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.
项目摘要
输尿管损伤是盆腔手术最严重的并发症之一,
在妇科手术中发生的伤害。这种损伤在膀胱切除术中尤其成问题
因为输尿管和附近的血管很接近。进步的一个障碍是
临床上可用的技术来识别输尿管、子宫动脉和工具尖端的相对位置,
足够的深度穿透和图像对比度。我们以前证明,光声成像实现
同时检测关键结构,在厘米深度处具有约25-30 dB的对比度,
以完全避开输尿管并更好地瞄准子宫动脉。不过,为了推进这项技术-
为了将神经学应用于外科实践,我们需要建立必要的光学、声学和导航参数
以实现工具尖端、血管和输尿管的最佳检测。优化光声成像系统
设计并在子宫切除术期间提供信息丰富的实时反馈将使这些手术能够
没有通常与输尿管损伤相关的并发症,包括广泛的再狭窄,
泥炭手术、完全肾衰竭、败血症、急性肾功能不全和患者死亡。我们的长期目标
是开发引导技术,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来推进光声技术。
在子宫切除术中,对输尿管、子宫动脉和工具尖端的鉴别。项目目标1
将定义腹腔镜手术工具尖端和底层的最佳可见性的光传输要求
结构.目标2将整合和优化光声的声音接收组件和参数
输尿管、子宫动脉和工具提示的成像。目标3将追求机器人滞后的体内演示-
使用光声成像系统组件的切开术导航。这三个目标将分别进行测试
结合模拟、尸体、猪和人类患者研究,
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图像-
在输尿管切除术期间能够避开输尿管的系统设计。该项目具有创新性,因为
光声方法和技术的新整合和改进,以区分输尿管
从子宫动脉中取出预计该项目的结果将对接受治疗的患者产生重大影响。
腹腔镜直肠切除术、机器人直肠切除术和其它机器人手术(例如,根治性脑切除术,
胸外科手术),并可能扩展到其他手术,其中关键结构位于靠近
接近拟议的研究与NIBIB的使命一致,以加速生物医学技术的应用,
通过支持研究来推进关键结构可视化新工具的开发,
在微创手术中瞄准或避免。
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
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
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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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