Potential use of diffusion tensor imaging in level diagnosis of multilevel cervical spondylotic myelopathy

Imaging protocols for non-traumatic spinal cord injury: current state of the art and future directions

INTRODUCTION

Non-traumatic spinal cord injury (NTSCI) is a term used to describe damage to the spinal cord from sources other than trauma. Neuroimaging techniques such as computerized tomography (CT) and magnetic resonance imaging (MRI) have improved our ability to diagnose and manage NTSCIs. Several practice guidelines utilize MRI in the diagnostic evaluation of traumatic and non-traumatic SCI to direct surgical intervention.

AREAS COVERED

The authors review practices surrounding the imaging of various causes of NTSCI as well as recent advances and future directions for the use of novel imaging modalities in this realm. The authors also present discussions around the use of simple radiographs and advanced MRI modalities in clinical settings, and briefly highlight areas of active research that seek to advance our understanding and improve patient care.

EXPERT OPINION

Although several obstacles must be overcome, it appears highly likely that novel quantitative imaging features and advancements in artificial intelligence (AI) as well as machine learning (ML) will revolutionize degenerative cervical myelopathy (DCM) care by providing earlier diagnosis, accurate localization, monitoring for deterioration and neurological recovery, outcome prediction, and standardized practice. Some intriguing findings in these areas have been published, including the identification of possible serum and cerebrospinal fluid biomarkers, which are currently in the early phases of translation.

Evaluating tissue injury in cervical spondylotic myelopathy with spinal cord MRI: a systematic review

PURPOSE

Cervical Spondylotic Myelopathy (CSM) is a degenerative condition that leads to loss of cervical spinal cord (CSC) integrity. Various spinal cord Magnetic Resonance Imaging (MRI) methods can identify and characterize the extent of this damage. This systematic review aimed to evaluate the diagnostic, biomarker, and predictive utilities of different spinal cord MRI methods in clinical research studies of CSM. The aim was to provide a comprehensive understanding of the progress in this direction for future studies and effective diagnosis and management of CSM.

METHODS

A comprehensive literature search was conducted on PubMed and EMBASE from 2010 to 2022 according to PRISMA guidelines. Studies with non-human subjects, less than 3T magnetic field strength, non-clinical design, or not quantitatively focusing on the structural integrity of CSC were excluded. The extracted data from each study included demographics, disease severity, MRI machine characteristics, quantitative metrics, and key findings in terms of diagnostic, biomarker, and predictive utilities of each MRI method. The risk of bias was performed using the guide from AHRQ. The quality of evidence was assessed separately for each type of utility for different MRI methods using GRADE.

RESULTS

Forty-seven studies met the inclusion criteria, utilizing diffusion-weighted imaging (DTI) (n = 39), magnetization transfer (MT) (n = 6), MR spectroscopy (n = 3), and myelin water imaging (n = 1), as well as a combination of MRI methods (n = 12). The metric fractional anisotropy (FA) showed the highest potential in all facets of utilities, followed by mean diffusivity. Other promising metrics included MT ratio and intracellular volume fraction, especially in multimodal studies. However, the level of evidence for these promising metrics was low due to a small number of studies. Some studies, mainly DTI, also reported the usefulness of spinal cord MRI in mild CSM.

CONCLUSIONS

Spinal cord MRI methods can potentially facilitate the diagnosis and management of CSM by quantitatively interrogating the structural integrity of CSC. DTI is the most promising MRI method, and other techniques have also shown promise, especially in multimodal configurations. However, this field is in its early stages, and more studies are needed to establish the usefulness of spinal cord MRI in CSM.

Degenerative cervical myelopathy: Where have we been? Where are we now? Where are we going?

