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Image Analysis Can Reliably Quantify Median Nerve Echogenicity and Texture Changes in Patients with Carpal Tunnel Syndrome

Clinical Neurophysiology(2023)SCI 3区

Natl & Kapodistrian Univ Athens | Univ Tennessee | Univ Patras

Cited 0|Views34
Abstract
Objective: To study the ability of image analysis measures to quantify echotexture changes of median nerve in order to provide a complementary diagnostic tool in CTS.Methods: Image analysis measures (gray level co-occurrence matrix (GLCM), brightness, hypoechoic area percentage using max entropy and mean threshold) were calculated in normalized images of 39 (19 younger and 20 older than 65y) healthy controls and 95 CTS patients (37 younger and 58 older than 65y).Results: Image analysis measures were equivalent or superior (older patients) to subjective visual anal-ysis. In younger patients, GLCM measures showed equivalent diagnostic accuracy with cross sectional area (CSA) (Area Under Curve (AUC for inverse different moment = 0.97). In older patients all image anal-ysis measures showed similar diagnostic accuracy to CSA (AUC for brightness = 0.88). Moreover, they had abnormal values in many older patients with normal CSA values.Conclusions: Image analysis reliably quantifies median nerve echotexture alterations in CTS and offers similar diagnostic accuracy to CSA measurement. Significance: Image analysis may offer added value to existing measures in the evaluation of CTS, espe-cially in older patients. Its clinical implementation would require incorporation of mathematically simple software code for online nerve image analysis in ultrasound machines.(c) 2023 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
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Key words
Carpal Tunnel Syndrome,Ultrasound,EMG,Image analysis,Gray level co-occurrence matrix,GLCM
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