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Prediction of Neurological Impairment in Cervical Spondylotic Myelopathy using a Combination of Diffusion MRI and Proton MR Spectroscopy

PURPOSE: In the present study we investigated a combination of diffusion tensor imaging (DTI) and magnetic resonance spectroscopic (MRS) biomarkers in order to predict neurological impairment in patients with cervical spondylosis. METHODS: Twenty-seven patients with cervical spondylosis were evaluat...

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Autores principales: Ellingson, Benjamin M., Salamon, Noriko, Hardy, Anthony J., Holly, Langston T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4592013/
https://www.ncbi.nlm.nih.gov/pubmed/26431174
http://dx.doi.org/10.1371/journal.pone.0139451
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author Ellingson, Benjamin M.
Salamon, Noriko
Hardy, Anthony J.
Holly, Langston T.
author_facet Ellingson, Benjamin M.
Salamon, Noriko
Hardy, Anthony J.
Holly, Langston T.
author_sort Ellingson, Benjamin M.
collection PubMed
description PURPOSE: In the present study we investigated a combination of diffusion tensor imaging (DTI) and magnetic resonance spectroscopic (MRS) biomarkers in order to predict neurological impairment in patients with cervical spondylosis. METHODS: Twenty-seven patients with cervical spondylosis were evaluated. DTI and single voxel MRS were performed in the cervical cord. N-acetylaspartate (NAA) and choline (Cho) metabolite concentration ratios with respect to creatine were quantified, as well as the ratio of choline to NAA. The modified mJOA scale was used as a measure of neurologic deficit. Linear regression was performed between DTI and MRS parameters and mJOA scores. Significant predictors from linear regression were used in a multiple linear regression model in order to improve prediction of mJOA. Parameters that did not add value to model performance were removed, then an optimized multiparametric model was established to predict mJOA. RESULTS: Significant correlations were observed between the Torg-Pavlov ratio and FA (R(2) = 0.2021, P = 0.019); DTI fiber tract density and FA, MD, Cho/NAA (R(2) = 0.3412, P = 0.0014; R(2) = 0.2112, P = 0.016; and R(2) = 0.2352, P = 0.010 respectively); along with FA and Cho/NAA (R(2) = 0.1695, P = 0.033). DTI fiber tract density, MD and FA at the site of compression, along with Cho/NAA at C2, were significantly correlated with mJOA score (R(2) = 0.05939, P < 0.0001; R(2) = 0.4739, P < 0.0001; R(2) = 0.7034, P < 0.0001; R(2) = 0.4649, P < 0.0001). A combination biomarker consisting of DTI fiber tract density, MD, and Cho/NAA showed the best prediction of mJOA (R(2) = 0.8274, P<0.0001), with post-hoc tests suggesting fiber tract density, MD, and Cho/NAA were all significant contributors to predicting mJOA (P = 0.00053, P = 0.00085, and P = 0.0019, respectively). CONCLUSION: A linear combination of DTI and MRS measurements within the cervical spinal cord may be useful for accurately predicting neurological deficits in patients with cervical spondylosis. Additional studies may be necessary to validate these observations.
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spelling pubmed-45920132015-10-09 Prediction of Neurological Impairment in Cervical Spondylotic Myelopathy using a Combination of Diffusion MRI and Proton MR Spectroscopy Ellingson, Benjamin M. Salamon, Noriko Hardy, Anthony J. Holly, Langston T. PLoS One Research Article PURPOSE: In the present study we investigated a combination of diffusion tensor imaging (DTI) and magnetic resonance spectroscopic (MRS) biomarkers in order to predict neurological impairment in patients with cervical spondylosis. METHODS: Twenty-seven patients with cervical spondylosis were evaluated. DTI and single voxel MRS were performed in the cervical cord. N-acetylaspartate (NAA) and choline (Cho) metabolite concentration ratios with respect to creatine were quantified, as well as the ratio of choline to NAA. The modified mJOA scale was used as a measure of neurologic deficit. Linear regression was performed between DTI and MRS parameters and mJOA scores. Significant predictors from linear regression were used in a multiple linear regression model in order to improve prediction of mJOA. Parameters that did not add value to model performance were removed, then an optimized multiparametric model was established to predict mJOA. RESULTS: Significant correlations were observed between the Torg-Pavlov ratio and FA (R(2) = 0.2021, P = 0.019); DTI fiber tract density and FA, MD, Cho/NAA (R(2) = 0.3412, P = 0.0014; R(2) = 0.2112, P = 0.016; and R(2) = 0.2352, P = 0.010 respectively); along with FA and Cho/NAA (R(2) = 0.1695, P = 0.033). DTI fiber tract density, MD and FA at the site of compression, along with Cho/NAA at C2, were significantly correlated with mJOA score (R(2) = 0.05939, P < 0.0001; R(2) = 0.4739, P < 0.0001; R(2) = 0.7034, P < 0.0001; R(2) = 0.4649, P < 0.0001). A combination biomarker consisting of DTI fiber tract density, MD, and Cho/NAA showed the best prediction of mJOA (R(2) = 0.8274, P<0.0001), with post-hoc tests suggesting fiber tract density, MD, and Cho/NAA were all significant contributors to predicting mJOA (P = 0.00053, P = 0.00085, and P = 0.0019, respectively). CONCLUSION: A linear combination of DTI and MRS measurements within the cervical spinal cord may be useful for accurately predicting neurological deficits in patients with cervical spondylosis. Additional studies may be necessary to validate these observations. Public Library of Science 2015-10-02 /pmc/articles/PMC4592013/ /pubmed/26431174 http://dx.doi.org/10.1371/journal.pone.0139451 Text en © 2015 Ellingson et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Ellingson, Benjamin M.
Salamon, Noriko
Hardy, Anthony J.
Holly, Langston T.
Prediction of Neurological Impairment in Cervical Spondylotic Myelopathy using a Combination of Diffusion MRI and Proton MR Spectroscopy
title Prediction of Neurological Impairment in Cervical Spondylotic Myelopathy using a Combination of Diffusion MRI and Proton MR Spectroscopy
title_full Prediction of Neurological Impairment in Cervical Spondylotic Myelopathy using a Combination of Diffusion MRI and Proton MR Spectroscopy
title_fullStr Prediction of Neurological Impairment in Cervical Spondylotic Myelopathy using a Combination of Diffusion MRI and Proton MR Spectroscopy
title_full_unstemmed Prediction of Neurological Impairment in Cervical Spondylotic Myelopathy using a Combination of Diffusion MRI and Proton MR Spectroscopy
title_short Prediction of Neurological Impairment in Cervical Spondylotic Myelopathy using a Combination of Diffusion MRI and Proton MR Spectroscopy
title_sort prediction of neurological impairment in cervical spondylotic myelopathy using a combination of diffusion mri and proton mr spectroscopy
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4592013/
https://www.ncbi.nlm.nih.gov/pubmed/26431174
http://dx.doi.org/10.1371/journal.pone.0139451
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