Transforming Research and Clinical Knowledge in Spinal Cord Injury (TRACK-SCI): an overview of initial enrollment and demographics

Hydrogel-based therapeutic strategies for spinal cord injury repair: Recent advances and future prospects

Spinal cord injury (SCI) is a debilitating condition that can result in significant functional impairment and loss of quality of life. There is a growing interest in developing new therapies for SCI, and hydrogel-based multimodal therapeutic strategies have emerged as a promising approach. They offer several advantages for SCI repair, including biocompatibility, tunable mechanical properties, low immunogenicity, and the ability to deliver therapeutic agents. This article provides an overview of the recent advances in hydrogel-based therapy strategies for SCI repair, particularly within the past three years. We summarize the SCI hydrogels with varied characteristics such as phase-change hydrogels, self-healing hydrogel, oriented fibers hydrogel, and self-assembled microspheres hydrogel, as well as different functional hydrogels such as conductive hydrogels, stimuli-responsive hydrogels, adhesive hydrogel, antioxidant hydrogel, sustained-release hydrogel, etc. The composition, preparation, and therapeutic effect of these hydrogels are briefly discussed and comprehensively evaluated. In the end, the future development of hydrogels in SCI repair is prospected to inspire more researchers to invest in this promising field.

Protocol for the Chinese Real-World Evidence for Acute Spinal Cord Injury (ChiRES) study: a prospective, observational, multicentre cohort study of acute spinal cord injury

INTRODUCTION

Spinal cord injury (SCI) is a catastrophic event with devastating physical, social and occupational consequences for patients and their families. The number of patients with acute SCI in China continues to grow rapidly, but there have been no large prospective cohort studies of patients with acute SCI. This proposed study aims to establish a multicentre, extensive sample cohort of clinical data and biological samples of patients in China, which would aid the systematisation and standardisation of clinical research and treatment of acute SCI, thus reducing the heavy burden of acute SCI on patients and society.

METHODS AND ANALYSIS

The Chinese Real-World Evidence for Acute Spinal Cord Injury (ChiRES) study is an observational, multicentre cohort study of patients with acute SCI admitted to the Qilu Hospital of Shandong University and other participating centres with prospective collection of their clinical data and biological samples. We aim to recruit 2097 patients in this study. Demographics, disease history, emergency intervention information, motor and sensory examinations, surgical information, medication information and rehabilitation evaluation will be recorded. This will facilitate the development of a prediction model for complications and prognosis of patients with acute SCI and an evaluation of the current management of acute SCI. Among these variables, detailed information on surgical treatment will also be used to assess procedures for acute SCI treatment. Outcome measurements, including the International Standard for Neurological Classification of Spinal Cord Injury examinations, the occurrence of complications and death, will be performed repeatedly during follow-up. We will analyse imaging data and blood samples to develop SCI imaging markers and biomarkers.

ETHICS AND DISSEMINATION

This study protocol has been approved by the Medical Ethics Committee of the Qilu Hospital of Shandong University and all other participating centres. The findings will be disseminated in peer-reviewed journals and academic conferences.

The use of deep learning in medical imaging to improve spine care: A scoping review of current literature and clinical applications

Background

Artificial intelligence is a revolutionary technology that promises to assist clinicians in improving patient care. In radiology, deep learning (DL) is widely used in clinical decision aids due to its ability to analyze complex patterns and images. It allows for rapid, enhanced data, and imaging analysis, from diagnosis to outcome prediction. The purpose of this study was to evaluate the current literature and clinical utilization of DL in spine imaging.

Methods

This study is a scoping review and utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to review the scientific literature from 2012 to 2021. A search in PubMed, Web of Science, Embased, and IEEE Xplore databases with syntax specific for DL and medical imaging in spine care applications was conducted to collect all original publications on the subject. Specific data was extracted from the available literature, including algorithm application, algorithms tested, database type and size, algorithm training method, and outcome of interest.

