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Neuroimage Clin. 2019;24:102055. doi: 10.1016/j.nicl.2019.102055. Epub 2019 Nov 1.

Quantifying nerve decussation abnormalities in the optic chiasm.

Author information

1
Department of Ophthalmology, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany.
2
Department of Neurology, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany.
3
York Neuroimaging Centre, Department of Psychology, University of York, York, United Kingdom.
4
York Neuroimaging Centre, Department of Psychology, University of York, York, United Kingdom; York Biomedical Research Institute, University of York, York, United Kingdom.
5
Department of Psychological and Brain Sciences, Program in Neuroscience and Program in Cognitive Science, Indiana University, Bloomington, USA.
6
Department of Ophthalmology, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany. Electronic address: michael.hoffmann@med.ovgu.de.

Abstract

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 (R2 = 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.

KEYWORDS:

Albinism; Crossing nerves; Diffusion MRI; Functional MRI; Optic chiasm

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