Prognostic Value of DTI and fMRI of Cervical Myelopathy

Cervical Myelopathy

Cervical Myelopathy，Prognostication，Diffusion Tensor Imaging, fMRI

Cervical myelopathy (CM) is one of the most common degenerative spinal cord disorders affecting older people. The progression of CM is insidious and the neurological decline can vary between patients. Surgical decompression is considered the most effective way to treat CM, however, it is not free from risk and the surgical outcome is not always satisfactory. The expected outcome of surgical intervention for CM remains a difficulty. There is a pressing need for a reliable and quantitative approach to predict surgical outcomes of CM and the precise prognosis. Previous studies have suggested a number of prognostic factors, such as age, duration of symptoms, pre-operative neurological status and abnormal MRI, but their prognostic value remains controversial. Recently, diffusion tensor imaging (DTI) and fMRI have been proposed as a promising tool for predicting the surgical prognosis of CM. In previous study, the protocol was successfully established for DTI microstructural characterization and resting state fMRI of the cervical spinal cord. This study is to evaluate the value of DTI and fMRI in predicting the outcome of surgical treatment. The ultimate goal is to establish a clinical protocol for quantitative DTI and fMRI analysis that could give accurate prognosis for surgical intervention to CM.

Cervical myelopathy (CM) is the most common cause of spinal cord dysfunction in the elderly. Symptoms often develop insidiously and are characterized by neck stiffness, arm pain, numbness in the hands, and weakness of the hands and legs. The causes of this myelopathy are many, such as spinal canal narrowing, osteophytes, herniated discs and hypertrophy of the ligamentum flavum. Although the clinical signs and symptoms of CM are well documented in the literature, a precise localization of the maximum level of compression is sometimes difficult in the elderly patients where multiple levels of the cervical spine are degenerated. Also the lack of understanding of the pathophysiology and pathomechanism of CM has significantly hampered the development of a rational approach to the surgical treatment of such condition. The diagnosis is made based on clinical signs and symptoms with the help of conventional MRI imaging which demonstrates the levels of anatomical stenosis. Surgical decompression of the cervical spine is the most common form of treatment. Magnetic resonance imaging (MRI) has been used widely in the evaluation of patients with CM. The commonly applied MR techniques include spin echo sequence, both conventional spin echo and fast/turbo spin echo for T1 and T2 information; gradient echo sequences, which generate T2 images; STIR (short tau inversion recovery) images; fat suppressed T1 images; gadolinium enhanced images applied to either routine T1WIs or fat suppressed T1WIs; MR spinal angiography; and cerebrospinal fluid flow (CSF) studies (either magnitude or phase contrast). However, conventional MRI mainly concerns anatomical information about CM, with less pathophysiological information. BOLD-fMRI is able to present the activated neuronal volume decreased in CM patients along with an increase in neuronal activities. diffusion tensor imaging (DTI) permits the detection of tissue-water molecular diffusion at microscopic dimensions. Previous studies have demonstrated the feasibility of DTI in evaluating microstructural changes in the myelopathic cervical cord. The prognostic values of spinal cord DTI in CM have been addressed in several previous studies. In recent years, combination of DTI and fMRI has been proposed to be an accurate prognostic tool for surgical management of CM. Cervical myelopathy (CM) is caused by degenerative stenosis of the cervical spine with progressive compression on the spinal cord resulting in loss of sensory and motor functions in the upper and lower limbs. Surgical decompression of the cervical spine is the most common form of treatment. The objective of this project is to evaluate the value of DTI and fMRI in predicting the outcome of surgical treatment.

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