Automated Arthritis Detection Using Artificial Intelligence on Smartphone Photographs (AISynovitis)

Med2Measure

Status: Active, not recruiting

Conditions: Inflammatory Arthritis; Rheumatoid Arthritis &Amp; Other Inflammatory Polyarthropathies; Peripheral Spondyloarthritis

Treatments: Diagnostic Test: AI assisted smartphone diagnosis

Study type: Observational

Funder types: Industry; Other

Identifiers

NCT06715488

M2M-ID0001

Details and patient eligibility

About

The investigators are testing the ability of convolutional neural networks (CNNs), that is artificial intelligence, on smartphone photographs in detecting inflammatory arthritis. This promises to be an efficient, accurate, and non-invasive diagnostic tool that will significantly improve early detection and management of inflammatory arthritis.

Full description

Over the past 4 years the investigators have aimed to help the early detection of arthritis leveraging artificial intelligence. This project aims to detect arthritis based on smart phone photographs of joint areas that make it scalable and available in the community. This group first developed a compelling proof-of-concept pipeline and models using 100 patients. (published in Frontiers in Medicine, Nov 2023, wherein they demonstrated that this technology works with reasonable accuracy in the lab, viz Technology Readiness Level currently stands at 3-4). They followed with a newer paper (submitted for publication, available on preprint server MedRxiv) that trained two different CNNs, a screening CNN on uncropped hands that distinguishes patients from controls followed by joint specific detections.

The system involves supporting infrastructure that will enable efficient detection of arthritis. This includes

1. Collection of photos in a standardized manner using custom designed boxes
2. Using and testing a browser pipeline
3. The CNN models will be trained on the dataset of photographs taken in this and results will be deployed to doctors in the community. This ensures a doctor in the loop that can later take action on the results for further confirmatory tests or management.
4. Understanding knowledge, attitude of patients and doctors towards AI in clinical decision making algorithms

This is a Prospective, non-interventional study and this project only involves an investigator taking a smartphone photograph of some joint areas kept in standardized positions. This involves no risk to the patient.

Enrollment: 3,000 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Inflammatory arthritis of any etiology

Exclusion criteria

• Severe deformity that hampers standardization of photographs

Trial design

3,000 participants in 1 patient group

Inflammatory arthritis

Description:

Patients with inflammatory arthritis regardless of etiology including rheumatoid arthritis, psoriatic arthritis, systemic lupus erythematosis and viral arthritis

Treatment:

Diagnostic Test: AI assisted smartphone diagnosis