Clinical Study of Magnetic Resonance Imaging and Deep Learning of Joint Synovial Disease

Completed

• Conditions: Gout; Rheumatoid Arthritis; Synovial Diseases; Pigmented Villonodular Synovitis
• Interventions: Diagnostic Test: Synovitis diagnosis

• Registration Number: NCT04952896
• Lead Sponsor: Peking University Third Hospital

Brief Summary

Through the high-throughput feature extraction of magnetic resonance images, the deep learning prediction model of joint synovial lesions is constructed used for the diagnosis, differential diagnosis and curative effect monitoring of joint synovial lesions.

Detailed Description

The study applies magnetic resonance and deep learning (DL) to the diagnosis of joint synovial lesions, aims to have a more comprehensive understanding of the pathophysiology of the occurrence and development of joint synovial lesions. As a non-invasive imaging method to assess the condition of the disease, DL methods excavates the deep features contained in the image, quantifies the joint synovial lesions, and then gives more information to the clinician in the diagnosis and differential diagnosis of the joint synovial lesions, provide important information for the planning of individualized treatment plans for patients with joint synovial diseases.

Study Timeline

• Study Start: 2012-01-01
• Study First Submitted: 2021-06-29
• Study First Submitted QC: 2021-06-29
• Study First Posted: 2021-07-07
• Primary Completion: 2022-03-31
• Status Verified: 2022-05
• Study Completion: 2022-10-29
• Last Update Submitted: 2022-10-29
• Last Update Posted: 2022-11-02

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 350

Inclusion Criteria

1. Patients diagnosed with joint synovial disease through radiological examination, arthroscopy or pathological biopsy of the joint, or whose clinical manifestations meet the diagnostic criteria of the American College of Rheumatology (ACR) for joint synovial disease.
2. Patients received pre-treatment MR.

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Exclusion Criteria

1. Patients who have received surgery, medication or other systemic treatment before standardized MRI scan.
2. Poor image quality.
3. Articular hemorrhage.

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Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Group of patients with pigmented villonodular synovitis	Synovitis diagnosis	Diagnosis confirmed by arthroscopic pathological biopsy.
Group of patients with rheumatoid arthritis	Synovitis diagnosis	Diagnosis determined by clinical history, laboratory tests and arthroscopic pathology biopsy.
Group of patients with gout	Synovitis diagnosis	Diagnosis was determined by laboratory tests, energy spectrum imaging and arthroscopic pathology biopsy.

Primary Outcome Measures

Name	Time	Method
Patient's diagnosis	2019-2022	Type of synovitis disease in patients with a clear comprehensive diagnosis

Trial Locations

Locations (1)

Peking University third hospital; 🇨🇳 Beijing, Please Select An Option Below, China