# TRD 3: MRI parameters reflecting tissue composition and microstructure

> **NIH NIH P41** · HUGO W. MOSER RES INST KENNEDY KRIEGER · 2021 · $174,683

## Abstract

TRD3: MRI parameters reflecting tissue composition and microstructure
Lead Principal investigator: Peter van Zijl, Professor of Radiology
Co-investigators: Xu Li, Manisha Aggarwal, Hye-Young Heo, Jeremias Sulam, Susumu Mori
Consultant: Filip Szczepankiewicz (Lund University)
While TRDs 1 and 2 focus on MR approaches that measure actual physiological constants and metabolite
 signals, the definition of a Quantitative Imaging Biomarker (QIB) goes much further. In TRD3 we therefore
 exploit the inherent power of MRI to probe tissue composition and microstructure, the characteristics of
 which can be accessed through a multitude of MRI phenomena and parameters that can be seen as
 candidate biomarkers. The intensity and frequency of the water signal in an MRI voxel depend on the
 local microscopic fields and field differences imposed by tissue compartments and molecules. In addition,
 the motion of water measured by MRI is affected by compartment size and permeability, which may
 change in disease and thus contain potential biomarker information. The overall goal of this TRD is to
 design pulse sequences and analysis approaches to efficiently quantify MRI parameters that assess
 tissue composition and microstructure. We have the following specific aims:
AIM 1: Development of compartmental filtering and diffusional encoding methods to probe tissue
microstructure.
AIM 2: Development of integrated susceptibility and diffusion tensor imaging (STI and DTI) for fiber
 tractography, aiming at high resolution white matter fiber tractography in vivo. Gray matter iron content
 and blood oxygenation will also be assessed from these high-resolution susceptibility images
AIM 3: Development of fast multi-parameter acquisition and analysis approaches for simultaneous
 quantification of the MR-derived parameters in Aims 1 and 2 plus T1, T2(*), and Magnetization Transfer
 Ratio (MTR).
The parameters obtained will be used to synthetically generate multiple image contrasts (synthetic MRI),
including conventional ones with which the radiologists are familiar for reading and that currently can be
acquired only separately. Eight CPs will be involved in optimizing the methods and testing these approaches
for biomarker potential. Eight SPs will use them to extend the information content in their studies. The
developed tissue markers together with the diagnostic parameters of TRD1 and TRD2 will be made available
to TRD4, which will develop statistical and deep learning technologies to combine them and make them
available in age-dependent multi-parameter brain atlases.

## Key facts

- **NIH application ID:** 10270100
- **Project number:** 1P41EB031771-01
- **Recipient organization:** HUGO W. MOSER RES INST KENNEDY KRIEGER
- **Principal Investigator:** Peter CM Van Zijl
- **Activity code:** P41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $174,683
- **Award type:** 1
- **Project period:** 2021-07-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10270100

## Citation

> US National Institutes of Health, RePORTER application 10270100, TRD 3: MRI parameters reflecting tissue composition and microstructure (1P41EB031771-01). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10270100. Licensed CC0.

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