A New Infrared Thermography Based Approach to Ankylosing Spondylitis Assessment: A Preliminary Study.

Authors

Zede Wang, Ningning Li, Liming Chen, Bingbing Dai, Yuxin Wang, Yige Liu, Qingxi Zhang, Qi Qian, Mengxin Tu

Published in

Journal of imaging informatics in medicine. Jul 13, 2026. Epub Jul 13, 2026.

Abstract

The clinical assessment of ankylosing spondylitis (AS) traditionally relies on hospital-based procedures, imposing a significant time and economic burden on patients. To address this challenge, this study proposes a non-contact, home-based method for assessing AS status by analyzing infrared thermal images of the knee. Specifically, we propose an Adaptive Weight U-Net (AWU) framework to compute the temperature difference ( $\Delta T$ ) between the knee joint and peripheral skin. This $\Delta T$ is used to classify healthy individuals, patients with inactive AS, and patients with active AS. We further investigate the correlation between knee inflammation and AS status by evaluating the relationship between $\Delta T$ and two key clinical inflammatory markers, C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR). In a dataset of 221 participants (72 healthy, 77 inactive AS, 72 active AS), the framework achieves a classification accuracy of $77.38\%$ , with perfect discrimination between healthy and active AS cases. Kendall's correlation analysis reveals a moderate positive correlation between $\Delta T$ and CRP ( $\tau =0.5920$ , $p<0.001$ ) and a weak positive correlation with ESR ( $\tau =0.4236$ , $p<0.001$ ). The results indicate the potential of infrared thermography as a complementary tool for AS assessment and home monitoring.

PMID:
42443648
Bibliographic data and abstract were imported from PubMed on 14 Jul 2026.

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