UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Computational modelling of pathogenic protein behaviour-governing mechanisms in the brain

Georgiadis, K; Young, AL; Hütel, M; Razi, A; Semedo, C; Schott, J; Ourselin, S; ... Modat, M; + view all (2018) Computational modelling of pathogenic protein behaviour-governing mechanisms in the brain. In: Frangi, AF and Schnabel, JA and Davatzikos, C and Alberola-López, C and Fichtinger, G, (eds.) Medical Image Computing and Computer Assisted Intervention – MICCAI 2018, 21st International Conference: Proceedings, Part III. (pp. pp. 532-539). Springer: Cham, Switzerland. Green open access

[img]
Preview
Text
MICCAI2018FinalKostas.pdf - Accepted version

Download (261kB) | Preview

Abstract

Most neurodegenerative diseases are caused by pathogenic proteins. Pathogenic protein behaviour is governed by neurobiological mechanisms which cause them to spread and accumulate in the brain, leading to cellular death and eventually atrophy. Patient data suggests atrophy loosely follows a number of spatiotemporal patterns, with different patterns associated with each neurodegenerative disease variant. It is hypothesised that the behaviour of different pathogenic protein variants is governed by different mechanisms, which could explain the pattern variety. Machine learning approaches take advantage of the pattern predictability for differential diagnosis and prognosis, but are unable to reveal new information on the underlying mechanisms, which are still poorly understood. We propose a framework where computational models of these mechanisms were created based on neurobiological literature. Competing hypotheses regarding the mechanisms were modelled and the outcomes evaluated against empirical data of Alzheimer’s disease. With this approach, we are able to characterise the impact of each mechanism on the neurodegenerative process. We also demonstrate how our framework could evaluate candidate therapies.

Type: Proceedings paper
Title: Computational modelling of pathogenic protein behaviour-governing mechanisms in the brain
Event: MICCAI 2018, Medical Image Computing and Computer Assisted Intervention, 21st International Conference, 16-20 September 2018, Granada, Spain
ISBN-13: 9783030009304
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-030-00931-1_61
Publisher version: https://doi.org/10.1007/978-3-030-00931-1_61
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Computational modelling, Neurodegenerative disease
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10061002
Downloads since deposit
40Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item