Identification and Therapeutic Outcome Prediction of Cervical Spondylotic Myelopathy Based on the Functional Connectivity From Resting-State Functional MRI Data: A Preliminary Machine Learning Study

Characterizing brain network alterations in cervical spondylotic myelopathy using static and dynamic functional network connectivity and machine learning

BACKGROUND

Cervical spondylotic myelopathy (CSM) is a debilitating condition that affects the cervical spine, leading to neurological impairments. While the neural mechanisms underlying CSM remain poorly understood, changes in brain network connectivity, particularly within the context of static and dynamic functional network connectivity (sFNC and dFNC), may provide valuable insights into disease pathophysiology. This study investigates brain-wide connectivity alterations in CSM patients using both sFNC and dFNC, combined with machine learning approaches, to explore their potential as biomarkers for disease classification and progression.

METHODS

A total of 191 participants were included in this study, comprising 108 CSM patients and 83 healthy controls (HCs). Resting-state fMRI data were used to derive functional connectivity networks (FCNs), which were further analyzed to obtain sFNC and dFNC features. K-means clustering was applied to identify distinct dFNC states, and machine learning models, including support vector machine (SVM), decision tree (DT), linear discriminant analysis (LDA), logistic regression (LR), and random forests (RF), were constructed to classify CSM patients and HCs based on FNC features.

RESULTS

The sFNC analysis revealed significant alterations in brain network connectivity in CSM patients, including enhanced connectivity between the posterior default mode network (pDMN) and ventral attention network (vAN), and between the right and left frontoparietal networks (rFPN and lFPN), alongside weakened connectivity in multiple other network pairs. K-means clustering of dFNC identified four distinct functional states, with CSM patients exhibiting altered connectivity in State 1 and State 3. Machine learning models based on sFNC demonstrated excellent classification performance, with the SVM model achieving an AUC of 0.92, accuracy of 85.86%, and sensitivity and specificity both exceeding 0.80. Models based on dFNC also performed well, with the State 3-based model yielding an AUC of 0.91 and accuracy of 84.97%.

CONCLUSIONS

Our findings highlight significant alterations in both sFNC and dFNC in CSM patients, suggesting that these connectivity changes may reflect underlying neural mechanisms of the disease. Machine learning models based on FNC features, particularly SVM, exhibit strong potential for classifying CSM patients and may serve as valuable neuroimaging biomarkers for diagnosis and monitoring disease progression. Future research should explore longitudinal studies and multimodal neuroimaging approaches to further validate these findings.

Intra- and inter-network connectivity abnormalities associated with surgical outcomes in degenerative cervical myelopathy patients: a resting-state fMRI study

Resting-state functional MRI (fMRI) has revealed functional changes at the cortical level in degenerative cervical myelopathy (DCM) patients. The aim of this study was to systematically integrate static and dynamic functional connectivity (FC) to unveil abnormalities of functional networks of DCM patients and to analyze the prognostic value of these abnormalities for patients using resting-state fMRI. In this study, we collected clinical data and fMRI data from 44 DCM patients and 39 healthy controls (HC). Independent component analysis (ICA) was performed to investigate the group differences of intra-network FC. Subsequently, both static and dynamic FC were calculated to investigate the inter-network FC alterations in DCM patients. k-means clustering was conducted to assess temporal properties for comparison between groups. Finally, the support vector machine (SVM) approach was performed to predict the prognosis of DCM patients based on static FC, dynamic FC, and fusion of these two metrics. Relative to HC, DCM patients exhibited lower intra-network FC and higher inter-network FC. DCM patients spent more time than HC in the state in which both patients and HC were characterized by strong inter-network FC. Both static and dynamic FC could successfully classify DCM patients with different surgical outcomes. The classification accuracy further improved after fusing the dynamic and static FC for model training. In conclusion, our findings provide valuable insights into the brain mechanisms underlying DCM neuropathology on the network level.

