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关于皮肤镜中黑色细胞特征的存在和空间定位的专家协议
Konstantinos Liopyris1, Cristian Navarrete-Dechent2, Michael A Marchetti3
1Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, USA; Department of Dermatology, Andreas Syggros Hospital of Cutaneous & Venereal Diseases, University of Athens, Athens, Greece.
The Journal of investigative dermatology
|September 9, 2023
概括
专家关于皮肤镜检测黑色素瘤特征的专家协议使用示例图像进行了改进. 颜料网络和不规则球体等关键特征显示出高度共识,有助于诊断和机器学习应用.
科学领域:
- 皮肤病学 皮肤病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 皮肤透视对于黑色素瘤检测至关重要,但专家对特定特征的一致意见往往很低.
- 解释皮肤镜像的变化可能会影响诊断准确性和临床决策.
研究的目的:
- 通过使用示例图像,评估专家对黑色细胞特异性皮肤学特征及其空间定位的共识.
- 为了识别具有高观察者间可靠性的皮肤镜特征,以改善黑色素瘤诊断.
主要方法:
- 一个横截面的,多中心的观测研究,涉及25名世界专家提交皮肤镜像.
- 20名专家读者在一个网络平台上注释了248张图像,标记了特定的区域 (超级像素).
- 分析了由五位独立读者审查的图像集合中的4,507个特征观测.
主要成果:
- 在31个特征中,14个特征 (45.2%) 达成了良好至优秀的协议.
- 八个特征表现出了很好的一致性 (Gwet的AC>0.75),其中包括七个黑色素瘤特征.
- 在颗粒度,闪亮的白色条纹,典型的色素网络,不规则的斑点,负网络,不规则的球体,点状血管和蓝白色面方面观察到高度一致.
结论:
- 使用示例数据集显著改善了对关键皮肤镜特征的专家协议.
- 具有高度共识的识别特征对于区分瘤和黑色素瘤是有价值的.
- 公共数据集可用于教育,科学和机器学习目的.
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