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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.

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是通过乳房X光检查改善乳腺癌的监测和预防。美国每年进行超过4800万次筛查，多达10%的女性被召回进行进一步评估。40%的女性在乳房X光检查中发现的致密组织掩盖了肿瘤。超声被用作一种补充技术，但它可以检测恶性和非恶性肿瘤，并且需要额外的活检来检测癌症。超过90%的被召回的女性没有癌症，导致健康女性的成本增加和不必要的焦虑。另一方面，将召回限制在10%以下会导致一些癌症被遗漏。该项目提出了一种新的红外成像（IR）技术，不受乳腺密度的影响。它只对癌性肿瘤敏感，因为它使用它们更高的代谢特征，并且它可以提供乳腺内肿瘤大小和位置的准确估计。拟议的红外成像技术将降低整体医疗保健成本并改善临床结果。拟议的红外技术将提供一个有效的辅助乳房X光检查，它将确定致密乳腺组织中的癌性肿瘤以及。它使用非接触式红外成像以及从单个乳房的多视图红外图像获得的空间和热数据。IR图像是在俯卧位获得的，以避免重力失真，并在整个乳房（包括乳房下皱襞区域）上提供清晰的光学通路。从肿瘤到乳房表面的热传递被分析和建模为一个简单的物理系统。将乳房表面上的温度分布与IR图像迭代地进行比较，直到获得指示是否存在癌性肿瘤的匹配。该分析预测恶性肿瘤的大小，并将其位置清楚地显示给放射科医生。该方法是针对患者的。预计整体乳腺癌检出率将有所提高，同时降低健康女性的召回率和不必要的活检。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。