Cargando…

Novel insights into in‐vivo diffusion tensor cardiovascular magnetic resonance using computational modelling and a histology‐based virtual microstructure

PURPOSE: To develop histology‐informed simulations of diffusion tensor cardiovascular magnetic resonance (DT‐CMR) for typical in‐vivo pulse sequences and determine their sensitivity to changes in extra‐cellular space (ECS) and other microstructural parameters. METHODS: We synthesised the DT‐CMR sign...

Descripción completa

Detalles Bibliográficos
Autores principales: Rose, Jan N., Nielles‐Vallespin, Sonia, Ferreira, Pedro F., Firmin, David N., Scott, Andrew D., Doorly, Denis J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637383/
https://www.ncbi.nlm.nih.gov/pubmed/30350880
http://dx.doi.org/10.1002/mrm.27561
_version_ 1783436232895758336
author Rose, Jan N.
Nielles‐Vallespin, Sonia
Ferreira, Pedro F.
Firmin, David N.
Scott, Andrew D.
Doorly, Denis J.
author_facet Rose, Jan N.
Nielles‐Vallespin, Sonia
Ferreira, Pedro F.
Firmin, David N.
Scott, Andrew D.
Doorly, Denis J.
author_sort Rose, Jan N.
collection PubMed
description PURPOSE: To develop histology‐informed simulations of diffusion tensor cardiovascular magnetic resonance (DT‐CMR) for typical in‐vivo pulse sequences and determine their sensitivity to changes in extra‐cellular space (ECS) and other microstructural parameters. METHODS: We synthesised the DT‐CMR signal from Monte Carlo random walk simulations. The virtual tissue was based on porcine histology. The cells were thickened and then shrunk to modify ECS. We also created idealised geometries using cuboids in regular arrangement, matching the extra‐cellular volume fraction (ECV) of 16–40%. The simulated voxel size was 2.8 × 2.8 × 8.0 mm(3) for pulse sequences covering short and long diffusion times: Stejskal–Tanner pulsed‐gradient spin echo, second‐order motion‐compensated spin echo, and stimulated echo acquisition mode (STEAM), with clinically available gradient strengths. RESULTS: The primary diffusion tensor eigenvalue increases linearly with ECV at a similar rate for all simulated geometries. Mean diffusivity (MD) varies linearly, too, but is higher for the substrates with more uniformly distributed ECS. Fractional anisotropy (FA) for the histology‐based geometry is higher than the idealised geometry with low sensitivity to ECV, except for the long mixing time of the STEAM sequence. Varying the intra‐cellular diffusivity (D (IC)) results in large changes of MD and FA. Varying extra‐cellular diffusivity or using stronger gradients has minor effects on FA. Uncertainties of the primary eigenvector orientation are reduced using STEAM. CONCLUSIONS: We found that the distribution of ECS has a measurable impact on DT‐CMR parameters. The observed sensitivity of MD and FA to ECV and D (IC) has potentially interesting applications for interpreting in‐vivo DT‐CMR parameters.
format Online
Article
Text
id pubmed-6637383
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-66373832019-07-29 Novel insights into in‐vivo diffusion tensor cardiovascular magnetic resonance using computational modelling and a histology‐based virtual microstructure Rose, Jan N. Nielles‐Vallespin, Sonia Ferreira, Pedro F. Firmin, David N. Scott, Andrew D. Doorly, Denis J. Magn Reson Med Full Papers—Computer Processing and Modeling PURPOSE: To develop histology‐informed simulations of diffusion tensor cardiovascular magnetic resonance (DT‐CMR) for typical in‐vivo pulse sequences and determine their sensitivity to changes in extra‐cellular space (ECS) and other microstructural parameters. METHODS: We synthesised the DT‐CMR signal from Monte Carlo random walk simulations. The virtual tissue was based on porcine histology. The cells were thickened and then shrunk to modify ECS. We also created idealised geometries using cuboids in regular arrangement, matching