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MRI-based diagnostic biomarkers for early onset pediatric multiple sclerosis
Currently, it is unclear whether pediatric multiple sclerosis (PMS) is a pathoetiologically homogeneous disease phenotype due to clinical and epidemiological differences between early and late onset PMS (EOPMS and LOPMS). Consequently, the question was raised whether diagnostic guidelines need to be...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4310929/ https://www.ncbi.nlm.nih.gov/pubmed/25685704 http://dx.doi.org/10.1016/j.nicl.2014.06.015 |
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author | Weygandt, Martin Hummel, Hannah-Maria Schregel, Katharina Ritter, Kerstin Allefeld, Carsten Dommes, Esther Huppke, Peter Haynes, JohnDylan Wuerfel, Jens Gärtner, Jutta |
author_facet | Weygandt, Martin Hummel, Hannah-Maria Schregel, Katharina Ritter, Kerstin Allefeld, Carsten Dommes, Esther Huppke, Peter Haynes, JohnDylan Wuerfel, Jens Gärtner, Jutta |
author_sort | Weygandt, Martin |
collection | PubMed |
description | Currently, it is unclear whether pediatric multiple sclerosis (PMS) is a pathoetiologically homogeneous disease phenotype due to clinical and epidemiological differences between early and late onset PMS (EOPMS and LOPMS). Consequently, the question was raised whether diagnostic guidelines need to be complemented by specific EOPMS markers. To search for such markers, we analyzed cerebral MRI images acquired with standard protocols using computer-based classification techniques. Specifically, we applied classification algorithms to gray (GM) and white matter (WM) tissue probability parameters of small brain regions derived from T2-weighted MRI images of EOPMS patients (onset <12 years), LOPMS patients (onset ≥12 years), and healthy controls (HC). This was done for PMS subgroups matched for disease duration and participant age independently. As expected, maximal diagnostic information for distinguishing PMS patients and HC was found in a periventricular WM area containing lesions (87.1% accuracy, p < 2.2 × 10(−5)). MRI-based biomarkers specific for EOPMS were identified in prefrontal cortex. Specifically, a coordinate in middle frontal gyrus contained maximal diagnostic information (77.3%, p = 1.8 × 10(−4)). Taken together, we were able to identify biomarkers reflecting pathognomonic processes specific for MS patients with very early onset. Especially GM involvement in the separation between PMS subgroups suggests that conventional MRI contains a richer set of diagnostically informative features than previously assumed. |
format | Online Article Text |
id | pubmed-4310929 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-43109292015-02-14 MRI-based diagnostic biomarkers for early onset pediatric multiple sclerosis Weygandt, Martin Hummel, Hannah-Maria Schregel, Katharina Ritter, Kerstin Allefeld, Carsten Dommes, Esther Huppke, Peter Haynes, JohnDylan Wuerfel, Jens Gärtner, Jutta Neuroimage Clin Regular Article Currently, it is unclear whether pediatric multiple sclerosis (PMS) is a pathoetiologically homogeneous disease phenotype due to clinical and epidemiological differences between early and late onset PMS (EOPMS and LOPMS). Consequently, the question was raised whether diagnostic guidelines need to be complemented by specific EOPMS markers. To search for such markers, we analyzed cerebral MRI images acquired with standard protocols using computer-based classification techniques. Specifically, we applied classification algorithms to gray (GM) and white matter (WM) tissue probability parameters of small brain regions derived from T2-weighted MRI images of EOPMS patients (onset <12 years), LOPMS patients (onset ≥12 years), and healthy controls (HC). This was done for PMS subgroups matched for disease duration and participant age independently. As expected, maximal diagnostic information for distinguishing PMS patients and HC was found in a periventricular WM area containing lesions (87.1% accuracy, p < 2.2 × 10(−5)). MRI-based biomarkers specific for EOPMS were identified in prefrontal cortex. Specifically, a coordinate in middle frontal gyrus contained maximal diagnostic information (77.3%, p = 1.8 × 10(−4)). Taken together, we were able to identify biomarkers reflecting pathognomonic processes specific for MS patients with very early onset. Especially GM involvement in the separation between PMS subgroups suggests that conventional MRI contains a richer set of diagnostically informative features than previously assumed. Elsevier 2014-07-11 /pmc/articles/PMC4310929/ /pubmed/25685704 http://dx.doi.org/10.1016/j.nicl.2014.06.015 Text en © 2014 The Authors. Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). |
spellingShingle | Regular Article Weygandt, Martin Hummel, Hannah-Maria Schregel, Katharina Ritter, Kerstin Allefeld, Carsten Dommes, Esther Huppke, Peter Haynes, JohnDylan Wuerfel, Jens Gärtner, Jutta MRI-based diagnostic biomarkers for early onset pediatric multiple sclerosis |
title | MRI-based diagnostic biomarkers for early onset pediatric multiple sclerosis |
title_full | MRI-based diagnostic biomarkers for early onset pediatric multiple sclerosis |
title_fullStr | MRI-based diagnostic biomarkers for early onset pediatric multiple sclerosis |
title_full_unstemmed | MRI-based diagnostic biomarkers for early onset pediatric multiple sclerosis |
title_short | MRI-based diagnostic biomarkers for early onset pediatric multiple sclerosis |
title_sort | mri-based diagnostic biomarkers for early onset pediatric multiple sclerosis |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4310929/ https://www.ncbi.nlm.nih.gov/pubmed/25685704 http://dx.doi.org/10.1016/j.nicl.2014.06.015 |
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