Juvenile Idiopathic Arthritis: A Review of Novel Diagnostic and Monitoring Technologies

Garner, Amelia J.; Saatchi, Reza; Ward, Oliver; Hawley, Daniel P.

doi:10.3390/healthcare9121683

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Juvenile Idiopathic Arthritis: A Review of Novel Diagnostic and Monitoring Technologies

¹

The Medical School, University of Sheffield, Sheffield S10 2TN, UK

²

Industry and Innovation Research Institute, Sheffield Hallam University, Sheffield S1 1WB, UK

³

Department of Paediatric Rheumatology, Sheffield Children’s Hospital, Sheffield S10 2TH, UK

^*

Author to whom correspondence should be addressed.

Healthcare 2021, 9(12), 1683; https://doi.org/10.3390/healthcare9121683

Submission received: 4 November 2021 / Revised: 1 December 2021 / Accepted: 2 December 2021 / Published: 4 December 2021

(This article belongs to the Special Issue Artificial Intelligence Developments for Medical Diagnosis and Monitoring)

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Abstract

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease of childhood and is characterized by an often insidious onset and a chronic relapsing–remitting course, once diagnosed. With successive flares of joint inflammation, joint damage accrues, often associated with pain and functional disability. The progressive nature and potential for chronic damage and disability caused by JIA emphasizes the critical need for a prompt and accurate diagnosis. This article provides a review of recent studies related to diagnosis, monitoring and management of JIA and outlines recent novel tools and techniques (infrared thermal imaging, three-dimensional imaging, accelerometry, artificial neural networks and fuzzy logic) which have demonstrated potential value in assessment and monitoring of JIA. The emergence of novel techniques to assist clinicians’ assessments for diagnosis and monitoring of JIA has demonstrated promise; however, further research is required to confirm their clinical utility.

Keywords: juvenile idiopathic arthritis; rheumatoid arthritis; artificial intelligence; thermal imaging; accelerometry; fuzzy logic

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MDPI and ACS Style

Garner, A.J.; Saatchi, R.; Ward, O.; Hawley, D.P. Juvenile Idiopathic Arthritis: A Review of Novel Diagnostic and Monitoring Technologies. Healthcare 2021, 9, 1683. https://doi.org/10.3390/healthcare9121683

AMA Style

Garner AJ, Saatchi R, Ward O, Hawley DP. Juvenile Idiopathic Arthritis: A Review of Novel Diagnostic and Monitoring Technologies. Healthcare. 2021; 9(12):1683. https://doi.org/10.3390/healthcare9121683

Chicago/Turabian Style

Garner, Amelia J., Reza Saatchi, Oliver Ward, and Daniel P. Hawley. 2021. "Juvenile Idiopathic Arthritis: A Review of Novel Diagnostic and Monitoring Technologies" Healthcare 9, no. 12: 1683. https://doi.org/10.3390/healthcare9121683

APA Style

Garner, A. J., Saatchi, R., Ward, O., & Hawley, D. P. (2021). Juvenile Idiopathic Arthritis: A Review of Novel Diagnostic and Monitoring Technologies. Healthcare, 9(12), 1683. https://doi.org/10.3390/healthcare9121683

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Juvenile Idiopathic Arthritis: A Review of Novel Diagnostic and Monitoring Technologies

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