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Inter-scanner reproducibility of brain volumetry: influence of automated brain segmentation software
BACKGROUND: The inter-scanner reproducibility of brain volumetry is important in multi-site neuroimaging studies, where the reliability of automated brain segmentation (ABS) tools plays an important role. This study aimed to evaluate the influence of ABS tools on the consistency and reproducibility...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472704/ https://www.ncbi.nlm.nih.gov/pubmed/32887546 http://dx.doi.org/10.1186/s12868-020-00585-1 |
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author | Liu, Sirui Hou, Bo Zhang, Yiwei Lin, Tianye Fan, Xiaoyuan You, Hui Feng, Feng |
author_facet | Liu, Sirui Hou, Bo Zhang, Yiwei Lin, Tianye Fan, Xiaoyuan You, Hui Feng, Feng |
author_sort | Liu, Sirui |
collection | PubMed |
description | BACKGROUND: The inter-scanner reproducibility of brain volumetry is important in multi-site neuroimaging studies, where the reliability of automated brain segmentation (ABS) tools plays an important role. This study aimed to evaluate the influence of ABS tools on the consistency and reproducibility of the quantified brain volumetry from different scanners. METHODS: We included fifteen healthy volunteers who were scanned with 3D isotropic brain T1-weighted sequence on three different 3.0 Tesla MRI scanners (GE, Siemens and Philips). For each individual, the time span between image acquisitions on different scanners was limited to 1 h. All the T1-weighted images were processed with FreeSurfer v6.0, FSL v5.0 and AccuBrain(®) with default settings to obtain volumetry of brain tissues (e.g. gray matter) and substructures (e.g. basal ganglia structures) if available. Coefficient of variation (CV) was calculated to test inter-scanner variability in brain volumetry of various structures as quantified by these ABS tools. RESULTS: The mean inter-scanner CV values per brain structure among three MRI scanners ranged from 6.946 to 12.29% (mean, 9.577%) for FreeSurfer, 7.245 to 20.98% (mean, 12.60%) for FSL and 1.348 to 8.800% (mean value, 3.546%) for AccuBrain(®). In addition, AccuBrain(®) and FreeSurfer achieved the lowest mean values of region-specific CV between GE and Siemens scanners (from 0.818 to 5.958% for AccuBrain(®), and from 0.903 to 7.977% for FreeSurfer), while FSL-FIRST had the lowest mean values of region-specific CV between GE and Philips scanners (from 2.603 to 16.310%). AccuBrain(®) also had the lowest mean values of region-specific CV between Siemens and Philips scanners (from 1.138 to 6.615%). CONCLUSION: There is a large discrepancy in the inter-scanner reproducibility of brain volumetry when using different processing software. Image acquisition protocols and selection of ABS tool for brain volumetry quantification have impact on the robustness of results in multi-site studies. |
format | Online Article Text |
id | pubmed-7472704 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-74727042020-09-08 Inter-scanner reproducibility of brain volumetry: influence of automated brain segmentation software Liu, Sirui Hou, Bo Zhang, Yiwei Lin, Tianye Fan, Xiaoyuan You, Hui Feng, Feng BMC Neurosci Research Article BACKGROUND: The inter-scanner reproducibility of brain volumetry is important in multi-site neuroimaging studies, where the reliability of automated brain segmentation (ABS) tools plays an important role. This study aimed to evaluate the influence of ABS tools on the consistency and reproducibility of the quantified brain volumetry from different scanners. METHODS: We included fifteen healthy volunteers who were scanned with 3D isotropic brain T1-weighted sequence on three different 3.0 Tesla MRI scanners (GE, Siemens and Philips). For each individual, the time span between image acquisitions on different scanners was limited to 1 h. All the T1-weighted images were processed with FreeSurfer v6.0, FSL v5.0 and AccuBrain(®) with default settings to obtain volumetry of brain tissues (e.g. gray matter) and substructures (e.g. basal ganglia structures) if available. Coefficient of variation (CV) was calculated to test inter-scanner variability in brain volumetry of various structures as quantified by these ABS tools. RESULTS: The mean inter-scanner CV values per brain structure among three MRI scanners ranged from 6.946 to 12.29% (mean, 9.577%) for FreeSurfer, 7.245 to 20.98% (mean, 12.60%) for FSL and 1.348 to 8.800% (mean value, 3.546%) for AccuBrain(®). In addition, AccuBrain(®) and FreeSurfer achieved the lowest mean values of region-specific CV between GE and Siemens scanners (from 0.818 to 5.958% for AccuBrain(®), and from 0.903 to 7.977% for FreeSurfer), while FSL-FIRST had the lowest mean values of region-specific CV between GE and Philips scanners (from 2.603 to 16.310%). AccuBrain(®) also had the lowest mean values of region-specific CV between Siemens and Philips scanners (from 1.138 to 6.615%). CONCLUSION: There is a large discrepancy in the inter-scanner reproducibility of brain volumetry when using different processing software. Image acquisition protocols and selection of ABS tool for brain volumetry quantification have impact on the robustness of results in multi-site studies. BioMed Central 2020-09-04 /pmc/articles/PMC7472704/ /pubmed/32887546 http://dx.doi.org/10.1186/s12868-020-00585-1 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Liu, Sirui Hou, Bo Zhang, Yiwei Lin, Tianye Fan, Xiaoyuan You, Hui Feng, Feng Inter-scanner reproducibility of brain volumetry: influence of automated brain segmentation software |
title | Inter-scanner reproducibility of brain volumetry: influence of automated brain segmentation software |
title_full | Inter-scanner reproducibility of brain volumetry: influence of automated brain segmentation software |
title_fullStr | Inter-scanner reproducibility of brain volumetry: influence of automated brain segmentation software |
title_full_unstemmed | Inter-scanner reproducibility of brain volumetry: influence of automated brain segmentation software |
title_short | Inter-scanner reproducibility of brain volumetry: influence of automated brain segmentation software |
title_sort | inter-scanner reproducibility of brain volumetry: influence of automated brain segmentation software |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472704/ https://www.ncbi.nlm.nih.gov/pubmed/32887546 http://dx.doi.org/10.1186/s12868-020-00585-1 |
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