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Brain region's relative proximity as marker for Alzheimer's disease based on structural MRI.

Lillemark L, Sørensen L, Pai A, Dam EB, Nielsen M, Alzheimer's Disease Neuroimaging Initiati - BMC Med Imaging (2014)

Bottom Line: We found that both our markers was able to significantly classify the subjects.The surface connectivity marker showed the best results with an area under the curve (AUC) at 0.877 (p<0.001), 0.784 (p<0.001), 0,766 (p<0.001) for NC-AD, NC-MCI, and MCI-AD, respectively, for the functional regions in the brain.Our results demonstrate that our proximity markers have the potential to assist in early diagnosis of AD.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Science, University of Copenhagen, Universitetsparken 1, 2100 Copenhagen Ø, Denmark. lene.lillemark@gmail.com.

ABSTRACT

Background: Alzheimer's disease (AD) is a progressive, incurable neurodegenerative disease and the most common type of dementia. It cannot be prevented, cured or drastically slowed, even though AD research has increased in the past 5-10 years. Instead of focusing on the brain volume or on the single brain structures like hippocampus, this paper investigates the relationship and proximity between regions in the brain and uses this information as a novel way of classifying normal control (NC), mild cognitive impaired (MCI), and AD subjects.

Methods: A longitudinal cohort of 528 subjects (170 NC, 240 MCI, and 114 AD) from ADNI at baseline and month 12 was studied. We investigated a marker based on Procrustes aligned center of masses and the percentile surface connectivity between regions. These markers were classified using a linear discriminant analysis in a cross validation setting and compared to whole brain and hippocampus volume.

Results: We found that both our markers was able to significantly classify the subjects. The surface connectivity marker showed the best results with an area under the curve (AUC) at 0.877 (p<0.001), 0.784 (p<0.001), 0,766 (p<0.001) for NC-AD, NC-MCI, and MCI-AD, respectively, for the functional regions in the brain. The surface connectivity marker was able to classify MCI-converters with an AUC of 0.599 (p<0.05) for the 1-year period.

Conclusion: Our results show that our relative proximity markers include more information than whole brain and hippocampus volume. Our results demonstrate that our proximity markers have the potential to assist in early diagnosis of AD.

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Related in: MedlinePlus

A slide of the segmented brain where the segmented regions have different colors.
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Figure 1: A slide of the segmented brain where the segmented regions have different colors.

Mentions: The FreeSurfer segmentation provided 40 regions from which a visualization is shown in Figure 1. AD do not spread evenly across the brain and we are interested in capturing early signs of AD and the conversion from MCI to AD [3,25]. Therefore have we divided our regions into three groups; all, functional (func) and potato, described in Table 2. These groups are spread across the brain so we are not biasing toward anatomical placed groupings. The all group included the FreeSurfer segmented regions excluding left-vessel, right vessel and 5th ventricle because these regions were not segmented by FreeSurfer in all subjects. The functional group has excluded all non-function regions like CSF and hypointensities. The choroid plexus was included in the functional regions due to suggestions that the functionality is altered in the choroid plexus due to AD [38]. To get a even smaller subset, the potato group consisted of small potato shaped regions from a visual perspective where shape is clearly defined.


Brain region's relative proximity as marker for Alzheimer's disease based on structural MRI.

Lillemark L, Sørensen L, Pai A, Dam EB, Nielsen M, Alzheimer's Disease Neuroimaging Initiati - BMC Med Imaging (2014)

A slide of the segmented brain where the segmented regions have different colors.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4048460&req=5

Figure 1: A slide of the segmented brain where the segmented regions have different colors.
Mentions: The FreeSurfer segmentation provided 40 regions from which a visualization is shown in Figure 1. AD do not spread evenly across the brain and we are interested in capturing early signs of AD and the conversion from MCI to AD [3,25]. Therefore have we divided our regions into three groups; all, functional (func) and potato, described in Table 2. These groups are spread across the brain so we are not biasing toward anatomical placed groupings. The all group included the FreeSurfer segmented regions excluding left-vessel, right vessel and 5th ventricle because these regions were not segmented by FreeSurfer in all subjects. The functional group has excluded all non-function regions like CSF and hypointensities. The choroid plexus was included in the functional regions due to suggestions that the functionality is altered in the choroid plexus due to AD [38]. To get a even smaller subset, the potato group consisted of small potato shaped regions from a visual perspective where shape is clearly defined.

Bottom Line: We found that both our markers was able to significantly classify the subjects.The surface connectivity marker showed the best results with an area under the curve (AUC) at 0.877 (p<0.001), 0.784 (p<0.001), 0,766 (p<0.001) for NC-AD, NC-MCI, and MCI-AD, respectively, for the functional regions in the brain.Our results demonstrate that our proximity markers have the potential to assist in early diagnosis of AD.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Science, University of Copenhagen, Universitetsparken 1, 2100 Copenhagen Ø, Denmark. lene.lillemark@gmail.com.

ABSTRACT

Background: Alzheimer's disease (AD) is a progressive, incurable neurodegenerative disease and the most common type of dementia. It cannot be prevented, cured or drastically slowed, even though AD research has increased in the past 5-10 years. Instead of focusing on the brain volume or on the single brain structures like hippocampus, this paper investigates the relationship and proximity between regions in the brain and uses this information as a novel way of classifying normal control (NC), mild cognitive impaired (MCI), and AD subjects.

Methods: A longitudinal cohort of 528 subjects (170 NC, 240 MCI, and 114 AD) from ADNI at baseline and month 12 was studied. We investigated a marker based on Procrustes aligned center of masses and the percentile surface connectivity between regions. These markers were classified using a linear discriminant analysis in a cross validation setting and compared to whole brain and hippocampus volume.

Results: We found that both our markers was able to significantly classify the subjects. The surface connectivity marker showed the best results with an area under the curve (AUC) at 0.877 (p<0.001), 0.784 (p<0.001), 0,766 (p<0.001) for NC-AD, NC-MCI, and MCI-AD, respectively, for the functional regions in the brain. The surface connectivity marker was able to classify MCI-converters with an AUC of 0.599 (p<0.05) for the 1-year period.

Conclusion: Our results show that our relative proximity markers include more information than whole brain and hippocampus volume. Our results demonstrate that our proximity markers have the potential to assist in early diagnosis of AD.

Show MeSH
Related in: MedlinePlus