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.

总结 乳腺肿瘤微环境在癌症的早期发展中起着关键作用。一个 对肿瘤微环境的更好理解将有助于疾病的早期发现， 开发新的、更有效的治疗方法。目前对乳房X线照片的放射学解释是 基于识别乳腺病变和评估其潜在的恶性和致命性。生物医学 研究界还没有将微环境改变的乳房X线摄影特征与 伴随或甚至在肿瘤发生之前的组织稳态的丧失。 PI最近使用了一种新颖而强大的计算技术来证明组织 体内平衡的破坏和丧失可以从标准临床试验中定量和客观地评估， 乳房X光检查这些初步发现仅适用于单一诊断性乳房X光检查; AREA项目将分析多年前的纵向乳房X线照片序列， 接近诊断年份，从而揭示健康乳腺组织微环境的进展 走向分裂状态。据推测，组织解体签名存在于 乳房X线摄影数据与乳腺癌中的组织破坏和组织稳态的丧失有关。 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）验证乳房X线摄影组织破坏 伴随甚至可能先于肿瘤的发展; 2）开发一个计算机模型， 微钙化生长到乳房X线摄影乳腺组织环境中，3）改善计算 我们的数据分析效率，以及4）将乳腺肿瘤微环境的形态学特征 从通过乳房X线照相术成像到通过二次谐波产生显微镜成像的细胞尺度改变。 该研究将促进大学生的教育和职业准备， 缅因州唯一的生物医学工程项目，培养了大学之间不断增长的伙伴关系， 缅因州，频谱医疗保健合作伙伴和缅因州医学研究所，介绍了两个U缅因州教师 生物医学研究，并支持两名助理教授的早期职业发展。