Literature DB >> 23523441

Correlation of magnetic resonance diffusion tensor imaging and clinical findings of cervical myelopathy.

Woo-Kyoung Yoo1, Tae-Hwan Kim, Dinh-Mahn Hai, Shanmuga Sundaram, Young-Mi Yang, Moon Soo Park, Yong-Chan Kim, Yoon-Hae Kwak, Suk-Hoon Ohn, Seok Woo Kim.   

Abstract

BACKGROUND CONTEXT: Despite significant advances in the development of diagnostic technology, the diagnosis of cervical myelopathy (CM) still remains based on the clinical findings, which do not provide the means for a sufficiently accurate diagnosis. Furthermore, conventional magnetic resonance imaging (MRI) using T1- and T2-weighted sequences lacks sensitivity to detect and characterize spinal cord lesions. Considering these uncertainties, several investigators have assessed the diagnostic value of diffusion tensor imaging (DTI), an advanced MRI technique that measures the diffusion of water molecules.
PURPOSE: To determine the diagnostic value of DTI in CM in reliably characterizing spinal lesions and in associating them with the clinical findings. STUDY DESIGN/
SETTING: Prospective cohort study. PATIENT SAMPLE: Fifteen CM patients and five healthy volunteers without a history of neurological disorders or of symptoms as controls. OUTCOME MEASURES: Symptoms and signs of CM were evaluated by the use of a modified Japanese Orthopedic Score and the other clinical findings. T2-weighed MRI was used to note the number of compressed levels. Diffusion tensor imaging results were measured according to two parameters, fractional anisotropy (FA) and apparent diffusion coefficient (ADC), at anterior, lateral, and posterior regions of interest (ROIs) in each of five cervical vertebrae, C3-C7.
METHODS: On diagnosis of CM by clinical evaluation and findings from T2-weighted MRI, the 15 subjects were assigned to two subgroups based on complaints, symptoms, and signs. The nine subjects who had typical CM symptoms such as motor weakness, gait disturbance, clumsiness of the hands, and unilateral hypesthesia were assigned to the paralysis subgroup. The other six subjects, whose main symptom was pain and who had vague signs of upper motor neuron injury despite a definitive finding of CM by T2-weighted MRI, were assigned to the pain subgroup. Once assignments had been made, subjects underwent DTI done by the use of the same scanner as for T2-weighted MRI. Results of DTI for each subgroup and controls were averaged, and the mean was used for comparisons. Diffusion tensor imaging results from the paralysis subgroup were sorted into affected and unaffected sides according to the presence or the absence of symptoms.
RESULTS: The paralysis subgroup and the pain subgroup had similar findings from T2-weighted MRI on presentation. The paralysis subgroup had statistically significantly decreased FA values in the anterior and lateral ROIs on the affected side and in the anterior ROIs on the unaffected side, compared with controls. The paralysis subgroup also had statistically significantly increased ADC values in the anterior ROIs of the affected side, compared with controls. The pain subgroup showed significantly increased ADC values in anterior, lateral, and posterior ROIs.
CONCLUSIONS: Use of DTI to quantitatively compare compression in the cervical spinal cords of CM subjects and healthy controls explained individual differences in the clinical findings in the subjects. These findings even applied to CM subjects whose compressed spinal cords looked similar on conventional T2-weighted MRI. Therefore, DTI provided more accurate and reliable information than did conventional T2-weighted MRI about the relationship between spinal cord structure and clinical presentation of CM. Based on our DTI findings, we hypothesized that different clinical findings in CM are attributable to the stage of progression and the severity of pathologic change at presentation. We anticipate that the use of DTI to quantify the extent of myelopathological changes in CM could be more reliable than any other existing diagnostic tools and might provide invaluable information about selecting the optimal treatment for CM and predicting surgical outcomes and prognosis.
Copyright © 2013 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cervical myelopathy; Diffusion tensor imaging MRI; Quantitative analysis

Mesh:

Year:  2013        PMID: 23523441     DOI: 10.1016/j.spinee.2013.02.005

Source DB:  PubMed          Journal:  Spine J        ISSN: 1529-9430            Impact factor:   4.166


  18 in total

1.  Application of diffusion tensor imaging for the diagnosis of segmental level of dysfunction in cervical spondylotic myelopathy.

