NONINVASIVE DERMATOLOGICAL LESION CLASSIFIER

无创皮肤病病变分类器

• 批准号: 2645334
• 负责人: Eric R. Craine
• 金额: $ 10万
• 依托单位: WESTERN RESEARCH COMPANY, INC.
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-09-30 至 1999-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2645334
• 关键词: artificial intelligence; biomedical automation; biomedical equipment development; clinical research; diagnosis design /evaluation; fluorescence spectrometry; histology; human subject; neoplasm /cancer classification /staging; neoplasm /cancer diagnosis; noninvasive diagnosis; reflection spectrometry; skin neoplasms; spectrometry

Skin cancer is the fastest growing cancer in the United States today. Approximately 34,100 Americans developed cutaneous melanoma in 1995, and 7,200 died of the disease; of the survivors, many must contend with the ongoing trauma of disfigurement and fear. Skin biopsies are now the most frequently performed medical procedure reimbursed by Medicare. It is axiomatic among dermatologists that early detection and diagnosis are critical in the care and treatment of skin cancer patients. Great strides have been made in recent years in early detection of suspect skin lesions; however, the diagnosis remains based in the subjective evaluation of which skin lesions to biopsy. This decision is the basis of a great dilemma for physicians of at-risk patients who develop literally hundreds of lesions which could be pre-cancerous or cancerous. On one hand biopsies are expensive and traumatic; on the other, failure to biopsy the right lesion can lead to severe consequences. The dilemma is further exacerbated by the fact that 50-80% of biopsies prove unnecessary after the fact, contributing to an enormous of valuable health care dollars, patient trauma and negative patient behavior feedback. Recent developments in dermatological spectroscopy used to train an artificial neural net technology suggest that an automated clinical diagnostic aid which produces a quantitative rather than qualitative diagnostic assessment of skin lesions is possible. This project proposes development and testing of such a product. Spectroscopic samples of approximately 500 patients with abnormal skin lesions will be coupled with an equal number of normal skin spectra and used to train an artificial neural net classifier. This automated diagnostic aid will be tested against a large number of test samples for which a histological diagnosis is available for evaluation of the system. PROPOSED COMMERCIAL APPLICATIONS: The proposed project will lead to a non-invasive, in-office, real-time test to provide an automated, repeatable diagnostic probability of the nature of skin lesions prior to biopsy. Skin biopsies are now the most frequently performed reimbursed Medicare procedure, and as many as 50-80% are found not to be necessary after the fact. The low cost of this test, and rapid amortization of the system, coupled with the enormous health care cost savings possible in conjunction with a significant and widely recognized health problem, suggest that this product could have great commercial potential.

皮肤癌是当今美国增长最快的癌症。 1995年，大约有34，100名美国人患上了皮肤黑色素瘤， 7，200人死于疾病;幸存者中，许多人必须与疾病作斗争。 毁容和恐惧的持续创伤 皮肤活检现在是 经常进行医疗保险报销的医疗程序。 是 皮肤科医生中的一个公理是， 在皮肤癌患者的护理和治疗中至关重要。 伟大 近年来，在可疑皮肤早期检测方面已经取得了长足的进步 病变;然而，诊断仍然基于主观 评估哪些皮肤病变需要活检。 这个决定是 对于治疗高危患者的医生来说，这是一个巨大的困境 几乎有数百处可能是癌前病变或癌性病变。 一方面，活检是昂贵的和创伤性的;另一方面， 活检正确的病变可能会导致严重的后果。 的困境 50-80%的活组织检查证明 不必要的事后，有助于一个巨大的有价值的 医疗费用、患者创伤和患者负面行为 反馈 皮肤病光谱学的最新发展， 训练人工神经网络技术表明， 一种临床诊断辅助工具， 皮肤损伤的定性诊断评估是可能的。 这 该项目建议开发和测试这种产品。 大约500名皮肤异常患者的光谱样本 病变将与相等数量的正常皮肤光谱相结合， 用于训练人工神经网络分类器。 这种自动化 将针对大量测试样本测试诊断辅助工具， 其中组织学诊断可用于系统的评估。 拟议的商业应用： 拟议的项目将实现非侵入性、办公室内、实时 测试，以提供自动化的，可重复的诊断概率 活检前皮肤病变的性质。皮肤活检现在是 经常进行报销的医疗保险程序，多达50-80% 在事后发现是没有必要的。这个测试的低成本， 和系统的快速摊销，再加上巨大的健康 护理成本的节省可能与一个显着的和广泛的 公认的健康问题，建议这种产品可以有很大的 商业潜力。