Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Bédard, Sandrine, Cohen-Adad, Julien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
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
_version_ 1785085724600565760
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
work_keys_str_mv AT bedardsandrine automaticmeasureandnormalizationofspinalcordcrosssectionalareausingthepontomedullaryjunction
AT cohenadadjulien automaticmeasureandnormalizationofspinalcordcrosssectionalareausingthepontomedullaryjunction