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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

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11167))

Abstract

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.

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.

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Notes

  1. 1.

    “Greedy” tool (https://github.com/pyushkevich/greedy).

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Acknowledgements

This work was supported by NIH (grant numbers R01-AG056014, R01-AG040271, P30-AG010124, R01-EB017255, AG055005) and the donors of Alzheimer’s Disease Research, a program of the BrightFocus Foundation (L.E.M.W.).

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Xie, L. et al. (2018). 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. In: Reuter, M., Wachinger, C., Lombaert, H., Paniagua, B., Lüthi, M., Egger, B. (eds) Shape in Medical Imaging. ShapeMI 2018. Lecture Notes in Computer Science(), vol 11167. Springer, Cham. https://doi.org/10.1007/978-3-030-04747-4_3

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  • DOI: https://doi.org/10.1007/978-3-030-04747-4_3

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