Innovations in cervical cancer diagnosis for low resource settings using advanced optical imaging and machine learning diagnostic algorithms.

使用先进的光学成像和机器学习诊断算法在资源匮乏的情况下进行宫颈癌诊断创新。

• 批准号: 10654870
• 负责人: MARLEE KRIEGER
• 金额: $ 99.6万
• 依托单位: CALLA HEALTH FOUNDATION
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-13 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10654870
• 关键词: Acetic Acids; Address; Adoption; Algorithms; Ambulatory Care; American Society of Clinical Oncology; Back; Biopsy; Blood Vessels; Cancer Burden; Cervical Cancer Screening; Cessation of life; Client satisfaction; Clinic; Clinical Research; Clinical Trials; Cluster randomized trial; Collaborations; Colposcopes; Colposcopy; Community Health; Community Healthcare; Computer software; Cost Analysis; Cost Measures; Country; Coupled; Cytology; Data; Development; Devices; Diagnosis; Diagnostic; Disease; Disinfection; Disparity; Feedback; Fogs; Funding; Glycogen; Goals; Guidelines; Health Care Costs; Healthcare; Human Papillomavirus; Image; Incidence; Individual; Infrastructure; International; Interview; Kenya; Lesion; Lighting; Machine Learning; Malignant Neoplasms; Malignant neoplasm of cervix uteri; Medical Research; Modeling; Optics; Outcome; Pathology; Patients; Performance; Phase; Physicians; Predictive Value; Prevention; Primary Care; Protocols documentation; Provider; Public Health; Recommendation; Reliability of Results; Research Institute; Resource-limited setting; Rural; Sensitivity and Specificity; Site; Sledding; Small Business Innovation Research Grant; Specificity; Sterility; Surveys; Technology; Testing; Training; Triage; Universities; Vagina; Visual; Woman; Work; World Health Organization; automated algorithm; burden of illness; cancer diagnosis; cancer imaging; clinical investigation; cohort; community setting; cost; cost effectiveness; cost-effectiveness ratio; design; diagnostic algorithm; disability-adjusted life years; experience; health care delivery; health care settings; improved; incremental cost-effectiveness; innovation; low and middle-income countries; mortality; neovascularization; novel; optical imaging; overtreatment; point of care; population health; portability; primary care setting; relative cost; research and development; screening; screening program; visual performance

The broad goal of this project is to adapt a portable, low-cost, easy-to-use Pocket-sized Colposcope (developed under other funding) for use in a community setting, and develop automated algorithms that combine neovascularization, glycogen depletion and acetowhitening to provide comparable diagnosis to an expert. This work will be done in a collaboration between 3rd Stone Design, Inc, Duke University and Kenya Medical Research Institute. The specific aims of this proposal are: Aim 1 (Phase I): Improve Pocket colposcope by designing continuous magnification mechanism and improving device workflow integration to eliminate between-use disinfection through the use of a disposable optically clear sterile sleeve. Provider feedback on our previously developed Pocket colposcope has unanimously suggested the addition of a slider mechanism to control coarse zoom and a sleeve consumable to the Pocket colposcope design. Aim 2 (Phase I): Automated algorithms and software for cervical pre-cancer detection We will improve the specificity of VIA using a novel software application with embedded machine learning diagnostic algorithms for automated cervical cancer screening. We will apply and validate the individual algorithms for VIA and GIVI (green illumination vascular imaging) to existing images obtained from a 200-patient clinical study with the Pocket colposcope. We will then compare the performance of the algorithms to expert physician interpretation of the same images, with pathology serving as the gold standard. Aim 3 (Phase II): Document user experience with Pocket colposcope in Kenya. We will develop a culturally relevant training package directly in the community healthcare setting. We will collect quantitative and qualitative data including surveys, in-depth interviews, and clinic observations from both naive providers and patients and use these findings to and use these findings to improve the introduction of the Pocket colposcope in Kenya and simultaneously, inform the clinical investigations in Aim 4. Aim 4 (Phase II): Compare the performance of the Pocket colposcope to Visual Inspection with Acetic Acid for triage of HPV+ women in Kenya. We will carry out a cluster-randomized trial among 400 HPV+ women to compare the standard triage with that using the Pocket colposcope in Kisumu, Kenya. All HPV+ women will undergo biopsy to determine sensitivity, specificity and positive and negative predictive values of the different triage strategies. Data will be used to model the performance of the algorithm against that of expert colposcopists. Aim 5 (Phase II): Assess the costs, incremental cost-effectiveness and population health impact of HPV-based cervical cancer screening programs with proposed triage strategies. We will determine the incremental cost-effectiveness ratio and the absolute and relative costs for four triage strategies by measuring the costs and model population health outcomes (cancer cases, deaths and disability adjusted life years).

该项目的总体目标是采用一种便携式、低成本、易于使用的袖珍阴道镜（开发 在其他资助下）用于社区环境，并开发结合了自动化算法 新生血管形成、糖原消耗和醋酸美白，为专家提供可比较的诊断。这部作品 将由 3rd Stone Design, Inc、杜克大学和肯尼亚医学研究中心合作完成 研究所。该提案的具体目标是： 目标1（第一阶段）：通过设计连续放大机构和改进袖珍阴道镜 改进设备工作流程集成，通过使用 一次性光学透明无菌套管。供应商对我们之前开发的袖珍阴道镜的反馈 一致建议增加一个滑块机构来控制粗变焦和一个套筒消耗品 袖珍阴道镜设计。 目标2（第一阶段）：宫颈癌前检测的自动化算法和软件我们将改进 威盛使用具有嵌入式机器学习诊断算法的新颖软件应用程序来实现以下目的： 自动化宫颈癌筛查。我们将应用并验证 VIA 和 GIVI（绿色 照明血管成像）到使用 Pocket 进行的 200 名患者临床研究中获得的现有图像 阴道镜。然后，我们将算法的性能与专家医师对相同算法的解释进行比较 图像，以病理学作为金标准。 目标 3（第二阶段）：记录肯尼亚袖珍阴道镜的用户体验。我们将开发一个 直接在社区医疗保健环境中提供与文化相关的培训包。我们将收集定量和 定性数据，包括调查、深入访谈以及来自新手提供者和患者的临床观察 并利用这些发现来改进袖珍阴道镜在肯尼亚的推广 同时，为目标 4 中的临床研究提供信息。 目标 4（第二阶段）：比较袖珍阴道镜与目视检查的性能 醋酸用于肯尼亚 HPV+ 女性的分类。我们将在400个HPV+中进行整群随机试验 肯尼亚基苏木的女性将标准分类与使用袖珍阴道镜的分类进行比较。所有 HPV+ 女性 将进行活检以确定不同的敏感性、特异性以及阳性和阴性预测值 分类策略。数据将用于针对阴道镜专家的算法性能进行建模。 目标 5（第二阶段）：评估成本、增量成本效益和人口健康影响 基于 HPV 的宫颈癌筛查计划以及建议的分诊策略。我们将确定 通过衡量四种分类策略的增量成本效益比以及绝对和相对成本 成本和人口健康结果模型（癌症病例、死亡和残疾调整生命年）。