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2000
Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603

Abstract

Objective

The aim of this study was to assess the value of 3.0T magnetic resonance (MR) Diffusion tensor imaging (DTI) in the diagnosis of lumbosacral nerve root compression.

Methods

The radiology reports, and clinical records of 34 patients with nerve root compression caused by lumbar disc herniation or bulging and 21 healthy volunteers who had undergone magnetic resonance imaging (MRI) and DTI scan were retrospectively reviewed. The differences in fractional anisotropy (FA) and apparent diffusion coefficient (ADC) between compressed and non-compressed nerve roots from patients and the normal nerve roots from healthy volunteers were compared. Meanwhile, the nerve root fiber bundles were observed and analyzed.

Results

The average FA and ADC values of the compressed nerve roots were 0.254 ± 0.307 and 1.892 ± 0.346 10^-3mm2/s, respectively. The average FA and ADC values of the non-compressed nerve roots were 0.377 ± 0.659 and 1.353 ± 0.344 10^-3mm2/s, respectively. The FA value of compressed nerve roots was significantly lower than that of non-compressed nerve roots (P < 0.01). The ADC value of compressed nerve roots was significantly higher than that of non-compressed nerve roots. There were no significant differences between the left and right nerve roots of normal volunteers in FA and ADC values (P > 0.05). The nerve roots at different levels of L3-S1 had significantly different FA and ADC values (P < 0.01). Incomplete fiber bundles with extrusion deformation, displacement or partial defect were observed in the compressed nerve root fiber bundles. The real diagnosis of the clinical situation of the nerve can provide neuroscientists with an important computer tool to help them infer and understand the possible working mechanism from the experimental data of behavior and electrophysiology.

Conclusion

The compressed lumbosacral nerve roots can be accurately localized through 3.0T magnetic resonance DTI, which is instructive for accurate clinical diagnosis and preoperative localization.

© 2024 The Author(s). Published by Bentham Science Publisher. This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode
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2023-07-07
2024-11-23
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