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Renewal: Terahertz Polarization Imaging for Detecting Breast Tumor Margins

更新：用于检测乳腺肿瘤边缘的太赫兹偏振成像

基本信息

批准号：
10201049
负责人：
Magda El-Shenawee
金额：
$ 42.45万
依托单位：
UNIVERSITY OF ARKANSAS AT FAYETTEVILLE
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：
2017-03-03 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10201049
关键词：
Adipose tissue Algorithmic Analysis Algorithms Ambulatory Care Facilities Animal Model Area Award Biological Breast Breast Cancer Model Breast Cancer Patient Breast Carcinoma Breast-Conserving Surgery Cancer Detection Cancerous Carcinogens Clinical Clinical Trials Collaborations Collagen Data Detection Discrimination Ensure Ethylnitrosourea Evaluation Excision Fatty acid glycerol esters Frequencies Future Generations Goals Grant Growth Hospitals Human Hydration status Image Image Analysis Imaging technology Intelligence Light Liquid substance Malignant Neoplasms Mammary Neoplasms Methodology Methods Modeling Mouse Mammary Tumor Virus Operative Surgical Procedures Outcome Pathology Patients Peer Review Pre-Clinical Model Publications Rattus Repeat Surgery Research Sampling Services Signal Transduction Site Source Statistical Data Interpretation Statistical Methods Surgeon Surgical margins System Techniques Technology Testing Tissue Sample Tissues Transgenic Mice Tumor Tissue United States United States National Institutes of Health Validation Vendor Woman Work breast cancer progression breast lumpectomy cancer classification cancer imaging cancer surgery clinically relevant contrast enhanced contrast imaging design efficacy testing experience high risk human model imager imaging Segmentation improved in vivo instrument instrumentation malignant breast neoplasm novel strategies operation polarimetry primary outcome spectroscopic imaging statistics success symposium tumor tumor xenograft

项目摘要

Project Summary/Abstract Breast-conserving therapy (lumpectomy) is one of the most commonly performed breast cancer surgeries in the United States. The best outcome of the lumpectomy surgery is achieved when the surgical margins are free of cancer. When remnants of cancer are detected at the surgical margins after the initial operation, a second operation will be required to remove the cancer. Unfortunately, a significant number of patients undergo breast conserving surgery (BCS) at local hospitals that do not have access to immediate on-site pathology leading to high rates of re-excision or reoperation (greater than 30%). Therefore, there is a significant need for new intraoperative technology that can be made available for local hospitals and outpatient clinics. Our previous research concludes that while terahertz studies in pre-clinical models have shown strong differentiation between cancerous and fatty tissues, the more clinically relevant differentiation between cancerous and healthy non-fatty tissue remains challenging. To further build upon the successes of our previous award and improve the sensitivity of terahertz imaging cancer detection on the surgical margins, we have identified areas where we can significantly improve the instrumentation, the animal model, and the image analysis algorithms. As part of this renewal application, we will re-design our instrumentation to develop terahertz polarization- sensitive imaging methodology. In this new approach, all four polarizations of the waves will be incorporated to increase the spatial and spectral information about different types of tumor tissues (Aim 1). We will test the system in vivo in a carcinogen-induced model of breast cancer in rats and use biological tissue simulating phantoms to determine the sources of signal generation in the THz images (Aim 2). Finally, we will improve the detection algorithm accuracy by exploiting the spatial information embedded in the terahertz images with spatial statistics (Aim 3). The goal is to better detect the presence of healthy fibrous tissue due to their potential growth of healthy collagen adjacent to cancerous tissues in tumors. We anticipate that the new proposed approach will increase the image contrast between cancerous and healthy adjacent tissues, leading to better differentiation and classification of cancer on the tumor margins. This renewal application will allow us to develop an optimized approach that leverages multiple polarizations, the spatial information encoded in the terahertz images for analysis, and the validation of our approach on mammary tumors from rats. The success of the proposed research will allow us to expand our work to clinical trials using clinically translational and compatible terahertz technology.

项目总结/文摘

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Deep Learning Classification of Breast Cancer Tissue from Terahertz Imaging Through Wavelet Synchro-Squeezed Transformation and Transfer Learning.

DOI：
10.1007/s10762-021-00839-x
发表时间：
2022-01
期刊：
Journal of infrared, millimeter and terahertz waves
影响因子：
0
作者：
通讯作者：

Mammary tumors in Sprague Dawley rats induced by N-ethyl-N-nitrosourea for evaluating terahertz imaging of breast cancer

N-乙基-N-亚硝基脲诱导 Sprague Dawley 大鼠乳腺肿瘤用于评估乳腺癌太赫兹成像

DOI：
10.1117/1.jmi.8.2.023504
发表时间：
2021
期刊：
Journal of Medical Imaging
影响因子：
2.4
作者：
Vohra, Nagma;Chavez, Tanny;Troncoso, Joel R.;Rajaram, Narasimhan;Wu, Jingxian;Coan, Patricia N.;Jackson, Todd A.;Bailey, Keith;El-Shenawee, Magda
通讯作者：
El-Shenawee, Magda

A Phantom Study of Terahertz Spectroscopy and Imaging of Micro- and Nano-diamonds and Nano-onions as Contrast Agents for Breast Cancer.