A combination of functional magnetic resonance imaging and diffusion tensor image to explore structure&amp;ndash;function relationship in healthy and myelopathic spinal cord

Cui, Jike; Li, Guang-Sheng; Mak, Kwok Hang; Luk, K.D.K.; Hu, Yong

doi:10.2147/jn.s116450

Cited by 3 publications

(5 citation statements)

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“…Apart from intrinsic connectivity, resting-state fMRI focused on low-frequency blood oxygen level (BOLD) fluctuations has also been used to study intrinsic neural activity, showing that the amplitude of these fluctuations were higher in DCM patients at all cervical segments compared with healthy controls and that the severity of myelopathy correlated with an increase in the BOLD fluctuations 54. Building upon this, 1 study combined DTI and fMRI evaluations of patients with DCM, showing the FA value to have a significant negative linear correlation to the BOLD signal change suggesting a direct quantitative relationship between the structure (lower FA) and function (higher BOLD fluctuations) of the myelopathic cord 55…”

Section: New Imaging Modalities In Dcmmentioning

confidence: 77%

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New Imaging Modalities for Degenerative Cervical Myelopathy

Rajan

Pelle

Savage

2022

Clinical Spine Surgery: A Spine Publication

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Introduction: Degenerative cervical myelopathy (DCM) is defined as dysfunction of the spinal cord as a result of compression from degenerative changes to surrounding joints, intervertebral disks, or ligaments. Symptoms can include upper extremity numbness and diminished dexterity, difficulty with fine manipulation of objects, gait imbalance, and incoordination, and compromised bowel and bladder function. Accurate diagnosis and evaluation of the degree of impairment due to degenerative cervical myelopathy remain a challenging clinical endeavor requiring a thorough and accurate history, physical examination, and assessment of imaging findings. Methods: A narrative review is presented summarizing the current landscape of imaging modalities utilized in DCM diagnostics and the future direction of research for spinal cord imaging. Results and Discussion: Current imaging modalities, particularly magnetic resonance imaging and, to a lesser extent, radiographs/CT, offer important information to aid in decision making but are not ideal as stand-alone tools. Newer imaging modalities currently being studied in the literature include diffusion tensor imaging, MR spectroscopy, functional magnetic resonance imaging, perfusion imaging, and positron emission tomography. These newer imaging modalities attempt to more accurately evaluate the physical structure, intrinsic connectivity, biochemical and metabolic function, and perfusion of the spinal cord in DCM. Although there are still substantial limitations to implementation, future clinical practice will likely be revolutionized by these new imaging modalities to diagnose, localize, surgically plan and manage, and follow patients with DCM.

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Section: New Imaging Modalities In Dcmmentioning

confidence: 77%

“…54 Building upon this, 1 study combined DTI and fMRI evaluations of patients with DCM, showing the FA value to have a significant negative linear correlation to the BOLD signal change suggesting a direct quantitative relationship between the structure (lower FA) and function (higher BOLD fluctuations) of the myelopathic cord. 55…”

Section: Functional Mrimentioning

confidence: 99%

New Imaging Modalities for Degenerative Cervical Myelopathy

Rajan

Pelle

Savage

2022

Clinical Spine Surgery: A Spine Publication

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“…The prognosis for CM is very important, as it aids doctors in deciding on the appropriate treatment options and management of patient outcomes. Currently, the function of the existing prognostic indicators used in clinical practice is under debate, and the DTI technique is believed to achieve a better prognostic result for CM because of its ability to reflect the integrity of the spinal cord according to microstructural changes in the de‐ and remyelination process . Currently, DTI analysis for prognosis of CM is mostly performed via individual analysis of the whole‐cord‐based features at the MCCL .…”

Section: Discussionmentioning

confidence: 99%

“…Diffusion tensor imaging (DTI) has been demonstrated to have prognostic value for CM . In CM, demyelination is believed to be the main pathological change in the spinal cord, and this demyelination changes the organization of nerve fiber bundles, resulting in changes to DTI‐related signals.…”

