NIRFAST

描述(由申请人提供)：该项目将开发和传播一个关键的计算资源，用于将近红外光谱(NIRS)整合到磁共振成像(MRI)中。在MRI中无缝使用光谱学的方法是允许从MR图像体积通过有限元网格的灵活流动，发展到光谱学拟合和显示覆盖在MR图像上的光谱图像。现有的名为NIRFAST的软件已经可以做到这一点，并已分发给十几个研究中心，希望在图像引导设置中使用NIR。该项目将定制软件到一个真正的开源共享软件模式，在那里它可以免费下载，并可以由用户更新为未来的版本。将为参与的临床站点提供现场用户培训，以允许开发一项多中心试验，以研究MRI引导的乳腺癌近红外光谱，以确定这种MRI附加方法是否有可能减少MR乳腺检查的假阳性数量。这种软件开发和分发模式将提供在临床试验能够以多中心方式进行之前所需的基本软件工具。NCI赞助的影像翻译研究网络(NTR)的每个参与网站都将使用该软件和现有的资金参与研究，并将数据贡献给一个池。由此产生的数据将被分析并用来证明NIRFAST软件可以提供一个合作的学术平台，这种新的成像技术可以从中获得接受。软件的具体更新将允许更灵活地使用薄组织，并使用临床前实验和受试者数据验证代码。该项目的整体组织将由达特茅斯公司和埃克塞特公司的调查人员共享，作为一项合作开发。 与公众健康相关：该项目的相关性在于，它将为多个研究人员提供关键软件，以尝试将近红外光谱技术集成到乳腺癌的磁共振成像中，从而为放射科医生提供关于他们正在评估的图像中的病变的更多特定的分子信息。光谱学只有在实际集成到图像显示中时才能使用，正如本软件开发中计划的那样。该项目将对此进行开发，并允许多中心合作进行一项研究，以表明它可以集成到现有的磁共振成像系统中。

DESCRIPTION (provided by applicant): This project will develop and disseminate a key computational resource for integration of Near-Infrared Spectroscopy (NIRS) into Magnetic Resonance Imaging (MRI). The way to seamlessly use spectroscopy within MRI is to allow a flexible flow from MR image volumes through finite element mesh developed to spectroscopy fitting and display of spectral images overlying the MR images. The software existing, called NIRFAST, can already do this, and has been distributed to over a dozen research centers, wishing to use NIRS within an image guided setting. This project will customize the software into a truly open source shareware mode, where it is freely downloadable and can be updated by users for future versions. Onsite user training will be provided for participating clinical sites to allow development of a multicenter trial to study MRI- guided NIRS in breast cancer, to determine if this approach to an add-on to MRI could potentially reduce the number of false positive MR breast exams. This software development and distribution model will provide essential software tools needed before a clinical trial can be done in a multicenter manner. Participating sites in the NCI sponsored Network for Translational Research in Imaging (NTR) will each use the software with their existing funding to participate in the study, and contribute data to a pool. The resulting data will be analyzed and used to demonstrate that NIRFAST software can provide a collaborative academic platform from which acceptance of this new imaging technology can come. Specific updates to the software will allow more flexible use to thin tissues and validation of the code with pre-clinical experimental and subject data. Overall organization of the project will be shared between Dartmouth and Exeter investigators, as a collaborative development. PUBLIC HEALTH RELEVANCE: The relevance of this project is that it will provide key software to multiple investigators to try integration of Near-Infrared Spectroscopy into Magnetic Resonance imaging of breast cancer, and thereby provide radiologists more molecular-specific information about the lesions they are assessing in the image. Spectroscopy can only be used when realistically integrated into the image display, as is planned in this software development. The project will develop this, and allow multicenter collaboration on a study to show that it can be integrated into existing Magnetic resonance imaging systems.