Degenerative cervical myelopathy (DCM), a recently coined term, encompasses a group of age-related and genetically associated pathologies that affect the cervical spine, including cervical spondylotic myelopathy and ossification of the posterior longitudinal ligament (OPLL). Given the significant contribution of DCM to global disease and disability, there are worldwide efforts to promote research and innovation in this area. An AO Spine effort termed 'RECODE-DCM' was initiated to create an international multistakeholder consensus group, involving patients, caregivers, physicians and researchers, to focus on launching actionable discourse on DCM. In order to improve the management, treatment and results for DCM, the RECODE-DCM consensus group recently identified ten priority areas for translational research. The current article summarizes recent advancements in the field of DCM. We first discuss the comprehensive definition recently refined by the RECODE-DCM group, including steps taken to arrive at this definition and the supporting rationale. We then provide an overview of the recent advancements in our understanding of the pathophysiology of DCM and modalities to clinically assess and diagnose DCM. A focus will be set on advanced imaging techniques that may offer the opportunity to improve characterization and diagnosis of DCM. A summary of treatment modalities, including surgical and nonoperative options, is then provided along with future neuroprotective and neuroregenerative strategies. This review concludes with final remarks pertaining to the genetics involved in DCM and the opportunity to leverage this knowledge toward a personalized medicine approach.

Deep Learning-Based Auto-Segmentation of Spinal Cord Internal Structure of Diffusion Tensor Imaging in Cervical Spondylotic Myelopathy

Cervical spondylotic myelopathy (CSM) is a chronic disorder of the spinal cord. ROI-based features on diffusion tensor imaging (DTI) provide additional information about spinal cord status, which would benefit the diagnosis and prognosis of CSM. However, the manual extraction of the DTI-related features on multiple ROIs is time-consuming and laborious. In total, 1159 slices at cervical levels from 89 CSM patients were analyzed, and corresponding fractional anisotropy (FA) maps were calculated. Eight ROIs were drawn, covering both sides of lateral, dorsal, ventral, and gray matter. The UNet model was trained with the proposed heatmap distance loss for auto-segmentation. Mean Dice coefficients on the test dataset for dorsal, lateral, and ventral column and gray matter were 0.69, 0.67, 0.57, 0.54 on the left side and 0.68, 0.67, 0.59, 0.55 on the right side. The ROI-based mean FA value based on segmentation model strongly correlated with the value based on manual drawing. The percentages of the mean absolute error between the two values of multiple ROIs were 0.07, 0.07, 0.11, and 0.08 on the left side and 0.07, 0.1, 0.1, 0.11, and 0.07 on the right side. The proposed segmentation model has the potential to offer a more detailed spinal cord segmentation and would be beneficial for quantifying a more detailed status of the cervical spinal cord.

Imaging and Electrophysiology for Degenerative Cervical Myelopathy [AO Spine RECODE-DCM Research Priority Number 9]

STUDY DESIGN

Narrative review.

OBJECTIVE

The current review aimed to describe the role of existing techniques and emerging methods of imaging and electrophysiology for the management of degenerative cervical myelopathy (DCM), a common and often progressive condition that causes spinal cord dysfunction and significant morbidity globally.

METHODS

A narrative review was conducted to summarize the existing literature and highlight future directions.

RESULTS

Anatomical magnetic resonance imaging (MRI) is well established in the literature as the key imaging tool to identify spinal cord compression, disc herniation/bulging, and inbuckling of the ligamentum flavum, thus facilitating surgical planning, while radiographs and computed tomography (CT) provide complimentary information. Electrophysiology techniques are primarily used to rule out competing diagnoses. However, signal change and measures of cord compression on conventional MRI have limited utility to characterize the degree of tissue injury, which may be helpful for diagnosis, prognostication, and repeated assessments to identify deterioration. Early translational studies of quantitative imaging and electrophysiology techniques show potential of these methods to more accurately reflect changes in spinal cord microstructure and function.

CONCLUSION

Currently, clinical management of DCM relies heavily on anatomical MRI, with additional contributions from radiographs, CT, and electrophysiology. Novel quantitative assessments of microstructure, perfusion, and function have the potential to transform clinical practice, but require robust validation, automation, and standardization prior to uptake.

