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Proof of principle for the clinical use of a CE-certified automatic imaging analysis tool in rare diseases studying hereditary spastic paraplegia type 4 (SPG4)
Usage of MR imaging biomarkers is limited to experts. Automatic quantitative reports provide access for clinicians to data analysis. Automated data analysis was tested for usability in a small cohort of patients with hereditary spastic paraplegia type 4 (SPG4). We analyzed 3T MRI 3D-T1 datasets of n...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9772173/ https://www.ncbi.nlm.nih.gov/pubmed/36543827 http://dx.doi.org/10.1038/s41598-022-25545-z |
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author | Lindig, Tobias Bender, Benjamin Bürkle, Eva Kumar, Vinod Ernemann, Ulrike Schöls, Ludger Rattay, Tim W. |
author_facet | Lindig, Tobias Bender, Benjamin Bürkle, Eva Kumar, Vinod Ernemann, Ulrike Schöls, Ludger Rattay, Tim W. |
author_sort | Lindig, Tobias |
collection | PubMed |
description | Usage of MR imaging biomarkers is limited to experts. Automatic quantitative reports provide access for clinicians to data analysis. Automated data analysis was tested for usability in a small cohort of patients with hereditary spastic paraplegia type 4 (SPG4). We analyzed 3T MRI 3D-T1 datasets of n = 25 SPG4 patients and matched healthy controls using a commercial segmentation tool (AIRAscore structure 2.0.1) and standard VBM. In SPG4 total brain volume was reduced by 27.6 percentiles (p = 0.001) caused mainly by white matter loss (− 30.8th, p < 0.001) and stable total gray matter compared to controls. Brain volume loss occurred in: midbrain (− 41.5th, p = 0.001), pons (− 36.5th, p = 0.02), hippocampus (− 20.9th, p = 0.002), and gray matter of the cingulate gyrus (− 17.0th, p = 0.02). Ventricular volumes increased as indirect measures of atrophy. Group comparisons using percentiles aligned with results from VBM analyses. Quantitative imaging reports proved to work as an easily accessible, fully automatic screening tool for clinicians, even in a small cohort of a rare genetic disorder. We could delineate the involvement of white matter and specify involved brain regions. Group comparisons using percentiles provide comparable results to VBM analysis and are, therefore, a suitable and simple screening tool for all clinicians with and without in-depth knowledge of image processing. |
format | Online Article Text |
id | pubmed-9772173 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97721732022-12-23 Proof of principle for the clinical use of a CE-certified automatic imaging analysis tool in rare diseases studying hereditary spastic paraplegia type 4 (SPG4) Lindig, Tobias Bender, Benjamin Bürkle, Eva Kumar, Vinod Ernemann, Ulrike Schöls, Ludger Rattay, Tim W. Sci Rep Article Usage of MR imaging biomarkers is limited to experts. Automatic quantitative reports provide access for clinicians to data analysis. Automated data analysis was tested for usability in a small cohort of patients with hereditary spastic paraplegia type 4 (SPG4). We analyzed 3T MRI 3D-T1 datasets of n = 25 SPG4 patients and matched healthy controls using a commercial segmentation tool (AIRAscore structure 2.0.1) and standard VBM. In SPG4 total brain volume was reduced by 27.6 percentiles (p = 0.001) caused mainly by white matter loss (− 30.8th, p < 0.001) and stable total gray matter compared to controls. Brain volume loss occurred in: midbrain (− 41.5th, p = 0.001), pons (− 36.5th, p = 0.02), hippocampus (− 20.9th, p = 0.002), and gray matter of the cingulate gyrus (− 17.0th, p = 0.02). Ventricular volumes increased as indirect measures of atrophy. Group comparisons using percentiles aligned with results from VBM analyses. Quantitative imaging reports proved to work as an easily accessible, fully automatic screening tool for clinicians, even in a small cohort of a rare genetic disorder. We could delineate the involvement of white matter and specify involved brain regions. Group comparisons using percentiles provide comparable results to VBM analysis and are, therefore, a suitable and simple screening tool for all clinicians with and without in-depth knowledge of image processing. Nature Publishing Group UK 2022-12-21 /pmc/articles/PMC9772173/ /pubmed/36543827 http://dx.doi.org/10.1038/s41598-022-25545-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Lindig, Tobias Bender, Benjamin Bürkle, Eva Kumar, Vinod Ernemann, Ulrike Schöls, Ludger Rattay, Tim W. Proof of principle for the clinical use of a CE-certified automatic imaging analysis tool in rare diseases studying hereditary spastic paraplegia type 4 (SPG4) |
title | Proof of principle for the clinical use of a CE-certified automatic imaging analysis tool in rare diseases studying hereditary spastic paraplegia type 4 (SPG4) |
title_full | Proof of principle for the clinical use of a CE-certified automatic imaging analysis tool in rare diseases studying hereditary spastic paraplegia type 4 (SPG4) |
title_fullStr | Proof of principle for the clinical use of a CE-certified automatic imaging analysis tool in rare diseases studying hereditary spastic paraplegia type 4 (SPG4) |
title_full_unstemmed | Proof of principle for the clinical use of a CE-certified automatic imaging analysis tool in rare diseases studying hereditary spastic paraplegia type 4 (SPG4) |
title_short | Proof of principle for the clinical use of a CE-certified automatic imaging analysis tool in rare diseases studying hereditary spastic paraplegia type 4 (SPG4) |
title_sort | proof of principle for the clinical use of a ce-certified automatic imaging analysis tool in rare diseases studying hereditary spastic paraplegia type 4 (spg4) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9772173/ https://www.ncbi.nlm.nih.gov/pubmed/36543827 http://dx.doi.org/10.1038/s41598-022-25545-z |
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