Spinal cord injury (SCI) is a devastating syndrome that produces dysfunction in motor and sensory systems, manifesting as chronic paralysis, sensory changes, and pain disorders. The multi-faceted and heterogeneous nature of SCI has made effective rehabilitative strategies challenging. Work over the last 40 years has aimed to overcome these obstacles by harnessing the intrinsic plasticity of the spinal cord to improve functional locomotor recovery. Intensive training after SCI facilitates lower extremity function and has shown promise as a tool for retraining the spinal cord by engaging innate locomotor circuitry in the lumbar cord. As new training paradigms evolve, the importance of appropriate afferent input has emerged as a requirement for adaptive plasticity. The integration of kinematic, sensory, and loading force information must be closely monitored and carefully manipulated to optimize training outcomes. Inappropriate peripheral input may produce lasting maladaptive sensory and motor effects, such as central pain and spasticity. Thus, it is important to closely consider the type of afferent input the injured spinal cord receives. Here we review preclinical and clinical input parameters fostering adaptive plasticity, as well as those producing maladaptive plasticity that may undermine neurorehabilitative efforts. We differentiate between passive (hindlimb unloading [HU], limb immobilization) and active (peripheral nociception) forms of aberrant input. Furthermore, we discuss the timing of initiating exposure to afferent input after SCI for promoting functional locomotor recovery. We conclude by presenting a candidate rapid synaptic mechanism for maladaptive plasticity after SCI, offering a pharmacological target for restoring the capacity for adaptive spinal plasticity in real time.

Spinal cord injury (SCI) is a multifaceted phenomenon associated with alterations in both motor function and sensory function. A majority of patients with SCI report sensory disturbances, including not only loss of sensation, but in many cases enhanced abnormal sensation, dysesthesia and pain. Development of therapeutics to treat these abnormal sensory changes require common measurement tools that can enable cross-species translation from animal models to human patients. We review the current literature on translational nociception/pain measurement in SCI and discuss areas for further development. Although a number of tools exist for measuring both segmental and affective sensory changes, we conclude that there is a pressing need for better, integrative measurement of nociception/pain outcomes across species to enhance precise therapeutic innovation for sensory dysfunction in SCI.

Purpose

To couple quantitative compositional MRI, gait analysis, and machine learning multidimensional data analysis to study osteoarthritis (OA). OA is a multifactorial disorder accompanied by biochemical and morphological changes in the articular cartilage, modulated by skeletal biomechanics and gait. While we can now acquire detailed information about the knee joint structure and function, we are not yet able to leverage the multifactorial factors for diagnosis and disease management of knee OA.

Materials and methods

We mapped 178 subjects in a multidimensional space integrating: demographic, clinical information, gait kinematics and kinetics, cartilage compositional T_1ρ and T₂ and R₂ -R_1ρ (1/T₂ -1/T_1ρ ) acquired at 3T and whole-organ magnetic resonance imaging score morphological grading. Topological data analysis (TDA) and Kolmogorov-Smirnov test were adopted for data integration, analysis, and hypothesis generation. Regression models were used for hypothesis testing.

Results

The results of the TDA showed a network composed of three main patient subpopulations, thus potentially identifying new phenotypes. T₂ and T_1ρ values (T₂ lateral femur P = 1.45*10^-8 , T_1ρ medial tibia P = 1.05*10^-5 ), the presence of femoral cartilage defects (P = 0.0013), lesions in the meniscus body (P = 0.0035), and race (P = 2.44*10^-4 ) were key markers in the subpopulation classification. Within one of the subpopulations we observed an association between the composite metric R₂ -R_1ρ and the longitudinal progression of cartilage lesions.

Conclusion

The analysis presented demonstrates some of the complex multitissue biochemical and biomechanical interactions that define joint degeneration and OA using a multidimensional approach, and potentially indicates that R₂ -R_1ρ may be an imaging biomarker for early OA.

Level of evidence

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:78-90.

Combination therapies targeting multiple recovery mechanisms have the potential for additive or synergistic effects, but experimental design and analyses of multimodal therapeutic trials are challenging. To address this problem, we developed a data-driven approach to integrate and analyze raw source data from separate pre-clinical studies and evaluated interactions between four treatments following traumatic brain injury. Histologic and behavioral outcomes were measured in 202 rats treated with combinations of an anti-inflammatory agent (minocycline), a neurotrophic agent (LM11A-31), and physical therapy consisting of assisted exercise with or without botulinum toxin-induced limb constraint. Data was curated and analyzed in a linked workflow involving non-linear principal component analysis followed by hypothesis testing with a linear mixed model. Results revealed significant benefits of the neurotrophic agent LM11A-31 on learning and memory outcomes after traumatic brain injury. In addition, modulations of LM11A-31 effects by co-administration of minocycline and by the type of physical therapy applied reached statistical significance. These results suggest a combinatorial effect of drug and physical therapy interventions that was not evident by univariate analysis. The study designs and analytic techniques applied here form a structured, unbiased, internally validated workflow that may be applied to other combinatorial studies, both in animals and humans.