Authors:  Y Suetomi; T Kanchiku; S Nishijima; Y Imajo; H Suzuki; Y Yoshida; N Nishida; T Taguchi
Journal:  Spinal Cord       Date:  2015-10-27       Impact factor: 2.772

2.  The functional relevance of diffusion tensor imaging in comparison to conventional MRI in patients with cervical compressive myelopathy.

Authors:  Young-Mi Yang; Woo-Kyoung Yoo; Je Hyun Yoo; Yoon Hae Kwak; Jae-Keun Oh; Ji-Sun Song; Seok Woo Kim
Journal:  Skeletal Radiol       Date:  2017-07-17       Impact factor: 2.199

3.  Diffusion tensor imaging predicting neurological repair of spinal cord injury with transplanting collagen/chitosan scaffold binding bFGF.

Authors:  Xiao-Yin Liu; Jun Liang; Yi Wang; Lin Zhong; Chang-Yu Zhao; Meng-Guang Wei; Jing-Jing Wang; Xiao-Zhe Sun; Ke-Qiang Wang; Jing-Hao Duan; Chong Chen; Yue Tu; Sai Zhang; Dong Ming; Xiao-Hong Li
Journal:  J Mater Sci Mater Med       Date:  2019-11-04       Impact factor: 3.896

4.  Application of Neurite Orientation Dispersion and Density Imaging to Evaluate and Predict the Surgical Outcome for Degenerative Cervical Myelopathy.

Authors:  Xiao Han; Xiaodong Ma; Donghang Li; Jinchao Wang; Wen Jiang; Guangqi Li; Xiaoguang Cheng; Hua Guo; Wei Tian
Journal:  Orthop Surg       Date:  2022-06-10       Impact factor: 2.279

Review 5.  Spinal cord injury: how can we improve the classification and quantification of its severity and prognosis?

Authors:  Vibhor Krishna; Hampton Andrews; Abhay Varma; Jacobo Mintzer; Mark S Kindy; James Guest
Journal:  J Neurotrauma       Date:  2014-02-01       Impact factor: 5.269

6.  The Evaluation and Prediction of Laminoplasty Surgery Outcome in Patients with Degenerative Cervical Myelopathy Using Diffusion Tensor MRI.

Authors:  X Han; X Ma; D Li; J Wang; W Jiang; X Cheng; G Li; H Guo; W Tian
Journal:  AJNR Am J Neuroradiol       Date:  2020-08-13       Impact factor: 3.825

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

Authors:  Richu Jin; Yong Hu
Journal:  Quant Imaging Med Surg       Date:  2019-02

Review 8.  Assessment of the diagnostic value of diffusion tensor imaging in patients with spinal cord compression: a meta-analysis.

Authors:  X F Li; Y Yang; C B Lin; F R Xie; W G Liang
Journal:  Braz J Med Biol Res       Date:  2015-11-27       Impact factor: 2.590

9.  Determination of the ideal rat model for spinal cord injury by diffusion tensor imaging.

Authors:  Fang Wang; Sheng-Li Huang; Xi-Jing He; Xiao-Hui Li
Journal:  Neuroreport       Date:  2014-12-03       Impact factor: 1.837

10.  Correlation of diffusion tensor imaging parameters with neural status in Pott's spine.

Authors:  Nikhil Jain; Namita Singh Saini; Sudhir Kumar; Mukunth Rajagopalan; Kanti Lal Chakraborti; Anil Kumar Jain
Journal:  SICOT J       Date:  2016-04-29
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