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A Fast Protocol for Multiparametric Characterisation of Diffusion in the Brain and Brain Tumours

Multi-parametric tissue characterisation is demonstrated using a 4-minute protocol based on diffusion trace acquisitions. Three diffusion regimes are covered simultaneously: pseudo-perfusion, Gaussian, and non-Gaussian diffusion. The clinical utility of this method for fast multi-parametric mapping...

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Autores principales: Loução, Ricardo, Oros-Peusquens, Ana-Maria, Langen, Karl-Josef, Ferreira, Hugo Alexandre, Shah, N. Jon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8490752/
https://www.ncbi.nlm.nih.gov/pubmed/34621664
http://dx.doi.org/10.3389/fonc.2021.554205
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author Loução, Ricardo
Oros-Peusquens, Ana-Maria
Langen, Karl-Josef
Ferreira, Hugo Alexandre
Shah, N. Jon
author_facet Loução, Ricardo
Oros-Peusquens, Ana-Maria
Langen, Karl-Josef
Ferreira, Hugo Alexandre
Shah, N. Jon
author_sort Loução, Ricardo
collection PubMed
description Multi-parametric tissue characterisation is demonstrated using a 4-minute protocol based on diffusion trace acquisitions. Three diffusion regimes are covered simultaneously: pseudo-perfusion, Gaussian, and non-Gaussian diffusion. The clinical utility of this method for fast multi-parametric mapping for brain tumours is explored. A cohort of 17 brain tumour patients was measured on a 3T hybrid MR-PET scanner with a standard clinical MRI protocol, to which the proposed multi-parametric diffusion protocol was subsequently added. For comparison purposes, standard perfusion and a full diffusion kurtosis protocol were acquired. Simultaneous amino-acid ((18)F-FET) PET enabled the identification of active tumour tissue. The metrics derived from the proposed protocol included perfusion fraction, pseudo-diffusivity, apparent diffusivity, and apparent kurtosis. These metrics were compared to the corresponding metrics from the dedicated acquisitions: cerebral blood volume and flow, mean diffusivity and mean kurtosis. Simulations were carried out to assess the influence of fitting methods and noise levels on the estimation of the parameters. The diffusion and kurtosis metrics obtained from the proposed protocol show strong to very strong correlations with those derived from the conventional protocol. However, a bias towards lower values was observed. The pseudo-perfusion parameters showed very weak to weak correlations compared to their perfusion counterparts. In conclusion, we introduce a clinically applicable protocol for measuring multiple parameters and demonstrate its relevance to pathological tissue characterisation.
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spelling pubmed-84907522021-10-06 A Fast Protocol for Multiparametric Characterisation of Diffusion in the Brain and Brain Tumours Loução, Ricardo Oros-Peusquens, Ana-Maria Langen, Karl-Josef Ferreira, Hugo Alexandre Shah, N. Jon Front Oncol Oncology Multi-parametric tissue characterisation is demonstrated using a 4-minute protocol based on diffusion trace acquisitions. Three diffusion regimes are covered simultaneously: pseudo-perfusion, Gaussian, and non-Gaussian diffusion. The clinical utility of this method for fast multi-parametric mapping for brain tumours is explored. A cohort of 17 brain tumour patients was measured on a 3T hybrid MR-PET scanner with a standard clinical MRI protocol, to which the proposed multi-parametric diffusion protocol was subsequently added. For comparison purposes, standard perfusion and a full diffusion kurtosis protocol were acquired. Simultaneous amino-acid ((18)F-FET) PET enabled the identification of active tumour tissue. The metrics derived from the proposed protocol included perfusion fraction, pseudo-diffusivity, apparent diffusivity, and apparent kurtosis. These metrics were compared to the corresponding metrics from the dedicated acquisitions: cerebral blood volume and flow, mean diffusivity and mean kurtosis. Simulations were carried out to assess the influence of fitting methods and noise levels on the estimation of the parameters. The diffusion and kurtosis metrics obtained from the proposed protocol show strong to very strong correlations with those derived from the conventional protocol. However, a bias towards lower values was observed. The pseudo-perfusion parameters showed very weak to weak correlations compared to their perfusion counterparts. In conclusion, we introduce a clinically applicable protocol for measuring multiple parameters and demonstrate its relevance to pathological tissue characterisation. Frontiers Media S.A. 2021-09-21 /pmc/articles/PMC8490752/ /pubmed/34621664 http://dx.doi.org/10.3389/fonc.2021.554205 Text en Copyright © 2021 Loução, Oros-Peusquens, Langen, Ferreira and Shah https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Loução, Ricardo
Oros-Peusquens, Ana-Maria
Langen, Karl-Josef
Ferreira, Hugo Alexandre
Shah, N. Jon
A Fast Protocol for Multiparametric Characterisation of Diffusion in the Brain and Brain Tumours
title A Fast Protocol for Multiparametric Characterisation of Diffusion in the Brain and Brain Tumours
title_full A Fast Protocol for Multiparametric Characterisation of Diffusion in the Brain and Brain Tumours
title_fullStr A Fast Protocol for Multiparametric Characterisation of Diffusion in the Brain and Brain Tumours
title_full_unstemmed A Fast Protocol for Multiparametric Characterisation of Diffusion in the Brain and Brain Tumours
title_short A Fast Protocol for Multiparametric Characterisation of Diffusion in the Brain and Brain Tumours
title_sort fast protocol for multiparametric characterisation of diffusion in the brain and brain tumours
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8490752/
https://www.ncbi.nlm.nih.gov/pubmed/34621664
http://dx.doi.org/10.3389/fonc.2021.554205
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