Breast core-needle diagnostics in LMICs via millifluidics and direct-to-digital imaging: development and validation in Ghana

通过微流体和直接数字成像对中低收入国家进行乳腺空心针诊断：在加纳进行开发和验证

• 批准号: 10416550
• 负责人: RICHARD M. LEVENSON
• 金额: $ 64.19万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-05 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10416550
• 关键词: Address; American; Area; Artificial Intelligence; Back; Breast; Calibration; Caregivers; Caring; Centenarian; Cessation of life; Clinic; Clinical; Clinical Pathology; Collaborations; Computer software; Consultations; Core Biopsy; Costs and Benefits; Country; Data; Detection; Development; Diagnosis; Diagnostic; Diagnostic Neoplasm Staging; Disease Management; ERBB2 gene; Engineering; Environment; Evaluation; Evolution; Feedback; Fees; Generations; Ghana; Goals; Hand; Health Care Costs; Histology; Histopathology; Home; Hospitals; Image; Immunofluorescence Immunologic; Immunohistochemistry; Incidence; Income; Infrastructure; Institutional Review Boards; Intervention; Label; Laboratories; Logistics; Love; Machine Learning; Malignant Neoplasms; Marketing; Mechanics; Methods; Molecular; Molecular Probes; Morphology; Needle biopsy procedure; Needles; Optics; Pathologist; Pathology; Patient Recruitments; Patient Triage; Patients; Performance; Peripheral; Positioning Attribute; Procedures; Process; Protocols documentation; Reagent; Resolution; Resources; Sampling; Services; Slide; Societies; Surgeon; System; Techniques; Technology; Testing; Time; Tissues; Training; Universities; Validation; Visit; Washington; Woman; artificial intelligence algorithm; breast cancer diagnosis; breast lesion; clinical translation; cost; design; digital; digital imaging; experience; global health; histological specimens; imaging approach; imaging system; implementation evaluation; improved; innovation; instrument; low and middle-income countries; low income country; malignant breast neoplasm; member; molecular phenotype; mortality; opportunity cost; peace; phenotypic data; prototype; research clinical testing; success; tissue preparation; tool; treatment planning; usability; validation studies; Address; American; Area; Artificial Intelligence; Back; Breast; Calibration; Caregivers; Caring; Centenarian; Cessation of life; Clinic; Clinical; Clinical Pathology; Collaborations; Computer software; Consultations; Core Biopsy; Costs and Benefits; Country; Data; Detection; Development; Diagnosis; Diagnostic; Diagnostic Neoplasm Staging; Disease Management; ERBB2 gene; Engineering; Environment; Evaluation; Evolution; Feedback; Fees; Generations; Ghana; Goals; Hand; Health Care Costs; Histology; Histopathology; Home; Hospitals; Image; Immunofluorescence Immunologic; Immunohistochemistry; Incidence; Income; Infrastructure; Institutional Review Boards; Intervention; Label; Laboratories; Logistics; Love; Machine Learning; Malignant Neoplasms; Marketing; Mechanics; Methods; Molecular; Molecular Probes; Morphology; Needle biopsy procedure; Needles; Optics; Pathologist; Pathology; Patient Recruitments; Patient Triage; Patients; Performance; Peripheral; Positioning Attribute; Procedures; Process; Protocols documentation; Reagent; Resolution; Resources; Sampling; Services; Slide; Societies; Surgeon; System; Techniques; Technology; Testing; Time; Tissues; Training; Universities; Validation; Visit; Washington; Woman; artificial intelligence algorithm; breast cancer diagnosis; breast lesion; clinical translation; cost; design; digital; digital imaging; experience; global health; histological specimens; imaging approach; imaging system; implementation evaluation; improved; innovation; instrument; low and middle-income countries; low income country; malignant breast neoplasm; member; molecular phenotype; mortality; opportunity cost; peace; phenotypic data; prototype; research clinical testing; success; tissue preparation; tool; treatment planning; usability; validation studies

