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Automated Volumetric Molecular Ultrasound for Breast Cancer Imaging

用于乳腺癌成像的自动体积分子超声

基本信息

批准号：
10480758
负责人：
BRUCE L DANIEL
金额：
$ 36.68万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-01 至 2025-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10480758
关键词：
Acoustics Anatomy Animal Model Automobile Driving Biological Process Biopsy Breast Breast Cancer Detection Breast Cancer Model Breast Cancer Treatment Callback Cancer Etiology Cessation of life Clinic Clinical Clinical Trials Collaborations Computer software Contrast Media Core Biopsy Data Data Set Dedications Dependence Detection Development Devices Diagnosis Extravasation Family Foundations Frequencies General Population Health Care Costs Histology Human Image Image Analysis Imaging technology Immunohistochemistry Industrialization Malignant Neoplasms Mammary Gland Parenchyma Mammary Ultrasonography Mammography Measures Medical Methods Microbubbles Modality Molecular Molecular Profiling Monitor Morphologic artifacts Newly Diagnosed Nipples Patients Phosphotransferases Physiologic pulse Psychological Stress Research Research Proposals Resolution Rest Scanning Schedule Shapes Signal Transduction Speed Stains System Technology Testing Time Tissues Transducers Transgenic Mice Translating Translations Ultrasonic Transducer Ultrasonography United States Universities Visualization Woman accurate diagnosis breast cancer diagnosis breast imaging breast lesion cancer imaging cancer therapy cancer type clinical imaging clinical practice clinical translation cost cost efficient diagnostic accuracy experimental study first-in-human image visualization imager imaging approach imaging capabilities imaging detection imaging system improved malignant breast neoplasm molecular imaging neovasculature next generation novel pre-clinical prospective receptor targeted agent tool transmission process tumor ultrasound

项目摘要

Breast cancer is the second leading cause of cancer-related deaths in women in the United States. While mammography is the current first line imaging approach, its diagnostic accuracy is very limited in women with dense breast tissue. In those patients, ultrasound is used to supplement mammography for improved breast cancer detection and characterization. However, it often results in false positive findings with multiple unnecessary callbacks, biopsies, associated health care cost, and psychological stress for women. Ultrasound molecular imaging using contrast agents targeted at cancer-associated molecular signatures on the tumor neovasculature, such as kinase domain receptor (KDR), is an emerging strategy that has shown promising results for breast cancer detection and characterization in preclinical animal models as well as in a recent pilot clinical trial performed by our group. However, current limitations include its operator-dependency, limited anatomical coverage, and the lack of an optimized clinical imaging system for wide-spread breast ultrasound molecular imaging. The purpose of this interdisciplinary, academic-industrial collaboration between Stanford University and Siemens Medical Solutions USA, Inc. is to develop, optimize, and clinically test a new operator- independent whole-breast ultrasound imaging system based on a commercially available and widely used automated human breast volume scanner (ABVS), supporting molecular imaging for improved breast cancer imaging in the clinic. We will also develop imaging strategies to mitigate common artifacts encountered in ultrasound molecular imaging of the breast, including spurious contrast signal from tissue signal leakage and acoustic shadowing from the nipple. To assess feasibility and efficacy in the clinic, the new volumetric ultrasound molecular imaging system will then be clinically tested in women with focal breast lesions using histology and KDR staining levels on immunohistochemistry as gold standard. The technology used in this proposal can be integrated on similar other commercial devices beyond the ABVS (in the USA alone, approximately 1600 units are already used in routine clinical practice) and will therefore have immediate impact on the general public.

乳腺癌是美国女性癌症相关死亡的第二大原因。尽管乳房X光检查是目前的一线成像方法，其诊断准确性对于患有以下疾病的女性非常有限致密的乳房组织。在这些患者中，超声波用于补充乳房X光检查以改善乳房癌症检测和表征。然而，它经常导致多个假阳性结果不必要的复诊、活检、相关的医疗保健费用以及女性的心理压力。超声波使用针对肿瘤上癌症相关分子特征的造影剂进行分子成像新血管系统，例如激酶结构域受体（KDR），是一种新兴策略，已显示出有希望的临床前动物模型以及最近的试点中乳腺癌检测和表征的结果我们组进行的临床试验。然而，当前的局限性包括其对运营商的依赖性、有限的解剖覆盖范围，以及缺乏用于广泛乳腺超声的优化临床成像系统分子成像。斯坦福大学之间这种跨学科、学术与工业合作的目的大学和西门子医疗解决方案美国公司将开发、优化和临床测试一种新的操作员- 基于市售且广泛使用的独立全乳腺超声成像系统自动人体乳腺体积扫描仪 (ABVS)，支持分子成像以改善乳腺癌在诊所进行成像。我们还将开发成像策略来减轻在乳房超声分子成像，包括来自组织信号泄漏的虚假对比信号和来自乳头的声学阴影。为了评估临床的可行性和有效性，新的体积超声然后，分子成像系统将使用组织学和方法在患有局灶性乳腺病变的女性中进行临床测试。免疫组织化学 KDR 染色水平作为金标准。本提案中使用的技术可以是集成到 ABVS 之外的类似其他商业设备上（仅在美国，就有大约 1600 台已经用于常规临床实践），因此将对公众产生直接影响。