Section: Introductionmentioning

confidence: 99%

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

Jin

Luk

2019

NMR in Biomedicine

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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. KEYWORDS artificial intelligence (AI), cervical myelopathy (CM), diffusion tensor imaging (DTI), prognosis 1 | INTRODUCTION Cervical myelopathy (CM) is a common spinal cord dysfunction that affects millions of people worldwide. 1 Currently, surgical intervention is considered to be the most immediate way to provide relief from the spinal cord compression and to promote neurological recovery when coupled with active post-operative neural rehabilitation. 2,3 An accurate prognosis for the surgery would provide useful assistance to surgeons, helping them to decide on the most appropriate treatment option, manage patient expectations, and plan postoperative rehabilitation. 4 Several prognosticators of surgical outcomes have already been proposed. 5,6 However, the value of these prognosticators remains controversial, and researchers continue to search for more effective prognostic methods.Diffusion tensor imaging (DTI) has been demonstrated to have prognostic value for CM. [7][8][9] In CM, demyelination is believed to be the main pathological change in the spinal cord, and this demyelination changes the organization of nerve fiber bundles, resulting in changes to DTI-related signals. Based on this principle, researchers have used DTI to study CM. Also, it has been reported that DTI has great potential for distinguishing CM patients from healthy subjects and for predicting the exact cervical levels causing symptoms. [10][11][12] The pathological status of the spinal cord,

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Progression Prediction of Mild Cervical Spondylotic Myelopathy by Somatosensory-evoked Potentials

Feng

2019

Spine

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Study Design. Retrospective study to correlate classification of somatosensory-evoked potentials (SEPs) with symptomatic progress of patients with mild cervical spondylotic myelopathy (CSM). Objective. The aim of this study was to evaluate the usefulness of SEPs for predicting symptomatic progress of mild CSM. Summary of Background Data. SEPs have been used for clinical diagnosis and intraoperative neuromonitoring in patients with CSM. However, the prognostic value of SEPs in predicting the progression of CSM remains unclear. Methods. A total of 200 patients with a clinical diagnosis of mild CSM were enrolled between September 2014 and February 2018. All patients received clinical assessment with the modified Japanese Orthopedic Association scale (mJOA), magnetic resonance imaging, and SEP tests in the first clinical visit and at 1-year follow-up. A classification of upper and lower limbs SEP was developed. At 1-year follow-up, patients with symptom decline >2 points in mJOA were considered progressive myelopathy cases. The relationship of progressive myelopathy and classifications of SEP was investigated. Results. Fifty-four of 200 cases presented with progressive myelopathy. The incidence of progressive myelopathy was 2.6%, 27.7%, 23.8%, 86.7%, and 100% in Class I, II, III, IV, and V of upper SEPs, respectively, and 18.8%, 39.4%, 42.3%, and 62.5% in Class I, II, III, and IV of lower SEPs, respectively. For the combination classification of upper and lower SEPs, the incidence of progressive myelopathy was 0%, 13.7%, 24.3%, 91.1%, and 100% in Class I, II, III, IV, and V, respectively. There was a significant correlation of the incidence of progressive myelopathy with SEP classification for the upper SEPs (r = 0.94, P < 0.01) and the combination SEPs (r = 0.95, P < 0.01). Conclusion. The incidence of progressive degenerative myelopathy increased with the upper and combination SEP classifications. Thus, classification of SEPs could predict the clinical decline in mJOA in CSM, reflecting the probability of worsening of myelopathy. Level of Evidence: 4

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A combination of functional magnetic resonance imaging and diffusion tensor image to explore structure–function relationship in healthy and myelopathic spinal cord

Cited by 3 publications

References 45 publications

New Imaging Modalities for Degenerative Cervical Myelopathy

New Imaging Modalities for Degenerative Cervical Myelopathy

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

Progression Prediction of Mild Cervical Spondylotic Myelopathy by Somatosensory-evoked Potentials

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