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Measuring brain atrophy with a generalized formulation of the boundary shift integral.

Prados F, Cardoso MJ, Leung KK, Cash DM, Modat M, Fox NC, Wheeler-Kingshott CA, Ourselin S, Alzheimer's Disease Neuroimaging Initiati - Neurobiol. Aging (2014)

Bottom Line: 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.

View Article: PubMed Central - PubMed

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.

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Example of whole brain XOR regions, for manual KN-BSI, STEPS-KN-BSI, pBSI1, pBSIγ, and gBSI, obtained on an AD patient. In yellow binary XOR regions and in a red-yellow scale the XOR pBSIγ and gBSI values from 0 to 1. Abbreviations: AD, Alzheimer's disease; BSI, boundary shift integral; gBSI, generalized boundary shift integral. (For interpretation of the references to color in this Figure, the reader is referred to the web version of this article.)
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fig4: Example of whole brain XOR regions, for manual KN-BSI, STEPS-KN-BSI, pBSI1, pBSIγ, and gBSI, obtained on an AD patient. In yellow binary XOR regions and in a red-yellow scale the XOR pBSIγ and gBSI values from 0 to 1. Abbreviations: AD, Alzheimer's disease; BSI, boundary shift integral; gBSI, generalized boundary shift integral. (For interpretation of the references to color in this Figure, the reader is referred to the web version of this article.)

Mentions: Fig. 4 and Fig. 5 illustrate the resulting XOR regions for the various implementations of the BSI. The pXOR area (last column) appears quite similar to the conventional KN-BSI XOR region, except that the periphery of the region is weighted to be less than 1. It also appears to be generally more sensitive to the presence of closed sulci than the binary XOR, improving atrophy detection as illustrated by the red regions in these areas. The κ gain factor boosts the relevance of voxels surrounding the ROI boundary.


Measuring brain atrophy with a generalized formulation of the boundary shift integral.

Prados F, Cardoso MJ, Leung KK, Cash DM, Modat M, Fox NC, Wheeler-Kingshott CA, Ourselin S, Alzheimer's Disease Neuroimaging Initiati - Neurobiol. Aging (2014)

Example of whole brain XOR regions, for manual KN-BSI, STEPS-KN-BSI, pBSI1, pBSIγ, and gBSI, obtained on an AD patient. In yellow binary XOR regions and in a red-yellow scale the XOR pBSIγ and gBSI values from 0 to 1. Abbreviations: AD, Alzheimer's disease; BSI, boundary shift integral; gBSI, generalized boundary shift integral. (For interpretation of the references to color in this Figure, the reader is referred to the web version of this article.)
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4288791&req=5

fig4: Example of whole brain XOR regions, for manual KN-BSI, STEPS-KN-BSI, pBSI1, pBSIγ, and gBSI, obtained on an AD patient. In yellow binary XOR regions and in a red-yellow scale the XOR pBSIγ and gBSI values from 0 to 1. Abbreviations: AD, Alzheimer's disease; BSI, boundary shift integral; gBSI, generalized boundary shift integral. (For interpretation of the references to color in this Figure, the reader is referred to the web version of this article.)
Mentions: Fig. 4 and Fig. 5 illustrate the resulting XOR regions for the various implementations of the BSI. The pXOR area (last column) appears quite similar to the conventional KN-BSI XOR region, except that the periphery of the region is weighted to be less than 1. It also appears to be generally more sensitive to the presence of closed sulci than the binary XOR, improving atrophy detection as illustrated by the red regions in these areas. The κ gain factor boosts the relevance of voxels surrounding the ROI boundary.

Bottom Line: 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.

View Article: PubMed Central - PubMed

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.

Show MeSH
Related in: MedlinePlus