The Application of Ultrasound Image‐Based Radiomics in the Diagnosis of Mild Carpal Tunnel Syndrome

Abstract

Objectives The ultrasound diagnosis of mild carpal tunnel syndrome (CTS) is challenging. Radiomics can identify image information that the human eye cannot recognize. The purpose of our study was to explore the value of ultrasound image‐based radiomics in the diagnosis of mild CTS. Methods This retrospective study included 126 wrists in the CTS group and 88 wrists in the control group. The radiomics features were extracted from the cross‐sectional ultrasound images at the entrance of median nerve carpal tunnel, and the modeling was based on robust features. Two radiologists with different experiences diagnosed CTS according to two guidelines. The area under receiver (AUC) operating characteristic curve, sensitivity, specificity, and accuracy were used to evaluate the diagnostic efficacy of the two radiologists and the radiomics model. Results According to guideline one, the AUC values of the two radiologists for CTS were 0.72 and 0.67, respectively; according to guideline two, the AUC were 0.73 and 0.68, respectively. The radiomics model achieved the best accuracy when 16 important robust features were selected. The AUC values of training set and test set were 0.92 and 0.90, respectively. Conclusions The radiomics label based on ultrasound images had excellent diagnostic efficacy for mild CTS. It is expected to help radiologists to identify early CTS patients as soon as possible, especially for inexperienced doctors.

The Potential of Ultrasound Radiomics in Carpal Tunnel Syndrome Diagnosis: A Systematic Review and Meta-Analysis

“…Their initial study [21] aimed to compare the impact of changes as regards the setting of region of interest setting (i.e., inclusion vs. exclusion of the epineurium) on the diagnostic performance of ultrasound radiomics. In their subsequent study [22], they explored the potential application of ultrasound radiomics in diagnosing mild CTS. Finally, their third study [20] focused on emphasizing the importance of utilizing specific characteristics of ultrasonic images for diagnosing CTS, without the need to measure their cross-sectional area.…”

“…Concerning the seven criteria in the QUADAS-2 tool, two studies [21,24] did not meet the criteria for assessing the risk of bias related to flow and timing. Only three studies [20,22,23] clearly defined a specific time interval between the electrodiagnostic test and the ultrasound examination. In three studies conducted by Lyu et al [21,23,24], there was a lack of specification regarding exclusion criteria, which raised concerns about the applicability of their patient selection process.…”

Radiomics based on ultrasound images for diagnosis of minimal breast cancer

“…7 Presently, research on radiomics in breast cancer predominantly concentrates on tasks such as distinguishing between benign and malignant cases, molecular typing differentiation, assessing the effectiveness of chemotherapy, prognostic evaluation, recurrence scoring, metastasis assessment, and radiogenomics. [8][9][10] In this issue of the Journal of Clinical Ultrasound, Shuyi LYU et al 11 How should we interpret these results? When utilizing radiomics, a vast amount of information is extracted from ultrasound images and analyzed using mathematical algorithms, revealing features that are imperceptible to the naked eye.…”