Application of ultrasound images‐based radiomics in carpal tunnel syndrome: Without measuring the median nerve cross‐sectional area

Author:

Lyu Shuyi12ORCID,Zhang Meiwu1,Zhang Baisong1,Yu Jianjun3,Zhu Jiazhen4,Gao Libo1,Yang Liu1,Zhang Yan12

Affiliation:

1. Department of Interventional Therapy, Ningbo NO.2 Hospital Ningbo People's Republic of China

2. Department of Ultrasound Zhenhai Hospital of Traditional Chinese Medicine Ningbo People's Republic of China

3. Department of Neuroelectrophysiology, Ningbo NO.2 Hospital Ningbo People's Republic of China

4. Department of Multi‐Disciplinary Diagnosis and Treatment, Ningbo NO.2 Hospital Ningbo People's Republic of China

Abstract

AbstractPurposeBy constructing a prediction model of carpal tunnel syndrome (CTS) based on ultrasound images, it can automatically and accurately diagnose CTS without measuring the median nerve cross‐sectional area (CSA).MethodsA total of 268 wrists ultrasound images of 101 patients diagnosed with CTS and 76 controls in Ningbo NO.2 Hospital from December 2021 to August 2022 were retrospectively analyzed. The radiomics method was used to construct the Logistic model through the steps of feature extraction, feature screening, reduction, and modeling. The area under the receiver operating characteristic curve was calculated to evaluate the performance of the model, and the diagnostic efficiency of the radiomics model was compared with two radiologists with different experience.ResultsThe 134 wrists in the CTS group included 65 mild CTS, 42 moderate CTS, and 17 severe CTS. In the CTS group, 28 wrists median nerve CSA were less than the cut‐off value, 17 wrists were missed by Dr. A, 26 wrists by Dr. B, and only 6 wrists were missed by radiomics model. A total of 335 radiomics features were extracted from each MN, of which 10 features were significantly different between compressed and normal nerves, and were used to construct the model. The area under curve (AUC) value, sensitivity, specificity, and accuracy of the radiomics model in the training set and testing set were 0.939, 86.17%, 87.10%, 86.63%, and 0.891, 87.50%, 80.49%, and 83.95%, respectively. The AUC value, sensitivity, specificity, and accuracy of the two doctors in the diagnosis of CTS were 0.746, 75.37%, 73.88%, 74.63% and 0.679, 68.66%, 67.16%, and 67.91%, respectively. The radiomics model was superior to the two‐radiologist diagnosis, especially when there was no significant change in CSA.ConclusionRadiomics based on ultrasound images can quantitatively analyze the subtle changes in the median nerve, and can automatically and accurately diagnose CTS without measuring CSA, especially when there was no significant change in CSA, which was better than radiologists.

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging

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