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Predictive Clinical Diagnosis of Rheumatoid Arthritis Flares Using Non-Invasive Infra-red Thermal Imaging and an AI/ML Algorithm

NCT05124990 · Status: NO_LONGER_AVAILABLE · Type: EXPANDED_ACCESS

Last updated 2021-11-26

No results posted yet for this study

Summary

The hypothesis for this clinical research project is that the severity of RA may be detected and predicted using an optimized ML/AI algorithm that uses infrared thermal images of inflamed joints and standard clinical RA-related markers (i.e., ESR and CRP) by computing DAS-28 ESR scores in real-time. The infrared thermal images coupled with clinical laboratory markers and the ML/AI algorithm are expected to assist a practicing clinician in the RA diagnosis and the prediction of the occurrence of flares in RA patients. Physicians who use this technology, would need minimum training and will be able to accurately and reliably diagnose RA using a cheaper method which does not involve incident radiation emitted by other imaging modalities such a X-RAY, musculoskeletal (MSK) ultrasound, or a magnetic resonance imaging (MRI). The aim would be to have the Infrared thermal imaging devices at remote VA clinics that do not have a rheumatology specialist where veterans can go for their inflammatory arthritis flare and get this image by the local VA RN. These clinical results can then be assessed by and discussed with a Rheumatologist via telehealth visits.

Conditions

Interventions

DIAGNOSTIC_TEST

thermal imaging

no risk infrared thermal image would be used to capture pictures of the patients joints that are reported to be painful during a rheumatoid arthritis flare along iwth labs such as esr and crp. these will then be fed to a machine learning algorithm that will learn to predict the DAS 28 score for the RA patient and their flare.

Sponsors & Collaborators

  • Vivadox

    collaborator UNKNOWN

  • Infrared Cameras Incorporate

    collaborator INDUSTRY

  • North Florida Foundation for Research and Education

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
99 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05124990 on ClinicalTrials.gov