Validation of a lab-free low-cost screening test for prevention of cervical cancer: automated visual evaluation

验证用于预防宫颈癌的无需实验室的低成本筛查测试：自动视觉评估

• 批准号: 10441826
• 负责人: David Levitz
• 金额: $ 29.78万
• 依托单位: DL ANALYTICS, LLC
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10441826
• 关键词: Validation; lab; free; low; cost

PROJECT SUMMARY/ABSTRACT Artificial intelligence (AI) has the potential to revolutionize medicine by improving productivity, reducing human error, and assisting with diagnosis and treatment. Image classification algorithms can be used to develop automated visual evaluation (AVE): a potential game-changer for cervical cancer prevention in low- and middle-income countries (LMICs). AVE technology reads digital photographs of a cervix to provide diagnosis and treatment recommendations in seconds. AVE is a true point of care test, low cost and does not require a laboratory. AVE could be used either for stand-alone primary screening, or to triage HPV-positive women. We will compare AVE to common screening methods in LMICs: visual inspection with acetic acid (VIA) and conventional cytology. Enhanced Visual Assessment (EVA) System by MobileODT is a cloud-connected mobile colposcope on a smartphone platform. It is FDA cleared and used in 42 countries. MobileODT is uniquely poised to integrate AVE into the EVA System. Our aim is to validate and commercialize AVE on the EVA platform. Phase I aims will adapt AVE to run on the EVA system using an optimal neural network architecture, running either directly on the phone or as a cloud- based service. Phase II is a prospective clinical trial of 10,000 patients recruited at ministry of health sites in El Salvador. All screen-positive patients, and 10% of negative patients, will undergo colposcopy with biopsy. Sensitivity of AVE as a primary screening test will be compared to cytology and to VIA. In HPV-positive women, AVE will be compared to VIA as a triage test.

项目摘要/摘要 人工智能(AI)有可能通过提高生产力、减少人类 错误，并协助诊断和治疗。图像分类算法可用于开发 自动视觉评估(AVE)：低位和低位宫颈癌预防的潜在游戏规则改变者 中等收入国家(LMIC)。AVE技术读取宫颈的数字照片以提供诊断 以及几秒钟内的治疗建议。AVE是一种真正的关注点测试，成本低，不需要 实验室。AVE既可以用于独立的初级筛查，也可以用于对HPV阳性妇女进行分类。我们 将AVE与LMIC中常见的筛查方法进行比较：用醋酸目视检查(VIA)和 常规细胞学。MobileODT的增强型视觉评估(EVA)系统是云连接的 智能手机平台上的移动镜。它获得了FDA的批准，并在42个国家使用。MobileODT是 独一无二地准备将AVE整合到EVA系统。 我们的目标是在EVA平台上验证AVE并将其商业化。第一阶段AIMS将调整AVE以在 使用最佳神经网络架构的EVA系统，可以直接在手机上运行，也可以作为云运行- 基于服务的服务。第二阶段是一项前瞻性临床试验，有10,000名患者在El卫生部的地点招募 萨尔瓦多。所有筛查阳性患者和10%的阴性患者将接受阴道镜检查和活检。 将AVE作为初筛试验的敏感性与细胞学和VIA进行比较。在HPV阳性中 女性，大道将作为一种分流测试与VIA进行比较。