Characterizing Anatomical Variability and Alzheimer’s Disease Related Cortical Thinning in the Medial Temporal Lobe Using Graph-Based Groupwise Registration and Point Set Geodesic Shooting

The perirhinal cortex (PRC) is a site of early neurofibrillary tangle (NFT) pathology in Alzheimer’s disease (AD). Subtle morphological changes in the PRC have been reported in MRI studies of early AD, which has significance for clinical trials targeting preclinical AD. However, the PRC exhibits con...

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Bibliographic Details
Published inShape in Medical Imaging Vol. 11167; pp. 28 - 37
Main Authors Xie, Long, Wisse, Laura E. M., Das, Sandhitsu R., Ittyerah, Ranjit, Wang, Jiancong, Wolk, David A., Yushkevich, Paul A.
Format Book Chapter Journal Article
LanguageEnglish
Published Switzerland Springer International Publishing AG 01.01.2018
Springer International Publishing
SeriesLecture Notes in Computer Science
Online AccessGet full text
ISBN9783030047467
3030047466
ISSN0302-9743
1611-3349
DOI10.1007/978-3-030-04747-4_3

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Summary:The perirhinal cortex (PRC) is a site of early neurofibrillary tangle (NFT) pathology in Alzheimer’s disease (AD). Subtle morphological changes in the PRC have been reported in MRI studies of early AD, which has significance for clinical trials targeting preclinical AD. However, the PRC exhibits considerable anatomical variability with multiple discrete variants described in the neuroanatomy literature. We hypothesize that different anatomical variants are associated with different patterns of AD-related effects in the PRC. Single-template approaches conventionally used for automated image-based brain morphometry are ill-equipped to test this hypothesis. This study uses graph-based groupwise registration and diffeomorphic landmark matching with geodesic shooting to build statistical shape models of discrete PRC variants and examine variant-specific effects of AD on PRC shape and thickness. Experimental results demonstrate that the statistical models recover the folding patterns of the known PRC variants and capture the expected shape variability within the population. By applying the proposed pipeline to a large dataset with subjects from different stages in the AD spectrum, we find (1) a pattern of cortical thinning consistent with the NFT pathology progression, (2) different patterns of the initial spatial distribution of cortical thinning between anatomical variants, and (3) an effect of AD on medial temporal lobe shape. As such, the proposed pipeline could have important utility in the early detection and monitoring of AD.
Bibliography:Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.
ISBN:9783030047467
3030047466
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-030-04747-4_3