Beyond DTI: insights in heart infarcted tissue

Diffusion magnetic resonance imaging (dMRI) is an advanced clinical imaging technique based upon characterizing the water flow within body tissues. Although models of higher order (HO) than diffusion tensor imaging (DTI) have been successfully ap- plied to brain dMRI, the peculiarities of the heart hinder its appli- cation on this muscle. However, these models have been proven as a powerful way to get insights in the microstructure of organs. In this work we have applied both DTI and a HO model to two ex-vivo pig heart acquisitions for measuring their differences in a metric that we call “Non-Gaussianity” and then check how these differences are gathered on infarcted tissue. Further researching may be needed to both confirm this correlation and make these models feasible to clinical practice.

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Publication Details

Published
2026-03-09
DOI
https://doi.org/10.31428/10317/13622
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Beyond DTI: insights in heart infarcted tissue

Sánchez González Javier, Tristán Vega Antonio, Rodríguez Galván Justino R., Merino Caviedes Susana et al.
Advanced Neuroimaging Techniques and Applications
article

Beyond DTI: insights in heart infarcted tissue

Sánchez González Javier, Tristán Vega Antonio, Rodríguez Galván Justino R., Merino Caviedes Susana, Alberola López Carlos, Filgueiras Rama David
article en

Abstract

Diffusion magnetic resonance imaging (dMRI) is an advanced clinical imaging technique based upon characterizing the water flow within body tissues. Although models of higher order (HO) than diffusion tensor imaging (DTI) have been successfully ap- plied to brain dMRI, the peculiarities of the heart hinder its appli- cation on this muscle. However, these models have been proven as a powerful way to get insights in the microstructure of organs. In this work we have applied both DTI and a HO model to two ex-vivo pig heart acquisitions for measuring their differences in a metric that we call “Non-Gaussianity” and then check how these differences are gathered on infarcted tissue. Further researching may be needed to both confirm this correlation and make these models feasible to clinical practice.

Ministerio de Ciencia e Innovación
Clean water and sanitation
Openalex Percentile: Top 30%
Advanced Neuroimaging Techniques and Applications
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