# Metabolic Imaging Core

> **NIH NIH P30** · MASSACHUSETTS GENERAL HOSPITAL · 2020 · $182,204

## Abstract

Metabolic Imaging Core
Project Summary/Abstract
Substantial advances in non-invasive imaging technologies have enabled highly sophisticated assessments of
body composition, tissue physiology and brain function that accelerate translational research in human obesity
and nutrition. The central goal of the NORC-H Metabolic Imaging Core is to coordinate and centralize the
research imaging needs of NORC-H and encourage use of advanced metabolic imaging techniques. The
NORC-H Metabolic Imaging Core will also provide support in research design, including but not limited to
standard and emerging body composition techniques, positron emission tomography and tracer development,
functional magnetic resonance imaging and brain morphology protocols. The aims of the NORC-H Metabolic
Imaging Core are to: 1. Provide a variety of advanced imaging services and assistance in the development of
protocols for nutrition and obesity studies in need of imaging-based outcomes. 2. Provide consultative services
in imaging analysis, including quantitative interpretation of imaging data. 3. Provide a variety of image-guided
biopsy techniques for research purposes, including muscle, liver bone marrow and adipose tissue biopsies. 4.
Provide space and technical personnel for specialized imaging analyses. 5. Conduct tutorials and workshops in
imaging techniques used in metabolic investigation.

## Key facts

- **NIH application ID:** 9980372
- **Project number:** 5P30DK040561-24
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** MARTIN TORRIANI
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $182,204
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9980372

## Citation

> US National Institutes of Health, RePORTER application 9980372, Metabolic Imaging Core (5P30DK040561-24). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9980372. Licensed CC0.

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