Early detection of response to spinal cord injury (SCI) therapeutic intervention programs is vital, as it will enable early termination of intervention in non-responding patients, prevent unnecessary financial burden, and allow for early changes of the programs. In this project, we propose that resting state functional MRI (rsfMRI) can be used to detect early brain functional network changes that occur during intervention, and that the changes will be predictive of recovery in chronic SCI patients. The long-term goal of this study is to establish rsfMRI as a new imaging biomarker that is predictive of progress towards recovery in response to therapy. International Standard of Neurological Classification for Spinal Cord Injury (ISNCSCI) scoring system is the most widely used clinical classification system of SCI that describes neurological injury level and degree of functional preservation. It is also used to monitor the progress and response to interventions such as functional electrical stimulation (FES) therapy. However, monitoring responses using ISNSCI is challenging, because its ability to describe the degree of functional loss is limited. Therefore, there is a need in the field of SCI for a biomarker that is more sensitive to changes in function. We will recruit 2 groups of 24 chronic SCI patients. In one group, we will characterize the baseline time profile of rsfMRI outcome measures acquired during a 4-weeks passive cycling program, where movement is driven only by the cycle?s motor (no electric stimulation). RsfMRI data of the patients acquired at weeks 0, 2, and 4 will be used perform functional parcellation of the sensorimotor cortex using independent component analysis (ICA) and spectral clustering analysis (SCA) approaches. BNC will be calculated between pairs of sensory and motor brain parcels. Sensory and motor ISNCSCI scores will also be measured at weeks 0, 2, and 4. We will then test the hypothesis that we will observe stable baseline measures of sensory and motor cortex BNC and ISNCSCI scores of the patients during the 4-week passive cycling program, with minimal to no change in values. In the second group, we will characterize the time profile of the cortical reorganization in chronic SCI patients that occurs during the four-week FES cycling. Specifically, we predict that we will observe early functional network changes in the sensorimotor cortex of SCI patients (measured using BNC) at week 2 of the four-week FES cycling program, which will be predictive of changes in ISNSCI scores (neurological outcomes) at week 4. Finally, the longitudinal intra-subject reproducibility of the two parcellation methods will be investigated. If successful, the study will: 1) provide a new and effective clinical tool to study plastic cortical changes that occur after SCI, 2) provide a new non-invasive imaging biomarker that is predictive of progress towards recovery in response to therapy, and 3) extend our knowledge about the functional reorganization that takes place during and after therapeutic intervention.
Early detection of response to therapeutic intervention is vital, as it will enable early termination of intervention in non-responding patients, prevent unnecessary financial burden, and allow for early changes to the intervention program. Previous functional MRI (fMRI) studies have shown that changes in brain functional network in spinal cord injury (SCI) patients can occur after as little as one week of intervention. Resting state fMRI (rsfMRI) is a type of fMRI that does not require performance of explicit motor tasks, which makes the method especially suitable for SCI patient population. In this project, we propose that rsfMRI outcome measures can be used to detect early brain functional network changes that occur during intervention, and that the changes will be predictive of recovery in chronic SCI patients.
