# Quantitative Gait Metrics to Assess and Predict Gross Motor Impairment in Young Children with Neurofibromatosis Type 1

> **NIH NS K23** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2026 · $247,995

## Abstract

Project Summary/Abstract
Most children with neurofibromatosis type 1 (NF1), one of the most common inherited neurological disorders in
the United States, experience difficulties with large muscle movements. Current methods of measuring gross
motor impairment in young children with NF1 are time- and resource-intensive, reliant on coarse scoring from a
proxy typically based on the presence or absence of abilities without regard to the quality of function. These
limitations hamper counseling in the clinic on the severity of gross motor difficulties, prediction of future
function, and guidance on treatment planning. The objective of this K23 proposal is to develop office-based
tools to quantify gait in young children with NF1 that reflect overall gross motor impairment and predict future
gross motor difficulties. In this prospective observational study of ambulatory children less than six years old
with NF1, we will evaluate gait speed as the fastest time to walk 10 meters and interlimb coordination derived
from artificial intelligence-based pose estimates from video. We will conduct office-based gait assessments
with video, clinical exams, and neurodevelopmental evaluations during routine medical visits at baseline, 12
months, and 24 months at one of the largest NF1 centers in the U.S., the NYU Comprehensive
Neurofibromatosis Center. Using this design, our specific aims are to: (1) evaluate how well gait speed and
interlimb coordination reflect gross motor impairment compared to currently available neurodevelopmental
assessments; (2) determine the test-retest reliability of gait speed and interlimb coordination; and (3)
investigate the prognostic ability of gait speed and interlimb coordination to predict gross motor impairment up
to two years later. We expect these findings will result in improved developmental surveillance in clinic and
inform clinical trial design with the addition of performance-based endpoints. This proposal aligns with the
NINDS strategic plan of

## Key facts

- **NIH application ID:** 11283030
- **Project number:** 1K23NS146694-01
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Nicolas Julian Abreu
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NS
- **Fiscal year:** 2026
- **Award amount:** $247,995
- **Award type:** 1
- **Project period:** 2026-02-01T00:00:00 → 2031-01-31T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11283030

## Citation

> US National Institutes of Health, RePORTER application 11283030, Quantitative Gait Metrics to Assess and Predict Gross Motor Impairment in Young Children with Neurofibromatosis Type 1 (1K23NS146694-01). Retrieved via AI Analytics 2026-06-26 from https://api.ai-analytics.org/grant/nih/11283030. Licensed CC0.

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