Eye movement and diffusion tensor imaging analysis of treatment effects in a Niemann-Pick Type C patient

Scheel, Michael; Abegg, Mathias; Lanyon, Linda J; Mattman, Andre; Barton, Jason J (2010). Eye movement and diffusion tensor imaging analysis of treatment effects in a Niemann-Pick Type C patient. Molecular genetics and metabolism, 99(3), pp. 291-295. Amsterdam: Elsevier 10.1016/j.ymgme.2009.10.180

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New treatment options for Niemann-Pick Type C (NPC) have recently become available. To assess the efficiency and efficacy of these new treatment markers for disease status and progression are needed. Both the diagnosis and the monitoring of disease progression are challenging and mostly rely on clinical impression and functional testing of horizontal eye movements. Diffusion tensor imaging (DTI) provides information about the microintegrity especially of white matter. We show here in a case report how DTI and measures derived from this imaging method can serve as adjunct quantitative markers for disease management in Niemann-Pick Type C. Two approaches are taken--first, we compare the fractional anisotropy (FA) in the white matter globally between a 29-year-old NPC patient and 18 healthy age-matched controls and show the remarkable difference in FA relatively early in the course of the disease. Second, a voxelwise comparison of FA values reveals where white matter integrity is compromised locally and demonstrate an individualized analysis of FA changes before and after 1year of treatment with Miglustat. This method might be useful in future treatment trials for NPC to assess treatment effects.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Ophthalmology

UniBE Contributor:

Abegg, Mathias

ISSN:

1096-7192

Publisher:

Elsevier

Language:

English

Submitter:

Mathias Abegg

Date Deposited:

04 Oct 2013 14:08

Last Modified:

06 Feb 2017 12:58

Publisher DOI:

10.1016/j.ymgme.2009.10.180

PubMed ID:

19939718

Web of Science ID:

000275140900108

URI:

https://boris.unibe.ch/id/eprint/309 (FactScience: 197493)

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