Resting state fMRI as a marker for progression from mild cognitive impairment to Alzheimer’s disease
(2014)Medical Physics Programme
- Abstract
- The arc of progression in the most common neurological aiction known as Alzheimer's Disease
(AD), is characterized by a prodromal stage of Mild Cognitive Impairment (MCI). MCI subjects
have traditionally been diagnosed with a battery of cognitive tests, but in recent times two good
biomarker predictors of incipient AD have been identied. The cerebrospinal
uid levels of the protein residues amyloid-beta and phosphorylated tau can be quantied and directly relate to the imprint of associated pathologies in the brain. This work aims to elucidate the impact of tau- and
amyloid-related pathologies on the functional networks of the brain, as gauged by a resting-state fMRI
connectivity analysis. In this context, we aim to identify optimal... (More) - The arc of progression in the most common neurological aiction known as Alzheimer's Disease
(AD), is characterized by a prodromal stage of Mild Cognitive Impairment (MCI). MCI subjects
have traditionally been diagnosed with a battery of cognitive tests, but in recent times two good
biomarker predictors of incipient AD have been identied. The cerebrospinal
uid levels of the protein residues amyloid-beta and phosphorylated tau can be quantied and directly relate to the imprint of associated pathologies in the brain. This work aims to elucidate the impact of tau- and
amyloid-related pathologies on the functional networks of the brain, as gauged by a resting-state fMRI
connectivity analysis. In this context, we aim to identify optimal model parameters that yield maximal
contrast between subspecies of MCI and healthy controls, such as the most sensitive frequency interval
for the Blood Oxygenation Level Dependent (BOLD) time-series and the resolution of whole-brain
parcellation schemes. The connectivity analysis exposes the impact of biomarker pathology and
outlines a tentative progression pattern, relating the decline of functional connectivity to increasingly
pathological levels of biomarkers. A progression hypothesisis proposed, reviewing pattern progression
in the light of neuronal communication breakdown and phase-lag. Furthermore, failure of key hubs
are identied using graph theoretical centrality measures and the relative group separations with
connectivity pattern is evaluated by means of support-vector machines.
Relative healthy controls, MCI with non-pathological CSF levels of biomarkers exhibit a widespread
pattern of reduced connectivity, likely due to a mix many dementia subtypes. MCI subjects with
pathological amyloid CSF levels but normal values of tau, has a large set of failing links converg-
ing on crucial network hubs: thalamus, caudate nucleus and putamen, and are additionally aected
in key regions such as hippocampus. This nding supports the view of Alzheimer's progression in
terms of global disconnection syndrome by failing hub regions. Furthermore, these patterns are man-
ifested in relevant graph theoretical centrality measures. MCI with pathological levels of both CSF
biomarkers produce the strongest contrast relative healthy controls, involving reduced connectivity
beteween parietal and frontal areas, but also implicating areas linked with cognitive decline, such as
hippocampus and posterior cingulate cortex. The similarity of this contrast to that of controls vs.
Alzheimer's subjects, indicates the presence of a functional progression pattern with two biomarker
levels. Our ndings merit further investigation of the biomarker progression line using larger cohorts
further stratied with cognitive test scores. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/4934411
- author
- Strandberg, Tor Olof
- supervisor
- organization
- year
- 2014
- type
- H2 - Master's Degree (Two Years)
- subject
- language
- English
- id
- 4934411
- date added to LUP
- 2015-01-13 18:28:04
- date last changed
- 2015-01-13 18:28:04
@misc{4934411,
abstract = {{The arc of progression in the most common neurological aiction known as Alzheimer's Disease
(AD), is characterized by a prodromal stage of Mild Cognitive Impairment (MCI). MCI subjects
have traditionally been diagnosed with a battery of cognitive tests, but in recent times two good
biomarker predictors of incipient AD have been identied. The cerebrospinal
uid levels of the protein residues amyloid-beta and phosphorylated tau can be quantied and directly relate to the imprint of associated pathologies in the brain. This work aims to elucidate the impact of tau- and
amyloid-related pathologies on the functional networks of the brain, as gauged by a resting-state fMRI
connectivity analysis. In this context, we aim to identify optimal model parameters that yield maximal
contrast between subspecies of MCI and healthy controls, such as the most sensitive frequency interval
for the Blood Oxygenation Level Dependent (BOLD) time-series and the resolution of whole-brain
parcellation schemes. The connectivity analysis exposes the impact of biomarker pathology and
outlines a tentative progression pattern, relating the decline of functional connectivity to increasingly
pathological levels of biomarkers. A progression hypothesisis proposed, reviewing pattern progression
in the light of neuronal communication breakdown and phase-lag. Furthermore, failure of key hubs
are identied using graph theoretical centrality measures and the relative group separations with
connectivity pattern is evaluated by means of support-vector machines.
Relative healthy controls, MCI with non-pathological CSF levels of biomarkers exhibit a widespread
pattern of reduced connectivity, likely due to a mix many dementia subtypes. MCI subjects with
pathological amyloid CSF levels but normal values of tau, has a large set of failing links converg-
ing on crucial network hubs: thalamus, caudate nucleus and putamen, and are additionally aected
in key regions such as hippocampus. This nding supports the view of Alzheimer's progression in
terms of global disconnection syndrome by failing hub regions. Furthermore, these patterns are man-
ifested in relevant graph theoretical centrality measures. MCI with pathological levels of both CSF
biomarkers produce the strongest contrast relative healthy controls, involving reduced connectivity
beteween parietal and frontal areas, but also implicating areas linked with cognitive decline, such as
hippocampus and posterior cingulate cortex. The similarity of this contrast to that of controls vs.
Alzheimer's subjects, indicates the presence of a functional progression pattern with two biomarker
levels. Our ndings merit further investigation of the biomarker progression line using larger cohorts
further stratied with cognitive test scores.}},
author = {{Strandberg, Tor Olof}},
language = {{eng}},
note = {{Student Paper}},
title = {{Resting state fMRI as a marker for progression from mild cognitive impairment to Alzheimer’s disease}},
year = {{2014}},
}