Detection of inflammation from finger temperature profile in rheumatoid arthritis

Jolanta Pauk , Mikhail Ihnatouski , Agnieszka Wasilewska

Abstract

Rheumatoid arthritis (RA) is a chronic inflammatory tissue disease that leads to cartilage, bone, and periarticular tissue damage. This study aimed to investigate whether the use of infrared thermography and measurement of temperature profiles along the hand fingers could detect the inflammation and improve the diagnostic accuracy of the cold provocation test (0 °C for 5 s) and rewarming test (23 °C for180 s) in RA patients. Thirty RA patients (mean age = 49.5 years, standard deviation = 13.0 years) and 22 controls (mean age = 49.8 years, standard deviation = 7.5 years) were studied. Outcomes were the minimal and maximal: baseline temperature (T1), the temperature post-cooling (T2), the temperature post-rewarming (T3), and the Tmax-Tmin along the axis of each finger. The statistical significance was observed for the thumb, index finger, middle finger, and ring finger postcooling and post-rewarming. Receiver operating characteristics (ROC) analysis to distinguish between the two groups revealed that for the thumb, index finger, middle finger, and ring finger, the area under the ROC curve was statistically significantly (p < 0.05) post-cooling. The cold provocation test used in this study discriminates between RA patients and controls and detects an inflammation in RA patients by the measurement of temperature profiles along the fingers using an infrared camera.
Author Jolanta Pauk (FME / DACR)
Jolanta Pauk,,
- Department of Automatic Control and Robotics
, Mikhail Ihnatouski
Mikhail Ihnatouski,,
-
, Agnieszka Wasilewska
Agnieszka Wasilewska,,
-
Journal seriesMedical & Biological Engineering & Computing, [Medical and Biological Engineering and Computing], ISSN 0140-0118, e-ISSN 1741-0444, (N/A 70 pkt)
Issue year2019
Vol57
No12
Pages2629-2639
Publication size in sheets0.5
Keywords in EnglishThermography, Fingers, Rheumatoid arthritis, DFS algorithm, Image processing
ASJC Classification1706 Computer Science Applications; 2204 Biomedical Engineering
DOIDOI:10.1007/s11517-019-02055-1
URL https://link.springer.com/content/pdf/10.1007/s11517-019-02055-1.pdf
Internal identifierROC 19-20
Languageen angielski
LicenseJournal (articles only); published final; Uznanie Autorstwa (CC-BY); with publication
Score (nominal)70
Score sourcejournalList
ScoreMinisterial score = 70.0, 12-02-2020, ArticleFromJournal
Publication indicators Scopus SNIP (Source Normalised Impact per Paper): 2017 = 1.12; WoS Impact Factor: 2018 = 2.039 (2) - 2018=2.158 (5)
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