Standardized MRSI Data Analysis Platform (MAPS)
Biomedical Engineering
Carolina Avila, Dimitra Manatou, Rohit Panicker, Anneth Stephen, Christopher Zapata
Abstract
Our team M.A.P.S. focuses on developing a platform designed specifically for working with Magnetic Resonance Spectroscopic Imaging (MRSI) data. The main idea is to finally create one place where users can open, visualize, and interact with spectroscopy datasets without dealing with multiple programs, format issues, or missing metadata. We built the platform as a plugin inside Napari, since Napari provides a fast, flexible viewer for multidimensional medical imaging and gives us a strong foundation for real-time visualization. Within this environment, we combine anatomical images with their corresponding voxel-level spectra so users can explore metabolic information across the brain in a simple, intuitive interface.
The clinical need for this platform is clear. Currently, there is no reliable software that can open all MRSI data types. Each scanner vendor uses its own format, which forces clinicians and researchers to manually convert files, fix corrupted metadata, or write scripts just to view their data. This slows down both clinical workflows and research progress. Our platform solves this by supporting multiple MRSI formats including DICOM spectroscopy objects, NIfTI files, and vendor-specific exports and loading them directly into Napari without preprocessing. This gives users one unified environment for exploring spectroscopy data.
The design specifications include a universal MRSI data opener, a converter that exports spectra into NIfTI, a 2D/3D anatomical viewer inside Napari, and basic MRSI analysis tools like peak detection, spectral comparison, and simple quantification. Spectra updates in real time as users click through voxels, and the system remains lightweight enough for standard computers. Because our platform is a software-only tool, the design for manufacturing is extremely low-cost. It relies entirely on open-source libraries, distributes easily through PyPI or Napari’s plugin manager, and requires no dedicated hardware. The modular structure also makes future updates and feature expansions straightforward and inexpensive.