# Improving the sensitivity and specificity of diffusion MRI

> **NIH NS R01** · VANDERBILT UNIVERSITY · 2026 · $596,096

## Abstract

PROJECT SUMMARY/ABSTRACT
The ability to detect fiber pathways and assess tissue microstructure in vivo has opened a new window on the
brain, with important applications ranging from brain connectomics to stroke detection and surgical planning.
Diffusion Magnetic Resonance Imaging (DMRI) has the unique ability to reveal anatomical connectivity and
tissue microstructure using noninvasive imaging methods. The development of open-source software packages
for DMRI analysis has fueled the rapid growth of applications in both systems neuroscience and clinical
neuroimaging. However, these applications have raced far ahead of the validation effort required to establish the
reliability of the methods and quantify the impact of basic assumptions made by competing algorithms. For
example, simplifying assumptions in commonly used analysis packages preclude detailed tissue characterization,
ignoring untapped information in the diffusion weighted MRI signal. On the other hand, many microstructural
analysis methods ignore fiber dispersion, which is prevalent throughout the white matter. The goal of this project
is to quantify and improve the reliability of sub-voxel measurements of fiber properties by simultaneously
improving angular resolution and sensitivity to fiber-specific diffusion properties. The project has 3 specific aims.
The first aim is to develop and validate improved methods for sub-voxel fiber identification and tissue
characterization. Results of our previous studies show that current methods have limited ability to resolve
complex fiber distributions when crossing angles are less than ~40-60° (depending on data acquisition
parameters). This limit biases fiber tractography and precludes the possibility of accurate fiber-specific
microstructure measurements. We will compare the ability of our new method and current leading algorithms
to segment and characterize sub-voxel fibers, using confocal microscopy data from the squirrel monkey as
ground truth. The second aim i

## Key facts

- **NIH application ID:** 11293436
- **Project number:** 5R01NS136743-02
- **Recipient organization:** VANDERBILT UNIVERSITY
- **Principal Investigator:** Adam W Anderson
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NS
- **Fiscal year:** 2026
- **Award amount:** $596,096
- **Award type:** 5
- **Project period:** 2025-04-01T00:00:00 → 2030-03-31T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11293436

## Citation

> US National Institutes of Health, RePORTER application 11293436, Improving the sensitivity and specificity of diffusion MRI (5R01NS136743-02). Retrieved via AI Analytics 2026-06-26 from https://api.ai-analytics.org/grant/nih/11293436. Licensed CC0.

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