Use of Radiological Clips for Improving Quantitative Ultrasound Imaging

使用放射夹改善定量超声成像

基本信息

项目摘要

Project Summary Radiological markers or clips are an essential diagnostic and surgical tool. Radiological clips made of titanium or gold are widely used, compatible with MRI and have proven safe for use in human patients. These clips come in many shapes and sizes and are visible with both X-ray and ultrasound. The clips provide large ultrasonic scattering signals because they are made of gold or titanium, which have large impedance mismatch with tissue. For example, patients with locally advanced breast cancer (LABC) undergoing neoadjuvant chemotherapy have clips placed in the tumors so that surgeons can locate and excise, with accuracy, residual cancer tissue. Over the last fifteen years, we have been developing quantitative ultrasound (QUS) imaging techniques for a number of applications including monitoring of therapy response. We have demonstrated that QUS techniques can detect the response of tumors to therapy because QUS is sensitive to the presence of cell death. Recently, we were able to implement this approach in a small clinical study, where we demonstrated the ability of QUS to definitively detect and predict the response of LABC patients to chemotherapy between one and four weeks from therapy onset. We verified that QUS could identify LABC therapy responders and nonresponders. However, we hypothesize that accuracies of QUS estimates in humans can be dramatically improved by incorporating a novel calibration procedure that utilizes appropriate radiological clips as an in situ calibration target. Clinically, these clips are already being placed in tumors for various diagnostic tasks. By inserting an appropriate type of clip, the clip can be used as an in situ calibration providing a reference signal for QUS estimates. The in situ reference will automatically correct for attenuation and transmission losses from overlying tissue layers. Current reference phantom techniques are incomplete in providing corrections for attenuation and transmission losses. Therefore, the use of appropriate radiological clips as calibration targets will provides superior bias and variance of QUS estimates resulting in improved accuracy for identifying LABC response. The scientific premise of the proposed research is that radiological markers used for X-ray and conventional ultrasound can also be used as an in situ calibration target for improving QUS estimates in vivo. Novel calibration procedures will be tested and refined in phantom studies, in animals models of cancer and finally validated in human breast cancer patients undergoing neoadjuvant chemotherapy using QUS to identify early responders to therapy. To verify this scientific premise we propose three specific aims. 1) Develop and refine an in situ calibration approach in phantom studies that accounts for layering effects on QUS estimates thereby improving QUS estimate accuracy. 2) Validate the in situ calibration approach in animal models of cancer and quantify calibration properties in a longitudinal study. 3) Collect longitudinal QUS patient data at early time points during the course of neoadjuvant chemotherapy using a novel in situ calibration procedure and quantify the improvements of QUS classifier accuracy with the in situ calibration approach.
项目总结

项目成果

期刊论文数量(12)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Calibrating Data Mismatches in Deep Learning-Based Quantitative Ultrasound Using Setting Transfer Functions.
使用设置传输功能,在基于深度学习的定量超声中校准数据不匹配。
High-Level Synthesis Design of Scalable Ultrafast Ultrasound Beamformer With Single FPGA.
Effects of acoustic nonlinearity on communication performance in soft tissues.
声学非线性对软组织通信性能的影响。
A Data-Efficient Deep Learning Strategy for Tissue Characterization via Quantitative Ultrasound: Zone Training.
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Michael L. Oelze其他文献

Detection and localization of small metastatic foci in human lymph nodes using three-dimensional high-frequency quantitative ultrasound methods
使用三维高频定量超声方法检测和定位人体淋巴结中的小转移灶
  • DOI:
  • 发表时间:
    2011
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jonathan Mamou;Emi Saegusa-Beecroft;Alain Coron;Michael L. Oelze;Masaki Hata;Junji Machi;Eugene Yanagihara;Pascal Laugier;Tadashi Yamaguchi;Ernest J. Feleppa
  • 通讯作者:
    Ernest J. Feleppa
Low-frequency sound wave parameter measurement in gravels
  • DOI:
    10.1016/j.apacoust.2009.07.003
  • 发表时间:
    2010-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    George W. Swenson;Michael J. White;Michael L. Oelze
  • 通讯作者:
    Michael L. Oelze

Michael L. Oelze的其他文献

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{{ truncateString('Michael L. Oelze', 18)}}的其他基金

2022 In Vivo Ultrasound Imaging Gordon Research Conference
2022 体内超声成像戈登研究会议
  • 批准号:
    10535954
  • 财政年份:
    2022
  • 资助金额:
    $ 53.76万
  • 项目类别:
Development of radiological clips having ultrasound identification
具有超声识别功能的放射线夹的研制
  • 批准号:
    10493425
  • 财政年份:
    2021
  • 资助金额:
    $ 53.76万
  • 项目类别:
Development of radiological clips having ultrasound identification
具有超声识别功能的放射线夹的研制
  • 批准号:
    10365578
  • 财政年份:
    2021
  • 资助金额:
    $ 53.76万
  • 项目类别:
Use of Radiological Clips for Improving Quantitative Ultrasound Imaging
使用放射夹改善定量超声成像
  • 批准号:
    10202531
  • 财政年份:
    2020
  • 资助金额:
    $ 53.76万
  • 项目类别:
Use of Radiological Clips for Improving Quantitative Ultrasound Imaging
使用放射夹改善定量超声成像
  • 批准号:
    10400728
  • 财政年份:
    2020
  • 资助金额:
    $ 53.76万
  • 项目类别:
Use of Radiological Clips for Improving Quantitative Ultrasound Imaging
使用放射夹改善定量超声成像
  • 批准号:
    10029562
  • 财政年份:
    2020
  • 资助金额:
    $ 53.76万
  • 项目类别:
Development of super resolution ultrasound for detecting microcalcifications
开发用于检测微钙化的超分辨率超声
  • 批准号:
    9767772
  • 财政年份:
    2018
  • 资助金额:
    $ 53.76万
  • 项目类别:
Focused ultrasound therapy for remitting the symptoms of MS in a rat model
聚焦超声疗法可缓解大鼠模型中的多发性硬化症症状
  • 批准号:
    9454946
  • 财政年份:
    2017
  • 资助金额:
    $ 53.76万
  • 项目类别:
High speed ultrasonic communications for implanted medical devices
用于植入医疗设备的高速超声波通信
  • 批准号:
    9434036
  • 财政年份:
    2017
  • 资助金额:
    $ 53.76万
  • 项目类别:
Detection and Grading of Fatty and Fibrotic Liver Using Quantitative Ultrasound
使用定量超声检测脂肪肝和纤维化肝并对其进行分级
  • 批准号:
    9142321
  • 财政年份:
    2015
  • 资助金额:
    $ 53.76万
  • 项目类别:

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通过治疗前 MRI 预测乳腺癌新辅助化疗反应的放射基因组学工具
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辅助化疗预后生物标志物的分子机制分析
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