AUTOMATED PALPATION SYSTEM: A NOVEL TECHNIQUE FOR EARLY DETECTION OF BREAST CAN

自动触诊系统：早期检测乳腺罐头的新技术

• 批准号: 8171797
• 负责人: LOIS OLSON
• 金额: $ 0.11万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8171797
• 关键词: Age; Biomedical Research; Breast; Breast Cancer Detection; Breast Cancer Early Detection; Characteristics; Computer Retrieval of Information on Scientific Projects Database; Early Diagnosis; Fingers; Funding; Goals; Grant; High Performance Computing; Image; Institution; Mammary Neoplasms; Mammography; Manuals; Maps; Measurement; Measures; Mechanics; Painless; Palpation; Patients; Prone Position; Radiation; Research; Research Personnel; Resources; Risk; Site; Source; Surface; Survival Rate; System; Techniques; Tissues; United States National Institutes of Health; improved; novel; response

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Early detection of breast cancer will continue to be crucial in improving patient survival rates. Manual breast exams (breast palpation) and mammograms are currently the most effective and widely used techniques for early detection. Unfortunately, manual breast exams are limited in their ability to detect tumors reliably since they only produce local information about the site where the force is applied and do not provide quantitative measurements. Mammograms, while effective, expose the patient to radiation and hence routine mammograms are limited to those in specific age or risk groups. In addition, mammograms do not quantify tissue stiffness, an identifying characteristic of breast tumors. Our ultimate goal is to develop an Automated Palpation System (APS) which will be completely noninvasive and painless. We envision a table where the patient lays in a prone position in a manner that allows dozens of mechanical fingers to engage, gently manipulate, and measure the resulting response of the breast in order to obtain a force/deflection map of the breast surface. From this surface force/deflection map, an image of the tissue stiffness throughout the breast can be calculated. These recordable/quantitative images can be then be used to identify tumors because of their higher stiffness. This particular project focuses solely on developing efficient computational algorithms for the APS. When fully developed, the APS could be used as a relatively inexpensive and risk-free breast cancer screening mechanism.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 乳腺癌的早期发现对于提高患者存活率至关重要。手动乳房检查（乳房触诊）和乳房X线照片目前是早期检测最有效，最广泛使用的技术。不幸的是，手动乳房检查可靠地检测肿瘤的能力有限，因为它们仅产生有关施加力且不提供定量测量的部位的局部信息。乳房X线照片虽然有效地暴露于辐射，因此常规乳房X线照片仅限于特定年龄或风险组的乳房X线照片。另外，乳房X线照片不会量化组织刚度，这是乳腺肿瘤的识别特征。我们的最终目标是开发自动触诊系统（AP），该系统将完全无创和无痛。我们设想了一张表，患者以易于俯卧位的方式放置，以使数十个机械手指轻轻地接合，操纵并测量乳房的响应，以获得乳房表面的力/偏转图。从这个表面力/挠度图中，可以计算整个乳房的组织刚度的图像。这些可记录/定量图像可以用于识别肿瘤，因为它们的刚度较高。这个特定的项目仅着重于为APS开发有效的计算算法。当完全开发时，AP可以用作相对便宜且无风险的乳腺癌筛查机制。