Quantifying skin pigment: Comparison of five low-cost devices to the konica minolta CM-700d

Summary: Abstract Body: Background: Validated skin-specific colorimeters are typically expensive, and limited data exists about the performance of low-cost colorimeters in quantifying skin color. Our study evaluates multiple low-cost colorimeters in comparison to the Konica Minolta (KM) CM-700d to determine which may be suitable for ensuring diversity of skin pigment in medical device research. Methods: We used four colorimeters, ColorReaderPRO, AMTAST AMT510, WR10QC, Vinckolor ColorMeter Pro ($100-250), and one spectrocolorimeter, X-Rite RM200QC ($2,000) with the KM as reference. Triplicate individual typology angle (ITA) measurements were taken at the forehead (FH) and upper inner arm (UIA) in 38 adult participants and on color swatches from the Pantone SkinTone (PST) Guide. We compared repeatability, inter-operator variability, and ITA measurements by calculating the color difference using deltaE=√(delta(L2)+delta(a2)+delta(b2)). Results: The study population ITA ranged from 47 to -70 (median 17) at FH, and 60 to -62 (median 28) at UIA. The difference in median deltaE across all devices was <0.12 with three operators. With the PST, the difference in median deltaE across devices was <0.1. The RM200QC had the highest median deltaE at both skin sites. At the FH and UIA, all devices had a median deltaE of less than 0.3, except for the RM200QC (0.8 FH, 0.5 UIA). For the PST, the Mann-Whitney U test showed that the ITA values from all devices were not statistically significantly different from the KM. The same was seen with the skin data, except for the WR-10QC. Conclusion: When analyzing inter-operator variability and repeatability, the difference between median deltaEs is likely not clinically significant. Four of five colorimeters tested produced ITA values comparable to the KM, suggesting that they could possibly be used as lower-cost alternatives. Brandon Alford¹, Lily Ortiz¹, Ella Behnke¹, Danni Chen¹, Caroline Hughes¹, Michael Lipnick¹, Leonid Shmuylovich², Willem Verkruijsse³, Jenna Lester¹, Fekir Negussie¹, Tyler Law¹, Philip Bickler¹, Koyinsola Oyefeso¹, Yajaira Carreon¹, Kelvin Moore¹ 1. University of California San Francisco, San Francisco, CA, United States. 2. Washington University in St Louis, St. Louis, MO, United States. 3. Philips Medical Systems Nederland BV, Best, NB, Netherlands. Pigmentation, Melanoma, and Melanoma Immune Surveillance