ABSTRACT Breast cancer is an increasing challenge globally as it became the most prevalent malignancy at the end of 2020. More than 70% of all cancer mortality now occurs in low- and middle-income countries (LMICs). Histology, critical to the diagnosis and disease management for many cancers notably including breast cancer, is currently performed using techniques that are more than 100 years old. Market forces, technological advances in optics, and innovation in care strategies are opening the door for disruptive innovation that could massively reduce costs and time and improve accessibility while provide equivalent or even superior results. We propose to contribute to the field's evolution by combining two already functioning and complementary technologies: 1) a tissue millifluidics approach (developed in PI Seibel's lab) for hands-off core needle biopsy handling; and 2) a rapid, low-cost, direct-to-digital slide-free imaging solution (developed in PI Levenson's lab). The goal is to implement a context-appropriate, automated instrument that can capture diagnostic-quality histopathology images from core-needle biopsies vital to high-quality breast-cancer diagnosis and staging, at time of procedure. Additional project goals include implementation of innovative rapid immunofluorescence methods for near-real-time therapy guidance; and development of AI tools for patient triage or even local diagnostic support, the latter under the direction of Dr. Mahmood (BWH), a leader in multiclass AI algorithms. Key to success of this project is local implementation and clinical evaluation in Kumasi, Ghana, under the direction of Dr. Addai, consultant breast surgeon and CEO of Peace and Love Hospitals (established in 2002). Her group will critically assess performance, usability, and compatibility with the service environment in both a central hospital and a remote satellite clinic; clinical validation studies will eventually encompass at least several hundred patients recruited under IRB-approved protocols. Additional guidance will be provided by Dr. Dan Milner, CMO of the American Society for Clinical Pathology (ASCP), who has extensive experience in global-health-focused initiatives, as well as by our collaborating pathologists who are familiar with issues relevant to LMIC settings. Feedback will inform the design of the second-generation automated instruments to be delivered near the end of this project.

抽象的 乳腺癌在全球范围内越来越大的挑战，因为它成为最普遍的恶性肿瘤 2020年。现在所有癌症死亡率的70％以上发生在低收入和中等收入国家（LMIC）。 组织学对许多癌症的诊断和疾病管理至关重要，包括乳腺癌， 目前是使用已有1​​00多年历史的技术进行的。市场力量，技术 光学的进步和护理策略的创新正在为破坏性创新打开了大门 大大降低成本和时间，并提高可访问性，同时提供同等的甚至卓越的结果。 我们建议通过组合两个已经起作用和互补来为该领域的演变做出贡献 技术：1）用于手持核心针头活检的组织毫米学方法（在Pi Seibel的实验室中开发） 处理； 2）一种快速，低成本，直接到数字的无幻灯片成像解决方案（在Pi Levenson的实验室中开发）。 目的是实施适合上下文的自动化工具，以捕获诊断质量 组织病理学的图像来自核心针对高质量乳腺癌诊断和分期至关重要的核心细节活检图像 程序时间。其他项目目标包括实施创新的快速免疫荧光 近实时治疗指导的方法；并开发用于患者分类甚至本地的AI工具 诊断支持，后者在多类AI算法的领导者Mahmood博士（BWH）的指导下。 该项目成功的关键是加纳库马西的本地实施和临床评估 Addai博士，乳房外科医生兼和平与爱情医院首席执行官（成立于2002年）。 她的小组将在两个人中批判性地评估性能，可用性和与服务环境的兼容性 中央医院和远程卫星诊所；临床验证研究最终将至少包含 根据IRB批准的方案招募了数百名患者。博士将提供其他指导。 美国临床病理学会（ASCP）的CMO Dan Milner，他在 以全球健康为中心的举措以及我们熟悉问题的合作病理学家 与LMIC设置有关。反馈将为第二代自动化仪器的设计提供信息 将在该项目结束时交付。