Coherence-Based Photoacoustic Image Guidance of Transsphenoidal Surgeries

基于相干性的光声图像引导经蝶手术

基本信息

  • 批准号:
    9043878
  • 负责人:
  • 金额:
    $ 8.83万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-04-01 至 2017-03-31
  • 项目状态:
    已结题

项目摘要

 DESCRIPTION (provided by applicant): Endonasal transsphenoidal surgery is a minimally invasive procedure that involves grinding away sphenoidal bone in the nasal cavity to access and resect pituitary tumors. Each surgery incurs the risk of death resulting from injury to the carotid arteries located behind the sphenoidal bone on either side of the pituitary gland. The long-term objective of this project is to develop the imaging technology required for real-time photoacoustic visualization of blood vessels and bone to eliminate the risk of striking a carotid artery during surgery. The speci¿c aims of the mentored phase are to: (1) image vessel-like targets embedded in phantoms sur- rounded by cranial bone to characterize system requirements; and (2) develop the mathematical framework for optimized, coherence-based photoacoustic signal detection and display. This phase will be pursued at Johns Hopkins University, a pioneering institution of transsphenoidal surgeries. The speci¿c aims of the independent phase will build on the knowledge obtained during the mentored phase to design and assess a new class of coherence-based beamformers that overcome expected challenges with laser penetration, leading to the even- tual building, testing, and validation of a dedicated prototype system. The methods used to achieve these aims will include integration of beamforming theory with commercially- available optical equipment and ultrasound machines to form customized photoacoustic imaging systems. The systems will be tested on tissue-mimicking phantoms and human head models that simulate surgeries, culmi- nating with a pilot study on patients undergoing transsphenoidal surgeries. Quantitative metrics and observer studies are proposed to compare and assess image quality, while in vivo and ex vivo visualization of vessels and vessel-like targets will be correlated with endoscopic and magnetic resonance images. Although the system will initially be developed for transsphenoidal surgeries, it will be useful in any minimally- invasive surgery that requires visualization of hiddn blood vessels. In addition, the proposed coherence-based photoacoustic beamformers have broader implications for improving image quality and overcoming current depth penetration limits in multiple photoacoustic applications. My expert advisory team will consist of mentors and collaborators in interventional photoacoustics, optics, medical image analysis, neurosurgery, and the design of surgical systems. I will combine my experience in developing and implementing the ¿rst short-lag spatial coherence (SLSC) beamformer and my background in ultrasound physics and mechanical engineering with proposed training and career development in optics. Successful completion of the proposed plan promises to unlock new possibilities for clinical applications of photoacoustic imaging.
 描述(由适用提供):鼻鼻型类手术是一种微创手术,涉及将鼻腔中的蝶骨磨碎以进入和恢复垂体肿瘤。每次手术都会因垂体两侧的蝶骨后面的颈动脉受伤而导致死亡风险。该项目的长期目标是开发血管和骨骼实时光声可视化所需的成像技术,以消除手术期间撞击颈动脉的风险。修补阶段的特定目的是:(1)嵌入在颅骨中的幻影范围内的图像容器样靶标,以表征系统需求; (2)开发数学框架,用于优化,基于相干的光声信号检测和显示。这个阶段将在约翰·霍普金斯大学(Johns Hopkins University)进行,这是一个跨性类似手术机构的开创性机构。独立阶段的特定目标将建立在修补阶段中获得的知识,以设计和评估新的基于相干的束缚器,这些梁形器通过激光渗透来克服了预期的挑战,从而导致了均匀的构建,测试和验证专用的原型系统。用于实现这些目标的方法将包括将波束形成理论与商业上可用的光学设备和超声机的整合,以形成定制的光声成像系统。系统将在模拟组织模拟手术的模拟幻影和人头模型上进行测试,并通过对接受型类手术的患者进行试验研究。提出了定量指标和观察者研究来比较和评估图像质量,而体内和体内的容器和类似容器样目标的可视化将与内窥镜和磁共振图像相关。尽管该系统最初将用于跨类药物,但它在需要可视化隐藏血管的任何微创手术中都是有用的。此外,提出的基于相干的光声束形式对改善图像质量和克服当前深度渗透极限的影响更大。我的专家咨询团队将包括介入光学声学,光学,医学图像分析,神经外科手术和外科系统设计的导师和合作者。我将结合我在开发和实施第一个短空间连贯性(SLSC)波束形式方面的经验,以及我在超声物理和机械工程方面的背景,以及拟议的培训和光学的职业发展。成功完成建议的计划有望为光声成像的临床应用解锁新的可能性。

项目成果

期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Synthetic-aperture based photoacoustic re-beamforming (SPARE) approach using beamformed ultrasound data.
  • DOI:
    10.1364/boe.7.003056
  • 发表时间:
    2016-08
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
    Haichong K. Zhang;M. Bell;Xiaoyu Guo;Hyun-Jae Kang;E. Boctor
  • 通讯作者:
    Haichong K. Zhang;M. Bell;Xiaoyu Guo;Hyun-Jae Kang;E. Boctor
Toward Standardized Acoustic Radiation Force (ARF)-Based Ultrasound Elasticity Measurements With Robotic Force Control.
Spatial Angular Compounding of Photoacoustic Images.
  • DOI:
    10.1109/tmi.2016.2531109
  • 发表时间:
    2016-08
  • 期刊:
  • 影响因子:
    10.6
  • 作者:
    Kang HJ;Bell MA;Guo X;Boctor EM
  • 通讯作者:
    Boctor EM
Localization of Transcranial Targets for Photoacoustic-Guided Endonasal Surgeries.
  • DOI:
    10.1016/j.pacs.2015.05.002
  • 发表时间:
    2015-06
  • 期刊:
  • 影响因子:
    7.9
  • 作者:
    Lediju Bell MA;Ostrowski AK;Li K;Kazanzides P;Boctor EM
  • 通讯作者:
    Boctor EM
Design of a multifiber light delivery system for photoacoustic-guided surgery.
  • DOI:
    10.1117/1.jbo.22.4.041011
  • 发表时间:
    2017-04-01
  • 期刊:
  • 影响因子:
    3.5
  • 作者:
    Eddins B;Bell MA
  • 通讯作者:
    Bell MA
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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

Photoacoustic Image Guidance of Hysterectomies
子宫切除术的光声图像指导
  • 批准号:
    10586827
  • 财政年份:
    2023
  • 资助金额:
    $ 8.83万
  • 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:
    10417922
  • 财政年份:
    2022
  • 资助金额:
    $ 8.83万
  • 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:
    $ 8.83万
  • 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:
    $ 8.83万
  • 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:
    $ 8.83万
  • 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:
    $ 8.83万
  • 项目类别:

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