the extra‐cellular volume fraction (ECV) of 16–40%. The simulated voxel size was 2.8 × 2.8 × 8.0 mm(3) for pulse sequences covering short and long diffusion times: Stejskal–Tanner pulsed‐gradient spin echo, second‐order motion‐compensated spin echo, and stimulated echo acquisition mode (STEAM), with clinically available gradient strengths. RESULTS: The primary diffusion tensor eigenvalue increases linearly with ECV at a similar rate for all simulated geometries. Mean diffusivity (MD) varies linearly, too, but is higher for the substrates with more uniformly distributed ECS. Fractional anisotropy (FA) for the histology‐based geometry is higher than the idealised geometry with low sensitivity to ECV, except for the long mixing time of the STEAM sequence. Varying the intra‐cellular diffusivity (D (IC)) results in large changes of MD and FA. Varying extra‐cellular diffusivity or using stronger gradients has minor effects on FA. Uncertainties of the primary eigenvector orientation are reduced using STEAM. CONCLUSIONS: We found that the distribution of ECS has a measurable impact on DT‐CMR parameters. The observed sensitivity of MD and FA to ECV and D (IC) has potentially interesting applications for interpreting in‐vivo DT‐CMR parameters. John Wiley and Sons Inc. 2018-10-23 2019-04 /pmc/articles/PMC6637383/ /pubmed/30350880 http://dx.doi.org/10.1002/mrm.27561 Text en © 2018 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Full Papers—Computer Processing and Modeling
Rose, Jan N.
Nielles‐Vallespin, Sonia
Ferreira, Pedro F.
Firmin, David N.
Scott, Andrew D.
Doorly, Denis J.
Novel insights into in‐vivo diffusion tensor cardiovascular magnetic resonance using computational modelling and a histology‐based virtual microstructure
title Novel insights into in‐vivo diffusion tensor cardiovascular magnetic resonance using computational modelling and a histology‐based virtual microstructure
title_full Novel insights into in‐vivo diffusion tensor cardiovascular magnetic resonance using computational modelling and a histology‐based virtual microstructure
title_fullStr Novel insights into in‐vivo diffusion tensor cardiovascular magnetic resonance using computational modelling and a histology‐based virtual microstructure
title_full_unstemmed Novel insights into in‐vivo diffusion tensor cardiovascular magnetic resonance using computational modelling and a histology‐based virtual microstructure
title_short Novel insights into in‐vivo diffusion tensor cardiovascular magnetic resonance using computational modelling and a histology‐based virtual microstructure
title_sort novel insights into in‐vivo diffusion tensor cardiovascular magnetic resonance using computational modelling and a histology‐based virtual microstructure
topic Full Papers—Computer Processing and Modeling
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637383/
https://www.ncbi.nlm.nih.gov/pubmed/30350880
http://dx.doi.org/10.1002/mrm.27561
work_keys_str_mv AT rosejann novelinsightsintoinvivodiffusiontensorcardiovascularmagneticresonanceusingcomputationalmodellingandahistologybasedvirtualmicrostructure
AT niellesvallespinsonia novelinsightsintoinvivodiffusiontensorcardiovascularmagneticresonanceusingcomputationalmodellingandahistologybasedvirtualmicrostructure
AT ferreirapedrof novelinsightsintoinvivodiffusiontensorcardiovascularmagneticresonanceusingcomputationalmodellingandahistologybasedvirtualmicrostructure
AT firmindavidn novelinsightsintoinvivodiffusiontensorcardiovascularmagneticresonanceusingcomputationalmodellingandahistologybasedvirtualmicrostructure
AT scottandrewd novelinsightsintoinvivodiffusiontensorcardiovascularmagneticresonanceusingcomputationalmodellingandahistologybasedvirtualmicrostructure
AT doorlydenisj novelinsightsintoinvivodiffusiontensorcardiovascularmagneticresonanceusingcomputationalmodellingandahistologybasedvirtualmicrostructure