Introduction: Radiation-induced dermatitis (RID) is routinely graded by visual inspection. Inter-observer variability makes this approach inadequate for an objective assessment of the efficacy of different topical treatments. In this study we report on the first clinical application of a new image-analysis tool developed to measure the relevant effects quantitatively and to compare the effects of two different topical preparations used to treat RID.
Materials and methods: After completion of radiotherapy, RID was retrospectively assessed in 100 white female breast cancer patients who had received adjuvant breast irradiation. Of these patients, 34 were treated with R1&R2, a Lactokine-fluid derived from milk proteins, and 66 were treated with Bepanthen. In addition RID was graded independently by two experienced radiation oncologists in accordance with the Common Terminology Criteria for Adverse Events (CTCAE). For quantitative evaluation, the irradiated breast and the non-irradiated contralateral breast were photographed in a standardized manner including a color reference card. For analysis, all images were converted into the color space L*a*b* and mean values were calculated for each of the color parameters.
Results: The CTCAE-based grading revealed statistically significant inter-observer variability in the scoring of RID Grades 1, 2 and 3 (p<0.001). A difference between the two topical products could not be observed with visual inspection. By using augmented image analysis methods a statistically significant increase in a*-values (mean 4.15; 95%CI: 5.97-2.33, p<0.001) in patients treated with R1&R2 indicated more intense reddening. Digital subtraction was used to eliminate differences in individual baseline skin tone to generate a new, low-scatter parameter (ΔSEV).
Conclusions: Visual CTCAE-based evaluation of RID was not suitable for assessing the efficacy of the skin treatment products. In contrast, the novel image analysis enabled a quantitative evaluation independent of skin type and baseline skin tone in our cohort suggesting that augmented image analysis may be a suitable tool for this type of investigation. Prospective studies are needed to validate our findings.