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Original Articles

Relationships between the changes of skin temperature and radiation skin injury

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Pages 1159-1166 | Received 26 Jun 2019, Accepted 23 Oct 2019, Published online: 21 Nov 2019
 

Abstract

Background: Radiation skin injury (RSI) causes changes in skin temperature, but detailed information on the thermographic responses is currently lacking. We investigated thermographic patterns after radiotherapy. We hypothesized that skin temperature may be used as a diagnostic and early predictor of RSI severity.

Method: All breast cancer patients received radiotherapy after unilateral postmastectomy. The contralateral supraclavicular area served as control, and the frontal thermal image of torso was taken by a thermal infrared imager weekly. We defined areas of interest on bilateral symmetrical supraclavicular area, and analyzed the difference of average and maximum skin temperature (DSTaverage and DSTmax) between them. The extent of the weekly variation in DST (DSTW) was calculated using a mathematical formula to represent a trend of skin temperature change. RSI and symptoms related to RSI were scored from baseline to 2 weeks after the end of radiotherapy.

Results: Forty-one patients were enrolled in this study. In comparison to the baseline, the DSTaverage and DSTmax increased significantly over time during radiotherapy (p < .05). The onset of DST increase was accompanied by the onset of radiation dermatitis, and the maximal DST also appeared at the peak of Radiation Therapy Oncology Group (RTOG) and symptom scores. Radiation dose, DSTaverage, burning-feeling and pulling were the independent variables affecting RTOG score according to multivariate analysis (p < .001, p < .034, p < .001, p < .001). Patients with DSTWaverage >1.223 or DSTWmax >1.114 in second week showed a late higher dermatitis score (RTOG score ≥2).

Conclusion: This study confirmed that RSI was associated with thermographic response. Our results suggested that the follow-up observations of skin temperature during radiotherapy could provide the objective evaluation criteria and prediction methods for RSI.

Disclosure statement

The authors report no conflict of interest.

Additional information

Funding

This work funded by National Natural Science Foundation of China (81572970), Shandong Provincial Natural Science Foundation (No. ZR2016HM35) and the grants from Shandong Provincial key scientific and technological project of China (2018GSF118232).