TR&D 3: Revealing Microstructure: Biophysical Modeling and Validation for Discovery and Clinical Care

NIH RePORTER · NIH · P41 · $317,104 · view on reporter.nih.gov ↗

Abstract

TRD3 Project Summary The broad mission of our Center for Advanced Imaging Innovation and Research (CAI2R) is to bring together collaborative translational research teams for the development of high-impact biomedical imaging technologies, with the ultimate goal of changing day-to-day clinical practice. Technology Research and Development (TRD) Project 3 addresses the fundamental question of what MRI signal means at the cellular level. Unwilling to settle for the nominal resolution of clinical MRI, constrained to millimeter-sized voxels by fundamental physical and physiological limits, we have been exploring ways to quantify tissue microstructure at the scale of ∼ 1 − 10𝜇𝜇m, commensurate with water diffusion length. Incorporating diffusion MRI contrast into our acquisitions opens an avenue to supplement the subjective interpretation of anatomic images with objective parametric maps of cellular-scale biophysical parameters. Such maps, e.g., of cell sizes, water fractions in various cell types, membrane permeability and exchange rate, even if averaged over millimeter- scale voxels, would break new ground in clinical applications and basic research. In TRD3, we will integrate tissue microstructure mapping into comprehensive image data acquisitions, to address an unmet clinical need: achieving specificity to microstructural changes at the cellular level, to understand physiology and pathology, to detect disease at the earliest opportunity, to monitor disease progression, and to quantify efficacy of treatment. Building on our track record to date, we plan to develop and share acquisition, modeling, and validation tools, and translate them to the clinic. Each of the other TRDs, along with a wide range of CPs and SPs, will benefit from these tools. At the same time, microstructure research will also benefit from inclusion in the connective context of the NCBIB, with its mix of expertise (in hardware, image acquisition and reconstruction, machine learning, etc., complementing the TRD3 team’s expertise in biophysical modelling and validation), and with its track record of day-to-day interaction between researchers and clinicians.

Key facts

NIH application ID
10939349
Project number
2P41EB017183-11
Recipient
NEW YORK UNIVERSITY SCHOOL OF MEDICINE
Principal Investigator
Dmitry S Novikov
Activity code
P41
Funding institute
NIH
Fiscal year
2024
Award amount
$317,104
Award type
2
Project period
2014-09-30 → 2029-05-31