Identification of New Biomarkers for Determining Risk of Lower Extremity Fracture during Exoskeleton-assisted Ambulation: Developing a Personal Rehabilitation Approach to Optimize Function after SCI

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Persons with acute SCI have rapid and progressive sublesional bone loss, with up to 73% bone at the epiphyses resorbed within the first few years after injury, placing them at high risk of fragility fractures and post- fracture complications. It is estimated that 70-76% of persons with spinal cord injury (SCI) will sustain a low- impact, or pathologic, fracture during their lifetime. Over 80% of fragility fractures occur in the lower extremities, with the most common fracture site being the knee region (e.g., distal femur and proximal tibia). Pathological fractures and post-fracture complications lead to patient morbidity and substantial cost. Robotic exoskeletons will become a viable option for routine mobility for people with SCI. The Department of Veterans Affairs has already committed to providing an exoskeleton to every eligible Veteran with SCI who wants one, and it is only a matter of time before private insurance companies include robotic exoskeletons for ambulation as a component of standard care, likely accelerating the general popularity of such devices. The question that may be raised is what is the optimal clinical approach to accurately predict the risk of fracture in persons with SCI prior to prescribing an exoskeletal-assisted walking (EAW) device? Although substantial improvements in body composition, metabolism, psychology, and overall quality of life have been observed with EAW use, exoskeletons place an already vulnerable SCI population at an even greater risk of fracture. Fractures in persons with SCI during EAW have been reported, with incidence ranging from 7.1% to 10.0%. Thus, it is plausible to speculate that if less stringent criteria are employed for the clinical prescription of exoskeleton devices when their use becomes more widespread that the incidence of fracture will be higher. The ability to predict which persons with SCI are at highest risk for fracture during EAW will allow appropriate and preemptive approaches to minimize the occurrence of fractures and to maximize participant eligibility. Building on prior work, the proposed study will provide a scientific rationale for evidence-based thresholds for prescribing EAW in Veterans. The proposed study will develop new evidence-based biomarkers to identify persons with SCI at highest risk of long-bone and/or calcaneus fractures when participating in upright rehabilitation activities. The ability to predict which persons with SCI are at highest risk for fracture during EAW will allow evidence-based approaches to minimize fractures and associated morbidity, as well as prevent avoidable medical costs. The Aims of this work are: (1) to determine biomarkers of bone health in persons with SCI from subject- specific finite element (FE) models from a wide range of bone densities at the hip, knee, and calcaneus; (2) to determine the forces at the hip, knee, and ankle joints of persons with SCI during exoskeleton-assisted sit-to- stand and stand-to-sit; and (3) to determine the forces at the hip, knee, and ankle joints of persons with SCI during EAW. Our partnerships with ReWalk Robotics, Parker Hannifin, and Ekso Bionics will provide the investigators with access to proprietary motor torque data, enabling us to build accurate musculoskeletal models of human-robot interaction. Forty-five (45) participants with SCI and 10 able-bodied (AB) controls will be recruited for dual x-ray absorptiometry (DXA), peripheral quantitative computed tomography (pQCT), and computed tomography (CT) that will be performed at the James J. Peters Veterans Affairs Medical Center (JJP VAMC). Training in the devices will be performed at the JJP VAMC. The computational models and FE-based biomarkers will be developed, and the motion capture analyses of exoskeletal maneuvers, will be performed at the New Jersey Institute of Technology. While in the each of the three exoskeletal devices (ReWalk, Ekso, and Indego), the forces at the hip, knee, and ankle joints will be quantified in conjunction with motion analysis during sit-to- stand maneuvers (in 19 SCI and 7 AB controls) and during EAW (In 10 SCI and 4 AB controls). Subject-specific FE models with hip, knee, and ankle joint forces will be developed to quantify mechanical stress/strain during EAW and correlated to FE-based biomarkers. Novel insights into human-robot interaction should be obtained.