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.
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.
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