Fluorescence lifetime method for guided therapy of brain tumors

脑肿瘤引导治疗的荧光寿命法

基本信息

  • 批准号:
    7266952
  • 负责人:
  • 金额:
    $ 10万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2006
  • 资助国家:
    美国
  • 起止时间:
    2006-08-01 至 2009-07-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): We propose clinical evaluation and optimization studies of time-resolved fluorescence spectroscopy (TR-LIFS) technique for the intraoperative identification of tumor vs. normal brain during neurosurgical resection of brain tumors. A critical need currently for neurosurgeons operating on infiltrative glial neoplasms is the ability to distinguish between normal brain and glial tumor. This project is to demonstrate the feasibility of further development of a fluorescencebased device that will enhance the ability of neurosurgeons to distinguish tumor from normal brain intraoperatively without the need for biopsy. The device will use TR-LIFS technique to identify tumor margins and assess the efficacy of diagnostic procedures. If successful, this work will: (i) enhance the ability of neurosurgeons to distinguish tumor from normal brain tissue intraoperatively, (ii) improved specificity of diagnostic in brain biopsy, and (iii) increase the opportunity of image complete resection of brain tumors and decrease risk of resection of normal brain tissue. By measuring intraoperatively the time-resolved autofluorescence of human brain tumors (glioma, meningioma, metastatic) using an existing TR-LIFS research prototype apparatus and methodology, this STTR Phase I project will address 3 specific aims that combine clinical research and functionality studies over a period of 2 years: (1) To obtain a detailed knowledge of the measurability of time-resolved spectra from human brain tumors and surrounding normal tissue and to evaluate sources of experimental errors and optical loss including brain movements and blood absorption. (2) To identify the optimal TR-LIFS features/parameters which provide the best discrimination between tumor and the normal surrounding tissue by analyzing the characteristics of tissue fluorescence and comparing the spectroscopic findings to the tissue histopathology, immunohistochemical, and conventional pre-and intra-operative diagnostic techniques (MRI, Ultrasound). (3) To develop and test algorithms/software for near real-time TR-LIFS data analysis and brain tissue classification based on a representative subset of spectroscopic features. The result of Phase I will be a basis of knowledge sufficient to permit a TR-LIFS prototype device fabrication, optimized software design, and continued development in Phase II. While this project is initially tailored to brain tumors demarcation, the device could potentially be also applied to diagnosis of other tumor types.
描述(由申请人提供):我们提出时间分辨荧光光谱(TR-LIFS)技术在脑肿瘤神经外科手术中术中肿瘤与正常脑鉴别的临床评价和优化研究。目前对浸润性神经胶质肿瘤进行手术的神经外科医生的一个关键需求是区分正常脑和神经胶质肿瘤的能力。这个项目是为了证明进一步发展一种基于荧光的设备的可行性,这种设备将提高神经外科医生在手术中区分肿瘤和正常大脑的能力,而不需要活检。该设备将使用TR-LIFS技术来识别肿瘤边缘并评估诊断程序的有效性。如果成功,这项工作将:(i)提高神经外科医生术中区分肿瘤和正常脑组织的能力,(ii)提高脑活检诊断的特异性,(iii)增加图像完全切除脑肿瘤的机会,降低切除正常脑组织的风险。通过使用现有的TR-LIFS研究原型设备和方法测量术中人类脑肿瘤(胶质瘤、脑膜瘤、转移性肿瘤)的时间分辨自身荧光,该STTR I期项目将在2年内解决3个具体目标,结合临床研究和功能研究:(1)获得人类脑肿瘤和周围正常组织的时间分辨光谱可测量性的详细知识,并评估实验误差和光学损失的来源,包括大脑运动和血液吸收。(2)通过分析组织荧光特征,并将光谱结果与组织病理学、免疫组化、常规术前、术中诊断技术(MRI、超声)进行比较,确定最优的TR-LIFS特征/参数,以提供肿瘤与正常周围组织的最佳区分。(3)开发和测试基于代表性光谱特征子集的近实时TR-LIFS数据分析和脑组织分类算法/软件。第一阶段的结果将成为TR-LIFS原型设备制造、优化软件设计和第二阶段继续开发的知识基础。虽然这个项目最初是针对脑肿瘤的划分,但该设备也有可能应用于其他类型肿瘤的诊断。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Fluorescence Lifetime Spectroscopy and Imaging in Neurosurgery.
{{ 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 }}

Laura Marcu其他文献

Laura Marcu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('Laura Marcu', 18)}}的其他基金

TRD1: Interventional Fluorescence Lifetime Imaging Microscopy (iFLIM)
TRD1:介入荧光寿命成像显微镜 (iFLIM)
  • 批准号:
    10649455
  • 财政年份:
    2022
  • 资助金额:
    $ 10万
  • 项目类别:
Administrative Core
行政核心
  • 批准号:
    10649447
  • 财政年份:
    2022
  • 资助金额:
    $ 10万
  • 项目类别:
TRD1: Interventional Fluorescence Lifetime Imaging Microscopy (iFLIM)
TRD1:介入荧光寿命成像显微镜 (iFLIM)
  • 批准号:
    10424947
  • 财政年份:
    2022
  • 资助金额:
    $ 10万
  • 项目类别:
Administrative Core
行政核心
  • 批准号:
    10424946
  • 财政年份:
    2022
  • 资助金额:
    $ 10万
  • 项目类别:
Augmented reality visualization for intraoperative guidance based on fluorescence lifetime
基于荧光寿命的术中引导增强现实可视化
  • 批准号:
    9770855
  • 财政年份:
    2018
  • 资助金额:
    $ 10万
  • 项目类别:
A fiber-coupled multimodal imaging platform for in vitro assessment of engineering tissue
用于工程组织体外评估的光纤耦合多模态成像平台
  • 批准号:
    9434895
  • 财政年份:
    2017
  • 资助金额:
    $ 10万
  • 项目类别:
Fluorescence lifetime technique for detection of radiation necrosis vs gliom
用于检测放射性坏死与神经胶质细胞的荧光寿命技术
  • 批准号:
    8702828
  • 财政年份:
    2014
  • 资助金额:
    $ 10万
  • 项目类别:
Multi-modal high-resolution technology for tissue diagnostics
用于组织诊断的多模态高分辨率技术
  • 批准号:
    7922633
  • 财政年份:
    2009
  • 资助金额:
    $ 10万
  • 项目类别:
Fluorescence lifetime method for guided therapy of brain tumors
脑肿瘤引导治疗的荧光寿命法
  • 批准号:
    6991820
  • 财政年份:
    2006
  • 资助金额:
    $ 10万
  • 项目类别:
MOEMS device for fluorescence spectroscopy of tissues and cells
用于组织和细胞荧光光谱分析的 MOEMS 装置
  • 批准号:
    6983764
  • 财政年份:
    2005
  • 资助金额:
    $ 10万
  • 项目类别:

相似海外基金

CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
  • 批准号:
    2337776
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
  • 批准号:
    2338816
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
  • 批准号:
    2338846
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
  • 批准号:
    2348261
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
  • 批准号:
    2348346
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
  • 批准号:
    2348457
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
  • 批准号:
    2404989
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
  • 批准号:
    2339310
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
  • 批准号:
    2339669
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
  • 批准号:
    EP/Y029089/1
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Research Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了