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

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.

A Novel Algorithm Using Within-leg Calibration for Enhanced Accuracy of Detection of Arthritis by Infrared Thermal Imaging in Children.

OBJECTIVE: To standardize and improve the accuracy of detection of arthritis by thermal imaging. METHODS: Children with clinically active arthritis in the knee or ankle, as well as healthy controls, were enrolled to the development cohort; another group of children with knee symptoms was enrolled to the validation cohort. Ultrasound was performed in the arthritis subgroup for the development cohort. Joint exam by certified rheumatologists was used as a reference for the validation cohort. Infrared thermal data were analyzed using custom software. Temperature after within-limb calibration (TAWiC) was defined as the temperature differences between joint and ipsilateral mid-tibia. TAWiC of knees and ankles was evaluated using ANOVA across subgroups. Optimal thresholds were determined by receiver-operating characteristic analysis using Youden index. RESULTS: There were significant differences in mean and 95th TAWiC of knee in anterior, medial, lateral views, and of ankles in anterior view, between inflamed and uninflamed counterparts (P < 0.05). The area under the curve was higher by 30% when using TAWiCknee than that when using absolute temperature. Within the validation cohort, the sensitivity of accurate detection of arthritis in the knees using both mean and 95th TAWiC from individual views or all 3 views combined ranged from 0.60 to 0.70, and the specificity was > 0.90 in all views. CONCLUSION: Children with active arthritis or tenosynovitis in knees or ankles exhibited higher TAWiC than healthy joints. Our validation cohort study showed promise for the clinical utility of infrared thermal imaging for arthritis detection.