Ultrasound-based Artificial Intelligence for Classification of Carpal Tunnel Syndrome

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

500 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-11-15

Study Completion Date

2026-12-30

Brief Summary

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Carpal tunnel syndrome (CTS) is one of the most prevalent peripheral neuropathies, impacting approximately 4% of the general population. It is typically classified into three degrees: mild, moderate, and severe. Accurate grading of carpal tunnel syndrome (CTS) is essential for determining appropriate treatment options, thereby playing a crucial role in optimizing patient outcomes. Electrophysiological testing (EST) is a key parameter for grading carpal tunnel syndrome (CTS). However, it is limited by several factors, including its invasive nature, poor reproducibility, and reduced sensitivity for detecting early-stage disease. Recently, ultrasound has gained widespread acceptance among clinicians for the assessment and grading of CTS. Nonetheless, radiologists often encounter challenges in this process due to the variability in image quality, differences in experience, and inherent subjectivity.

To address these issues, artificial intelligence presents a promising solution. Therefore, this study aims to develop a deep learning model for grading CTS by leveraging multimodal imaging features, including B-mode ultrasound, superb microvascular imaging (SMI), and elastography. Additionally, the investigators intend to validate the model's effectiveness by testing it with images from various clinical centers, ensuring its generalizability across different clinical settings.

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Detailed Description

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Conditions

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Carpal Tunnel Syndrome (CTS) Ultrasound Artificial Intelligence (AI)

Study Design

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Observational Model Type

OTHER

Study Time Perspective

PROSPECTIVE

Study Groups

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Prospective test set

ultrasound examination

Intervention Type OTHER

The investigators intend to perform ultrasound examinations for the participants with CTS.

Interventions

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ultrasound examination

The investigators intend to perform ultrasound examinations for the participants with CTS.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* those who have complained about associated symptoms about CTS, including pain, numbness, and weakness of hand.
* those who perform ultrasound examinations of median nerve within 1 week of the symptom.
* those who have electrophysilogical test results as reference standard.

Exclusion Criteria

* those who had a surgery in the affected hand.
* those who had a trauma or fracture in the affected hand.
* those who had rheumatoid-related conditions, autoimmune diseases, and endocrine disorders.

Minimum Eligible Age

18 Years

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No