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Automated signal intensity analysis of the spinal cord for detection of degenerative cervical myelopathy — a matched-pair MRI study

PURPOSE: Detection of T2 hyperintensities in suspected degenerative cervical myelopathy (DCM) is done subjectively in clinical practice. To gain objective quantification for dedicated treatment, signal intensity analysis of the spinal cord is purposeful. We investigated fully automated quantificatio...

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Autores principales: Hohenhaus, Marc, Klingler, Jan-Helge, Scholz, Christoph, Volz, Florian, Hubbe, Ulrich, Beck, Jürgen, Reisert, Marco, Würtemberger, Urs, Kremers, Nico, Wolf, Katharina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10497437/
https://www.ncbi.nlm.nih.gov/pubmed/37386202
http://dx.doi.org/10.1007/s00234-023-03187-w
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author Hohenhaus, Marc
Klingler, Jan-Helge
Scholz, Christoph
Volz, Florian
Hubbe, Ulrich
Beck, Jürgen
Reisert, Marco
Würtemberger, Urs
Kremers, Nico
Wolf, Katharina
author_facet Hohenhaus, Marc
Klingler, Jan-Helge
Scholz, Christoph
Volz, Florian
Hubbe, Ulrich
Beck, Jürgen
Reisert, Marco
Würtemberger, Urs
Kremers, Nico
Wolf, Katharina
author_sort Hohenhaus, Marc
collection PubMed
description PURPOSE: Detection of T2 hyperintensities in suspected degenerative cervical myelopathy (DCM) is done subjectively in clinical practice. To gain objective quantification for dedicated treatment, signal intensity analysis of the spinal cord is purposeful. We investigated fully automated quantification of the T2 signal intensity (T2-SI) of the spinal cord using a high-resolution MRI segmentation. METHODS: Matched-pair analysis of prospective acquired cervical 3D T2-weighted sequences of 114 symptomatic patients and 88 healthy volunteers. Cervical spinal cord was segmented automatically through a trained convolutional neuronal network with subsequent T2-SI registration slice-by-slice. Received T2-SI curves were subdivided for each cervical level from C2 to C7. Additionally, all levels were subjectively classified concerning a present T2 hyperintensity. For T2-positive levels, corresponding T2-SI curves were compared to curves of age-matched volunteers at the identical level. RESULTS: Forty-nine patients showed subjective T2 hyperintensities at any level. The corresponding T2-SI curves showed higher signal variabilities reflected by standard deviation (18.51 vs. 7.47 a.u.; p < 0.001) and range (56.09 vs. 24.34 a.u.; p < 0.001) compared to matched controls. Percentage of the range from the mean absolute T2-SI per cervical level, introduced as “T2 myelopathy index” (T2-MI), was correspondingly significantly higher in T2-positive segments (23.99% vs. 10.85%; p < 0.001). ROC analysis indicated excellent differentiation for all three parameters (AUC 0.865–0.920). CONCLUSION: This fully automated T2-SI quantification of the spinal cord revealed significantly increased signal variability for DCM patients compared to healthy volunteers. This innovative procedure and the applied parameters showed sufficient diagnostic accuracy, potentially diagnosing radiological DCM more objective to optimize treatment recommendation. TRIAL REGISTRATION: DRKS00012962 (17.01.2018) and DRKS00017351 (28.05.2019)
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spelling pubmed-104974372023-09-14 Automated signal intensity analysis of the spinal cord for detection of degenerative cervical myelopathy — a matched-pair MRI study Hohenhaus, Marc Klingler, Jan-Helge Scholz, Christoph Volz, Florian Hubbe, Ulrich Beck, Jürgen Reisert, Marco Würtemberger, Urs Kremers, Nico Wolf, Katharina Neuroradiology Spinal Neuroradiology PURPOSE: Detection of T2 hyperintensities in suspected degenerative cervical myelopathy (DCM) is done subjectively in clinical practice. To gain objective quantification for dedicated treatment, signal intensity analysis of the spinal cord is purposeful. We investigated fully automated quantification of the T2 signal intensity (T2-SI) of the spinal cord using a high-resolution MRI segmentation. METHODS: Matched-pair analysis of prospective acquired cervical 3D T2-weighted sequences of 114 symptomatic patients and 88 healthy volunteers. Cervical spinal cord was segmented automatically through a trained convolutional neuronal network with subsequent T2-SI registration slice-by-slice. Received T2-SI curves were subdivided for each cervical level from C2 to C7. Additionally, all levels were subjectively classified concerning a present T2 hyperintensity. For T2-positive levels, corresponding T2-SI curves were compared to curves of age-matched volunteers at the identical level. RESULTS: Forty-nine patients showed subjective T2 hyperintensities at any level. The corresponding T2-SI curves showed higher signal variabilities reflected by standard deviation (18.51 vs. 7.47 a.u.; p < 0.001) and range (56.09 vs. 24.34 a.u.; p < 0.001) compared to matched controls. Percentage of the range from the mean absolute T2-SI per cervical level, introduced as “T2 myelopathy index” (T2-MI), was correspondingly significantly higher in T2-positive segments (23.99% vs. 10.85%; p < 0.001). ROC analysis indicated excellent differentiation for all three parameters (AUC 0.865–0.920). CONCLUSION: This fully automated T2-SI quantification of the spinal cord revealed significantly increased signal variability for DCM patients compared to healthy volunteers. This innovative procedure and the applied parameters showed sufficient diagnostic accuracy, potentially diagnosing radiological DCM more objective to optimize treatment recommendation. TRIAL REGISTRATION: DRKS00012962 (17.01.2018) and DRKS00017351 (28.05.2019) Springer Berlin Heidelberg 2023-06-30 2023 /pmc/articles/PMC10497437/ /pubmed/37386202 http://dx.doi.org/10.1007/s00234-023-03187-w Text en © The Author(s) 2023 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 Spinal Neuroradiology
Hohenhaus, Marc
Klingler, Jan-Helge
Scholz, Christoph
Volz, Florian
Hubbe, Ulrich
Beck, Jürgen
Reisert, Marco
Würtemberger, Urs
Kremers, Nico
Wolf, Katharina
Automated signal intensity analysis of the spinal cord for detection of degenerative cervical myelopathy — a matched-pair MRI study
title Automated signal intensity analysis of the spinal cord for detection of degenerative cervical myelopathy — a matched-pair MRI study
title_full Automated signal intensity analysis of the spinal cord for detection of degenerative cervical myelopathy — a matched-pair MRI study
title_fullStr Automated signal intensity analysis of the spinal cord for detection of degenerative cervical myelopathy — a matched-pair MRI study
title_full_unstemmed Automated signal intensity analysis of the spinal cord for detection of degenerative cervical myelopathy — a matched-pair MRI study
title_short Automated signal intensity analysis of the spinal cord for detection of degenerative cervical myelopathy — a matched-pair MRI study
title_sort automated signal intensity analysis of the spinal cord for detection of degenerative cervical myelopathy — a matched-pair mri study
topic Spinal Neuroradiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10497437/
https://www.ncbi.nlm.nih.gov/pubmed/37386202
http://dx.doi.org/10.1007/s00234-023-03187-w
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