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Automated Quantification of Brain Lesion Volume From Post-trauma MR Diffusion-Weighted Images

OBJECTIVES: Determining the volume of brain lesions after trauma is challenging. Manual delineation is observer-dependent and time-consuming and cannot therefore be used in routine practice. The study aimed to evaluate the feasibility of an automated atlas-based quantification procedure (AQP) based...

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Autores principales: Mistral, Thomas, Roca, Pauline, Maggia, Christophe, Tucholka, Alan, Forbes, Florence, Doyle, Senan, Krainik, Alexandre, Galanaud, Damien, Schmitt, Emmanuelle, Kremer, Stéphane, Kastler, Adrian, Troprès, Irène, Barbier, Emmanuel L., Payen, Jean-François, Dojat, Michel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8905597/
https://www.ncbi.nlm.nih.gov/pubmed/35281992
http://dx.doi.org/10.3389/fneur.2021.740603
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author Mistral, Thomas
Roca, Pauline
Maggia, Christophe
Tucholka, Alan
Forbes, Florence
Doyle, Senan
Krainik, Alexandre
Galanaud, Damien
Schmitt, Emmanuelle
Kremer, Stéphane
Kastler, Adrian
Troprès, Irène
Barbier, Emmanuel L.
Payen, Jean-François
Dojat, Michel
author_facet Mistral, Thomas
Roca, Pauline
Maggia, Christophe
Tucholka, Alan
Forbes, Florence
Doyle, Senan
Krainik, Alexandre
Galanaud, Damien
Schmitt, Emmanuelle
Kremer, Stéphane
Kastler, Adrian
Troprès, Irène
Barbier, Emmanuel L.
Payen, Jean-François
Dojat, Michel
author_sort Mistral, Thomas
collection PubMed
description OBJECTIVES: Determining the volume of brain lesions after trauma is challenging. Manual delineation is observer-dependent and time-consuming and cannot therefore be used in routine practice. The study aimed to evaluate the feasibility of an automated atlas-based quantification procedure (AQP) based on the detection of abnormal mean diffusivity (MD) values computed from diffusion-weighted MR images. METHODS: The performance of AQP was measured against manual delineation consensus by independent raters in two series of experiments based on: (i) realistic trauma phantoms (n = 5) where low and high MD values were assigned to healthy brain images according to the intensity, form and location of lesion observed in real TBI cases; (ii) severe TBI patients (n = 12 patients) who underwent MR imaging within 10 days after injury. RESULTS: In realistic TBI phantoms, no statistical differences in Dice similarity coefficient, precision and brain lesion volumes were found between AQP, the rater consensus and the ground truth lesion delineations. Similar findings were obtained when comparing AQP and manual annotations for TBI patients. The intra-class correlation coefficient between AQP and manual delineation was 0.70 in realistic phantoms and 0.92 in TBI patients. The volume of brain lesions detected in TBI patients was 59 ml (19–84 ml) (median; 25–75th centiles). CONCLUSIONS: Our results support the feasibility of using an automated quantification procedure to determine, with similar accuracy to manual delineation, the volume of low and high MD brain lesions after trauma, and thus allow the determination of the type and volume of edematous brain lesions. This approach had comparable performance with manual delineation by a panel of experts. It will be tested in a large cohort of patients enrolled in the multicenter OxyTC trial (NCT02754063).
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spelling pubmed-89055972022-03-10 Automated Quantification of Brain Lesion Volume From Post-trauma MR Diffusion-Weighted Images Mistral, Thomas Roca, Pauline Maggia, Christophe Tucholka, Alan Forbes, Florence Doyle, Senan Krainik, Alexandre Galanaud, Damien Schmitt, Emmanuelle Kremer, Stéphane Kastler, Adrian Troprès, Irène Barbier, Emmanuel L. Payen, Jean-François Dojat, Michel Front Neurol Neurology OBJECTIVES: Determining the volume of brain lesions after trauma is challenging. Manual delineation is observer-dependent and time-consuming and cannot therefore be used in routine practice. The study aimed to evaluate the feasibility of an automated atlas-based quantification procedure (AQP) based on the detection of abnormal mean diffusivity (MD) values computed from diffusion-weighted MR images. METHODS: The performance of AQP was measured against manual delineation consensus by independent raters in two series of experiments based on: (i) realistic trauma phantoms (n = 5) where low and high MD values were assigned to healthy brain images according to the intensity, form and location of lesion observed in real TBI cases; (ii) severe TBI patients (n = 12 patients) who underwent MR imaging within 10 days after injury. RESULTS: In realistic TBI phantoms, no statistical differences in Dice similarity coefficient, precision and brain lesion volumes were found between AQP, the rater consensus and the ground truth lesion delineations. Similar findings were obtained when comparing AQP and manual annotations for TBI patients. The intra-class correlation coefficient between AQP and manual delineation was 0.70 in realistic phantoms and 0.92 in TBI patients. The volume of brain lesions detected in TBI patients was 59 ml (19–84 ml) (median; 25–75th centiles). CONCLUSIONS: Our results support the feasibility of using an automated quantification procedure to determine, with similar accuracy to manual delineation, the volume of low and high MD brain lesions after trauma, and thus allow the determination of the type and volume of edematous brain lesions. This approach had comparable performance with manual delineation by a panel of experts. It will be tested in a large cohort of patients enrolled in the multicenter OxyTC trial (NCT02754063). Frontiers Media S.A. 2022-02-23 /pmc/articles/PMC8905597/ /pubmed/35281992 http://dx.doi.org/10.3389/fneur.2021.740603 Text en Copyright © 2022 Mistral, Roca, Maggia, Tucholka, Forbes, Doyle, Krainik, Galanaud, Schmitt, Kremer, Kastler, Troprès, Barbier, Payen and Dojat. 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 Neurology
Mistral, Thomas
Roca, Pauline
Maggia, Christophe
Tucholka, Alan
Forbes, Florence
Doyle, Senan
Krainik, Alexandre
Galanaud, Damien
Schmitt, Emmanuelle
Kremer, Stéphane
Kastler, Adrian
Troprès, Irène
Barbier, Emmanuel L.
Payen, Jean-François
Dojat, Michel
Automated Quantification of Brain Lesion Volume From Post-trauma MR Diffusion-Weighted Images
title Automated Quantification of Brain Lesion Volume From Post-trauma MR Diffusion-Weighted Images
title_full Automated Quantification of Brain Lesion Volume From Post-trauma MR Diffusion-Weighted Images
title_fullStr Automated Quantification of Brain Lesion Volume From Post-trauma MR Diffusion-Weighted Images
title_full_unstemmed Automated Quantification of Brain Lesion Volume From Post-trauma MR Diffusion-Weighted Images
title_short Automated Quantification of Brain Lesion Volume From Post-trauma MR Diffusion-Weighted Images
title_sort automated quantification of brain lesion volume from post-trauma mr diffusion-weighted images
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8905597/
https://www.ncbi.nlm.nih.gov/pubmed/35281992
http://dx.doi.org/10.3389/fneur.2021.740603
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