Resting-state brain plasticity is associated with the severity in cervical spondylotic myelopathy

OBJECTIVE

To investigate the brain mechanism of non-correspondence between imaging presentations and clinical symptoms in cervical spondylotic myelopathy (CSM) patients and to test the utility of brain imaging biomarkers for predicting prognosis of CSM.

METHODS

Forty patients with CSM (22 mild-moderate CSM, 18 severe CSM) and 25 healthy controls (HCs) were recruited for rs-fMRI and cervical spinal cord diffusion tensor imaging (DTI) scans. DTI at the spinal cord (level C2/3) with fractional anisotropy (FA) and degree centrality (DC) were recorded. Then one-way analysis of covariance (ANCOVA) was conducted to detect the group differences in the DC and FA values across the three groups. Pearson correlation analysis was then separately performed between JOA with FA and DC.

RESULTS

Among them, degree centrality value of left middle temporal gyrus exhibited a progressive increase in CSM groups compared with HCs, the DC value in severe CSM group was higher compared with mild-moderate CSM group. (P < 0.05), and the DC values of the right superior temporal gyrus and precuneus showed a decrease after increase. Among them, DC values in the area of precuneus in severe CSM group were significantly lower than those in mild-moderate CSM and HCs. (P < 0.05). The fractional anisotropy (FA) values of the level C2/3 showed a progressive decrease in different clinical stages, that severe CSM group was the lowest, significantly lower than those in mild-moderate CSM and HCs (P < 0.05). There was negative correlation between DC value of left middle temporal gyrus and JOA scores (P < 0.001), and the FA values of dorsal column in the level C2/3 positively correlated with the JOA scores (P < 0.001).

CONCLUSION

Structural and functional changes have taken place in the cervical spinal cord and brain of CSM patients. The Brain reorganization plays an important role in maintaining the symptoms and signs of CSM, aberrant DC values in the left middle temporal gyrus may be the possible mechanism of inconsistency between imaging findings and clinical symptoms. Degree centrality is a potentially useful prognostic functional biomarker in cervical spondylotic myelopathy.

Resting-state functional magnetic resonance imaging indices are related to electrophysiological dysfunction in degenerative cervical myelopathy

The age-related degenerative pathologies of the cervical spinal column that comprise degenerative cervical myelopathy (DCM) cause myelopathy due spinal cord compression. Functional neurological assessment of DCM can potentially reveal the severity and pathological mechanism of DCM. However, functional assessment by conventional MRI remains difficult. This study used resting-state functional MRI (rs-fMRI) to investigate the relationship between functional connectivity (FC) strength and neurophysiological indices and examined the feasibility of functional assessment by FC for DCM. Preoperatively, 34 patients with DCM underwent rs-fMRI scans. Preoperative central motor conduction time (CMCT) reflecting motor functional disability and intraoperative somatosensory evoked potentials (SEP) reflecting sensory functional disability were recorded as electrophysiological indices of severity of the cervical spinal cord impairment. We performed seed-to-voxel FC analysis and correlation analyses between FC strength and the two electrophysiological indices. We found that FC strength between the primary motor cortex and the precuneus correlated significantly positively with CMCT, and that between the lateral part of the sensorimotor cortex and the lateral occipital cortex also showed a significantly positive correlation with SEP amplitudes. These results suggest that we can evaluate neurological and electrophysiological severity in patients with DCM by analyzing FC strengths between certain brain regions.

Brain MRI changes in degenerative cervical myelopathy: a systematic review

BACKGROUND

Degenerative cervical myelopathy (DCM) is the most common cause of adult spinal cord dysfunction globally. Associated neurological symptoms and signs have historically been explained by pathobiology within the cervical spine. However, recent advances in imaging have shed light on numerous brain changes in patients with DCM, and it is hypothesised that these changes contribute to DCM pathogenesis. The aetiology, significance, and distribution of these supraspinal changes is currently unknown. The objective was therefore to synthesise all current evidence on brain changes in DCM.

