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  • 1
    In: Alzheimer's & Dementia, Wiley, Vol. 17, No. S4 ( 2021-12)
    Abstract: Measurements of medial temporal lobe (MTL) neurodegeneration derived using MRI have been shown to be sensitive to changes during the early stages of AD. The specificity of these measurements to tau neurofibrillary tangle (NFT) pathology is limited by other frequently comorbid non‐AD factors which also cause structural changes in the MTL. Here, we directly link changes in MTL structure to underlying NFT pathology by combining ex vivo MRI with ratings of NFT severity derived from serial histology using a dataset of 18 human MTL specimens. We hypothesize that such an analysis can be used to define MTL “hotspots” where in vivo measures will be more sensitive to disease progression in preclinical AD than current state of the art biomarkers. Method Ex vivo specimens from 18 donors were scanned at 0.2x0.2x0.2mm 3 on 9.4T MRI. Following MRI scanning, the specimens underwent histological processing with staining for cytoarchitecture and in 15 specimens, immunohistochemistry (IHC) with the anti‐tau AT8 antibody. Using a topological unfolding method (DeKraker et al. 2018), we created 2D representations of the extra‐hippocampal cortex which implicitly align cortical folding patterns across specimens (Fig. 1). An average MTL subregion segmentation was generated in unfolded space using manual segmentations completed in 11 specimens on the basis of cytoarchitecture. Additionally, heat maps quantifying NFT burden in each of the specimens with anti‐tau IHC sections were generated using a deep learning algorithm (Yushkevich et al. 2021). Using the heatmaps and the average subregion segmentation, we investigated the relationship between NFT severity and cortical thickness. Result Correlation analysis between NFT measures and thickness (correcting for age) reveals strong associations in the entorhinal cortex and the border of Brodmann Area 35, consistent with the early Braak regions, and parts of Brodmann Area 36 (Fig. 2). Conclusion We present an unfolding framework applied to the MTL cortex, which allows us to visualize, for the first time, the distribution of MTL subregions and NFT pathology in an unfolded space. This framework provides a promising tool for detailed investigation of structural changes due to NFT pathology while explicitly accounting for the complex topology of the MTL, thereby enhancing our understanding of early AD.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2201940-6
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  • 2
    In: Alzheimer's & Dementia, Wiley, Vol. 16, No. S4 ( 2020-12)
    Abstract: Finding effective biomarkers that can support early‐stage clinical trials is a major challenge in Alzheimer’s Disease (AD). MRI measures of structural change in the medial temporal lobe (MTL) have proven to be sensitive to change in the early stages of AD. However, other frequently comorbid non‐AD factors (e.g. cerebrovascular disease, TDP‐43 pathology) also cause changes in the MTL. For MRI biomarkers to detect changes specifically linked to AD pathology , patterns of structural change must be linked to the underlying neuropathology. To provide this linkage, we use ex vivo imaging with pathologically derived ratings of AD and non‐AD pathology to study the localized effects of the disease on MTL structure. We hypothesize that such an analysis can be used to define MTL “hotspots” where in vivo measures will be more sensitive to disease progression in preclinical AD than current state of the art biomarkers. Method Ex vivo MTL specimens from 24 donors were scanned at 0.2x0.2x0.2mm 3 on 9.4T MRI. The specimens contain varying degrees of pathology spanning the spectrum of AD and common co‐morbid non‐AD pathologies. For 21 specimens, a pathologist provided semi‐quantitative ratings of tau and TDP‐43 severity (Table 1). Extending on techniques developed in our prior work, a computational atlas of the MTL was built via groupwise registration of all specimens’ MRI scans (Adler et al, 2018; Ravikumar et al, 2020). The atlas was used to investigate the correlation between tau pathology and cortical thickness. Result The developed atlas achieves excellent groupwise alignment and captures anatomical variability in the MTL despite its complex geometry (Figure 1). Correlation analysis between tau pathology and atrophy (correcting for age and TDP‐43) reveals significant clusters near the transentorhinal region and subiculum (Figure 2). Conclusion These correlation patterns are consistent with the early Braak stages and resemble results from a previous study which looked at the association between in vivo tau PET measures and atrophy (Das et al, 2019) (Figure 3). In future work, our novel ex vivo atlas will be leveraged to study variability in the distribution of tau pathology in 3D, by mapping quantitative serial pathology images into the atlas space (Figure 4).
