Measurement of hippocampal atrophy using 4D graph-cut segmentation

Application to ADNI

Robin Wolz (Corresponding Author), Rolf A. Heckemann, Paul Aljabar, Joseph V. Hajnal, Alexander Hammers, Jyrki Lötjönen, Daniel Rueckert, The Alzheimer’s Disease Neuroimaging Initiative

Research output: Contribution to journalArticleScientificpeer-review

103 Citations (Scopus)

Abstract

We propose a new method of measuring atrophy of brain structures by simultaneously segmenting longitudinal magnetic resonance (MR) images. In this approach a 4D graph is used to represent the longitudinal data: edges are weighted based on spatial and intensity priors and connect spatially and temporally neighboring voxels represented by vertices in the graph. Solving the min-cut/max-flow problem on this graph yields the segmentation for all timepoints in a single step. By segmenting all timepoints simultaneously, a consistent and atrophy-sensitive segmentation is obtained. The application to hippocampal atrophy measurement in 568 image pairs (Baseline and Month 12 follow-up) as well as 362 image triplets (Baseline, Month 12, and Month 24) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) confirms previous findings for atrophy in Alzheimer's disease (AD) and healthy aging. Highly significant correlations between hippocampal atrophy and clinical variables (Mini Mental State Examination, MMSE and Clinical Dementia Rating, CDR) were found and atrophy rates differ significantly according to subjects' ApoE genotype. Based on one year atrophy rates, a correct classification rate of 82% between AD and control subjects is achieved. Subjects that converted from Mild Cognitive Impairment (MCI) to AD after the period for which atrophy was measured (i.e., after the first 12 months) and subjects for whom conversion is yet to be identified were discriminated with a rate of 64%, a promising result with a view to clinical application. Power analysis shows that 67 and 206 subjects are needed for the AD and MCI groups respectively to detect a 25% change in volume loss with 80% power and 5% significance.
Original languageEnglish
Pages (from-to)109-118
JournalNeuroImage
Volume52
Issue number1
DOIs
Publication statusPublished - 2010
MoE publication typeA1 Journal article-refereed

Fingerprint

Neuroimaging
Atrophy
Alzheimer Disease
Apolipoproteins E
Dementia
Magnetic Resonance Spectroscopy
Genotype
Brain

Keywords

  • Structural MR images
  • Image segmentation
  • Graph cuts
  • Hippocampal atrophy
  • Alzheimer's disease

Cite this

Wolz, R., Heckemann, R. A., Aljabar, P., Hajnal, J. V., Hammers, A., Lötjönen, J., ... The Alzheimer’s Disease Neuroimaging Initiative (2010). Measurement of hippocampal atrophy using 4D graph-cut segmentation: Application to ADNI. NeuroImage, 52(1), 109-118. https://doi.org/10.1016/j.neuroimage.2010.04.006
Wolz, Robin ; Heckemann, Rolf A. ; Aljabar, Paul ; Hajnal, Joseph V. ; Hammers, Alexander ; Lötjönen, Jyrki ; Rueckert, Daniel ; The Alzheimer’s Disease Neuroimaging Initiative. / Measurement of hippocampal atrophy using 4D graph-cut segmentation : Application to ADNI. In: NeuroImage. 2010 ; Vol. 52, No. 1. pp. 109-118.
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abstract = "We propose a new method of measuring atrophy of brain structures by simultaneously segmenting longitudinal magnetic resonance (MR) images. In this approach a 4D graph is used to represent the longitudinal data: edges are weighted based on spatial and intensity priors and connect spatially and temporally neighboring voxels represented by vertices in the graph. Solving the min-cut/max-flow problem on this graph yields the segmentation for all timepoints in a single step. By segmenting all timepoints simultaneously, a consistent and atrophy-sensitive segmentation is obtained. The application to hippocampal atrophy measurement in 568 image pairs (Baseline and Month 12 follow-up) as well as 362 image triplets (Baseline, Month 12, and Month 24) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) confirms previous findings for atrophy in Alzheimer's disease (AD) and healthy aging. Highly significant correlations between hippocampal atrophy and clinical variables (Mini Mental State Examination, MMSE and Clinical Dementia Rating, CDR) were found and atrophy rates differ significantly according to subjects' ApoE genotype. Based on one year atrophy rates, a correct classification rate of 82{\%} between AD and control subjects is achieved. Subjects that converted from Mild Cognitive Impairment (MCI) to AD after the period for which atrophy was measured (i.e., after the first 12 months) and subjects for whom conversion is yet to be identified were discriminated with a rate of 64{\%}, a promising result with a view to clinical application. Power analysis shows that 67 and 206 subjects are needed for the AD and MCI groups respectively to detect a 25{\%} change in volume loss with 80{\%} power and 5{\%} significance.",
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Wolz, R, Heckemann, RA, Aljabar, P, Hajnal, JV, Hammers, A, Lötjönen, J, Rueckert, D & The Alzheimer’s Disease Neuroimaging Initiative 2010, 'Measurement of hippocampal atrophy using 4D graph-cut segmentation: Application to ADNI', NeuroImage, vol. 52, no. 1, pp. 109-118. https://doi.org/10.1016/j.neuroimage.2010.04.006

