SOFTWARE DEVELOPMENT FOR REAL TIME ANALYSIS OF IN VIVO SPECTRA

体内光谱实时分析的软件开发

• 批准号: 7600873
• 负责人: RAMACHANDRA R DASARI
• 金额: $ 3.52万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-06-01 至 2008-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7600873
• 关键词: Algorithms; Biochemical; Biopsy; Charge; Collagen; Computer Retrieval of Information on Scientific Projects Database; Computer software; Diffuse; Environment; Fluorescence; Fluorescence Spectroscopy; Funding; Grant; Institution; Light; Measurement; Modeling; NADH; Nuclear; Research; Research Personnel; Resources; Site; Source; Spectrum Analysis; Time; Tissue Extracts; Tissues; United States National Institutes of Health; detector; in vivo; instrument; light scattering; programs; size; software development

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We are developing software to implement multi-modal spectroscopy as a real-time guide to biopsy. The FastEEM spectrofluorometer collects reflectance and fluorescence spectra in a fraction of a second. These spectra are then calibrated to correct for the lineshape and intensity of the incident light and the background charge of the detector. Trimodal spectroscopic algorithms (diffuse reflectance, light scattering, and intrinsic fluorescence spectroscopy) are then used to extract tissue specific parameters such as nuclear size distribution, biochemical constituents such as NADH and collagen, and reduced scattering coefficients. These tissue parameters are then used to classify tissue as normal or diseased. The software will be particularly adapted for each tissue as the modeling varies somewhat for various tissue sites. We use the graphical programming environment of National Instruments LabView in combination with Matlab to implement these algorithms along with the control software for the FastEEMspectrofluorometer. Our spectral analysis algorithms require less than one second for tissue characterization. We also collect and store the error associated with each measurement.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 我们正在开发用于实施多模式光谱的软件，作为活检的实时指南。 FastEem光谱仪以一秒钟的一小部分收集反射率和荧光光谱。然后对这些光谱进行校准，以校正入射光的线形和强度以及检测器的背景电荷。然后使用三峰光谱算法（弥漫性反射率，光散射和固有的荧光光谱）来提取组织特定参数，例如核大小分布，诸如NADH和胶原蛋白等生化成分，以及散射系数的降低。然后，这些组织参数用于将组织分类为正常或患病的组织。该软件将特别适合每个组织，因为该模型在各种组织位点有所不同。我们将LabView的图形编程环境与MATLAB结合使用，以实现这些算法以及Fasteemspectrofluorometer的控制软件。我们的光谱分析算法需要不到一秒钟才能进行组织表征。我们还收集并存储与每个测量相关的错误。