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
- 来源:
- 关键词:AccelerationAcousticsAcute Kidney FailureAdvanced DevelopmentAgeAnatomyArteriesBenchmarkingBiomedical TechnologyBiometryBlood VesselsCadaverCessation of lifeClinicalClutteringsComplicationContrast MediaCustomDetectionDevelopmentDyesEngineeringExcisionFDA approvedFacultyFamily suidaeFeedbackFiber OpticsFoundationsFutureGoalsGynecologicGynecologic Surgical ProceduresHemoglobinHemorrhageHospitalsHumanHysterectomyImageImaging DeviceImaging technologyInjuryKidney FailureLaparoscopic Surgical ProceduresLength of StayLettersLightMetalsMethodsMethylene blueMissionMorphologic artifactsNational Institute of Biomedical Imaging and BioengineeringOperative Surgical ProceduresOpticsPatientsPelvisPenetrationPerformancePilot ProjectsPositioning AttributeProceduresPropertyProstatectomyPublic HealthRadical ProstatectomyRecoveryRepeat SurgeryResearchResearch SupportResourcesRobotRoboticsSepsisSeriesSignal TransductionStructureSurgeonSystemTechniquesTechnologyTestingThoracic Surgical ProceduresTimeTranslationsUltrasonographyUniversitiesUreterUrineUterine myomectomyUterusVaginaVeterinary PathologyVisualizationVisualization softwareWomanWorkabsorptionauditory feedbackclinical translationcontrast imagingdeep learningdesignexperienceexperimental studyimage guidedimaging systemin vivoinnovationmechanical pressureminimally invasivemolecular imagingnoveloptical fiberphotoacoustic imagingpreferencepreservationrobot assistancesimulationsoundtooltransmission processtrendurinary
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.
项目概要
输尿管损伤是盆腔手术最严重的并发症之一,其中大多数是
妇科手术期间发生的伤害在子宫切除术期间尤其成问题。
由于输尿管和附近血管很接近,进展的障碍之一是缺乏。
临床可用技术可识别输尿管、子宫动脉和工具尖端的相对位置
我们之前证明了光声成像可以实现良好的深度穿透和图像对比度。
在厘米深度处以大约 25-30 dB 对比度同时检测关键结构,从而允许
然而,为了完全避开输尿管并更好地瞄准子宫动脉,要推进这项技术。
将科学融入外科实践中,我们需要建立必要的光学、声学和导航参数
优化光声成像系统,实现工具尖端、血管和输尿管的最佳检测。
在子宫切除术期间设计并提供信息丰富的实时反馈将使这些手术能够
进行时不会出现通常与输尿管损伤相关的并发症,包括广泛的再治疗
泥炭手术、完全肾衰竭、败血症、急性肾功能不全和患者死亡。
是开发引导技术以在手术过程中实时区分关键结构。
该提案的总体目标是建立最佳参数以推进光声技术 -
该项目的目标 1 是在子宫切除术期间区分输尿管、子宫动脉和工具提示。
将定义腹腔镜手术工具尖端和底层的最佳可见度的光传输要求
目标 2 将集成和优化光声的声音接收组件和参数。
Aim 3 将进行输尿管、子宫动脉和工具提示的体内演示。
tomy导航用光声成像系统组件这三个目标将被独立测试。
结合模拟、尸体、猪和人类患者研究,产生多种可能性
部署所提议的技术。
拟议项目的成功完成将建立一系列可行的光声成像
荷兰国际集团的系统设计可以在子宫切除术期间避免输尿管。该项目具有创新性,因为。
光声方法和技术的新颖集成和改进来区分输尿管
预计该项目的结果将对接受子宫动脉治疗的患者产生重大影响。
腹腔镜子宫切除术、机器人子宫切除术和其他机器人手术(例如根治性前列腺切除术、
胸部手术),并可能扩展到关键结构位于附近的其他手术
拟议的研究符合 NIBIB 加速生物医学技术应用的使命。
通过支持研究来推进关键结构可视化新工具的开发
在微创手术期间瞄准或避免。
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)
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Muyinatu A. Lediju Bell其他文献
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
Muyinatu A. Lediju Bell的其他文献
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{{ 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:
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