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Quantifying nerve decussation abnormalities in the optic chiasm

OBJECTIVE: The human optic chiasm comprises partially crossing optic nerve fibers. Here we used diffusion MRI (dMRI) for the in-vivo identification of the abnormally high proportion of crossing fibers found in the optic chiasm of people with albinism. METHODS: In 9 individuals with albinism and 8 co...

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Autores principales: Puzniak, Robert J., Ahmadi, Khazar, Kaufmann, Jörn, Gouws, Andre, Morland, Antony B., Pestilli, Franco, Hoffmann, Michael B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6849426/
https://www.ncbi.nlm.nih.gov/pubmed/31722288
http://dx.doi.org/10.1016/j.nicl.2019.102055
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author Puzniak, Robert J.
Ahmadi, Khazar
Kaufmann, Jörn
Gouws, Andre
Morland, Antony B.
Pestilli, Franco
Hoffmann, Michael B.
author_facet Puzniak, Robert J.
Ahmadi, Khazar
Kaufmann, Jörn
Gouws, Andre
Morland, Antony B.
Pestilli, Franco
Hoffmann, Michael B.
author_sort Puzniak, Robert J.
collection PubMed
description OBJECTIVE: The human optic chiasm comprises partially crossing optic nerve fibers. Here we used diffusion MRI (dMRI) for the in-vivo identification of the abnormally high proportion of crossing fibers found in the optic chiasm of people with albinism. METHODS: In 9 individuals with albinism and 8 controls high-resolution 3T dMRI data was acquired and analyzed with a set of methods for signal modeling [Diffusion Tensor (DT) and Constrained Spherical Deconvolution (CSD)], tractography, and streamline filtering (LiFE, COMMIT, and SIFT2). The number of crossing and non-crossing streamlines and their weights after filtering entered ROC-analyses to compare the discriminative power of the methods based on the area under the curve (AUC). The dMRI results were cross-validated with fMRI estimates of misrouting in a subset of 6 albinotic individuals. RESULTS: We detected significant group differences in chiasmal crossing for both unfiltered DT (p = 0.014) and CSD tractograms (p = 0.0009) also reflected by AUC measures (for DT and CSD: 0.61 and 0.75, respectively), underlining the discriminative power of the approach. Estimates of crossing strengths obtained with dMRI and fMRI were significantly correlated for CSD (R(2) = 0.83, p = 0.012). The results show that streamline filtering methods in combination with probabilistic tracking, both optimized for the data at hand, can improve the detection of crossing in the human optic chiasm. CONCLUSIONS: Especially CSD-based tractography provides an efficient approach to detect structural abnormalities in the optic chiasm. The most realistic results were obtained with filtering methods with parameters optimized for the data at hand. SIGNIFICANCE: Our findings demonstrate a novel anatomy-driven approach for the individualized diagnostics of optic chiasm abnormalities.
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spelling pubmed-68494262019-11-15 Quantifying nerve decussation abnormalities in the optic chiasm Puzniak, Robert J. Ahmadi, Khazar Kaufmann, Jörn Gouws, Andre Morland, Antony B. Pestilli, Franco Hoffmann, Michael B. Neuroimage Clin Regular Article OBJECTIVE: The human optic chiasm comprises partially crossing optic nerve fibers. Here we used diffusion MRI (dMRI) for the in-vivo identification of the abnormally high proportion of crossing fibers found in the optic chiasm of people with albinism. METHODS: In 9 individuals with albinism and 8 controls high-resolution 3T dMRI data was acquired and analyzed with a set of methods for signal modeling [Diffusion Tensor (DT) and Constrained Spherical Deconvolution (CSD)], tractography, and streamline filtering (LiFE, COMMIT, and SIFT2). The number of crossing and non-crossing streamlines and their weights after filtering entered ROC-analyses to compare the discriminative power of the methods based on the area under the curve (AUC). The dMRI results were cross-validated with fMRI estimates of misrouting in a subset of 6 albinotic individuals. RESULTS: We detected significant group differences in chiasmal crossing for both unfiltered DT (p = 0.014) and CSD tractograms (p = 0.0009) also reflected by AUC measures (for DT and CSD: 0.61 and 0.75, respectively), underlining the discriminative power of the approach. Estimates of crossing strengths obtained with dMRI and fMRI were significantly correlated for CSD (R(2) = 0.83, p = 0.012). The results show that streamline filtering methods in combination with probabilistic tracking, both optimized for the data at hand, can improve the detection of crossing in the human optic chiasm. CONCLUSIONS: Especially CSD-based tractography provides an efficient approach to detect structural abnormalities in the optic chiasm. The most realistic results were obtained with filtering methods with parameters optimized for the data at hand. SIGNIFICANCE: Our findings demonstrate a novel anatomy-driven approach for the individualized diagnostics of optic chiasm abnormalities. Elsevier 2019-11-01 /pmc/articles/PMC6849426/ /pubmed/31722288 http://dx.doi.org/10.1016/j.nicl.2019.102055 Text en © 2019 Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Puzniak, Robert J.
Ahmadi, Khazar
Kaufmann, Jörn
Gouws, Andre
Morland, Antony B.
Pestilli, Franco
Hoffmann, Michael B.
Quantifying nerve decussation abnormalities in the optic chiasm
title Quantifying nerve decussation abnormalities in the optic chiasm
title_full Quantifying nerve decussation abnormalities in the optic chiasm
title_fullStr Quantifying nerve decussation abnormalities in the optic chiasm
title_full_unstemmed Quantifying nerve decussation abnormalities in the optic chiasm
title_short Quantifying nerve decussation abnormalities in the optic chiasm
title_sort quantifying nerve decussation abnormalities in the optic chiasm
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6849426/
https://www.ncbi.nlm.nih.gov/pubmed/31722288
http://dx.doi.org/10.1016/j.nicl.2019.102055
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