Measurement of hippocampal atrophy using 4D graph-cut segmentation : Application to ADNI. / Wolz, Robin (Corresponding Author); Heckemann, Rolf A.; Aljabar, Paul; Hajnal, Joseph V.; Hammers, Alexander; Lötjönen, Jyrki; Rueckert, Daniel; The Alzheimer’s Disease Neuroimaging Initiative.

In: NeuroImage, Vol. 52, No. 1, 2010, p. 109-118.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Measurement of hippocampal atrophy using 4D graph-cut segmentation

T2 - Application to ADNI

AU - Wolz, Robin

AU - Heckemann, Rolf A.

AU - Aljabar, Paul

AU - Hajnal, Joseph V.

AU - Hammers, Alexander

AU - Lötjönen, Jyrki

AU - Rueckert, Daniel

AU - The Alzheimer’s Disease Neuroimaging Initiative

PY - 2010

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N2 - We propose a new method of measuring atrophy of brain structures by simultaneously segmenting longitudinal magnetic resonance (MR) images. In this approach a 4D graph is used to represent the longitudinal data: edges are weighted based on spatial and intensity priors and connect spatially and temporally neighboring voxels represented by vertices in the graph. Solving the min-cut/max-flow problem on this graph yields the segmentation for all timepoints in a single step. By segmenting all timepoints simultaneously, a consistent and atrophy-sensitive segmentation is obtained. The application to hippocampal atrophy measurement in 568 image pairs (Baseline and Month 12 follow-up) as well as 362 image triplets (Baseline, Month 12, and Month 24) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) confirms previous findings for atrophy in Alzheimer's disease (AD) and healthy aging. Highly significant correlations between hippocampal atrophy and clinical variables (Mini Mental State Examination, MMSE and Clinical Dementia Rating, CDR) were found and atrophy rates differ significantly according to subjects' ApoE genotype. Based on one year atrophy rates, a correct classification rate of 82% between AD and control subjects is achieved. Subjects that converted from Mild Cognitive Impairment (MCI) to AD after the period for which atrophy was measured (i.e., after the first 12 months) and subjects for whom conversion is yet to be identified were discriminated with a rate of 64%, a promising result with a view to clinical application. Power analysis shows that 67 and 206 subjects are needed for the AD and MCI groups respectively to detect a 25% change in volume loss with 80% power and 5% significance.

AB - We propose a new method of measuring atrophy of brain structures by simultaneously segmenting longitudinal magnetic resonance (MR) images. In this approach a 4D graph is used to represent the longitudinal data: edges are weighted based on spatial and intensity priors and connect spatially and temporally neighboring voxels represented by vertices in the graph. Solving the min-cut/max-flow problem on this graph yields the segmentation for all timepoints in a single step. By segmenting all timepoints simultaneously, a consistent and atrophy-sensitive segmentation is obtained. The application to hippocampal atrophy measurement in 568 image pairs (Baseline and Month 12 follow-up) as well as 362 image triplets (Baseline, Month 12, and Month 24) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) confirms previous findings for atrophy in Alzheimer's disease (AD) and healthy aging. Highly significant correlations between hippocampal atrophy and clinical variables (Mini Mental State Examination, MMSE and Clinical Dementia Rating, CDR) were found and atrophy rates differ significantly according to subjects' ApoE genotype. Based on one year atrophy rates, a correct classification rate of 82% between AD and control subjects is achieved. Subjects that converted from Mild Cognitive Impairment (MCI) to AD after the period for which atrophy was measured (i.e., after the first 12 months) and subjects for whom conversion is yet to be identified were discriminated with a rate of 64%, a promising result with a view to clinical application. Power analysis shows that 67 and 206 subjects are needed for the AD and MCI groups respectively to detect a 25% change in volume loss with 80% power and 5% significance.

KW - Structural MR images

KW - Image segmentation

KW - Graph cuts

KW - Hippocampal atrophy

KW - Alzheimer's disease

U2 - 10.1016/j.neuroimage.2010.04.006

DO - 10.1016/j.neuroimage.2010.04.006

M3 - Article

VL - 52

SP - 109

EP - 118

JO - NeuroImage

JF - NeuroImage

SN - 1053-8119

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Wolz R, Heckemann RA, Aljabar P, Hajnal JV, Hammers A, Lötjönen J et al. Measurement of hippocampal atrophy using 4D graph-cut segmentation: Application to ADNI. NeuroImage. 2010;52(1):109-118. https://doi.org/10.1016/j.neuroimage.2010.04.006