Coupling Advanced Computational Analyses for Mammography and SHG Imaging for Early Detection of Breast Cancer Tissue Microenvironment Disruptions Accompanying Tumorigenesis

将乳房 X 线摄影和 SHG 成像的高级计算分析相结合，以早期检测伴随肿瘤发生的乳腺癌组织微环境破坏

基本信息

批准号：
10046750
负责人：
Andre Khalil
金额：
$ 41.85万
依托单位：
UNIVERSITY OF MAINE ORONO
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-07 至 2024-08-31
项目状态：
已结题

项目摘要

Summary The breast tumor microenvironment plays a key role in the early development of cancer. An improved understanding of the tumor microenvironment will support the early detection of disease and the development of novel, more effective therapies. Current radiological interpretation of mammograms is based on identifying breast lesions and assessing their potential malignancy and lethality. The biomedical research community has yet to correlate the mammographic signatures of microenvironment alterations and loss of tissue homeostasis accompanying, or even preceding tumorigenesis. The PI recently used a novel and powerful computational technique to demonstrate that tissue disruption and loss of homeostasis can be quantitatively and objectively assessed from standard clinical mammography. These preliminary findings pertain only to single diagnostic mammograms; the proposed AREA project will analyze longitudinal sequences of mammograms over multiple years prior to, and approaching the year of diagnosis, thus revealing the progression of healthy breast tissue microenvironment towards a disrupted state. It is hypothesized that the tissue disorganization signature present in mammographic data is associated with tissue disruption and loss of tissue homeostasis in the microenvironment. Team members will verify this hypothesis by imaging breast tissue samples to characterize, at the cellular level, disruption of collagen structures associated to tumor microenvironment alterations accompanying tumorigenesis. This project's specific aims include: 1) verifying that mammographic tissue disruption accompanies and perhaps even precedes tumor development; 2) developing an in silico model of microcalcification growth into mammographic breast tissue environment, 3) improving the computational efficiency of our data analysis, and 4) linking morphological features of the breast tumor microenvironment imaged by mammography to cellular-scale alterations imaged by second harmonic generation microscopy. The proposed research will advance the education and career preparation of undergraduates within Maine's only biomedical engineering program, nurture a growing partnership among the University of Maine, Spectrum Healthcare Partners and Maine Medical Research Institute, introduce two UMaine faculty to biomedical research, and support the early career development of two assistant professors.

概括乳腺肿瘤微环境在癌症的早期发展中起着关键作用。一个提高对肿瘤微环境的了解将支持疾病的早期发现和治疗开发新颖、更有效的疗法。目前对乳房X线照片的放射学解释是基于识别乳腺病变并评估其潜在的恶性程度和致死率。生物医学研究界尚未将微环境变化与乳房X线照相特征相关联伴随或什至在肿瘤发生之前的组织稳态丧失。 PI 最近使用了一种新颖且强大的计算技术来证明组织体内平衡的破坏和丧失可以通过标准临床定量和客观地评估乳房X光检查。这些初步结果仅适用于单次诊断性乳房X光检查；拟议的 AREA 项目将分析之前多年的乳房 X 光检查的纵向序列，以及接近诊断年份，从而揭示健康乳腺组织微环境的进展走向混乱的状态。据推测，组织解体特征存在于乳房X线照相数据与组织破坏和组织稳态丧失有关微环境。团队成员将通过对乳腺组织样本进行成像来验证这一假设在细胞水平上表征与肿瘤微环境相关的胶原蛋白结构的破坏伴随肿瘤发生的改变。该项目的具体目标包括：1) 验证乳腺 X 线摄影组织破坏伴随甚至可能先于肿瘤的发展； 2）开发计算机模型微钙化生长到乳腺 X 线摄影乳腺组织环境中，3) 改进计算我们的数据分析的效率，以及4）联系乳腺肿瘤微环境的形态特征通过乳房X线照相术成像到通过二次谐波发生显微镜成像的细胞尺度变化。拟议的研究将促进本科生的教育和职业准备缅因州唯一的生物医学工程项目，培养了缅因大学之间不断发展的合作伙伴关系缅因州、Spectrum Healthcare Partners 和缅因州医学研究所介绍了两名缅因大学教员致力于生物医学研究，并支持两名助理教授的早期职业发展。