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Updated: Feb 5, 2026

Diffusion Tensor Magnetic Resonance Imaging in Chronic Spinal Cord Compression
Published on: May 7, 2019
[Diffusion Tensor Imaging in Early Diagnosis and Prognostic Prediction of Intervertebral Disc Change in Patients with
Peng Wu1, Yu-Jiao Zhang1, Fang Qin2
1Department of Imaging,the First Hospital Affiliated to Hebei North University,Zhangjiakou,Hebei 075000,China.
Abstract:
Objective To explore the value of fractional anisotropy(FA) and apparent diffusion coefficient(ADC) in the early diagnosis of intervertebral disc change in patients with Brucella spondylitis(BS) and in the assessment of BS disc changes after treatment and to further investigate the imaging features of BS in its acute,subacute,and chronic stages. Methods Totally 60 serologically or pathologically confirmed BS patients who were treated in the First Hospital Affiliated to Hebei North University(n=20) or ZhangJiakou Infectious Diseases Hospital(n=40) were enrolled. BS patients were scanned by CT,magnetic resonance imaging,and diffusion tensor imaging,and the FA and ADC values of the disc were measured using the DTI Fiber Trak package. The FA and ADC values were compared in each period and after treatment. Results The ADC value significantly increased and the FA value significantly decreased in different stages(P<0.01). Six months after treatment,the ADC value was significantly lower than the pre-treatment,and the FA value was significantly increased(P<0.01). The ADC value 12 months after treatment for patients in acute or subacute stage and the FA value 12 months after treatment for patients in all stages were significantly different from those in the 6th month after treatment(P<0.01),and the only exception was that the ADC value in the chronic stage was not significantly different between 12th and 6th month after treatment(P=0.089).Conclusion FA and ADC values are more sensitive than conventional MRI sequences in the diagnosis of BS intervertebral disc change and therefore can be used for the early diagnosis and prognostic prediction.
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