Artificial Intelligence Enhanced Optical Coherence Tomography (AI-OCT) Imaging for Pre-surgical Margin Detection of Basal Cell Carcinoma
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 30
- 主要终点
- Validation of AI-OCT as an accurate method for detecting basal cell carcinomas
研究概览
简要总结
Basal cell carcinomas (BCCs) are the most common human malignancy, affecting about 2 million Americans each year. Mohs micrographic surgery (MMS) removes tissue by sequential excision. Costs for MMS could be reduced if the number of necessary excision stages were decreased by a more accurate initial tumor margin assessment.
The goal of this observational study is to learn if Optical Coherence Tomography (OCT) used in conjunction with artificial intelligence algorithms is accurate in the detection of superficial BCC margins prior to MMS. This study also aims to determine if AI-OCT guided margin delineation can reduce the number of stages in MMS.
Researchers will first focus on validating AI-OCT as a method for accurately detecting BCCs. A follow-up study would then address the guided pre-surgical margin delineation.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Male or Female, ages 18 or older
- •at least one biopsy proven superficial or nodular BCC
- •willingness to have photographs taken of the treatment area
- •ability to understand and willingness to sign a written informed consent document
排除标准
- •infiltrative, micronodular, or morpheaform BCC
- •pregnant women
- •subjects not willing to have a biopsy taken from the treatment area
- •subjects with herpes simplex virus infection in the treatment area
结局指标
主要结局
Validation of AI-OCT as an accurate method for detecting basal cell carcinomas
时间窗: 2 years
次要结局
未报告次要终点
研究者
David M. Ozog
Principal Investigator
Henry Ford Health System