Results

A total of 365 studies (total sample of 232,394 patients) were included and grouped into 4 general applications: diagnostic tools, clinical decision support tools, automated clinical/instrumentation assessment, and clinical outcome prediction. Notable disparities exist in the selected algorithms and the training across multiple disparate databases. The most frequently used algorithms were U-Net and ResNet. A DL model was developed and validated in 92% of included studies, while a pre-existing DL model was investigated in 8%. Of all developed models, only 15% of them have been externally validated.

Conclusions

Based on this scoping review, DL in spine imaging is used in a broad range of clinical applications, particularly for diagnosing spinal conditions. There is a wide variety of DL algorithms, database characteristics, and training methods. Future studies should focus on external validation of existing models before bringing them into clinical use.

Fighting for recovery on multiple fronts: The past, present, and future of clinical trials for spinal cord injury

Through many decades of preclinical research, great progress has been achieved in understanding the complex nature of spinal cord injury (SCI). Preclinical research efforts have guided and shaped clinical trials, which are growing in number by the year. Currently, 1,149 clinical trials focused on improving outcomes after SCI are registered in the U.S. National Library of Medicine at ClinicalTrials.gov. We conducted a systematic analysis of these SCI clinical trials, using publicly accessible data downloaded from ClinicalTrials.gov. After extracting all available data for these trials, we categorized each trial according to the types of interventions being tested and the types of outcomes assessed. We then evaluated clinical trial characteristics, both globally and by year, in order to understand the areas of growth and change over time. With regard to clinical trial attributes, we found that most trials have low enrollment, only test single interventions, and have limited numbers of primary outcomes. Some gaps in reporting are apparent; for instance, over 75% of clinical trials with "Completed" status do not have results posted, and the Phase of some trials is incorrectly classified as "Not applicable" despite testing a drug or biological compound. When analyzing trials based on types of interventions assessed, we identified the largest representation in trials testing rehab/training/exercise, neuromodulation, and behavioral modifications. Most highly represented primary outcomes include motor function of the upper and lower extremities, safety, and pain. The most highly represented secondary outcomes include quality of life and pain. Over the past 15 years, we identified increased representation of neuromodulation and rehabilitation trials, and decreased representation of drug trials. Overall, the number of new clinical trials initiated each year continues to grow, signifying a hopeful future for the clinical treatment of SCI. Together, our work provides a comprehensive glimpse into the past, present, and future of SCI clinical trials, and suggests areas for improvement in clinical trial reporting.

Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome

Artificial intelligence and machine learning (AI/ML) is becoming increasingly more accessible to biomedical researchers with significant potential to transform biomedicine through optimization of highly-accurate predictive models and enabling better understanding of disease biology. Automated machine learning (AutoML) in particular is positioned to democratize artificial intelligence (AI) by reducing the amount of human input and ML expertise needed. However, successful translation of AI/ML in biomedicine requires moving beyond optimizing only for prediction accuracy and towards establishing reproducible clinical and biological inferences. This is especially challenging for clinical studies on rare disorders where the smaller patient cohorts and corresponding sample size is an obstacle for reproducible modeling results. Here, we present a model-agnostic framework to reinforce AutoML using strategies and tools of explainable and reproducible AI, including novel metrics to assess model reproducibility. The framework enables clinicians to interpret AutoML-generated models for clinical and biological verifiability and consequently integrate domain expertise during model development. We applied the framework towards spinal cord injury prognostication to optimize the intraoperative hemodynamic range during injury-related surgery and additionally identified a strong detrimental relationship between intraoperative hypertension and patient outcome. Furthermore, our analysis captured how evolving clinical practices such as faster time-to-surgery and blood pressure management affect clinical model development. Altogether, we illustrate how expert-augmented AutoML improves inferential reproducibility for biomedical discovery and can ultimately build trust in AI processes towards effective clinical integration.

Decision tree–based machine learning analysis of intraoperative vasopressor use to optimize neurological improvement in acute spinal cord injury

OBJECTIVE

Previous work has shown that maintaining mean arterial pressures (MAPs) between 76 and 104 mm Hg intraoperatively is associated with improved neurological function at discharge in patients with acute spinal cord injury (SCI). However, whether temporary fluctuations in MAPs outside of this range can be tolerated without impairment of recovery is unknown. This retrospective study builds on previous work by implementing machine learning to derive clinically actionable thresholds for intraoperative MAP management guided by neurological outcomes.