Automatic spinal cord segmentation from axial-view MRI slices using CNN with grayscale regularized active contour propagation

Accurate positioning of the responsible segment for patients with cervical spondylotic myelopathy (CSM) is clinically important not only to the surgery but also to reduce the incidence of surgical trauma and complications. Spinal cord segmentation is a crucial step in the positioning procedure. This study proposed a fully automated approach for spinal cord segmentation from 2D axial-view MRI slices of patients with CSM. The proposed method was trained and tested using clinical data from 20 CSM patients (359 images) acquired by the Peking University Third Hospital, with ground truth labeled by professional radiologists. The accuracy of the proposed method was evaluated using quantitative measures, the reliability metric as well as visual assessment. The proposed method yielded a Dice coefficient of 87.0%, Hausdorff distance of 9.7 mm, root-mean-square error of 5.9 mm. Higher conformance with ground truth was observed for the proposed method in comparison to the state-of-the-art algorithms. The results are also statistically significant with p-values calculated between state-of-the-art methods and the proposed methods.

Application of multishot diffusion tensor imaging in spinal cord tumors

Objective:

To explore the usefulness of multishot diffusion tensor imaging (DTI) for evaluating the neurological function of patients with spinal cord tumors

Methods:

Routine magnetic resonance imaging and multishot DTI were performed in five patients with spinal cord tumors. The values of fractional anisotropy (FA) and radial diffusivity (RD) were analyzed.

Results:

Multishot DTI of spinal cord tumors allowed for defining the margins of tumors and determining the relationship of tumors with the adjacent white matter structures of the spinal cord. Multishot DTI demonstrated significantly increased RD and decreased FA of spinal cord tumors compared with those of the normal spinal cord.

Conclusions:

Multishot DTI is a potentially useful modality for differentiating resectable tumors from nonresectable ones based on preoperative imaging alone as well as for differentiating intramedullary tumors from extramedullary ones. Further prospective studies are warranted to confirm these results.

Prognosis of cervical myelopathy based on diffusion tensor imaging with artificial intelligence methods

Diffusion tensor imaging (DTI) has been proposed for the prognosis of cervical myelopathy (CM), but the manual analysis of DTI features is complicated and time consuming. This study evaluated the potential of artificial intelligence (AI) methods in the analysis of DTI for the prognosis of CM. Seventy-five patients who underwent surgical treatment for CM were recruited for DTI imaging and were divided into two groups based on their one-year follow-up recovery. The DTI features of fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity were extracted from DTI maps of all cervical levels. Conventional AI models using logistic regression (LR), k-nearest neighbors (KNN), and a radial basis function kernel support vector machine (RBF-SVM) were built using these DTI features. In addition, a deep learning model was applied to the DTI maps. Their performances were compared using 50 repeated 10-fold cross-validations. The accuracy of the classifications reached 74.2% ± 1.6% for LR, 85.6% ± 1.4% for KNN, 89.7% ± 1.6% for RBF-SVM, and 59.2% ± 3.8% for the deep leaning model. The RBF-SVM algorithm achieved the best accuracy, with sensitivity and specificity of 85.0% ± 3.4% and 92.4% ± 1.9% respectively. This finding indicates that AI methods are feasible and effective for DTI analysis for the prognosis of CM.

Effect of segmentation from different diffusive metric maps on diffusion tensor imaging analysis of the cervical spinal cord

Background

Segmentation is a crucial and necessary step in diffusion tensor imaging (DTI) analysis of the cervical spinal cord. In existing studies, different diffusive metric maps [B0, fractional anisotropy (FA) and axial diffusivity (AD) maps] have been involved in the segmentation of tissues of the cervical spinal cord. The selection of a diffusive metric map for segmentation may affect the accuracy of segmentation and then affect the validity and effectiveness of the extracted diffusive features. However, there are few discussions on this problem. Therefore, this study would like to examine the effect of segmentation based on different diffusive metric maps for DTI analysis of the cervical spinal cord.