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2201940-6
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  • 3
    In: Alzheimer's & Dementia, Wiley, Vol. 18, No. S5 ( 2022-12)
    Abstract: Neurodegenerative disorders are associated with different pathologies that often co‐occur and have differential contribution to the pattern of cognitive impairment. The majority of these pathologies cannot be detected or measured by in‐vivo methods; therefore, recognition of the topographic patterns of them and association with MRI findings may provide probabilistic non‐invasive biomarkers. We investigated the association of cortical and medial temporal lobe subregional thickness measured from postmortem MRI and semi‐quantitative pathologic measures in order to provide a methodological approach for linking pathological and radiological measures. Method 22 brain hemispheres from donors with Alzheimer’s disease (AD) spectrum diagnosis were included. T2‐weighted images were obtained on 7 Tesla scanner (0.28 mm isotropic) and patches of cortex around 16 anatomical locations were segmented using semi‐automated active contour segmentation in ITK‐SNAP. Immunohistochemistry evaluation was performed using previously validated antibodies to detect amyloid‐β, phosphorylated tau, phosphorylated TDP‐43 deposits and pathological conformation of α‐synuclein on contralateral hemispheres. Neuronal loss was visually assessed. Thickness measures at each location were associated with pathology measures at corresponding or closest to corresponding anatomical location. Multivariate linear models were used for statistical analyses. Result The mean age of donors at death was 80.2±10.7 years (range 63‐99) and 8 (36%) were female. The median Braak stage was 5 (range: 2‐6). Linear models including regional Tau and TDP43 scores and age showed significant relationships between increased regional tau score and reduced thickness in anterior temporal pole, entorhinal, angular and superior parietal cortices. (Table 1, Figure 1) Linear models including Braak stages, TDP43 scores and age showed significant correlation between Braak stage and thickness in anterior temporal pole and entorhinal cortices and BA35 region of medial temporal lobe. Conclusion The aim of the current study is to validate methods for development of 3D pathology maps which can be directly linked to local neurodegeneration measures. As the primary result of such an effort, the present study demonstrates an association of semi‐quantitative measures of AD pathology and with local tissue loss in several common AD regions despite limited range of pathology in these cases. These promising results provide support for future studies directly linking pathology with post‐mortem measures of structure.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2201940-6
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  • 4
    In: Alzheimer's & Dementia, Wiley, Vol. 19, No. 6 ( 2023-06), p. 2355-2364
    Abstract: Neurodegenerative disorders are associated with different pathologies that often co‐occur but cannot be measured specifically with in vivo methods. Methods Thirty‐three brain hemispheres from donors with an Alzheimer's disease (AD) spectrum diagnosis underwent T2‐weighted magnetic resonance imaging (MRI). Gray matter thickness was paired with histopathology from the closest anatomic region in the contralateral hemisphere. Results Partial Spearman correlation of phosphorylated tau and cortical thickness with TAR DNA‐binding protein 43 (TDP‐43) and α‐synuclein scores, age, sex, and postmortem interval as covariates showed significant relationships in entorhinal and primary visual cortices, temporal pole, and insular and posterior cingulate gyri. Linear models including Braak stages, TDP‐43 and α‐synuclein scores, age, sex, and postmortem interval showed significant correlation between Braak stage and thickness in the parahippocampal gyrus, entorhinal cortex, and Broadman area 35. Conclusion We demonstrated an association of measures of AD pathology with tissue loss in several AD regions despite a limited range of pathology in these