METHODS

Seventy-four surgically treated patients were retrospectively analyzed as part of a longitudinal study assessing outcomes following SCI. Each patient underwent intraoperative hemodynamic monitoring with recordings at 5-minute intervals for a cumulative 28,594 minutes, resulting in 5718 unique data points for each parameter. The type of vasopressor used, dose, drug-related complications, average intraoperative MAP, and time spent in an extreme MAP range (< 76 mm Hg or > 104 mm Hg) were collected. Outcomes were evaluated by measuring the change in American Spinal Injury Association Impairment Scale (AIS) grade over the course of acute hospitalization. Features most predictive of an improvement in AIS grade were determined statistically by generating random forests with 10,000 iterations. Recursive partitioning was used to establish clinically intuitive thresholds for the top features.

RESULTS

At discharge, a significant improvement in AIS grade was noted by an average of 0.71 levels (p = 0.002). The hemodynamic parameters most important in predicting improvement were the amount of time intraoperative MAPs were in extreme ranges and the average intraoperative MAP. Patients with average intraoperative MAPs between 80 and 96 mm Hg throughout surgery had improved AIS grades at discharge. All patients with average intraoperative MAP > 96.3 mm Hg had no improvement. A threshold of 93 minutes spent in an extreme MAP range was identified after which the chance of neurological improvement significantly declined. Finally, the use of dopamine as compared to norepinephrine was associated with higher rates of significant cardiovascular complications (50% vs 25%, p < 0.001).

CONCLUSIONS

An average intraoperative MAP value between 80 and 96 mm Hg was associated with improved outcome, corroborating previous results and supporting the clinical verifiability of the model. Additionally, an accumulated time of 93 minutes or longer outside of the MAP range of 76–104 mm Hg is associated with worse neurological function at discharge among patients undergoing emergency surgical intervention for acute SCI.

Appendicular fracture and polytrauma correlate with outcome of spinal cord injury (SCI): A TRACK-SCI study

Spinal cord injuries (SCIs) frequently occur in combination with other major organ injuries, such as traumatic brain injury (TBI) and injuries to the chest, abdomen, and musculoskeletal system (e.g., extremity, pelvic, and spine fractures). However, the effects of appendicular fractures on SCI recovery are poorly understood. We investigated whether the presence of SCI-concurrent appendicular fractures is predictive of a less robust SCI recovery. Patients enrolled in the Transforming Research And Clinical Knowledge in SCI (TRACK-SCI) prospective cohort study were identified and included in this secondary analysis study. Inclusion criteria resulted in 147 patients consisting of 120 isolated SCIs and 27 with concomitant appendicular fracture. The primary outcome was ASIA Impairment Scale (AIS) neurological grades at hospital discharge. Secondary outcomes included hospital length of stay, ICU length of stay, and AIS grade improvement during hospitalization. Multivariable binomial logistic regression analyses assessed whether SCI-concomitant appendicular fractures associate with SCI function and secondary outcomes. These analyses were adjusted for age, gender, injury severity, and non-fracture polytrauma. Appendicular fractures were associated with more severe AIS grades at hospital discharge, though covariate adjustments diminished statistical significance of this effect. Notably, non-fracture injuries to the chest and abdomen were influential covariates. Secondary analyses suggested that appendicular fractures also increased hospital length of stay. Our study indicated that SCI-associated polytrauma is important for predicting SCI functional outcomes. Further statistical evaluation is required to disentangle the effects of appendicular fractures, non-fracture solid organ injury, and SCI physiology to improve health outcomes amongst SCI patients.

The Natural History of Spinal Cord Injury

The natural history of spinal cord injury is in a state of flux. Our knowledge about the prevalence, epidemiology, and natural history spinal cord injury is in evolution. In this article, we summarize these considerations to provide a state-of-the-art synopsis of the neurologic outcomes of this condition.

