课题基金 / 基金详情

Photoacoustic Image Guidance of Hysterectomies

Photoacoustic Image Guidance of Hysterectomies
子宫切除术的光声图像指导
批准号:
10586827
负责人:
Muyinatu A. Lediju Bell
金额:
$35.94万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-01 至 2027-05-31

项目摘要

项目成果

Muyinatu A. Lediju Bell的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
Project Summary Ureteral injury represents one of the most serious complications of pelvic surgery, with a majority of these injuries occurring during gynecological procedures. This injury is particularly problematic during hysterectomies because of the proximity between the ureter and nearby blood vessels. One barrier to progress is the absence of clinically available technology to identify relative positions of the ureter, uterine arteries, and tool tips with suf- ficient depth penetration and image contrast. We previously demonstrated that photoacoustic imaging achieves simultaneous detection of critical structures with approximately 25-30 dB contrast at centimeter depths, allowing for complete avoidance of the ureter and better targeting of the uterine arteries. However, to advance this tech- nology into surgical practice, we need to establish the optical, acoustic, and navigation parameters necessary to achieve optimal detection of tool tips, blood vessels, and ureters. Optimizing photoacoustic imaging system designs and providing informative real-time feedback during hysterectomies will enable these surgeries to be performed without the complications that are typically associated with ureteral injuries, including extensive re- peat surgeries, complete kidney failure, sepsis, acute renal insufficiency, and patient death. Our long-term goal is to develop guidance technology to differentiate critical structures in real-time during surgery. The overall objective of this proposal is to establish optimal parameters to advance photoacoustic technol- ogy toward differentiation of ureters, uterine arteries, and tool tips during hysterectomies. Aim 1 of this project will define the light delivery requirements for optimal visibility of laparoscopic surgical tool tips and underlying structures. Aim 2 will integrate and optimize sound reception components and parameters for photoacoustic imaging of the ureter, uterine artery, and tool tips. Aim 3 will pursue in vivo demonstrations of robotic hysterec- tomy navigation with photoacoustic imaging system components. These three aims will be tested independently with a combination of simulation, cadaver, swine, and human patient studies, resulting in multiple possibilities for deploying the proposed technology. Successful completion of the proposed project will establish a series of viable photoacoustic imag- ing system designs to enable ureter avoidance during hysterectomies. This project is innovative because of the novel integration and refinement of photoacoustic approaches and techniques to distinguish the ureter from the uterine artery. The project results are anticipated to have a significant impact on patients undergoing laparoscopic hysterectomies, robotic hysterectomies, and other robotic surgeries (e.g., radical prostatectomies, thoracic surgeries), with possible extensions to additional surgeries wherein critical structures reside in close proximity. The proposed research aligns with NIBIB’s mission to accelerate the application of biomedical tech- nologies by supporting research to advance the development of new tools for visualizing critical structures to target or avoid during minimally invasive surgeries.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Minimizing Uncertainty in Breast Ultrasound Imaging with Real-Time Coherence-Based Beamforming
  • 批准号:
    10417922
  • 项目类别:
  • 资助金额:
    $35.2万
  • 财政年份:
    2022
  • 负责人:
    Muyinatu A. Lediju Bell
  • 依托单位:
Minimizing Uncertainty in Breast Ultrasound Imaging with Real-Time Coherence-Based Beamforming
  • 批准号:
    10679017
  • 项目类别:
  • 资助金额:
    $34.42万
  • 财政年份:
    2022
  • 负责人:
    Muyinatu A. Lediju Bell
  • 依托单位:
A Machine Learning Alternative to Beamforming to Improve Ultrasound Image Quality for Interventional Access to the Kidney
  • 批准号:
    10170765
  • 项目类别:
  • 资助金额:
    $23.5万
  • 财政年份:
    2020
  • 负责人:
    Muyinatu A. Lediju Bell
  • 依托单位:
A Machine Learning Alternative to Beamforming to Improve Ultrasound Image Quality for Interventional Access to the Kidney
  • 批准号:
    9913520
  • 项目类别:
  • 资助金额:
    $23.5万
  • 财政年份:
    2018
  • 负责人:
    Muyinatu A. Lediju Bell
  • 依托单位:
海外基金