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: 10618560
• 负责人: MARLEE KRIEGER
• 金额: $ 99.8万
• 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 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10618560
• 关键词: Acetic Acids; Address; Adoption; Algorithmic Software; Algorithms; Ambulatory Care; American Society of Clinical Oncology; Back; Biopsy; Blood Vessels; Cancer Burden; Cervical; 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; Detection; Development; Devices; Diagnosis; Diagnostic; Disease; Disinfection; Feedback; Fogs; Foundations; Funding; Glycogen; Goals; Gold; 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 Health Care; Protocols documentation; Provider; Public Health; 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; base; 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

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).

该项目的广泛目标是调整便携式，低成本，易于使用的袖珍尺寸阴道镜（已开发 根据其他资金）用于社区环境，并开发自动化算法 新生血管形成，糖原耗竭和乙腹，可与专家提供可比的诊断。这项工作 将在第三Stone Design，Inc，Duke University和Kenya Medical Research之间的合作中完成 研究所。该提案的具体目的是： AIM 1（I阶段）：通过设计连续放大机制和 改善设备工作流程集成，以消除通过使用 一次性透明无菌袖子。提供者对我们先前开发的口袋阴道镜的反馈 一致建议添加滑块机制来控制粗变焦和可消耗的套筒 口袋神经镜设计。 AIM 2（I阶段）：自动化算法和用于宫颈前检测的软件，我们将改进 通过使用嵌入式机器学习诊断算法的新型软件应用程序的特异性 自动宫颈癌筛查。我们将应用并验证VIA和GIVI的单个算法（绿色 照明血管成像）到从口袋的200名患者临床研究中获得的现有图像 阴道镜。然后，我们将将算法的性能与专家医师的解释进行比较 图像，病理作为黄金标准。 AIM 3（II阶段）：肯尼亚的Pocket Roposcope用户体验。我们将发展一个 在社区医疗保健环境中直接与文化相关的培训计划。我们将收集定量和 定性数据，包括调查，深入访谈以及幼稚提供者和患者的诊所观察 并使用这些发现并使用这些发现来改善肯尼亚和 同时，在AIM 4中告知临床研究。 AIM 4（II阶段）：将口袋阴道镜的性能与视觉检查的性能与 乙酸在肯尼亚的HPV+女性分类的乙酸。我们将在400 hpv+中进行集群随机试验 妇女将标准分类与使用肯尼亚基苏木的口袋阴道镜进行比较。所有HPV+女性 将进行活检以确定不同的敏感性，特异性以及正面和阴性预测值 分类策略。数据将用于对算法对专家阴道镜的性能进行建模。 目标5（第二阶段）：评估成本，成本，成本效益和人口健康的影响 基于HPV的宫颈癌筛查计划具有拟议的分类策略。我们将确定 通过测量该策略的增量成本效益比以及四个分诊策略的绝对和相对成本 成本和模型人口健康结果（癌症病例，死亡和残疾调整了生命年）。