Methods

Twenty-nine healthy subjects and thirty patients with cervical spondylotic myelopathy (CSM) were finally included in this study. All subjects accepted DTI scanning at cervical levels from C2 to C7/T1. For healthy subjects, all cervical levels were included for analysis; while, for each patient, only one compressed cervical level was included. After DTI scanning, DTI metrics including B0, FA, AD, radial diffusivity (RD) and mean diffusivity (MD) were calculated. The evaluation was performed to B0, FA and AD maps from two aspects. First, the accuracy of segmentation was evaluated via a comparison between segmentation based on each diffusive metric map and segmentation based on an average image, which was acquired by averaging B0, FA, AD, RD and MD maps. The segmentation was achieved by a semi-automatic segmentation process, and the similarity between two segmentation results was denoted by the intersection of the union (IOU). Second, the diversity of extracted diffusive features was equalized as their performance in the classification of image pixels of different regions of interest (ROIs) and then was evaluated by mutual information (MI) and area under the curve (AUC). One-way ANOVA and Bonferroni's post hoc tests were applied to compare the evaluation results.

Results

One-way ANOVA suggested that there were differences (P<0.001) in IOU, MI and AUC values among the three diffusive metric maps for both healthy subjects and patients. The post-hoc tests further indicated that FA performed the best (P<0.001), i.e., the most substantial accuracy of segmentation and the highest diversity in extracted diffusive features.

Conclusions

Different evaluation results had been observed for segmentation based on different diffusive metric maps, suggesting the necessity of selection of diffusive metric maps for segmentation in DTI analysis of the cervical spinal cord. Moreover, FA map is suggested for segmentation due to its best performance in the evaluation.

Magnetic resonance imaging assessment of degenerative cervical myelopathy: a review of structural changes and measurement techniques

Degenerative cervical myelopathy encompasses a spectrum of age-related structural changes of the cervical spine that result in static and dynamic injury to the spinal cord and collectively represent the most common cause of myelopathy in adults. Although cervical myelopathy is determined clinically, the diagnosis requires confirmation via imaging, and MRI is the preferred modality. Because of the heterogeneity of the condition and evolution of MRI technology, multiple techniques have been developed over the years in an attempt to quantify the degree of baseline severity and potential for neurological recovery. In this review, these techniques are categorized anatomically into those that focus on bone, ligaments, discs, and the spinal cord. In addition, measurements for the cervical spine canal size and sagittal alignment are also described briefly. These tools have resulted collectively in the identification of numerous useful parameters. However, the development of multiple techniques for assessing the same feature, such as cord compression, has also resulted in a number of challenges, including introducing ambiguity in terms of which methods to use and hindering effective comparisons of analysis in the literature. In addition, newer techniques that use advanced MRI are emerging and providing exciting new tools for assessing the spinal cord in patients with degenerative cervical myelopathy.

Diffusion Assessment of Cortical Changes, Induced by Traumatic Spinal Cord Injury

Promising treatments are being developed to promote functional recovery after spinal cord injury (SCI). Magnetic resonance imaging, specifically Diffusion Tensor Imaging (DTI) has been shown to non-invasively measure both axonal and myelin integrity following traumatic brain and SCI. A novel data-driven model-selection algorithm known as Diffusion Basis Spectrum Imaging (DBSI) has been proposed to more accurately delineate white matter injury. The objective of this study was to investigate whether DTI/DBSI changes that extend to level of the cerebral peduncle and internal capsule following a SCI could be correlated with clinical function. A prospective non-randomized cohort of 23 patients with chronic spinal cord injuries and 17 control subjects underwent cranial diffusion weighted imaging, followed by whole brain DTI and DBSI computations. Region-based analyses were performed on cerebral peduncle and internal capsule. Three subgroups of patients were included in the region-based analysis. Tract-Based Spatial Statistics (TBSS) was also applied to allow whole-brain white matter analysis between controls and all patients. Functional assessments were made using International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) as modified by the American Spinal Injury Association (ASIA) Scale. Whole brain white matter analysis using TBSS finds no statistical difference between controls and all patients. Only cervical ASIA A/B patients in cerebral peduncle showed differences from controls in DTI and DBSI results with region-based analysis. Cervical ASIA A/B SCI patients had higher levels of axonal injury and edema/tissue loss as measured by DBSI at the level of the cerebral peduncle. DTI Fractional Anisotropy (FA), Axial Diffusivity (AD) and Radial Diffusivity (RD) was able to detect differences in cervical ASIA A/B patients, but were non-specific to pathologies. Increased water fraction indicated by DBSI non-restricted isotropic diffusion fraction in the cerebral peduncle, explains the simultaneously increased DTI AD and DTI RD values. Our results further demonstrate the utility of DTI to detect disruption in axonal integrity in white matter, yet a clear shortcoming in differentiating true axonal injury from inflammation/tissue loss. Our results suggest a preservation of axonal integrity at the cortical level and has implications for future regenerative clinical trials.

