Dhanoo Andrew S, Ramroach Sterling K, Hill-Briggs Felicia, Cockburn Brian N
Department of Life Sciences, University of the West Indies, St. Augustine, St. Augustine, Trinidad and Tobago.
Department of Electrical and Computer Engineering, University of the West Indies, St. Augustine, St. Augustine, Trinidad and Tobago.
Diabetes Spectr. 2024 Spring;37(2):139-148. doi: 10.2337/ds23-0042. Epub 2024 Feb 5.
The objective of this study was to develop ANcam, a novel method for identifying acanthosis nigricans (AN) using a smartphone camera and computer-aided color analysis for noninvasive screening of people with impaired glucose tolerance (IGT).
Adult and juvenile participants with or without diagnosed type 2 diabetes were recruited in Trinidad and Tobago. After obtaining informed consent, participants' history, demographics, anthropometrics, and A1C were collected and recorded. Three subject matter experts independently graded pictures of the posterior neck and upper back using the ANcam smartphone application and Burke methods. A correlation matrix investigated 25 color channels for association with hyperpigmentation, and the diagnostic thresholds were determined with a receiver operating characteristic curve analysis.
For the 227 participants with captured images and A1C values, the cyan/magenta/yellow/black (CMYK) model color channel CMYK_K was best correlated with IGT at an A1C cutoff of 5.7% (39 mmol/mol) ( = 0.45, <0.001). With high predictive accuracy (area under the curve = 0.854), the cutoff of 7.67 CMYK_K units was chosen, with a sensitivity of 81.1% and a specificity of 70.3%. ANcam had low interrater variance ( = 1.99, = 0.137) compared with Burke grading ( = 105.71, <0.001). ANcam detected hyperpigmentation on the neck at double the self-reported frequency. Elevated BMI was 2.9 (95% CI 1.9-4.3) times more likely, elevated blood pressure was 1.7 (95% CI 1.2-2.4) times more likely, and greater waist-to-hip ratio was 2.3 (95% CI 1.4-3.6) times more likely with AN present.
ANcam offers a sensitive, reproducible, and user-friendly IGT screening tool to any smartphone user that performs well with most skin tones and lighting conditions.
本研究的目的是开发一种名为ANcam的新方法,该方法利用智能手机摄像头和计算机辅助颜色分析来识别黑棘皮病(AN),用于对糖耐量受损(IGT)人群进行无创筛查。
在特立尼达和多巴哥招募了有或无2型糖尿病诊断的成年和青少年参与者。在获得知情同意后,收集并记录参与者的病史、人口统计学、人体测量学和糖化血红蛋白(A1C)。三位主题专家使用ANcam智能手机应用程序和伯克方法对后颈部和上背部的图片进行独立评分。相关矩阵研究了25个颜色通道与色素沉着过度的关联,并通过受试者工作特征曲线分析确定诊断阈值。
对于227名有捕获图像和A1C值的参与者,青色/品红色/黄色/黑色(CMYK)模型颜色通道CMYK_K在A1C临界值为5.7%(39 mmol/mol)时与IGT的相关性最佳( = 0.45, <0.001)。在预测准确性较高(曲线下面积 = 0.854)的情况下,选择7.67个CMYK_K单位的临界值,灵敏度为81.1%,特异性为70.3%。与伯克评分( = 105.71, <0.001)相比,ANcam的评分者间差异较低( = 1.99, = 0.137)。ANcam检测到颈部色素沉着过度的频率是自我报告频率的两倍。存在AN时,BMI升高的可能性是原来的2.9倍(95%置信区间1.9 - 4.3),血压升高的可能性是原来的1.7倍(95%置信区间1.2 - 2.4),腰臀比增大的可能性是原来的2.3倍(95%置信区间1.4 - 3.6)。
ANcam为任何智能手机用户提供了一种敏感、可重复且用户友好的IGT筛查工具,在大多数肤色和光照条件下都能表现良好。