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Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Standardized Data Acquisition for Neuromelanin-Sensitive Magnetic Resonance Imaging of the Substantia Nigra

Standardized Data Acquisition for Neuromelanin-Sensitive Magnetic Resonance Imaging of the Substantia Nigra

Published on: September 8, 2021

Versatile MRI acquisition and processing protocol for population-based neuroimaging.

Alexandra Koch¹, Rüdiger Stirnberg², Santiago Estrada^1,3

¹Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.

Nature Protocols

|December 13, 2024

Summary

This summary is machine-generated.

We developed a versatile magnetic resonance imaging (MRI) protocol for large-scale population studies. This comprehensive brain imaging protocol enhances data comparability and reusability in neuroimaging research.

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Last Updated: Jun 5, 2025

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Published on: September 8, 2021

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Making MR Imaging Child's Play - Pediatric Neuroimaging Protocol, Guidelines and Procedure

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Published on: July 30, 2009

Area of Science:

Neuroimaging
Population Neuroscience
Medical Imaging

Background:

Neuroimaging is crucial for understanding brain health, cerebrovascular, and neurodegenerative diseases.
Versatile magnetic resonance imaging (MRI) acquisition and processing protocols are essential for these studies.
Existing protocols may lack the comprehensive nature required for large-scale, long-term population studies.

Purpose of the Study:

To design and develop a multipurpose, high-resolution MRI protocol for large-scale and long-term population neuroimaging studies.
To integrate MRI acquisition with automated processing pipelines and quality assurance.
To improve the comparability, interoperability, and reusability of neuroimaging data.

Main Methods:

Developed a modular MRI protocol including structural, diffusion-weighted, and functional MRI modalities.
Integrated MRI acquisition with fully automated data processing pipelines.
Implemented quality assurance for MRI data and image-derived phenotypes.

Main Results:

The protocol, taking ~1 hour of scan time, is dedicated to brain imaging.
Successfully implemented in the Rhineland Study (>11,000 participants).
Demonstrated suitability for epidemiological and clinical cross-sectional and longitudinal, multisite studies.

Conclusions:

The developed MRI protocol is suitable for large-scale, long-term population neuroimaging.
Automated processing and quality assurance enhance data reliability and comparability.
Making the protocol, sequences, and pipelines publicly available promotes data reusability and advances neuroimaging research.