Yazdanparast Taraneh, Shamsipour Mansour, Ayatollahi Azin, Delavar Shohreh, Ahmadi Maryam, Samadi Aniseh, Firooz Alireza
From the Center for Research and Training in Skin Diseases and Leprosy, Tehran University of Medical Sciences, Tehran, Iran.
Department of Research Methodology and Data Analysis, Tehran University of Medical Sciences, Tehran, Iran.
Indian J Dermatol. 2024 Jul-Aug;69(4):296-300. doi: 10.4103/ijd.ijd_61_24. Epub 2024 Aug 19.
Rapid diagnosis of melanoma is necessary for a good prognosis. Using teledermatology and artificial intelligence for this issue is developing, but its diagnostic accuracy is less measured in a clinical setting.
The purpose of this study was to assess the diagnostic accuracy of the teledermoscopy method using the FotoFinder device as well as the Moleanalyzer Pro artificial intelligence (AI) Assistant and to compare them with the face-to-face clinical examination for the diagnosis of melanoma confirmed with histopathology.
Thirty melanocytic moles of 29 patients were included in the study. Each mole was assessed face-to-face, using FotoFinder teledermoscopy and Moleanalyzer Pro software methods. The results obtained from each method were compared with the results of the gold standard (pathology). The sensitivity and specificity of the three methods were calculated for malignant and borderline versus benign lesions. Inter-method reliability between a gold standard and other methods was evaluated using per cent agreement and Cohen's kappa coefficient.
Five moles had a histopathological diagnosis of melanoma, and six and 19 moles were diagnosed as borderline and benign, respectively. Sensitivities and specificities were, respectively, as follows: face-to-face (90.9%, 57.9%), FotoFinder teledermoscopy (63.6%, 78.9%), FotoFinder® Moleanalyzer Pro (36.4%, 42.1%). Agreement with biopsy-obtained diagnosis categories of benign, borderline and malignant for face-to-face was 63.33%, FotoFinder teledermoscopy 73.33%, and FotoFinder® Moleanalyzer Pro 40%.
Teledermoscopy had the highest agreement with reference diagnosis as well as the highest specificities that caused a reduction of biopsy referrals. The FotoFinder® Moleanalyzer Pro had the lowest agreement. Therefore, it cannot replace dermatologist decision making.
黑色素瘤的快速诊断对于良好预后至关重要。利用远程皮肤病学和人工智能解决这一问题的方法正在不断发展，但其在临床环境中的诊断准确性评估较少。
本研究旨在评估使用FotoFinder设备的远程皮肤镜检查方法以及Moleanalyzer Pro人工智能（AI）助手的诊断准确性，并将其与用于诊断经组织病理学确诊的黑色素瘤的面对面临床检查进行比较。
本研究纳入了29例患者的30个黑素细胞痣。每个痣均通过面对面检查、使用FotoFinder远程皮肤镜检查和Moleanalyzer Pro软件方法进行评估。将每种方法获得的结果与金标准（病理学）结果进行比较。计算三种方法对恶性和临界性病变与良性病变的敏感性和特异性。使用一致性百分比和科恩kappa系数评估金标准与其他方法之间的方法间可靠性。
5个痣经组织病理学诊断为黑色素瘤，6个和19个痣分别被诊断为临界性和良性。敏感性和特异性分别如下：面对面检查（90.9%，57.9%）、FotoFinder远程皮肤镜检查（63.6%，78.9%）、FotoFinder® Moleanalyzer Pro（36.4%，42.1%）。面对面检查与活检获得的良性、临界性和恶性诊断类别的一致性为63.33%，FotoFinder远程皮肤镜检查为73.33%，FotoFinder® Moleanalyzer Pro为40%。
远程皮肤镜检查与参考诊断的一致性最高，特异性也最高，这减少了活检转诊。FotoFinder® Moleanalyzer Pro的一致性最低。因此，它不能取代皮肤科医生的决策。
