Validating within-limb calibrated algorithm using a smartphone attached infrared thermal camera for detection of arthritis in children

Erin Balay-Dustrude; Nivrutti Bhide; Joshua Scheck; Erin Sullivan; Kevin Cain; Debosmita Biswas; Savannah C Partridge; Yongdong Zhao

doi:10.1016/j.jtherbio.2022.103437

Validating within-limb calibrated algorithm using a smartphone attached infrared thermal camera for detection of arthritis in children

J Therm Biol. 2023 Jan:111:103437. doi: 10.1016/j.jtherbio.2022.103437. Epub 2022 Dec 19.

Authors

Erin Balay-Dustrude¹, Nivrutti Bhide², Joshua Scheck³, Erin Sullivan², Kevin Cain⁴, Debosmita Biswas⁵, Savannah C Partridge⁵, Yongdong Zhao⁶

Affiliations

¹ Pediatric Rheumatology, Seattle Children's Hospital, Department of Pediatrics, University of Washington, Seattle, WA, USA.
² Center for Clinical and Translational Research, Seattle Children's Research Institute, Seattle, WA, USA.
³ Pediatric Rheumatology, Seattle Children's Hospital, Department of Pediatrics, University of Washington, Seattle, WA, USA; Center for Clinical and Translational Research, Seattle Children's Research Institute, Seattle, WA, USA.
⁴ Department of Statistics, School of Nursing, University of Washington, Seattle, WA, USA.
⁵ Department of Radiology, University of Washington, Seattle, WA, USA.
⁶ Pediatric Rheumatology, Seattle Children's Hospital, Department of Pediatrics, University of Washington, Seattle, WA, USA; Center for Clinical and Translational Research, Seattle Children's Research Institute, Seattle, WA, USA. Electronic address: Yongdong.zhao@seattlechildrens.org.

PMID: 36585071
DOI: 10.1016/j.jtherbio.2022.103437

Abstract

Objectives: To determine the impact of physical activity on temperature after within-limb calibration (TAWiC) measures and their reproducibility. To determine if thermal imaging from a smartphone attached thermal camera is comparable to thermal imaging using a handheld thermal camera for detection of arthritis in children.

Methods: Children without symptoms were enrolled to the "asymptomatic exercise cohort", and received infrared imaging, using a standard handheld camera, after initial resting period, after activity, and after second resting period. Children seen in the rheumatology clinic with knee pain were enrolled into the "symptomatic knee pain cohort" and received imaging with both the smartphone-attached and handheld cameras before a routine clinical exam. TAWiC was defined as the temperature differences between joint and ipsilateral mid-tibia as the main readout for arthritis detection.

Results: The asymptomatic exercise cohort demonstrated notable changes in absolute and TAWiC temperatures collected by thermal imaging after physical activity, and temperatures did not consistently return to pre-activity levels after a second period of rest. The 95th TAWiC from anterior view were, resting one -0.1 C (0.5), activity -0.7 C (0.5), resting two -0.2 C (0.6) (resting 1 vs resting 2, p-value = 0.13). In the symptomatic knee pain cohort, the smartphone attached and handheld thermal cameras performed similarly in regards to detection of joint inflammation and evaluation of joint temperature using the TAWiC algorithm, with high sensitivity of 80% (55.2-100.0%) and specificity of 84.2% (76.0-92.4%) in the anterior knee view when compared with the gold standard joint exam performed by a pediatric rheumatologist. The mean 95th TAWiC temperature difference between the two cameras was -0.1 C (-0.1 to 0.0) (p = 0.0004).

Conclusions: This study showed continued validity of the TAWiC algorithm across two distinct thermal camera platforms and demonstrates promise for improved accessibility and utility of this technology for arthritis detection.

Keywords: Ankle; Juvenile idiopathic arthritis; Knee; Pediatric rheumatology; Telemedicine; Thermal imaging.

MeSH terms

Arthritis*
Body Temperature
Child
Humans
Pain
Reproducibility of Results
Smartphone*