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Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction
Spinal cord cross-sectional area (CSA) is a relevant biomarker to assess spinal cord atrophy in neurodegenerative diseases. However, the considerable inter-subject variability among healthy participants currently limits its usage. Previous studies explored factors contributing to the variability, ye...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406309/ https://www.ncbi.nlm.nih.gov/pubmed/37555172 http://dx.doi.org/10.3389/fnimg.2022.1031253 |
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author | Bédard, Sandrine Cohen-Adad, Julien |
author_facet | Bédard, Sandrine Cohen-Adad, Julien |
author_sort | Bédard, Sandrine |
collection | PubMed |
description | Spinal cord cross-sectional area (CSA) is a relevant biomarker to assess spinal cord atrophy in neurodegenerative diseases. However, the considerable inter-subject variability among healthy participants currently limits its usage. Previous studies explored factors contributing to the variability, yet the normalization models required manual intervention and used vertebral levels as a reference, which is an imprecise prediction of the spinal levels. In this study we implemented a method to measure CSA automatically from a spatial reference based on the central nervous system (the pontomedullary junction, PMJ), we investigated factors to explain variability, and developed normalization strategies on a large cohort (N = 804). Following automatic spinal cord segmentation, vertebral labeling and PMJ labeling, the spinal cord CSA was computed on T1w MRI scans from the UK Biobank database. The CSA was computed using two methods. For the first method, the CSA was computed at the level of the C2–C3 intervertebral disc. For the second method, the CSA was computed at 64 mm caudally from the PMJ, this distance corresponding to the average distance between the PMJ and the C2–C3 disc across all participants. The effect of various demographic and anatomical factors was explored, and a stepwise regression found significant predictors; the coefficients of the best fit model were used to normalize CSA. CSA measured at C2–C3 disc and using the PMJ differed significantly (paired t-test, p-value = 0.0002). The best normalization model included thalamus, brain volume, sex and the interaction between brain volume and sex. The coefficient of variation went down for PMJ CSA from 10.09 (without normalization) to 8.59%, a reduction of 14.85%. For CSA at C2–C3, it went down from 9.96 to 8.42%, a reduction of 15.13 %. This study introduces an end-to-end automatic pipeline to measure and normalize cord CSA from a neurological reference. This approach requires further validation to assess atrophy in longitudinal studies. The inter-subject variability of CSA can be partly accounted for by demographics and anatomical factors. |
format | Online Article Text |
id | pubmed-10406309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104063092023-08-08 Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction Bédard, Sandrine Cohen-Adad, Julien Front Neuroimaging Neuroimaging Spinal cord cross-sectional area (CSA) is a relevant biomarker to assess spinal cord atrophy in neurodegenerative diseases. However, the considerable inter-subject variability among healthy participants currently limits its usage. Previous studies explored factors contributing to the variability, yet the normalization models required manual intervention and used vertebral levels as a reference, which is an imprecise prediction of the spinal levels. In this study we implemented a method to measure CSA automatically from a spatial reference based on the central nervous system (the pontomedullary junction, PMJ), we investigated factors to explain variability, and developed normalization strategies on a large cohort (N = 804). Following automatic spinal cord segmentation, vertebral labeling and PMJ labeling, the spinal cord CSA was computed on T1w MRI scans from the UK Biobank database. The CSA was computed using two methods. For the first method, the CSA was computed at the level of the C2–C3 intervertebral disc. For the second method, the CSA was computed at 64 mm caudally from the PMJ, this distance corresponding to the average distance between the PMJ and the C2–C3 disc across all participants. The effect of various demographic and anatomical factors was explored, and a stepwise regression found significant predictors; the coefficients of the best fit model were used to normalize CSA. CSA measured at C2–C3 disc and using the PMJ differed significantly (paired t-test, p-value = 0.0002). The best normalization model included thalamus, brain volume, sex and the interaction between brain volume and sex. The coefficient of variation went down for PMJ CSA from 10.09 (without normalization) to 8.59%, a reduction of 14.85%. For CSA at C2–C3, it went down from 9.96 to 8.42%, a reduction of 15.13 %. This study introduces an end-to-end automatic pipeline to measure and normalize cord CSA from a neurological reference. This approach requires further validation to assess atrophy in longitudinal studies. The inter-subject variability of CSA can be partly accounted for by demographics and anatomical factors. Frontiers Media S.A. 2022-11-02 /pmc/articles/PMC10406309/ /pubmed/37555172 http://dx.doi.org/10.3389/fnimg.2022.1031253 Text en Copyright © 2022 Bédard and Cohen-Adad. 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 | Neuroimaging Bédard, Sandrine Cohen-Adad, Julien Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction |
title | Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction |
title_full | Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction |
title_fullStr | Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction |
title_full_unstemmed | Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction |
title_short | Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction |
title_sort | automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction |
topic | Neuroimaging |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406309/ https://www.ncbi.nlm.nih.gov/pubmed/37555172 http://dx.doi.org/10.3389/fnimg.2022.1031253 |
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