Trigeminal neuralgia due to neurovascular compression: high-spatial-resolution diffusion-tensor imaging reveals microstructural neural changes.
Аннотация
PURPOSE: To preoperatively detect, by using diffusion-tensor imaging coregistered with anatomic magnetic resonance (MR) imaging, suspected microstructural tissue changes of the trigeminal nerves in patients with trigeminal neuralgia (TN) resulting from neurovascular compression.
MATERIALS AND
METHODS
The study was approved by the institutional review board, and written informed consent was obtained from all patients. Twenty patients (mean age, 51.3 years) with TN and evidence of neurovascular contact were examined with use of a 3.0-T MR unit combined with an eight-channel head coil before undergoing surgical decompression. A single-shot diffusion-tensor echo-planar sequence was used along 15 different diffusion directions, with a b value of 1000 sec/mm(2) and a section thickness of 2 mm. For anatomic correlation, 0.6-mm isotropic three-dimensional fast imaging employing steady-state images were acquired for coregistration with the functional diffusion-tensor maps. After region of interest placement, mean fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were calculated for each nerve by using the paired-sample two-tailed t test (with P < .005 indicating significance) and compared with surgical findings.
RESULTS
FA was significantly lower (P = .004) on the trigeminal neuralgia-affected side (mean FA, 0.203) than on the contralateral side (mean FA, 0.239). ADCs were nearly identical between the normal and TN-affected nerve tissues.
CONCLUSION
These findings suggest that diffusion-tensor imaging enables the identification and quantification of anisotropic changes between normal nerve tissue and TN-affected trigeminal nerves. Coregistration of anatomic three-dimensional fast imaging employing steady-state imaging and diffusion-tensor imaging facilitates excellent delineation of the cisternal segments of the trigeminal nerves.
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История · было → стало
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