Elastography-based Analytics for Benign and Malignant Breast Disease

基于弹性成像的良性和恶性乳腺疾病分析

• 批准号: 9516398
• 负责人: Jingfeng Jiang
• 金额: $ 45.02万
• 依托单位: MICHIGAN TECHNOLOGICAL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9516398
• 关键词: 3D ultrasound; Adopted; Aftercare; Algorithms; Benign; Biomedical Engineering; Biopsy; Breast; Breast Diseases; Breast biopsy; Clinical; Clinical Research; Complex; Computer software; Computers; Connective Tissue; Data; Development; Diagnosis; Environment; Equipment; Evaluation; Excision; Feasibility Studies; Future; Goals; Health Care Costs; Healthcare; Heterogeneity; Human; Image; Knowledge Discovery; Learning; Lesion; Malignant - descriptor; Malignant Neoplasms; Mammary Neoplasms; Mammary Ultrasonography; Mathematics; Measurement; Measures; Mechanics; Medical; Medicine; Mentors; Methods; Michigan; Motion; Noise; Operative Surgical Procedures; Outcome; Pathologic; Pathology; Patients; Physics; Pilot Projects; Positioning Attribute; Process; Psyche structure; Recurrence; Research; Research Training; Resources; Safety; Scanning; Students; Techniques; Technology; Time; Tissues; Training; Ultrasonics; Ultrasonography; United States; Universities; Woman; base; breast imaging; breast lesion; cancer imaging; career; clinically relevant; cost effectiveness; design; elastography; follow-up; human subject; imaging modality; improved; in vivo; indexing; malignant breast neoplasm; mechanical load; novel; programs; prospective; public health relevance; simulation; social; soft tissue; therapeutic evaluation; tool; treatment planning; undergraduate research; undergraduate student

Project Summary Breast cancer is a significant healthcare and social-economical problem. The primary objective is to develop a quantitative, noninvasive technique that enables accurate characterization of breast tumors by incorporation of local shear deformation. The technique could be integrated into 3D automated breast ultrasound (ABUS) scanner or conventional 2D ultrasound scanners, in a way which could provide clinically relevant information for lesion differentiation and management during diagnosis, treatment planning, and post-treatment evaluation. Specific research aims are: (1) improve displacement measurements by developing a novel physics-based denoising algorithm as a post- processing tool, (2) investigate novel metrics to accurately quantify local ultrasound strain elastography-derived shear deformation and (3) determine improved usefulness of elastography- based analytics. An integral plan of this AREA proposal is also to mentor and encourage undergraduate students to pursue careers in quantitative biomedical engineering through impactful cancer imaging research. To establish the feasibility, computer-simulated ultrasound elastography data and in vivo 2D and 3D ultrasound data involving biopsy-confirmed breast lesions will be used to validate our approach. If feasibility is established, a follow-up project is planned to examine the clinical utility of this technique in a prospective clinical study by integrating all developed techniques into an ABUS scanner. This AREA proposal may also make impacts on Michigan Technological University by providing resources for training undergraduate students and building a nationally recognized research and educational program in human healthcare.

项目概要 乳腺癌是一个重大的医疗保健和社会经济问题。主要目标是 开发一种定量、非侵入性技术，能够准确表征乳腺肿瘤 通过结合局部剪切变形。该技术可以集成到 3D 自动化中 乳房超声 (ABUS) 扫描仪或传统的 2D 超声扫描仪，以一种可以 在诊断过程中为病变区分和管理提供临床相关信息， 治疗计划和治疗后评估。具体研究目标是：（1）提高 通过开发一种新颖的基于物理的去噪算法作为后处理来进行位移测量 处理工具，(2) 研究新的指标以准确量化局部超声应变 弹性成像导出的剪切变形和（3）确定弹性成像的改进用途- 基于分析。该 AREA 提案的一个整体计划也是指导和鼓励 本科生通过有影响力的方式从事定量生物医学工程职业 癌症影像研究。 建立可行性、计算机模拟超声弹性成像数据以及体内 2D 和 3D 涉及活检证实的乳腺病变的超声数据将用于验证我们的方法。如果 可行性已确定，计划开展后续项目来检验该技术的临床实用性 通过将所有开发的技术集成到 ABUS 扫描仪中进行前瞻性临床研究。这 AREA 提案还可能通过提供资源对密歇根理工大学产生影响 培养本科生并建立国家认可的研究和教育机构 人类保健计划。