Amplitude of Low Frequency Fluctuation (ALFF) in the Cervical Spinal Cord with Stenosis: A Resting State fMRI Study

Cervical spondylotic myelopathy (CSM) is a common spinal cord dysfunction disease with complex symptoms in clinical presentation. Resting state fMRI (rsfMRI) has been introduced to study the mechanism of neural development of CSM. However, most of those studies focused on intrinsic functional connectivity rather than intrinsic regional neural activity level which is also frequently analyzed in rsfMRI studies. Thus, this study aims to explore whether the level of neural activity changes on the myelopathic cervical cord and evaluate the possible relationship between this change and clinical symptoms through amplitude of low frequency fluctuation (ALFF). Eighteen CSM patients and twenty five healthy subjects participated in rsfMRI scanning. ALFF was investigated on each patient and subject. The results suggested that ALFF values were higher in the CSM patients at all cervical segments, compared to the healthy controls. The severity of myelopathy was associated with the increase of ALFF. This finding would enrich our understanding on the neural development mechanism of CSM.

Fractional anisotropy to quantify cervical spondylotic myelopathy severity

BACKGROUND

A number of clinical tools exist for measuring the severity of cervical spondylotic myelopathy (CSM). Several studies have recently described the use of non-invasive imaging biomarkers to assess severity of disease. These imaging markers may provide an additional tool to measure disease progression and represent a surrogate marker of response to therapy. Correlating these imaging biomarkers with clinical quantitative measures is critical for accurate therapeutic stratification and quantification of axonal injury.

METHODS

Fourteen patients and seven healthy control subjects were enrolled. Patients were classified as mildly (7) or moderately (7) impaired based on Modified Japanese Orthopedic Association Scale. All patients underwent diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI) analyses. In addition to standard neurological examination, all participants underwent 30-m Walking Test, 9-hole Peg Test (9HPT), grip strength, key pinch, and vibration sensation thresholds in the index finger and great toe. Differences in assessment scores between controls, mild and moderate CSM patients were correlated with DTI and DBSI derived fractional anisotropy (FA).

RESULTS

Clinically, 30-meter walking times were significantly longer in the moderately impaired group than in the control group. Maximum 9HPT times were significantly longer in both the mildly and moderately impaired groups as compared to normal controls. Scores on great toe vibration sensation thresholds were lower in the mildly impaired and moderately impaired groups as compared to controls. We found no clear evidence for any differences in minimum grip strength, minimum key pinch, or index finger vibration sensation thresholds. There were moderately strong associations between DTI and DBSI FA values and 30-meter walking times and 9HPT.

CONCLUSIONS

The 30-m Walking Test and 9HPT were both moderately to strongly associated with DTI/DBSI FA values. FA may represent an additional measure to help differentiate and stratify patients with mild or moderate CSM.

Translating state-of-the-art spinal cord MRI techniques to clinical use: A systematic review of clinical studies utilizing DTI, MT, MWF, MRS, and fMRI

BACKGROUND

A recent meeting of international imaging experts sponsored by the International Spinal Research Trust (ISRT) and the Wings for Life Foundation identified 5 state-of-the-art MRI techniques with potential to transform the field of spinal cord imaging by elucidating elements of the microstructure and function: diffusion tensor imaging (DTI), magnetization transfer (MT), myelin water fraction (MWF), MR spectroscopy (MRS), and functional MRI (fMRI). However, the progress toward clinical translation of these techniques has not been established.

METHODS

A systematic review of the English literature was conducted using MEDLINE, MEDLINE-in-Progress, Embase, and Cochrane databases to identify all human studies that investigated utility, in terms of diagnosis, correlation with disability, and prediction of outcomes, of these promising techniques in pathologies affecting the spinal cord. Data regarding study design, subject characteristics, MRI methods, clinical measures of impairment, and analysis techniques were extracted and tabulated to identify trends and commonalities. The studies were assessed for risk of bias, and the overall quality of evidence was assessed for each specific finding using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework.

