Laboratory of Investigative Dermatology, The Rockefeller University, New York, NY, USA.
Department of Dermatology, Johns Hopkins Hospital, Columbia, MD, USA.
Exp Dermatol. 2021 Mar;30(3):377-383. doi: 10.1111/exd.14224. Epub 2020 Nov 30.
Physician rating of cutaneous erythema is central to clinical dermatological assessment as well as quantification of outcome measures in clinical trials in a number of dermatologic conditions. However, issues with inter-rater reliability and variability in the setting of higher Fitzpatrick skin types make visual erythema assessment unreliable. We developed and validated a computer-assisted image-processing algorithm (EQscore) to reliably quantify erythema (across a range of skin types) in the dermatology clinical setting. Our image processing algorithm evaluated erythema based upon green light suppression differentials between affected and unaffected skin. A group of four dermatologists used a 4-point Likert scale as a human evaluation of similar erythematous patch tests. The algorithm and dermatologist scores were compared across 164 positive patch test reactions. The intra-class correlation coefficient of groups and the correlation coefficient between groups were calculated. The EQscore was validated on and independent image set of psoriasis, minimal erythema dose testing and steroid-induced blanching images. The reliability of the erythema quantification method produced an intra-class correlation coefficient of 0.84 for the algorithm and 0.67 for dermatologists. The correlation coefficient between groups was 0.85. The EQscore demonstrated high agreement with clinical scoring and superior reliability compared with clinical scoring, avoiding the pitfalls of erythema underrating in the setting of pigmentation. The EQscore is easily accessible (http://lab.rockefeller.edu/krueger/EQscore), user-friendly, and may allow dermatologists to more readily and accurately rate the severity of dermatological conditions and the response to therapeutic treatments.
医师对皮肤红斑的评估是临床皮肤科评估的核心，也是许多皮肤科疾病临床试验中量化结局指标的关键。然而，在较高的 Fitzpatrick 皮肤类型下，存在着评估者间可靠性和可变性的问题，使得视觉红斑评估变得不可靠。我们开发并验证了一种计算机辅助图像处理算法（EQscore），可在皮肤科临床环境中可靠地量化红斑（包括各种皮肤类型）。我们的图像处理算法根据受影响和未受影响皮肤之间绿光抑制的差异来评估红斑。一组四名皮肤科医生使用 4 分李克特量表作为对类似红斑斑贴试验的人类评估。比较了算法和皮肤科医生评分在 164 个阳性斑贴试验反应中的表现。计算了组内相关性系数和组间相关性系数。在独立的银屑病、最小红斑量测试和皮质类固醇诱导的褪色图像数据集上验证了 EQscore。红斑量化方法的可靠性产生了算法的组内相关系数为 0.84，皮肤科医生的组内相关系数为 0.67。组间相关性系数为 0.85。EQscore 与临床评分高度一致，与临床评分相比具有更高的可靠性，避免了在色素沉着的情况下低估红斑的陷阱。EQscore 易于访问（http://lab.rockefeller.edu/krueger/EQscore），用户友好，并且可以使皮肤科医生更轻松、更准确地评估皮肤病的严重程度和治疗反应。
