# IMPROVED MONITORING OF PREMANIFEST AND EARLY HUNTINGTONS USING 7T MULTIMODAL MRI

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2021 · $626,757

## Abstract

PROJECT ABSTRACT
Huntington's disease (HD) is a genetic neurodegenerative disorder with a long latent period that usually lasts
into early adulthood, until motor, cognitive and psychiatric symptoms overtly impact functional capacity and
then gradually advance with time. The age of onset, severity of symptoms, and rate of progression vary
significantly across affected individuals, and there is a strong need to develop objective metrics to characterize
disease status in order to appropriately counsel patients, design clinical trials, and evaluate the efficacy of
putative therapeutic interventions. Existing markers for prognosis based on age and genetic testing lack
predictive power, and indicators of disease progression use clinical and neuropsychological evaluation that
suffer from poor sensitivity and reproducibility. Longitudinal changes in striatal volume are established markers
for disease progression, but fail to capture the heterogeneity seen during the disease course across patients.
The goal of this study is to increase the sensitivity to regional brain changes in premanifest and early
symptomatic HD multi-contrast 7T MRI based on quantitative susceptibility mapping (QSM), quantitative
morphometry of structural MRI, and brain connectivity analysis with diffusion tensor imaging in order to develop
spatially varying, time-dependent, multi-modal models capable of predicting disease course in HD.
We propose to longitudinally study patients using anatomic, susceptibility-sensitive, and diffusion-weighted
MRI. Using measurements of striatal volume and shape, regional values of quantitative susceptibility, and
tract-specific white matter diffusion derived from 7T MRI examinations, we aim to detect and characterize the
regional distribution and temporal course of neuronal loss, disease-related iron deposition, and white matter
injury in this disorder. High-field 7T MRI will be used to enhance measurements of microscopic tissue
susceptibility, and recently developed techniques for striatal shape analysis and white matter diffusion
alterations are applied to increase the sensitivity to disease progression. Data will be collected in 45 individuals
with premanifest HD and 45 individuals with early symptomatic HD, as well as 30 healthy controls.
Aim 1 will evaluate multi-contrast 7T MRI for monitoring progression of subclinical and early HD by
estimating regional cross-sectional differences and within-patient longitudinal changes in imaging parameters.
Aim 2 will determine whether including QSM in a multivariate model of disease burden improves
predictive accuracy of the manifestation of symptoms by generating a patient-level multivariate model and
voxel-level spatial map of affected brain regions that discriminates each disease stage, and relating imaging
metrics to measures of disease burden, cognitive function, and clinical impairment.
The proposed study will ultimately result in an understanding of the complicated relationship between iron
depositi...

## Key facts

- **NIH application ID:** 10210445
- **Project number:** 5R01NS099564-05
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Christopher Paul Hess
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $626,757
- **Award type:** 5
- **Project period:** 2017-07-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10210445

## Citation

> US National Institutes of Health, RePORTER application 10210445, IMPROVED MONITORING OF PREMANIFEST AND EARLY HUNTINGTONS USING 7T MULTIMODAL MRI (5R01NS099564-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10210445. Licensed CC0.

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