RESULTS

A total of 6597 unique citations were identified in the database search, and after full-text review of 274 articles, a total of 104 relevant studies were identified for final inclusion (97% from the initial database search). Among these, 69 studies utilized DTI and 25 used MT, with both techniques showing an increased number of publications in recent years. The review also identified 1 MWF study, 11 MRS studies, and 8 fMRI studies. Most of the studies were exploratory in nature, lacking a priori hypotheses and showing a high (72%) or moderately high (20%) risk of bias, due to issues with study design, acquisition techniques, and analysis methods. The acquisitions for each technique varied widely across studies, rendering direct comparisons of metrics invalid. The DTI metric fractional anisotropy (FA) had the strongest evidence of utility, with moderate quality evidence for its use as a biomarker showing correlation with disability in several clinical pathologies, and a low level of evidence that it identifies tissue injury (in terms of group differences) compared with healthy controls. However, insufficient evidence exists to determine its utility as a sensitive and specific diagnostic test or as a tool to predict clinical outcomes. Very low quality evidence suggests that other metrics also show group differences compared with controls, including DTI metrics mean diffusivity (MD) and radial diffusivity (RD), the diffusional kurtosis imaging (DKI) metric mean kurtosis (MK), MT metrics MT ratio (MTR) and MT cerebrospinal fluid ratio (MTCSF), and the MRS metric of N-acetylaspartate (NAA) concentration, although these results were somewhat inconsistent.

CONCLUSIONS

State-of-the-art spinal cord MRI techniques are emerging with great potential to improve the diagnosis and management of various spinal pathologies, but the current body of evidence has only showed limited clinical utility to date. Among these imaging tools DTI is the most mature, but further work is necessary to standardize and validate its use before it will be adopted in the clinical realm. Large, well-designed studies with a priori hypotheses, standardized acquisition methods, detailed clinical data collection, and robust automated analysis techniques are needed to fully demonstrate the potential of these rapidly evolving techniques.

Trial-to-trial latency variability of somatosensory evoked potentials as a prognostic indicator for surgical management of cervical spondylotic myelopathy

Background

Early detection of neural conductivity changes at the compressed spinal cord is important for predicting the surgical outcomes of patients with cervical spondylotic myelopathy (CSM). The prognostic value of median nerve somatosensory evoked potential (SEP) has been proposed previously. The present prospective study evaluates the use of trial-to-trial variability in SEP as a valuable predictor of neurological recovery after surgery of CSM.

Methods

A total of 35 CSM patients who underwent surgery with up to 6-month follow-up were recruited in this study. SEP signals were recorded preoperatively. The single trial SEP was extracted by a newly developed second-order blind identification method. The postoperative recovery was assessed using the modified Japanese Orthopaedic Association. The correlation between the latency variability of trial-to-trial SEP and post-operative recovery ratio was analyzed. The prognostic value of trial-to-trial SEP for CSM was evaluated using a receiver operator characteristic curve which can accurately reflect the relationship between sensitivity and specificity of a diagnostic method and represent the accuracy of prognosis.

Results

The correlation coefficient of trial-to-trial latency variability and the 6-month recovery ratio was statistically significant (r = −0.82, P < 0.01). The trial-to-trial SEP had a higher prognostic accuracy (AUC = 0.928, P < 0.001) with an optimal prognostic value of 9.25 % compared with averaged SEP when the threshold of recovery ratio was 40 %, and was more sensitive (93.80 %) than the averaged SEP (43.80 %).

Conclusions

These findings indicate that the latency variability of trial-to-trial SEP reflect the recovery ratio of CSM patients after surgery. It is suggested that the latency variability of trial-to-trial SEP is useful for predicting the surgical outcomes for patients with CSM, which would be a potential indication of surgical treatment for CSM to help decision making of surgical planning for CSM patients.

Electronic supplementary material

The online version of this article (doi:10.1186/s12984-015-0042-4) contains supplementary material, which is available to authorized users.