title: Measuring brain atrophy with a generalized formulation of the boundary shift integral.
abstract: Brain atrophy measured using structural magnetic resonance imaging (MRI) has been widely used as an imaging biomarker for disease diagnosis and tracking of pathologic progression in neurodegenerative diseases. In this work, we present a generalized and extended formulation of the boundary shift integral (gBSI) using probabilistic segmentations to estimate anatomic changes between 2 time points. This method adaptively estimates a non-binary exclusive OR region of interest from probabilistic brain segmentations of the baseline and repeat scans to better localize and capture the brain atrophy. We evaluate the proposed method by comparing the sample size requirements for a hypothetical clinical trial of Alzheimer's disease to that needed for the current implementation of BSI as well as a fuzzy implementation of BSI. The gBSI method results in a modest but reduced sample size, providing increased sensitivity to disease changes through the use of the probabilistic exclusive OR region.
authors.affiliation: Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK; NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK. Electronic address: f.carrasco@ucl.ac.uk.
authors.forename: Ferran
authors.initials: F
authors.lastname: Prados
authors.affiliation: Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
authors.forename: Manuel Jorge
authors.initials: MJ
authors.lastname: Cardoso
authors.affiliation: Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.
authors.forename: Kelvin K
authors.initials: KK
authors.lastname: Leung
authors.affiliation: Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK; Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.
authors.forename: David M
authors.initials: DM
authors.lastname: Cash
authors.affiliation: Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK; Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.
authors.forename: Marc
authors.initials: M
authors.lastname: Modat
authors.affiliation: Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.
authors.forename: Nick C
authors.initials: NC
authors.lastname: Fox
authors.affiliation: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK.
authors.forename: Claudia A M
authors.initials: CA
authors.lastname: Wheeler-Kingshott
authors.affiliation: Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK; Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.
authors.forename: Sebastien
authors.initials: S
authors.lastname: Ourselin
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000473:pathology*; D001284:Atrophy; D001921:Brain / Q000473:pathology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D059906:Neuroimaging / Q000379:methods*
keywords: Alzheimer's disease; Biomarker; Clinical trials; MRI; boundary shift integral