Diagnostic blood RNA profiles for human acute spinal cord injury

Diagnosis of spinal cord injury (SCI) severity at the ultra-acute stage is of great importance for emergency clinical care of patients as well as for potential enrollment into clinical trials. The lack of a diagnostic biomarker for SCI has played a major role in the poor results of clinical trials. We analyzed global gene expression in peripheral white blood cells during the acute injury phase and identified 197 genes whose expression changed after SCI compared with healthy and trauma controls and in direct relation to SCI severity. Unsupervised coexpression network analysis identified several gene modules that predicted injury severity (AIS grades) with an overall accuracy of 72.7% and included signatures of immune cell subtypes. Specifically, for complete SCIs (AIS A), ROC analysis showed impressive specificity and sensitivity (AUC: 0.865). Similar precision was also shown for AIS D SCIs (AUC: 0.938). Our findings indicate that global transcriptomic changes in peripheral blood cells have diagnostic and potentially prognostic value for SCI severity.

Injury volume extracted from MRI predicts neurologic outcome in acute spinal cord injury: A prospective TRACK-SCI pilot study

Conventional MRI measures of traumatic spinal cord injury severity largely rely on 2-dimensional injury characteristics such as intramedullary lesion length and cord compression. Recent advances in spinal cord (SC) analysis have led to the development of a robust anatomic atlas incorporated into an open-source platform called the Spinal Cord Toolbox (SCT) that allows for quantitative volumetric injury analysis. In the current study, we evaluate the prognostic value of volumetric measures of spinal cord injury on MRI following registration of T2-weighted (T2w) images and segmented lesions from acute SCI patients with a standardized atlas. This IRB-approved prospective cohort study involved the image analysis of 60 blunt cervical SCI patients enrolled in the TRACK-SCI clinical research protocol. Axial T2w MRI data obtained within 24 h of injury were processed using the SCT. Briefly, SC MRIs were automatically segmented using the sct_deepseg_sc tool in the SCT and segmentations were manually corrected by a neuro-radiologist. Lesion volume data were used as predictor variables for correlation with lower extremity motor scores at discharge. Volumetric MRI measures of T2w signal abnormality comprising the SCI lesion accurately predict lower extremity motor scores at time of patient discharge. Similarly, MRI measures of injury volume significantly correlated with motor scores to a greater degree than conventional 2-D metrics of lesion size. The volume of total injury and of injured spinal cord motor regions on T2w MRI is significantly and independently associated with neurologic outcome at discharge after injury.

Factors related to improved American Spinal Injury Association grade of acute traumatic spinal cord injury

BACKGROUND

Acute traumatic spinal cord injury (ATSCI) usually results in disability, yet data on contemporary national trends of ATSCI incidence are limited.

AIM

To provide a systematic and basic theoretical basis for improving the treatment of acute spinal cord injury.

METHODS

Data from the Peking University Third Hospital Inpatient Sample databases were analyzed. A total of 304 patients with ATSCI were included from 2012 to 2017. The epidemiological data, treatment, complications and clinical outcomes of these patients were reviewed.

RESULTS

Of the 304 patients, 257 (84.5%) were male, and 75% of the patients were 55 years old or younger. 135 patients had improved follow-up American Spinal Injury Association (ASIA) grades (44.4%). Only 14 patients with ASIA grade A improved. A statistically significant difference in prognosis between patients who underwent surgery within 72 h and those who underwent surgery after 72 h was observed (P < 0.05). Surgery within 72 h resulted in better prognosis. The Steroid group and the Non-Steroid group showed a significant difference in outcome among patients with ASIA grades A and B (P < 0.05). Patients with pneumonia had a poorer prognosis than patients without pneumonia (P < 0.05). Surgery within 72 h resulted in better prognosis.

CONCLUSION

This study found that there was no significant difference in hospitalization time and prognosis between the Steroid group and the Non-Steroid group, but the patients with severe spinal cord injury (ASIA grades A and B) who underwent surgery combined with steroid therapy had a better prognosis than those who underwent surgery alone. The disastrous consequences of ATSCI and lack of consensus on the management strategy are obvious. Further improvements in treatment planns are needed in order to obtain more reliable functional outcomes.