Assessment of reduced field of view in diffusion tensor imaging of the lumbar nerve roots at 3 T
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To assess the value of reduced field of view (rFOV) imaging in diffusion tensor imaging (DTI) and tractography of the lumbar nerve roots at 3 T from the perspective of future clinical trials.
DTI images of the lumbar nerves were obtained in eight healthy volunteers, with and without the rFOV technique. Non-coplanar excitation and refocusing pulses associated with outer volume suppression (OVS) were used to achieve rFOV imaging. Tractography was performed. A visual evaluation of image quality was made by two observers, both senior musculoskeletal radiologists. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were measured in L5 and S1 roots.
rFOV images of the L5 and S1 roots were assessed as being superior to full FOV (fFOV) images. Image quality was rated as good to excellent by both observers. Interobserver agreement was good. No significant difference was found in FA and ADC measurements of the L5 or S1 roots. On the contrary, only poor-quality images could be obtained with fFOV imaging as major artefacts were present.
The rFOV approach was essential to achieve high-quality DTI imaging of lumbar nerve roots on 3-T MRI.
• Diffusion tensor 3-T MR imaging of lumbar nerve roots creates severe artefacts.
• A reduced field of view drastically reduces artefacts, thereby improving image quality.
• Good-quality tractography images can even be obtained with rFOV imaging.
• rFOV DTI is better than fFOV DTI for clinical studies.
KeywordsMagnetic resonance imaging Diffusion tensor imaging Peripheral nerves Echo planar imaging Lumbosacral region
Abbreviations and Acronyms
apparent diffusion coefficient
diffusion tensor imaging
echo planar imaging
full field of view
reduced field of view
outer volume suppression
region of interest
signal to noise ratio
The authors would like to thank Prof. Xavier Leclerc, PhD, from the Neuroradiology Department of the CHRU, who gave us access to the imaging platform of IFR 114– IMPRT, and Mr. David Chechin, PhD, Philips Healthcare, for his technical advice.
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