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Imaging biomarkers for the diagnosis of Prion disease
Author(s): Liane S. Canas; Benjamin Yvernault; Carole Sudre; Enrico De Vita; M. Jorge Cardoso; John Thornton; Frederik Barkhof; Sébastien Ourselin; Simon Mead; Marc Modat
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Paper Abstract

Prion diseases are a group of progressive neurodegenerative conditions which cause cognitive impairment and neurological deficits. To date, there is no accurate measure that can be used to diagnose this illness, or to quantify the evolution of symptoms over time. Prion disease, due to its rarity, is in fact commonly mistaken for other types of dementia. A robust tool to diagnose and quantify the progression of the disease is key as it would lead to more appropriately timed clinical trials, and thereby improve patients’ quality of life. The approaches used to study other types of neurodegenerative diseases are not satisfactory to capture the progression of human form of Prion disease. This is due to the large heterogeneity of phenotypes of Prion disease and to the lack of consistent geometrical pattern of disease progression. In this paper, we aim to identify and select imaging biomarkers that are relevant for the diagnostic on Prion disease. We extract features from magnetic resonance imaging data and use genetic and demographic information from a cohort affected by genetic forms of the disease. The proposed framework consists of a multi-modal subjectspecific feature extraction step, followed by a Gaussian Process classifier used to calculate the probability of a subject to be diagnosed with Prion disease. We show that the proposed method improves the characterisation of Prion disease.

Paper Details

Date Published: 2 March 2018
PDF: 6 pages
Proc. SPIE 10574, Medical Imaging 2018: Image Processing, 1057405 (2 March 2018); doi: 10.1117/12.2293676
Show Author Affiliations
Liane S. Canas, Univ. College London (United Kingdom)
Benjamin Yvernault, Univ. College London (United Kingdom)
Carole Sudre, Univ. College London (United Kingdom)
UCL Institute of Neurology (United Kingdom)
Enrico De Vita, National Hospital for Neurology and Neurosurgery (United Kingdom)
M. Jorge Cardoso, Univ. College London (United Kingdom)
UCL Institute of Neurology (United Kingdom)
John Thornton, National Hospital for Neurology and Neurosurgery (United Kingdom)
Frederik Barkhof, Univ. College London (United Kingdom)
Sébastien Ourselin, Univ. College London (United Kingdom)
UCL Institute of Neurology (United Kingdom)
Simon Mead, UCL Institute of Neurology (United Kingdom)
Marc Modat, Univ. College London (United Kingdom)
UCL Institute of Neurology (United Kingdom)


Published in SPIE Proceedings Vol. 10574:
Medical Imaging 2018: Image Processing
Elsa D. Angelini; Bennett A. Landman, Editor(s)

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