Dataset Information

Multi-template analysis of human perirhinal cortex in brain MRI: Explicitly accounting for anatomical variability.

ABSTRACT: The human perirhinal cortex (PRC) plays critical roles in episodic and semantic memory and visual perception. The PRC consists of Brodmann areas 35 and 36 (BA35, BA36). In Alzheimer's disease (AD), BA35 is the first cortical site affected by neurofibrillary tangle pathology, which is closely linked to neural injury in AD. Large anatomical variability, manifested in the form of different cortical folding and branching patterns, makes it difficult to segment the PRC in MRI scans. Pathology studies have found that in ~97% of specimens, the PRC falls into one of three discrete anatomical variants. However, current methods for PRC segmentation and morphometry in MRI are based on single-template approaches, which may not be able to accurately model these discrete variants METHODS: A multi-template analysis pipeline that explicitly accounts for anatomical variability is used to automatically label the PRC and measure its thickness in T2-weighted MRI scans. The pipeline uses multi-atlas segmentation to automatically label medial temporal lobe cortices including entorhinal cortex, PRC and the parahippocampal cortex. Pairwise registration between label maps and clustering based on residual dissimilarity after registration are used to construct separate templates for the anatomical variants of the PRC. An optimal path of deformations linking these templates is used to establish correspondences between all the subjects. Experimental evaluation focuses on the ability of single-template and multi-template analyses to detect differences in the thickness of medial temporal lobe cortices between patients with amnestic mild cognitive impairment (aMCI, n=41) and age-matched controls (n=44).The proposed technique is able to generate templates that recover the three dominant discrete variants of PRC and establish more meaningful correspondences between subjects than a single-template approach. The largest reduction in thickness associated with aMCI, in absolute terms, was found in left BA35 using both regional and summary thickness measures. Further, statistical maps of regional thickness difference between aMCI and controls revealed different patterns for the three anatomical variants.

SUBMITTER: Xie L

PROVIDER: S-EPMC5183532 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Multi-template analysis of human perirhinal cortex in brain MRI: Explicitly accounting for anatomical variability.

Xie Long L Pluta John B JB Das Sandhitsu R SR Wisse Laura E M LEM Wang Hongzhi H Mancuso Lauren L Kliot Dasha D Avants Brian B BB Ding Song-Lin SL Manjón José V JV Wolk David A DA Yushkevich Paul A PA

NeuroImage 20161001 Pt A

<h4>Rational</h4>The human perirhinal cortex (PRC) plays critical roles in episodic and semantic memory and visual perception. The PRC consists of Brodmann areas 35 and 36 (BA35, BA36). In Alzheimer's disease (AD), BA35 is the first cortical site affected by neurofibrillary tangle pathology, which is closely linked to neural injury in AD. Large anatomical variability, manifested in the form of different cortical folding and branching patterns, makes it difficult to segment the PRC in MRI scans. ...[more]

PMID: 27702610

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Project description:Our brain disambiguates the objects in our cluttered visual world seemingly effortlessly, enabling us to understand their significance and to act appropriately. The role of anteromedial temporal structures in this process, particularly the perirhinal cortex, is highly controversial. In some accounts, the perirhinal cortex is necessary for differentiating between perceptually and semantically confusable objects. Other models claim that the perirhinal cortex neither disambiguates perceptually confusable objects nor plays a unique role in semantic processing. One major hurdle to resolving this central debate is the fact that brain damage in human patients typically encompasses large portions of the anteromedial temporal lobe, such that the identification of individual substructures and precise neuroanatomical locus of the functional impairments has been difficult. We tested these competing accounts in patients with Alzheimer's disease with varying degrees of atrophy in anteromedial structures, including the perirhinal cortex. To assess the functional contribution of each anteromedial temporal region separately, we used a detailed region of interest approach. From each participant, we obtained magnetic resonance imaging scans and behavioural data from a picture naming task that contrasted naming performance with living and non-living things as a way of manipulating perceptual and semantic confusability; living things are more similar to one another than non-living things, which have more distinctive features. We manually traced neuroanatomical regions of interest on native-space cortical surface reconstructions to obtain mean thickness estimates for the lateral and medial perirhinal cortex and entorhinal cortex. Mean cortical thickness in each region of interest, and hippocampal volume, were submitted to regression analyses predicting naming performance. Importantly, atrophy of the medial perirhinal cortex, but not lateral perirhinal cortex, entorhinal cortex or hippocampus, significantly predicted naming performance on living relative to non-living things. These findings indicate that one specific anteromedial temporal lobe region-the medial perirhinal cortex-is necessary for the disambiguation of perceptually and semantically confusable objects. Taken together, these results support a hierarchical account of object processing, whereby the perirhinal cortex at the apex of the ventral object processing system is required to bind properties of not just perceptually, but also semantically confusable objects together, enabling their disambiguation from other similar objects and thus comprehension. Significantly, this model combining a hierarchical object processing architecture with a semantic feature statistic account explains why category-specific semantic impairments for living things are associated with anteromedial temporal lobe damage, and pinpoints the root of this syndrome to perirhinal cortex damage.

Project description:Most fetal brain MRI reconstruction algorithms rely only on brain tissue-relevant voxels of low-resolution (LR) images to enhance the quality of inter-slice motion correction and image reconstruction. Consequently the fetal brain needs to be localized and extracted as a first step, which is usually a laborious and time consuming manual or semi-automatic task. We have proposed in this work to use age-matched template images as prior knowledge to automatize brain localization and extraction. This has been achieved through a novel automatic brain localization and extraction method based on robust template-to-slice block matching and deformable slice-to-template registration. Our template-based approach has also enabled the reconstruction of fetal brain images in standard radiological anatomical planes in a common coordinate space. We have integrated this approach into our new reconstruction pipeline that involves intensity normalization, inter-slice motion correction, and super-resolution (SR) reconstruction. To this end we have adopted a novel approach based on projection of every slice of the LR brain masks into the template space using a fusion strategy. This has enabled the refinement of brain masks in the LR images at each motion correction iteration. The overall brain localization and extraction algorithm has shown to produce brain masks that are very close to manually drawn brain masks, showing an average Dice overlap measure of 94.5%. We have also demonstrated that adopting a slice-to-template registration and propagation of the brain mask slice-by-slice leads to a significant improvement in brain extraction performance compared to global rigid brain extraction and consequently in the quality of the final reconstructed images. Ratings performed by two expert observers show that the proposed pipeline can achieve similar reconstruction quality to reference reconstruction based on manual slice-by-slice brain extraction. The proposed brain mask refinement and reconstruction method has shown to provide promising results in automatic fetal brain MRI segmentation and volumetry in 26 fetuses with gestational age range of 23 to 38 weeks.

Dataset Information

Multi-template analysis of human perirhinal cortex in brain MRI: Explicitly accounting for anatomical variability.

Publications

Multi-template analysis of human perirhinal cortex in brain MRI: Explicitly accounting for anatomical variability.

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