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Magnetic Resonance Imaging

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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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Updated: May 7, 2025

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

Multi-view fusion of diffusion MRI microstructural models: a preterm birth study.

Rosella Trò¹, Monica Roascio¹, Domenico Tortora²

¹Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, Genoa, Italy.

Frontiers in Neuroscience

|January 6, 2025

Summary

This summary is machine-generated.

Advanced diffusion imaging reveals distinct white matter changes in preterm infants. This study identifies non-invasive markers for altered brain development in premature babies using multiple analysis methods for better prediction and insight.

Keywords:

diffusion Magnetic Resonance Imaging inference intramodal imaging approach prediction preterm birth

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Last Updated: May 7, 2025

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

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Published on: November 8, 2012

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Published on: December 31, 2015

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

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Published on: September 12, 2011

Area of Science:

Neuroimaging
Developmental Neuroscience
Medical Physics

Background:

High Angular Resolution Diffusion Imaging (HARDI) offers detailed microstructural insights beyond standard dMRI.
Preterm birth can lead to altered white matter development, necessitating non-invasive markers for early detection.

Purpose of the Study:

To explore advanced microstructural diffusion models for identifying non-invasive markers of altered white matter development in preterm infants.
To investigate discriminative patterns of preterm birth using multiple analysis methods.

Main Methods:

Utilized HARDI techniques on preterm infants (n=46) and term-born neonates (n=23) using a 3T scanner.
Employed Tract-Based Spatial Statistics (TBSS) for inference, Support Vector Machine (SVM) for univariate prediction, and Canonical Correlation Analysis (CCA) for multivariate prediction.

Main Results:

TBSS identified significant white matter differences between preterm and term cohorts across multiple HARDI features.
SVM classification achieved satisfactory accuracy, particularly with parameters indicating fiber directionality.
CCA revealed joint changes in measures with less agreement between TBSS and SVM, highlighting complementary information.

Conclusions:

A data-driven, intramodal imaging approach is essential for comprehensive information gathering.
Combining different analytical focuses (inference and prediction) provides both mechanistic insight and optimizes predictive accuracy for prematurity-related white matter changes.