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

• 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
• 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
• 来源: https://reporter.nih.gov/project-details/10046750
• 关键词: 3-Dimensional; Adoption; Algorithms; Benign; Biomedical Engineering; Biomedical Research; Breast; Breast Cancer Early Detection; Breast Cancer Patient; Breast Cancer Treatment; Breast Microcalcification; Cancerous; Clinical; Collagen; Communities; Complex; Computational Technique; Computer Analysis; Consequentialism; Coupling; Data; Data Analyses; Databases; Detection; Development; Diagnosis; Diagnostic; Discipline; Disease; Disseminated Malignant Neoplasm; Early Diagnosis; Education; Environment; Faculty; Generations; Genetic Programming; Goals; Growth; Healthcare; Histologic; Homeostasis; Image; Image Analysis; Label; Laboratories; Legal patent; Link; Maine; Malignant - descriptor; Malignant Neoplasms; Mammary Gland Parenchyma; Mammary Neoplasms; Mammographic screening; Mammography; Mathematics; Measurable; Measurement; Measures; Medical Research; Metastatic breast cancer; Methods; Microscopy; Modeling; Modulus; Morphology; Motion; Normalcy; Pathology; Pathology Report; Patients; Play; Publications; Radiology Specialty; Randomized; Research; Research Institute; Research Support; Slide; Structure; Techniques; Technology; Therapeutic; Tissue Sample; Tissues; Training; Universities; Woman; Work; base; breast cancer diagnosis; breast imaging; breast lesion; career development; career preparation; cell motility; clinically relevant; cohort; data mining; density; effective therapy; falls; improved; in silico; longitudinal analysis; malignant breast neoplasm; member; men; millimeter; novel; patient screening; physical process; prediction algorithm; professor; programs; radiologist; screening; second harmonic; second harmonic generation imaging; tumor; tumor growth; tumor microenvironment; tumorigenesis; undergraduate student

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 对肿瘤微环境的了解的提高将支持疾病的早期发现和 开发新颖，更有效的疗法。乳房X线照片的当前放射学解释是 基于识别乳房病变并评估其潜在的恶性肿瘤和致死性。生物医学 研究界尚未将微环境改变的乳房X线学特征与 伴随的组织稳态丧失，甚至在肿瘤发生之前。 PI最近使用了一种新颖而强大的计算技术来证明该组织 可以从标准临床上进行定量和客观地评估稳态的破坏和丧失 乳房X线摄影。这些初步发现仅与单个诊断乳房X线照片有关。提议 区域项目将在几年前分析乳房X线照片的纵向序列，并分析 接近诊断年，从而揭示了健康乳腺组织微环境的进展 走向破坏状态。假设组织混乱的签名存在于 乳房X线图数据与组织中断和组织稳态丧失有关 微环境。团队成员将通过对乳房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。 该项目的具体目的包括：1）验证乳房X线摄影组织中断 伴随甚至可能先于肿瘤发育； 2）开发一个硅模型 微钙化生长到乳房X线乳房组织环境中，3）改进计算 我们的数据分析的效率，以及4）连接乳腺肿瘤微环境的形态特征 通过乳房X线摄影对第二次谐波生成显微镜成像的细胞尺度改变成像。 拟议的研究将推进本科生的教育和职业准备 缅因州唯一的生物医学工程计划，培育了大学越来越多的合作伙伴关系 缅因州，Spectrum Healthcare Partners和缅因州医学研究所，介绍了两位Umaine教师 生物医学研究，并支持两位助理教授的早期职业发展。