Co-analysis of resting state functional magnetic resonance imaging and 
diffusion tensor imaging for correlation of default mode network and 
ultra-structural deficit in posterior cortical atrophy

Giapitzakis, IA; Quest, RA; Waldman, AD

doi:10.1007/s10334-013-0382-7

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Co-analysis of resting state functional magnetic resonance imaging and diffusion tensor imaging for correlation of default mode network and ultra-structural deficit in posterior cortical atrophy

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Giapitzakis, I., Quest, R., & Waldman, A. (2013). Co-analysis of resting state functional magnetic resonance imaging and diffusion tensor imaging for correlation of default mode network and ultra-structural deficit in posterior cortical atrophy. Poster presented at 30th Annual Scientific Meeting ESMRMB 2013, Toulouse, France.

Cite as: https://hdl.handle.net/21.11116/0000-0001-517E-7

Abstract

Purpose/Introduction: Posterior cortical atrophy (PCA) is a progressive dementia syndrome characterised by early visuospatial and executive dysfunction, and differential parietal and occipital lobe atrophy; it is typically a variant of Alzheimer’s disease. This study used DTI and rsfMRI to examine the relationship between structural and functional connectivity to examine the nature of regional deficits in PCA and as proof of principle for other specific neurodegenerative disorders whose regional predilection reflects specific functional deficit. Purpose/Introduction: Posterior cortical atrophy (PCA) is a progressive dementia syndrome characterised by early visuospatial and executive dysfunction, and differential parietal and occipital lobe atrophy; it is typically a variant of Alzheimer’s disease. This study used DTI and rsfMRI to examine the relationship between structural and functional connectivity to examine the nature of regional deficits in PCA and as proof of principle for other specific neurodegenerative disorders whose regional predilection reflects specific functional deficit. Subjects and Methods: 8 PCA subjects and 12 age-matched healthy controls were compared. Data from 15 younger subjects were used to develop regional functional connectivity templates. Analyses were performed using FMRIB Software Library (FSL). Indices of functional connectivity were calculated using MELODIC (1). These were compared with structural connectivity measures within defined functional networks derived from DTI data using tract-based spatial statistics (TBSS;2). Results: There were significant differences (p<0.05) in the co-activation of the default Mode Network (DMN) and in white matter in PCA subjects compared to healthy people. Functional connectivity differed between healthy controls and PCA patients in the PCC to left and right ILPLs connections and rILPL-lILPL connection. Structural connectivity differed between healthy controls and PCA patients in the left and right ILPLs to PCC connections, rILPL-lILPL connection, MPFC-rILPL connection and MPFC-PCC connection.