METHODS

A systematic review was performed. Cross-sectional and longitudinal studies with magnetic resonance imaging on a cohort of patients with DCM were eligible. PRISMA guidelines were followed. MEDLINE and Embase were searched to 28th August 2023. Duplicate title/abstract screening, data extraction and risk of bias assessments were conducted. A qualitative synthesis of the literature is presented as per the Synthesis Without Meta-Analysis (SWiM) reporting guideline. The review was registered with PROSPERO (ID: CRD42022298538).

FINDINGS

Of the 2014 studies that were screened, 47 studies were identified that used MRI to investigate brain changes in DCM. In total, 1500 patients with DCM were included in the synthesis, with a mean age of 53 years. Brain alterations on MRI were associated with DCM both before and after surgery, particularly within the sensorimotor network, visual network, default mode network, thalamus and cerebellum. Associations were commonly reported between brain MRI alterations and clinical measures, particularly the Japanese orthopaedic association (JOA) score. Risk of bias of included studies was low to moderate.

INTERPRETATION

The rapidly expanding literature provides mounting evidence for brain changes in DCM. We have identified key structures and pathways that are altered, although there remains uncertainty regarding the directionality and clinical significance of these changes. Future studies with greater sample sizes, more detailed phenotyping and longer follow-up are now needed.

FUNDING

ODM is supported by an Academic Clinical Fellowship at the University of Cambridge. BMD is supported by an NIHR Clinical Doctoral Fellowship at the University of Cambridge (NIHR300696). VFJN is supported by an NIHR Rosetrees Trust Advanced Fellowship (NIHR302544). This project was supported by an award from the Rosetrees Foundation with the Storygate Trust (A2844).

Transcriptional correlates of frequency-dependent brain functional activity associated with symptom severity in degenerative cervical myelopathy

BACKGROUND

Neuroimaging techniques provide insights into the brain abnormalities secondary to degenerative cervical myelopathy (DCM) and their association with neurological deficits. However, the neural correlates underlying the discrepancy between symptom severity and the degree of spinal cord compression, as well as the transcriptional correlates of these cortical abnormalities, remain unknown in DCM patients.

METHODS

In this cross-sectional study, which collected resting-state functional MRI (rs-fMRI) images and the Japanese Orthopedic Association (JOA) score, enrolled 104 participants (54 patients and 50 healthy controls). The frequency-dependent amplitude of low-frequency fluctuation (ALFF) was obtained for all participants. We investigated the ALFF differences between mild-symptom DCM patients and severe-symptom DCM patients while carefully matching the degree of compression between these two groups via both univariate comparison and searchlight classification for three frequency bands (e.g., Slow-4, Slow-5, and Full-band). Additionally, we identified genes associated with symptom severity in DCM patients by linking the spatial patterns of gene expression of Allen Human Brain Atlas and brain functional differences between mild symptom and severe symptom groups.

RESULTS

(1) We found that the frequency-specific brain activities within the sensorimotor network (SMN), visual network (VN), and default mode network (DMN) were associated with the varying degrees of functional impairment in DCM patients; (2) the frequency-specific brain activity within the SMN correlated with the functional recovery in patients with DCM; (3) a spatial correlation between the brain-wide expression of genes involved in neuronal migration and the brain functional activities associated with symptom severity was identified in DCM patients.

CONCLUSION

In conclusion, our study bridges gaps between genes, cell classes, biological processes, and brain functional correlates of DCM. While our findings are correlational in nature, they suggest that the neural activities of sensorimotor cortices in DCM are associated with the severity of symptoms and might be associated with neuronal migration within the brain.

Predicting responses to cognitive behavioral therapy in obsessive-compulsive disorder based on multilevel indices of rs-fMRI

OBJECTIVE

This study aimed to identify neuroimaging predictors to predict the response of cognitive behavioral therapy (CBT) in patients with obsessive-compulsive disorder (OCD) based on indices of resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS

Fifty patients with OCD were enrolled and allocated to either high or low responder groups after CBT using a 50 % response rate as the delineator. The pre-treatment amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and degree centrality (DC) in each cerebrum region, defined by automated anatomical labeling atlas, were extracted. Least absolute shrinkage and selection operator and logistic regression were used to select features and establish models.

