# BrainSuite: Software for Analysis and Visualization of Multimodal Brain Imaging Data

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2021 · $407,962

## Abstract

Abstract
For the past 20 years, we have developed and distributed BrainSuite, a collection of open-source software tools
that provide advanced capabilities for analysis and visualization of brain MRI. Since 2011, this effort has been
largely supported by the parent NINDS Grant R01-NS078940. The parent grant was awarded under the
“Extended Development, Hardening and Dissemination of Technologies in Biomedical Computing, Informatics
and Big Data Science” mechanism (PA-14-156), and is largely focused on developing new tools for coregistration
of multimodal imaging data, modeling and analysis of diffusion data, and quantitative analysis of functional and
structural connectivity. These tools have been developed with the goal of supporting a broad a range of
neuroimaging studies, but we have not previously had an Alzheimer’s disease (AD) on this project.
In the present application, we identified key areas where BrainSuite can be applied and extended to create new
methods specifically designed for probing brain imaging data to identify functional and structural changes that
indicate neurodegeneration in subjects in the early stages of Alzheimer’s disease. These new methods will focus
on two areas of the brain, the transentorhinal and entorhinal region of the medial temporal lobe, that are known
to show tau tangles in the earliest stages of the disease. The transentorhinal cortex in particular is one that has
not often been analyzed using computational anatomy methods despite its implication in early-stage AD.
Our proposal builds on recently developed longitudinal diffeomorphic analysis methods and applying them to the
study of the transentorhinal cortex (TEC) and entorhinal cortex (ERC), which relied upon manual delineation to
identify TEC and ERC. Given the high potential for these new methods to be of value in AD research, we have
developed Aim 1 of the supplement proposal to adapt BrainSuite’s registration and labeling tools, developed
under the parent grant, to automatically identify TEC and ERC. This will accelerate the use of the longitudinal
diffeomorphic analysis methods. Under Aim 2 of the supplement proposal, we will develop the longitudinal
diffeomorphic pipeline as a tool integrated into BrainSuite. This will accelerate the ability of investigators to apply
this framework in the research setting. In Aim 2, we will also develop tools to examine AD-related functional
changes in resting-state fMRI data. This will build on the methods we have developed in the parent grant for
analyzing fMRI data, and enable the examination of changes in functional connectivity associated with TEC and
ERC that are likely to result as a product of neurodegeneration associated with AD.
We anticipate that the new research supported by this supplement will lead to new tools that will provide an AD
biomarker that provides an early indicator of AD, as well as a mechanism for tracking AD progression. As with
all BrainSuite tools, these new methods will be made available...

## Key facts

- **NIH application ID:** 10289681
- **Project number:** 3R01NS074980-10S1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Richard M Leahy
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $407,962
- **Award type:** 3
- **Project period:** 2011-05-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10289681

## Citation

> US National Institutes of Health, RePORTER application 10289681, BrainSuite: Software for Analysis and Visualization of Multimodal Brain Imaging Data (3R01NS074980-10S1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10289681. Licensed CC0.

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