Fast high-resolution simultaneous metabolic and multiparametric imaging of the whole brain

PROJECT SUMMARY The ongoing paradigm shift in healthcare towards personalized and precision medicine is posing a critical need for noninvasive imaging technology that can provide quantitative tissue and molecular information. The primary goal of this proposed Bioengineering Partnership with Industry (BPI) project is to develop and validate a new magnetic resonance-based multimodal imaging technology that can simultaneously acquire a large set of molecular and tissue property biomarkers from the whole brain in high spatial resolution and imaging speed. To this end, we have established an Academic-Industrial Partnership and assembled a special project team consisting of four PIs and seven co-investigators from University of Illinois at Urbana-Champaign, Yale University, Emory University, Johns Hopkins University, and Siemens Healthineers. The project team has unique complementary technical, medical and industrial expertise and resources in magnetic resonance spectroscopic imaging (MRSI) technology development and clinical applications. The project team will collaborate closely to: a) develop and deliver a next-generation MRSI data acquisition sequence for simultaneous multimodal imaging, b) develop and build a novel machine learning-assisted data processing pipeline, and c) carry out a multisite experimental study to evaluate and characterize the performance of the proposed multimodal imaging technology and assess its clinical potential. The proposed technology is based on innovative development of 1H-MRSI without water suppression and machine learning-assisted processing of multimodal data. By utilizing the unsuppressed water spectroscopic signals, the technology will generate quantitative tissue property maps, including T1, T2, spin density, myelin water fraction, and magnetic susceptibility at 1×1×1 mm3 resolution, which are important imaging markers for brain diseases. The technology will also simultaneously measure and quantify multiple endogenous brain metabolites and neurotransmitters, including N-acetyl aspartate, Myo-inositol, Choline, Creatine, Glutamate, Glutamine, Lactate, and γ-aminobutyric acid at 2×3×3 mm3 resolution. These molecules provide important biomarkers for brain neuronal integrity, glial proliferation, cell membrane turnover, astrocytosis, inflammation, hypoxia, and excitatory/inhibitory synaptic neurotransmission. When fully developed and validated through this partnership project, the proposed technology will provide about six-fold reduction in scan time compared with the existing state-of-the-art imaging technology that performs quantitative tissue property imaging and metabolic imaging independently. The new imaging capability is expected to greatly enhance our ability to diagnose and characterize brain diseases and assess their treatment response and efficacy. Although the proposed development and partnership target the Siemens MRI platform and use a brain tumor application as a testbed, the developed technology will readily be ported to other vendor platforms and used for other applications, such as neurodegenerative diseases.