RESULTS

The combination of multilevel rs-fMRI indices achieved the best performance, with a cross-validation area under the receiver operating characteristic curve (AUC) of 0.900. In this combined model, an increase of interquartile range (IQR) in fALFF of right inferior orbital frontal gyrus (IOFG), and ReHo of left hippocampus and superior occipital gyrus (SOG) corresponded to a 26.52 %, 38.67 % and 24.38 % increase in the possibility to be high responders of CBT, respectively. ALFF of left thalamus and ReHo of left putamen were negatively associated with the response to CBT, with a 14.30 % and 19.91 % decrease per IQR increase of the index value.

CONCLUSION

The combination of ALFF, fALFF and ReHo achieved a better predictive performance than separate index. Pre-treatment ALFF of the left thalamus, fALFF of the right IOFG, ReHo of the left hippocampus, SOG and putamen can be used as predictors of CBT response.

Brain connectivity markers in degenerative cervical myelopathy patients with depression for predicting the prognosis following decompression surgery

OBJECTIVE

To determine if brain functional connectivity (FC) is associated with the prognosis in depressed degenerative cervical myelopathy patients (DCM) and to investigate the possible brain functional mechanism.

METHODS

Resting-state fMRI scans and peripheral blood cell counts from 33 depressed DCM patients, 33 age and gender-matched DCM patients without depression were analyzed. All patients were evaluated using Japanese Orthopedic Association score before and 6 weeks after decompression surgery. JOA recovery rate was calculated to assess the functional recovery for DCM patients. For each participant, seed-based functional connectivity maps based on sub-regions centered on the striatum were computed and compared between groups. Pearson correlations were performed to explore the relationships between clinical measures and brain alterations in depressed DCM patients. To further investigate the relationships between brain alterations and clinical measures in depressed DCM patients, mediation analyses were performed. Flow cytometry was also performed on the three of the 33 depressed DCM patients, and the results were analyzed.

RESULTS

In comparison to patients without depression, DCM patients exhibited lower FC between the dorsal caudate (dC) and the inferior frontal operculum, which is located in the dorsal lateral prefrontal cortex (dlPFC). In depressed DCM patients, the altered dC-dlPFC FC was associated with inflammation as determined by the neutrophils/lymphocyte's ratio and prognosis. Furthermore, the mediation analysis demonstrated that the dC-dlPFC FC mediated the effect of inflammation on prognosis. The outcomes of our three cases followed a similar pattern to these findings.

CONCLUSION

In conclusion, our findings imply that inflammation slowed the functional recovery in depressed DCM patients through the striatal-frontal FC pathway.

Clinical and Research MRI Techniques for Assessing Spinal Cord Integrity in Degenerative Cervical Myelopathy-A Scoping Review

BACKGROUND

Degenerative cervical myelopathy (DCM) manifests as the primary cause of spinal cord dysfunction and is non-traumatic, chronic and progressive in nature. Decompressive surgery is typically utilised to halt further disability and neurological dysfunction. The limitations of current diagnostic options surrounding assessment and prognostic potential render DCM still largely a clinical diagnosis.

AIMS

To outline the limitations of current diagnostic techniques, present evidence behind novel quantitative MRI (qMRI) techniques for assessing spinal cord integrity in DCM and suggest future directions.

METHOD

Articles published up to November 2021 were retrieved from Medline, EMBASE and EBM using key search terms: spinal cord, spine, neck, MRI, magnetic resonance imaging, qMRI, T1, T2, T2*, R2*, DTI, diffusion tensor imaging, MT, magnetisation transfer, SWI, susceptibility weighted imaging, BOLD, blood oxygen level dependent, fMRI, functional magnetic resonance imaging, functional MRI, MRS, magnetic resonance spectroscopy.

