SBIR Phase I: Innovative Breast Cancer Detection Algorithm Using Infrared Images

SBIR 第一阶段：使用红外图像的创新乳腺癌检测算法

基本信息

批准号：
2136325
负责人：
Isaac Perez-Raya
金额：
$ 25.6万
依托单位：
BIRED IMAGING INC
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-01-01 至 2022-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2136325&HistoricalAwards=false
关键词：
SBIR Phase Innovative Breast Cancer

项目摘要

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve monitoring and prevention of breast cancer with mammograms. Over 48 million screenings are performed each year in the US, and up to 10% women are recalled for further evaluation. Dense tissue found in 40% of women masks tumors in mammograms. Ultrasound is used as a complementary technique but it detects both malignant and non-malignant tumors and an additional biopsy is needed to detect cancer. Over 90% of the recalled women do not have cancer, resulting in added cost and unnecessary anxiety among healthy women. On the other hand, limiting the recalls to under 10% causes some cancers to be missed. This project advances a new infrared imaging (IR) technology unaffected by breast density. It is sensitive to only cancerous tumors because it uses their higher metabolic signature, and it can provide accurate estimates of the tumor size and location within the breast. The proposed IR imaging technology will reduce the overall healthcare cost and improve clinical outcomes. The proposed IR technology will provide an effective adjunct to mammography and it will identify cancerous tumors in dense breast tissue as well. It uses contactless IR imaging and the spatial and thermal data obtained from multi-view IR images of individual breasts. The IR images are obtained in prone position to avoid gravitational distortions and provide clear optical access over the entire breast, including the region of inframammary folds. The heat transfer from the tumor to the breast’s surface is analyzed and modeled as a straightforward physical system. The temperature profile on the breast surface is iteratively compared with the IR images until a match is obtained indicating whether a cancerous tumor is present. The analysis predicts the malignant tumor size and its location is clearly displayed to a radiologist. The approach is patient-specific. The overall breast cancer detection rate is expected to improve, while reducing the recall rates and unneeded biopsies in healthy women.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项小型企业创新研究（SBIR）I期项目的更广泛的影响/商业潜力是通过乳房X线照片改善监测和预防乳腺癌的监测和预防。在美国，每年进行超过4800万张筛查，最多召回10％的女性进行进一步评估。在乳房X线照片中，有40％的女性掩盖肿瘤发现了致密的组织。超声用作完整的技术，但它检测到恶性肿瘤和非恶性肿瘤，并且需要额外的活检才能检测到癌症。超过90％的被召回妇女没有癌症，从而增加了健康女性的成本和不必要的焦虑。另一方面，将召回限制在10％以下会导致一些癌症被错过。该项目推进了一种不受乳房密度影响的新红外成像（IR）技术。它仅对癌性肿瘤很敏感，因为它使用了较高的代谢特征，并且可以对乳房内的肿瘤大小和位置进行准确的估计。提出的IR成像技术将降低整体医疗保健成本并改善临床结果。拟议的IR技术将为乳房X线摄影提供有效的辅助功能，并且还将鉴定出致密的乳房组织中取消的肿瘤。它使用非接触式IR成像以及从单个乳房的多视图IR图像获得的空间和热数据。 IR图像的位置易于避免重力扭曲，并在整个乳房（包括非乳腺褶皱区域）提供明显的光学通道。分析从肿瘤到乳房表面的热传递，并将其建模为直接的物理系统。与IR图像相比，乳房表面上的温度曲线是在获得匹配的情况下进行比较的，以指示是否存在取消的肿瘤。该分析预测，恶性肿瘤的大小及其位置清楚地显示给放射科医生。该方法是特定于患者的。预计总体乳腺癌检测率将有所提高，同时降低了健康女性中的召回率和不需要的活检。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响来评估。