Visualization of lumbar nerves using reduced fieldofview diffusion tensor imaging in healthy volunteers and patients with degenerative lumbar disorders.

Abstract

We investigated high resolution diffusion tensor imaging (DTI) of lumbar nerves with reduced fieldofview (rFOV) using 3T MRI. DTI measured with rFOV was compared with conventional FOV (cFOV) 3.0 T MRI in 5 healthy volunteers and 10 patients with degenerative lumbar disorders. The intracanal, foramina and extraforamina of the L5 nerve were established as the regionsofinterest and fractional anisotropy (FA) values and apparent diffusion coefficient (ADC) values were measured. Image quality for tractography and FA maps and ADC maps, interindividual and intraindividual reliability of FA and ADC, and signal-to-noise(SNR) were studied. Both of image qualities with tractography, FA map and ADC map showed that lumbar nerves were more clearly imaged with the rFOV. Intraindividual reliability was higher with rFOV compared with the conventional method for ADC values, while interindividual reliability was higher for both FA values and ADC values with the rFOV method over the conventional method (p < 0.05). Significantly higher SNR was obtained with rFOV compared with cFOV in the spinal canal (p < 0.05). rFOV enabled clearer imaging of the lumbar nerve, allowing for more accurate measurement of FA and ADC values. Significantly higher SNR was obtained with rFOV compared with cFOV in the spinal canal. To our knowledge, this research showed for the first time the usefulness of rFOV in patients with degenerative lumbar disorders. High resolution DTI using rFOV may become useful in clinical applications because visualization of nerve entrapments and quantification of DTI parameters may allow more accurate diagnoses of lumbar nerve dysfunction. Advances in knowledge: Compared with traditional methods, rFOV allows for clear imaging of the lumbar nerve and enables accurate measurements of the FA and ADC values. High-resolution DTI with rFOV may be used to visualize nerve entrapments and allow for more accurate diagnosis of DTI parameter quantification with opportunities for clinical applications.