Diffuse Optical Probe for Breast Cancer Screening and Monitoring

用于乳腺癌筛查和监测的漫射光学探头

• 批准号: RGPIN-2022-04460
• 负责人: Golnaraghi, Farid
• 金额: $ 2.84万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=760560
• 关键词: Diffuse; Optical; Probe; Breast; Cancer

The proposed research program aims to improve breast cancer screening for early detection and effective treatment using low-cost, accessible technologies. This work aligns with the NSERC eligibility criteria for research aiming to develop or optimize a new diagnostic technology based on available data. Breast cancer is ranked as the second leading cause of cancer-related death in North America. Ultrasound, x-ray mammography, and magnetic resonance imaging (MRI) are commonly used for breast cancer detection, where X-ray mammography is the primary screening technique for breast cancer detection. Although X-ray mammography is the principal modality for breast cancer screening, it is not suitable for all women because it has low sensitivity (67.8%) for younger women or women with dense breasts. In addition, it has a potential health risk due to the effect of ionizing radiation. Diffuse optical spectroscopy is a relatively new, non-invasive, and nonionizing technique for breast cancer diagnosis. Over the past three decades, near-infrared (NIR) optical imaging, has been developed very rapidly as currently, NIR optical imaging approaches have been advanced for biological imaging and sensing. This technique is a non-invasive and promising method for compositional and functional imaging of extremely scattering mediums, such as the breast. This proposal represents an ongoing research program towards developing a proprietary handheld diffuse optical breast-scanning (DOB-Scan) probe to diagnose breast cancer at an early stage. Over the past ten years, we have designed and successfully tested four generations of the probe, representing a safe, non-invasive, portable, and cost-effective technology that gives detailed information about breast tissue's constituents, which are markers for healthy or cancerous tissues. At this stage, the DOB-scan probe has proven effective in its previous iterations at characterizing the optical absorption properties of various materials, including cancerous breast tissue, relative to healthy tissue, in clinical studies. However, there are limitations on this ability both due to the complexity of non-homogenous tissue and probe design itself-for example, the DOB-Scan experiences inaccuracies in the breast tissue's functional and compositional cross-sectional imaging. In addition, the model-based algorithms used are expensive computationally, prohibiting real-time application. We would incorporate a real-time imaging system, enhanced algorithms for image reconstruction, and easy-to-use hardware and software. Using optical phantoms and available clinical test results, we will build intelligence to provide the location and quantitative information on the type of breast tissue (normal, benign, or cancerous lesions or infections) with a higher degree of confidence. Addressing these issues would also enable us to extend the technology to other healthcare applications.

拟议的研究计划旨在改善乳腺癌筛查，以便使用低成本，可获得的技术进行早期发现和有效治疗。这项工作符合NSERC的研究资格标准，旨在根据现有数据开发或优化新的诊断技术。 乳腺癌在北美被列为癌症相关死亡的第二大原因。超声、X射线乳房摄影和磁共振成像（MRI）通常用于乳腺癌检测，其中X射线乳房摄影是乳腺癌检测的主要筛查技术。虽然X射线乳房X光检查是乳腺癌筛查的主要方式，但它并不适合所有女性，因为它对年轻女性或乳房致密女性的敏感性较低（67.8%）。此外，由于电离辐射的影响，它具有潜在的健康风险。扩散光学光谱是一种相对较新的、非侵入性的、非电离的乳腺癌诊断技术。近红外（NIR）光学成像技术在过去的三十年中得到了迅速的发展，目前，近红外光学成像技术已经发展到生物成像和传感领域。该技术是一种非侵入性的和有前途的方法，用于极其散射的介质（如乳房）的成分和功能成像。 该提案代表了一项正在进行的研究计划，旨在开发一种专有的手持式漫射光学乳腺扫描（DOB-Scan）探头，以在早期诊断乳腺癌。在过去的十年里，我们设计并成功测试了四代探针，代表了一种安全、无创、便携且具有成本效益的技术，可以提供有关乳腺组织成分的详细信息，这些成分是健康或癌组织的标志物。在这个阶段，DOB扫描探头已经在其先前的迭代中被证明在临床研究中有效地表征各种材料（包括癌性乳腺组织）相对于健康组织的光学吸收特性。然而，由于非同质组织和探头设计本身的复杂性，这种能力存在局限性-例如，DOB扫描在乳房组织的功能和组成横截面成像中经历不准确性。此外，所使用的基于模型的算法计算成本很高，无法进行实时应用。我们将结合一个实时成像系统，增强的图像重建算法，以及易于使用的硬件和软件。使用光学幻影和可用的临床测试结果，我们将建立智能，以提供更高置信度的乳腺组织类型（正常，良性或癌性病变或感染）的位置和定量信息。解决这些问题也将使我们能够将该技术扩展到其他医疗保健应用。