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Responding or not responding to training; prediction of balance rehabilitation outcome from structural and functional brain networks in Cerebral Palsy.

Periodic Reporting for period 1 - CP-RehOP (Responding or not responding to training; prediction of balance rehabilitation outcome from structural and functional brain networks in Cerebral Palsy.)

Reporting period: 2016-03-01 to 2018-02-28

When an injury occurs to the developing brain, as in Cerebral Palsy (CP), these children typically experience sensorimotor disorders such as muscle weakness, and abnormal muscle activity. Poor balance control is a primary deficit in CP, which has a large impact on a child’s daily life, since it is crucial for independent mobility and greatly affects the risk of falls. CP is the most common developmental cause of physical disability in the world, with a prevalence of 2-3 in 1000 live births. To improve their quality of life, adequate treatment is essential. However, studies investigating the effectiveness of balance rehabilitation in CP have revealed mixed results. This is due to two reasons. First, due to the various clinical scales and experimental measures available, each measuring different components of balance, it is very complex to diagnose balance control in CP. Second, it is currently unknown which are the underlying neural causes of poor balance control in CP.
Since the success of well-targeted treatment depends on this basic knowledge, a novel experiment was performed that provides fundamental insights in both areas. The current project, therefore, entailed a virtual reality training paradigm to train balance in children with CP. Balance is tested comprehensively in these children, before and after training, using both clinical scales as biomechanical measures. Additionally, brain imaging scans have been performed before and after training.
Therefore, the objectives of the current project were;
1. Determine the best practice diagnostic tool for balance control in Cerebral Palsy.
2. Define the functional and structural brain networks involved in balance control in Cerebral Palsy.
3. Identify the underlying neural causes of responsiveness, and the prediction of individual responsiveness based on medical brain images.
The balance training comprises exercises on the latest serious gaming product; X-box One Kinect (Microsoft). This system is used to train balance with motivational games. The user’s body (rather than a remote held in one hand) is the controller with real-time feedback optimized for children. In the CP-RehOP project the children underwent a 6-week training program (5x/week, 30min/session) – data collection ongoing. Kinect games with a focus on balancing movements are be used (Kinect Sports Rivals; soccer, tennis, bowling). In these games, participants make movements that challenge their balance in response to requirements for the game (e.g. stand on one leg and swing the other leg to kick the ball for soccer). Kinect results are also automatically saved to the participant’s account, and are used to determine adherence. From the clinical and biomechanical measures of balance, the effectiveness of the VR training is assessed. Additionally, the sensitivity of the different measures of balance to training is examined, which further provides insightful information in the determination of the best diagnostic tool for impaired balance control in CP. The first results of this training paradigm are published in Meyns et al. 2017 (10.1016/j.gaitpost.2017.06.390).

The first aim of the CP-RehOP project was to determine the best diagnostic tool for imbalance in CP. Therefore, we have assessed both clinical and biomechanical measures in children with CP – data collection ongoing. Often used clinical scales were assessed including the Pediatric Balance Scale, ‘balance’ and ‘running speed and agility’ subtest of Bruininks-Oseretsky Test of Motor Proficiency, and 3) Trunk Control Measurement Scale. Additionally, biomechanical measures have been assessed while walking on the GRAIL-system (Motek, Amsterdam), which consists of an instrumented dual-belt treadmill, with motion-capture and synchronized VR. From these measurements, biomechanical measures of balance during perturbed and unperturbed walking were extracted, including spatiotemporal gait parameters of the legs (e.g. step width, step time variability) and kinematics of the arms (as these are related to gait instability in CP), Margins of Stability, Gait Sensitivity Norm, and Foot Placement Estimator. Additionally, on the GRAIL the Sensory Organization Test was evaluated to assess the individual’s ability to use visual, proprioceptive and vestibular cues to maintain postural stability in stance, using posturography. As such, this project can for the first time assess the relationship between clinical tests and experimental balance measures in CP, thus, provide an answer to how to diagnose balance control in this population.

To investigate the second and third aim, diffusion tensor imaging and resting state functional magnetic resonance imaging scans were acquired in the same group of children with CP – data collection ongoing. Given the wide range of affected brain areas in CP, a whole-brain and graph-theoretical approach is used to determine specific neural biomarkers of impaired balance control. From the neural biomarkers identified in these neuroimaging scans, underlying neural causes of non-responsiveness to balance training can be identified for the first time in CP. These results provide important new insights into the possible reason of the inconsistent results concerning the efficacy of balance training paradigms in CP. Additionally, the combination of behavioral and neurological assessments allows for the prediction of individual responsiveness of a patient based on medical brain images.
Finally, literature suggests that improvements after VR training observed in CP are associated to changes in the reorganization of neural networks. However, this has not been investigated for balance in CP. To the best of our knowledge, in CP only two pilot studies have investigated functional neuroplastic changes after training. These two pilots investigated the adaptations i
This project is the first initiative to provide the proof-of-principle whether magnetic resonance imaging connectivity indices can predict rehabilitation outcome in children with CP. Additionally, I have taken the first steps in the identification of (1) relevant neural biomarkers of impaired balance control and (2) the best diagnostic tools to determine impaired balance control, that go beyond traditional clinical assessments in CP.