Photoacoustic Image Guidance of Hysterectomies

子宫切除术的光声图像指导

基本信息

  • 批准号:
    10586827
  • 负责人:
  • 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
  • 起止时间:
    2023-08-01 至 2027-05-31
  • 项目状态:
    未结题

项目摘要

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.
项目总结

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Muyinatu A. Lediju Bell其他文献

Overfit detection method for deep neural networks trained to beamform ultrasound images
用于训练以对超声图像进行波束形成的深度神经网络的过拟合检测方法
  • DOI:
    10.1016/j.ultras.2024.107562
  • 发表时间:
    2025-04-01
  • 期刊:
  • 影响因子:
    4.100
  • 作者:
    Jiaxin Zhang;Muyinatu A. Lediju Bell
  • 通讯作者:
    Muyinatu A. Lediju Bell
Deep Learning-Based Displacement Tracking for Post-Stroke Myofascial Shear Strain Quantification
基于深度学习的位移跟踪,用于中风后肌筋膜剪切应变量化
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Md Ashikuzzaman;Jonny Huang;Steve Bonwit;Azin Etemadimanesh;Preeti Raghavan;Muyinatu A. Lediju Bell
  • 通讯作者:
    Muyinatu A. Lediju Bell
Mitigating skin tone bias in linear array emin vivo/em photoacoustic imaging with short-lag spatial coherence beamforming
利用短滞后空间相干波束形成减轻线性阵列体内/体外光声成像中的肤色偏差
  • DOI:
    10.1016/j.pacs.2023.100555
  • 发表时间:
    2023-10-01
  • 期刊:
  • 影响因子:
    6.800
  • 作者:
    Guilherme S.P. Fernandes;João H. Uliana;Luciano Bachmann;Antonio A.O. Carneiro;Muyinatu A. Lediju Bell;Theo Z. Pavan
  • 通讯作者:
    Theo Z. Pavan

Muyinatu A. Lediju Bell的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Muyinatu A. Lediju Bell', 18)}}的其他基金

Minimizing Uncertainty in Breast Ultrasound Imaging with Real-Time Coherence-Based Beamforming
通过基于实时相干的波束形成最大限度地减少乳房超声成像的不确定性
  • 批准号:
    10417922
  • 财政年份:
    2022
  • 资助金额:
    $ 35.94万
  • 项目类别:
Minimizing Uncertainty in Breast Ultrasound Imaging with Real-Time Coherence-Based Beamforming
通过基于实时相干的波束形成最大限度地减少乳房超声成像的不确定性
  • 批准号:
    10679017
  • 财政年份:
    2022
  • 资助金额:
    $ 35.94万
  • 项目类别:
A Machine Learning Alternative to Beamforming to Improve Ultrasound Image Quality for Interventional Access to the Kidney
波束成形的机器学习替代方案可提高肾脏介入治疗的超声图像质量
  • 批准号:
    10170765
  • 财政年份:
    2020
  • 资助金额:
    $ 35.94万
  • 项目类别:
A Machine Learning Alternative to Beamforming to Improve Ultrasound Image Quality for Interventional Access to the Kidney
波束成形的机器学习替代方案可提高肾脏介入治疗的超声图像质量
  • 批准号:
    9913520
  • 财政年份:
    2018
  • 资助金额:
    $ 35.94万
  • 项目类别:
Coherence-Based Photoacoustic Image Guidance of Transsphenoidal Surgeries
基于相干性的光声图像引导经蝶手术
  • 批准号:
    8891530
  • 财政年份:
    2015
  • 资助金额:
    $ 35.94万
  • 项目类别:
Coherence-Based Photoacoustic Image Guidance of Transsphenoidal Surgeries
基于相干性的光声图像引导经蝶手术
  • 批准号:
    9043878
  • 财政年份:
    2015
  • 资助金额:
    $ 35.94万
  • 项目类别:

相似海外基金

Nonlinear Acoustics for the conditioning monitoring of Aerospace structures (NACMAS)
用于航空航天结构调节监测的非线性声学 (NACMAS)
  • 批准号:
    10078324
  • 财政年份:
    2023
  • 资助金额:
    $ 35.94万
  • 项目类别:
    BEIS-Funded Programmes
ORCC: Marine predator and prey response to climate change: Synthesis of Acoustics, Physiology, Prey, and Habitat In a Rapidly changing Environment (SAPPHIRE)
ORCC:海洋捕食者和猎物对气候变化的反应:快速变化环境中声学、生理学、猎物和栖息地的综合(蓝宝石)
  • 批准号:
    2308300
  • 财政年份:
    2023
  • 资助金额:
    $ 35.94万
  • 项目类别:
    Continuing Grant
University of Salford (The) and KP Acoustics Group Limited KTP 22_23 R1
索尔福德大学 (The) 和 KP Acoustics Group Limited KTP 22_23 R1
  • 批准号:
    10033989
  • 财政年份:
    2023
  • 资助金额:
    $ 35.94万
  • 项目类别:
    Knowledge Transfer Partnership
User-controllable and Physics-informed Neural Acoustics Fields for Multichannel Audio Rendering and Analysis in Mixed Reality Application
用于混合现实应用中多通道音频渲染和分析的用户可控且基于物理的神经声学场
  • 批准号:
    23K16913
  • 财政年份:
    2023
  • 资助金额:
    $ 35.94万
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
Combined radiation acoustics and ultrasound imaging for real-time guidance in radiotherapy
结合辐射声学和超声成像,用于放射治疗的实时指导
  • 批准号:
    10582051
  • 财政年份:
    2023
  • 资助金额:
    $ 35.94万
  • 项目类别:
Comprehensive assessment of speech physiology and acoustics in Parkinson's disease progression
帕金森病进展中言语生理学和声学的综合评估
  • 批准号:
    10602958
  • 财政年份:
    2023
  • 资助金额:
    $ 35.94万
  • 项目类别:
The acoustics of climate change - long-term observations in the arctic oceans
气候变化的声学——北冰洋的长期观测
  • 批准号:
    2889921
  • 财政年份:
    2023
  • 资助金额:
    $ 35.94万
  • 项目类别:
    Studentship
Collaborative Research: Estimating Articulatory Constriction Place and Timing from Speech Acoustics
合作研究:从语音声学估计发音收缩位置和时间
  • 批准号:
    2343847
  • 财政年份:
    2023
  • 资助金额:
    $ 35.94万
  • 项目类别:
    Standard Grant
Flow Physics and Vortex-Induced Acoustics in Bio-Inspired Collective Locomotion
仿生集体运动中的流动物理学和涡激声学
  • 批准号:
    DGECR-2022-00019
  • 财政年份:
    2022
  • 资助金额:
    $ 35.94万
  • 项目类别:
    Discovery Launch Supplement
Collaborative Research: Estimating Articulatory Constriction Place and Timing from Speech Acoustics
合作研究:从语音声学估计发音收缩位置和时间
  • 批准号:
    2141275
  • 财政年份:
    2022
  • 资助金额:
    $ 35.94万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了