RESULTS

A total of 2057 articles were retrieved with 68 articles included for analysis. The search yielded 2 articles on Quantitative T1 mapping which suggested higher T1 values in spinal cord of moderate-severe DCM; 43 articles on DTI which indicated a strong correlation of fractional anisotropy and modified Japanese Orthopaedic Association scores; 15 articles on fMRI (BOLD) which demonstrated positive correlation of functional connectivity and volume of activation of various connections in the brain with post-surgical recovery; 6 articles on MRS which suggested that Choline/N-acetylaspartate (Cho/NAA) ratio presents the best correlation with DCM severity; and 4 articles on MT which revealed a preliminary negative correlation of magnetisation transfer ratio with DCM severity. Notably, most studies were of low sample size with short timeframes within 6 months.

CONCLUSIONS

Further longitudinal studies with higher sample sizes and longer time horizons are necessary to determine the full prognostic capacity of qMRI in DCM.

Identification of radiographic characteristics associated with pain in hallux valgus patients: A preliminary machine learning study

Objective

To investigate the association between the structural deformity and foot pain in hallux valgus (HV) patients using a multi-variate pattern analysis (MVPA) approach.

Methods

Plain radiographic metrics were calculated from 36 painful and 36 pain-free HV feet. In analysis 1, univariate analyses were performed to investigate the clinical and radiographic differences between painful and pain-free HV. In analysis 2, we investigated the pattern differences for radiographic metrics between these two groups using a MVPA approach utilizing a support vector machine. In analysis 3, sequential backward selection and exhaustive search were performed as a feature-selection procedure to identify an optimal feature subtype. In analysis 4, hierarchical clustering analysis was used to identify the optimal radiographic HV subtype associated with pain in HV.

Results

We found that: (1) relative to feet with pain-free HV, the painful ones exhibited a higher hallux valgus angle, i.e., the magnitude of distal metatarsal and phalangeal deviation; (2) painful HV could be accurately differentiated from pain-free HV via MVPA. Using sequential backward selection and exhaustive search, a 5-feature subset was identified with optimal performance for classifying HV as either painful or pain-free; and (3) by applying hierarchical clustering analysis, a radiographic subtype with an 80% pain incidence was identified.

Conclusion

The pain in HV is multifactorial and associated with a radiographic pattern measured by various angles on plain radiographs. The combination of hallux valgus angle, inter-phalangeal angle, distal metatarsal articular angle, metatarsal cuneiform angle and metatarsal protrusion distance showed the optimal classification performance between painful and pain-free HV.

Brain Structural and Functional Dissociated Patterns in Degenerative Cervical Myelopathy: A Case-Controlled Retrospective Resting-State fMRI Study

Background

Previous studies have shown the whole-brain global functional connectivity density (gFCD) and gray matter volume (GMV) alterations in patients with degenerative cervical myelopathy (DCM). However, no study aimed to investigate the associations between the spatial patterns of GMV and gFCD alterations in patients with DCM.

Methods

Structural data and resting-state functional MRI data of 35 DCM patients and 35 matched healthy controls were collected to assess their gFCD and GMV and investigate gFCD and GMV alterations in patients with DCM and their spatial pattern associations.

Results

In our current study, significant gFCD and GMV differences were observed in some regions of the visual system, sensorimotor cortices, and cerebellum between patients with DCM and healthy controls. In our findings, decreased gFCD was found in areas primarily located at the sensorimotor cortices, while increased gFCD was observed primarily within areas located at the visual system and cerebellum. Decreased GMV was seen in the left thalamus, bilateral supplementary motor area (SMA), and left inferior occipital cortices in patients with DCM, while increased GMV was observed in the cerebellum.

Conclusion

Our findings suggest that structural and functional alterations independently contributed to the neuropathology of DCM. However, longitudinal studies are still needed to further illustrate the associations between structural deficits and functional alterations underlying the onset of brain abnormalities as DCM develops.