Background: Patients with skin lesions suspicious for skin cancer or atypical melanocytic nevi of uncertain malignant potential often present to dermatologists, who may have variable dermoscopy triage clinical experience. Objective: To evaluate the clinical utility of a digital dermoscopy image-based artificial intelligence algorithm (DDI-AI device) on the diagnosis and management of skin cancers by dermatologists. Methods: Thirty-six United States board-certified dermatologists evaluated 50 clinical images and 50 digital dermoscopy images of the same skin lesions (25 malignant and 25 benign), first without and then with knowledge of the DDI-AI device output. Participants indicated whether they thought the lesion was likely benign (unremarkable) or malignant (suspicious). Results: The management sensitivity of dermatologists using the DDI-AI device was 91.1%, compared to 84.3% with DDI, and 70.0% with clinical images. The management specificity was 71.0%, compared to 68.4% and 64.9%, respectively. The diagnostic sensitivity of dermatologists using the DDI-AI device was 86.1%, compared to 78.8% with DDI, and 63.4% with clinical images. Diagnostic specificity using the DDI-AI device increased to 80.7%, compared to 75.9% and 73.6%, respectively. Conclusion: The use of the DDI-AI device may quickly, safely, and effectively improve dermoscopy performance, skin cancer diagnosis, and management when used by dermatologists, independent of training and experience.
背景：皮肤科医生常接诊疑似皮肤癌或恶性潜能不确定的非典型黑素细胞痣患者，但临床医生在皮肤镜分诊方面的经验存在差异。目的：评估基于数字皮肤镜图像的人工智能算法（DDI-AI设备）对皮肤科医生诊断和管理皮肤癌的临床效用。方法：36名美国认证皮肤科医生评估了相同皮损的50张临床图像和50张数字皮肤镜图像（25例恶性，25例良性），先在不了解DDI-AI设备输出结果的情况下评估，后在获知设备输出结果的情况下再次评估。参与者需判断皮损可能为良性（无异常）或恶性（可疑）。结果：使用DDI-AI设备时，皮肤科医生的管理敏感度为91.1%，而仅使用数字皮肤镜图像时为84.3%，仅使用临床图像时为70.0%。管理特异度分别为71.0%、68.4%和64.9%。使用DDI-AI设备时，诊断敏感度为86.1%，而仅使用数字皮肤镜图像时为78.8%，仅使用临床图像时为63.4%。使用DDI-AI设备时诊断特异度提升至80.7%，而仅使用数字皮肤镜图像时为75.9%，仅使用临床图像时为73.6%。结论：DDI-AI设备的使用可快速、安全、有效地提升皮肤科医生的皮肤镜判读能力、皮肤癌诊断及管理水平，且其效果不受培训背景与临床经验影响。
肿瘤(癌症)患者之家