| 1. |
- Ravikumar, Sadhana, et al.
(författare)
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Ex vivo MRI atlas of the human medial temporal lobe : characterizing neurodegeneration due to tau pathology
- 2021
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Ingår i: Acta Neuropathologica Communications. - : Springer Science and Business Media LLC. - 2051-5960. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Tau neurofibrillary tangle (NFT) pathology in the medial temporal lobe (MTL) is closely linked to neurodegeneration, and is the early pathological change associated with Alzheimer’s disease (AD). To elucidate patterns of structural change in the MTL specifically associated with tau pathology, we compared high-resolution ex vivo MRI scans of human postmortem MTL specimens with histology-based pathological assessments of the MTL. MTL specimens were obtained from twenty-nine brain donors, including patients with AD, other dementias, and individuals with no known history of neurological disease. Ex vivo MRI scans were combined using a customized groupwise diffeomorphic registration approach to construct a 3D probabilistic atlas that captures the anatomical variability of the MTL. Using serial histology imaging in eleven specimens, we labelled the MTL subregions in the atlas based on cytoarchitecture. Leveraging the atlas and neuropathological ratings of tau and TAR DNA-binding protein 43 (TDP-43) pathology severity, morphometric analysis was performed to correlate regional MTL thickness with the severity of tau pathology, after correcting for age and TDP-43 pathology. We found significant correlations between tau pathology and thickness in the entorhinal cortex (ERC) and stratum radiatum lacunosum moleculare (SRLM). When focusing on cases with low levels of TDP-43 pathology, we found strong associations between tau pathology and thickness in the ERC, SRLM and the subiculum/cornu ammonis 1 (CA1) subfields of the hippocampus, consistent with early Braak stages.
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| 2. |
- Ravikumar, Sadhana, et al.
(författare)
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Improved Segmentation of Deep Sulci in Cortical Gray Matter Using a Deep Learning Framework Incorporating Laplace’s Equation
- 2023
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Ingår i: Information Processing in Medical Imaging - 28th International Conference, IPMI 2023, Proceedings. - 0302-9743 .- 1611-3349. - 9783031340475 ; 13939 LNCS, s. 692-704
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Konferensbidrag (refereegranskat)abstract
- When developing tools for automated cortical segmentation, the ability to produce topologically correct segmentations is important in order to compute geometrically valid morphometry measures. In practice, accurate cortical segmentation is challenged by image artifacts and the highly convoluted anatomy of the cortex itself. To address this, we propose a novel deep learning-based cortical segmentation method in which prior knowledge about the geometry of the cortex is incorporated into the network during the training process. We design a loss function which uses the theory of Laplace’s equation applied to the cortex to locally penalize unresolved boundaries between tightly folded sulci. Using an ex vivo MRI dataset of human medial temporal lobe specimens, we demonstrate that our approach outperforms baseline segmentation networks, both quantitatively and qualitatively.
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| 3. |
- Ravikumar, Sadhana, et al.
(författare)
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Postmortem imaging reveals patterns of medial temporal lobe vulnerability to tau pathology in Alzheimer’s disease
- 2024
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Ingår i: Nature Communications. - 2041-1723. ; 15:1
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Tidskriftsartikel (refereegranskat)abstract
- Our current understanding of the spread and neurodegenerative effects of tau neurofibrillary tangles (NFTs) within the medial temporal lobe (MTL) during the early stages of Alzheimer’s Disease (AD) is limited by the presence of confounding non-AD pathologies and the two-dimensional (2-D) nature of conventional histology studies. Here, we combine ex vivo MRI and serial histological imaging from 25 human MTL specimens to present a detailed, 3-D characterization of quantitative NFT burden measures in the space of a high-resolution, ex vivo atlas with cytoarchitecturally-defined subregion labels, that can be used to inform future in vivo neuroimaging studies. Average maps show a clear anterior to poster gradient in NFT distribution and a precise, spatial pattern with highest levels of NFTs found not just within the transentorhinal region but also the cornu ammonis (CA1) subfield. Additionally, we identify granular MTL regions where measures of neurodegeneration are likely to be linked to NFTs specifically, and thus potentially more sensitive as early AD biomarkers.
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| 4. |
- Ravikumar, Sadhana, et al.
(författare)
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Unfolding the Medial Temporal Lobe Cortex to Characterize Neurodegeneration Due to Alzheimer’s Disease Pathology Using Ex vivo Imaging
- 2021
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Ingår i: Machine Learning in Clinical Neuroimaging - 4th International Workshop, MLCN 2021, Held in Conjunction with MICCAI 2021, Proceedings. - Cham : Springer International Publishing. - 0302-9743 .- 1611-3349. - 9783030875855 ; 13001 LNCS, s. 3-12
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Konferensbidrag (refereegranskat)abstract
- Neurofibrillary tangle (NFT) pathology in the medial temporal lobe (MTL) is closely linked to neurodegeneration, and is the early pathological change associated with Alzheimer’s Disease (AD). In this work, we investigate the relationship between MTL morphometry features derived from high-resolution ex vivo imaging and histology-based measures of NFT pathology using a topological unfolding framework applied to a dataset of 18 human postmortem MTL specimens. The MTL has a complex 3D topography and exhibits a high degree of inter-subject variability in cortical folding patterns which poses a significant challenge for volumetric registration methods typically used during MRI template construction. By unfolding the MTL cortex, the proposed framework explicitly accounts for the sheet-like geometry of the MTL cortex and provides a two-dimensional reference coordinate space which can be used to implicitly register cortical folding patterns across specimens based on distance along the cortex despite large anatomical variability. Leveraging this framework in a subset of 15 specimens, we characterize the associations between NFTs and morphological features such as cortical thickness and surface curvature and identify regions in the MTL where patterns of atrophy are strongly correlated with NFT pathology.
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| 5. |
- Yushkevich, Paul A., et al.
(författare)
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Three-dimensional mapping of neurofibrillary tangle burden in the human medial temporal lobe
- 2021
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Ingår i: Brain. - : Oxford University Press (OUP). - 0006-8950 .- 1460-2156. ; 144:9, s. 2784-2797
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Tidskriftsartikel (refereegranskat)abstract
- Tau protein neurofibrillary tangles are closely linked to neuronal/synaptic loss and cognitive decline in Alzheimer's disease and related dementias. Our knowledge of the pattern of neurofibrillary tangle progression in the human brain, critical to the development of imaging biomarkers and interpretation of in vivo imaging studies in Alzheimer's disease, is based on conventional two-dimensional histology studies that only sample the brain sparsely. To address this limitation, ex vivo MRI and dense serial histological imaging in 18 human medial temporal lobe specimens (age 75.3 ± 11.4 years, range 45 to 93) were used to construct three-dimensional quantitative maps of neurofibrillary tangle burden in the medial temporal lobe at individual and group levels. Group-level maps were obtained in the space of an in vivo brain template, and neurofibrillary tangles were measured in specific anatomical regions defined in this template. Three-dimensional maps of neurofibrillary tangle burden revealed significant variation along the anterior-posterior axis. While early neurofibrillary tangle pathology is thought to be confined to the transentorhinal region, we found similar levels of burden in this region and other medial temporal lobe subregions, including amygdala, temporopolar cortex, and subiculum/cornu ammonis 1 hippocampal subfields. Overall, the three-dimensional maps of neurofibrillary tangle burden presented here provide more complete information about the distribution of this neurodegenerative pathology in the region of the cortex where it first emerges in Alzheimer's disease, and may help inform the field about the patterns of pathology spread, as well as support development and validation of neuroimaging biomarkers.
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