further improve stroke recovery and treatment outcomes. Such challenge requires to gain a detailed and fundamental knowledge about the precise neuronal mechanisms associated with behavioral recovery, with a particular emphasis on brain networks changes. In addition, is essential to investigate the different domains impacted by the stroke instead of focusing on one behavioral outcome. As network and behavioral alterations following stroke are dynamic and not linear, a longitudinal investigation is of great importance. Such phenotyping will allow to distinguish distinct profiles of patients with associated dynamics of brain reorganization over the course of recovery. Enhancing the fundamental knowledge of stroke diversity through a multimodal and multidomain approach would serve as a basis to pave the way for personalized precision medicine in the field of stroke recovery to achieve maximal treatment effects.

To take up this challenge, the TiMeS project aims at characterizing in details phenotypes of stroke patients allowing to determine the individual course and degree of recovery following stroke and to identify relevant biomarkers associated with recovery. To that purpose, the goal is to collect a large multidimensional dataset that would be representative for the stroke population. Measurements will come from synergistic state-of-the-art systems neuroscience methods including magnetic resonance imaging (MRI), transcranial magnetic stimulation (TMS) coupled with electroencephalography (EEG), in a longitudinal assessment from acute to chronic stage during the first year after the stroke. As stroke is not a focal disorder, subsequent analyses will focus on networks properties within the whole brain and their changes over time, in combination with stroke behavioral outcomes with a focus on motor domain and further investigations of other neurocognitive domains. To provide detailed knowledge about the behavioral patterns and relationships between domains, the procedure will contain an extensive evaluation of behavioral outcomes in multiple domains, including a multi-domain cognitive assessment. The multidimensional dataset acquired through this research will enable to assess for the first time the complex interactions of structural and functional brain connectivity parameters within certain domain-specific networks as well as within the whole brain, and to associate them with stroke behavioral outcomes and functional recovery.