Godoy Sebastián E, Hayat Majeed M, Ramirez David A, Myers Stephen A, Padilla R Steven, Krishna Sanjay
Center for High Technology Materials, University of New Mexico, 1313 Goddard Street SE, MSC04 2710, Albuquerque, NM 87106-4343, USA.
Department of Electrical and Computer Engineering, University of New Mexico, 1 University of New Mexico, MSC01 1100, Albuquerque, NM 87131-0001, USA.
Biomed Opt Express. 2017 Mar 22;8(4):2301-2323. doi: 10.1364/BOE.8.002301. eCollection 2017 Apr 1.
Skin cancer is the most common cancer in the United States with over 3.5M annual cases. Presently, visual inspection by a dermatologist has good sensitivity (> 90%) but poor specificity (< 10%), especially for melanoma, which leads to a high number of unnecessary biopsies. Here we use dynamic thermal imaging (DTI) to demonstrate a rapid, accurate and non-invasive imaging system for detection of skin cancer. In DTI, the lesion is cooled down and the thermal recovery is recorded using infrared imaging. The thermal recovery curves of the suspected lesions are then utilized in the context of continuous-time detection theory in order to define an optimal statistical decision rule such that the sensitivity of the algorithm is guaranteed to be at a maximum for every prescribed false-alarm probability. The proposed methodology was tested in a pilot study including 140 human subjects demonstrating a sensitivity in excess of 99% for a prescribed specificity in excess of 99% for detection of skin cancer. To the best of our knowledge, this is the highest reported accuracy for any non-invasive skin cancer diagnosis method.
皮肤癌是美国最常见的癌症，每年有超过350万例病例。目前，皮肤科医生的目视检查具有良好的敏感性（>90%），但特异性较差（<10%），尤其是对于黑色素瘤，这导致了大量不必要的活检。在此，我们使用动态热成像（DTI）来展示一种用于检测皮肤癌的快速、准确且非侵入性的成像系统。在DTI中，病变部位被冷却，然后使用红外成像记录热恢复情况。接着，在连续时间检测理论的背景下利用疑似病变的热恢复曲线，以定义一个最优的统计决策规则，从而确保算法的敏感性在每个规定的误报概率下都能达到最大值。所提出的方法在一项包括140名人类受试者的初步研究中进行了测试，结果表明，对于规定的超过99%的特异性，检测皮肤癌的敏感性超过99%。据我们所知，这是任何非侵入性皮肤癌诊断方法所报道的最高准确率。
