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Performance Evaluation of High-Resolution Ultrasound versus Magnetic Resonance Imaging in Diagnosing Peripheral Nerve Pathologies
Background High-resolution ultrasound (HRUS) and magnetic resonance neurography (MRN) are considered complementary to clinical and neurophysiological assessment for neuropathies.
Aims The aim of our study was to compare the accuracy of HRUS and MRN for detecting various peripheral nerve pathologies, to choose the correct investigation to facilitate prompt patient management.
Materials and Methods This prospective study was done using HRUS with 14 MHz linear-transducer and 3 or 1.5T MR in cases referred for the assessment of peripheral nerve pathologies. Image interpretation was done using a scoring system (score 0–3 confidence level) to assess for nerve continuity/discontinuity, increased nerve signal/edema, fascicular change, caliber change, and neuroma/mass lesion. We determined the accuracy, sensitivity, and specificity of these modalities compared with the diagnostic standard determined by surgical and/or histopathological, if not performed then clinical and/or electrodiagnostic evaluation.
Results The overall accuracy of MRN was 89.3% (specificity: 66.6%, sensitivity: 92.6%, negative predictive value [NPV]: 57.1%, positive predictive value [PPV]: 95%) and that of HRUS was 82.9% (specificity: 100%, sensitivity: 80.4%, NPV: 42.8, PPV: 100). The confidence level for detecting nerve discontinuity and change in nerve caliber was found to be higher on ultrasonography than magnetic resonance imaging (MRI) (100 vs. 70% and 100 vs. 50%, respectively). Pathology of submillimeter caliber nerves was accurately detected by HRUS and these could not be well-visualized on MRI.
Conclusion HRUS is a powerful tool that may be used as the first-line imaging modality for the evaluation of peripheral nerve pathologies, and a better means of evaluation of peripheral nerves with submillimeter caliber.
19 April 2021 (online)
© 2021. Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
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