Objectives: To evaluate the diagnostic accuracy of infrared thermography (IT) using temperature difference (ΔT) and gray-level co-occurrence matrix (GLCM)-based textural parameters for detecting patellar tendinopathy (PT) in athletes, and to determine the optimal region of interest (ROI) size for analysis.
Design: Cross-sectional study following STARD criteria.
Setting: Physical therapy center with controlled environmental conditions.
Participants: 54 athletes (27 with unilateral PT; 27 healthy controls).
Main outcome measures: Temperature differences (ΔT) and GLCM features (energy, homogeneity, contrast, correlation, entropy) from thermal images of tendon and knee ROIs.
Results: Athletes with PT showed higher ΔT in the tendon ROI (0.5 ± 0.36 °C vs. 0.2 ± 0.20 °C; d = 0.77; p = 0.013). Among GLCM parameters, tendon ROI correlation (TCOR) differed significantly between groups (p = 0.042). Diagnostic performance analysis identified ΔT as the best single variable (AUC 0.83; sensitivity 78 %; specificity 78 %). The ΔT + GLCM combination achieved highest accuracy for tendon ROI (AUC 0.93). The patellar tendon-specific ROI provided better discrimination than the knee ROI.
Conclusions: IRT combined with GLCM enhances PT diagnostic precision, with the tendon ROI optimal for detecting local physiological differences. This accessible multimodal approach could complement clinical diagnosis in athletes.
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