Literature examining magnetic resonance imaging (MRI) in acute spinal cord injury (SCI) has focused on cervical SCI. Reproducible systems have been developed for MRI-based grading; however, it is unclear how they apply to thoracic SCI. Our hypothesis is that MRI measures will group as coherent multivariate principal component (PC) ensembles, and that distinct PCs and individual variables will show discriminant validity for predicting early impairment in thoracic SCI. We undertook a retrospective cohort study of 25 patients with acute thoracic SCI who underwent MRI on admission and had American Spinal Injury Association Impairment Scale (AIS) assessment at hospital discharge. Imaging variables of axial grade, sagittal grade, length of injury, thoracolumbar injury classification system (TLICS), maximum canal compromise (MCC), and maximum spinal cord compression (MSCC) were collected. We performed an analytical workflow to detect multivariate PC patterns followed by explicit hypothesis testing to predict AIS at discharge. All imaging variables loaded positively on PC1 (64.3% of variance), which was highly related to AIS at discharge. MCC, MSCC, and TLICS also loaded positively on PC2 (22.7% of variance), while variables concerning cord signal abnormality loaded negatively on PC2. PC2 was highly related to the patient undergoing surgical decompression. Variables of signal abnormality were all negatively correlated with AIS at discharge with the highest level of correlation for axial grade as assessed with the Brain and Spinal Injury Center (BASIC) score. A multiple variable model identified BASIC as the only statistically significant predictor of AIS at discharge, signifying that BASIC best captured the variance in AIS within our study population. Our study provides evidence of convergent validity, construct validity, and clinical predictive validity for the sampled MRI measures of SCI when applied in acute thoracic and thoracolumbar SCI.

A correction to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Study design

Retrospective analysis.

Objective

To assess the impact of mean arterial blood pressure (MAP) during surgical intervention for spinal cord injury (SCI) on motor recovery.

Setting

Level-one Trauma Hospital and Acute Rehabilitation Hospital in San Jose, CA, USA.

Methods

Twenty-five individuals with traumatic SCI who received surgical and acute rehabilitation care at a level-one trauma center were included in this study. The Surgical Information System captured intraoperative MAPs on a minute-by-minute basis and exposure was quantified at sequential thresholds from 50 to 104 mmHg. Change in International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) motor score was calculated based on physiatry evaluations at the earliest postoperative time and at discharge from acute rehabilitation. Linear regression models were used to estimate the rate of recovery across the entire MAP range.

Results

An exploratory analysis revealed that increased time within an intraoperative MAP range (70-94 mmHg) was associated with ISNCSCI motor score improvement. A significant regression equation was found for the MAP range 70-94 mmHg (F[1, 23] = 5.07, r² = 0.181, p = 0.034). ISNCSCI motor scores increased 0.039 for each minute of exposure to the MAP range 70-94 mmHg during the operative procedure; this represents a significant correlation between intraoperative time with MAP 70-94 and subsequent motor recovery. Blood pressure exposures above or below this range did not display a positive association with motor recovery.

Conclusions

Hypertension as well as hypotension during surgery may impact the trajectory of recovery in individuals with SCI, and there may be a direct relationship between intraoperative MAP and motor recovery.

The development of a non-human primate (NHP) model of spinal cord injury (SCI) based on mechanical and computational modeling is described. We scaled up from a rodent model to a larger primate model using a highly controllable, friction-free, electronically-driven actuator to generate unilateral C6-C7 spinal cord injuries. Graded contusion lesions with varying degrees of functional recovery, depending upon pre-set impact parameters, were produced in nine NHPs. Protocols and pre-operative magnetic resonance imaging (MRI) were used to optimize the predictability of outcomes by matching impact protocols to the size of each animal's spinal canal, cord, and cerebrospinal fluid space. Post-operative MRI confirmed lesion placement and provided information on lesion volume and spread for comparison with histological measures. We evaluated the relationships between impact parameters, lesion measures, and behavioral outcomes, and confirmed that these relationships were consistent with our previous studies in the rat. In addition to providing multiple univariate outcome measures, we also developed an integrated outcome metric describing the multivariate cervical SCI syndrome. Impacts at the higher ranges of peak force produced highly lateralized and enduring deficits in multiple measures of forelimb and hand function, while lower energy impacts produced early weakness followed by substantial recovery but enduring deficits in fine digital control (e.g., pincer grasp). This model provides a clinically relevant system in which to evaluate the safety and, potentially, the efficacy of candidate translational therapies.

Recent preclinical advances highlight the therapeutic potential of treatments aimed at boosting regeneration and plasticity of spinal circuitry damaged by spinal cord injury (SCI). With several promising candidates being considered for translation into clinical trials, the SCI community has called for a non-human primate model as a crucial validation step to test efficacy and validity of these therapies prior to human testing. The present paper reviews the previous and ongoing efforts of the California Spinal Cord Consortium (CSCC), a multidisciplinary team of experts from 5 University of California medical and research centers, to develop this crucial translational SCI model. We focus on the growing volumes of high resolution data collected by the CSCC, and our efforts to develop a biomedical informatics framework aimed at leveraging multidimensional data to monitor plasticity and repair targeting recovery of hand and arm function. Although the main focus of many researchers is the restoration of voluntary motor control, we also describe our ongoing efforts to add assessments of sensory function, including pain, vital signs during surgery, and recovery of bladder and bowel function. By pooling our multidimensional data resources and building a unified database infrastructure for this clinically relevant translational model of SCI, we are now in a unique position to test promising therapeutic strategies' efficacy on the entire syndrome of SCI. We review analyses highlighting the intersection between motor, sensory, autonomic and pathological contributions to the overall restoration of function. This article is part of a Special Issue entitled SI: Spinal cord injury.