cases. Highlights Neurodegenerative disorders are associated with co‐occurring pathologies that cannot be measured specifically with in vivo methods. Identification of the topographic patterns of these pathologies in structural magnetic resonance imaging (MRI) may provide probabilistic biomarkers. We demonstrated the correlation of the specific patterns of tissue loss from ex vivo brain MRI with underlying pathologies detected in postmortem brain hemispheres in patients with Alzheimer's disease (AD) spectrum disorders. The results provide insight into the interpretation of in vivo structural MRI studies in patients with AD spectrum disorders.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2201940-6
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  • 5
    In: Alzheimer's & Dementia, Wiley, Vol. 16, No. S4 ( 2020-12)
    Abstract: The medial temporal lobe (MTL) is a hotspot of different neurodegenerative pathologies, and recent studies have shown associations of severity of pathology with atrophy measured on antemortem MRI. However, these studies are limited by the interval between time of scan and death and the relatively low resolution of the commonly acquired in vivo MRI scans, limiting the granularity of the regions being measured. We investigate the association of different neurodegenerative pathologies, particularly TDP‐43, and the thickness of different MTL subregions measured on high‐resolution postmortem MRI. As prior work suggests an anterior‐to‐posterior gradient of atrophy for TDP‐43 in frontotemporal dementia spectrum disorders and Limbic‐predominant Age‐related TDP‐43 Encephalopathy (LATE), we also examined differences along the long axis of the MTL. Method Tau, TDP‐43, β‐amyloid and α‐synuclein pathology were rated (0‐absent – 3‐frequent) in the hippocampus and entorhinal cortex (ERC) of 35 individuals with and without neurodegenerative diseases (Table 1). Thickness measurements were obtained from 0.2x0.2x0.2 mm 3 post‐mortem MRI scans of excised MTL specimens from the contralateral hemisphere (Figure 1) in the ERC, Brodmann Area 35 and 36, parahippocampal cortex, subiculum, cornu ammonis (CA)1 and the stratum radiatum lacunosum moleculare. For each region, thickness was measured at an anterior and posterior location using a semi‐automated approach (Figure 2). Spearman’s rank correlations were performed, correcting for age, sex and hemisphere, including all four proteinopathies in the model. Result We find strong negative associations of TDP‐43 with thickness in all cortical MTL regions (Table 2, Figure 3) and with CA1, averaged over the two locations. We repeated the analyses for the thickness measurements separately in the anterior and posterior locations, but did not find a clear difference along the longitudinal axis. This is potentially due to the severity of the TDP‐43 pathology. Conclusion In this unique dataset with neurodegenerative pathologies and high‐resolution scans of the MTL, preliminary results show strong associations between TDP‐43 pathology and atrophy in several MTL subregions. As this dataset continues to grow, we will be able to tease apart the effects of multiple MTL pathologies at a subregional level.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2201940-6
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  • 6
    In: Alzheimer's & Dementia, Wiley, Vol. 18, No. S5 ( 2022-12)
    Abstract: Ex vivo magnetic resonance imaging (MRI) of the brain provides remarkable advantages over in vivo MRI for linking neuroanatomy and morphometry to underlying pathology (Yushkevich et al. 2021, Ravikumar et al. 2021). Subcortical structures show atrophy in certain neurodegenerative diseases, especially Frontotemporal Lobar Degeneration with TDP‐43 (FTLD‐TDP) and four‐repeat (4R) tauopathies (i.e., Corticobasal Degeneration, Progressive Supranuclear Palsy) (Miletić et al. 2022), yet few methods exist to measure subcortical atrophy in ex vivo MRI. We present a framework to quantify subcortical morphometry using 7 Tesla ex vivo MRI and distinguish atrophy patterns across neurodegenerative spectrums. Method A deep learning method, nnU‐Net (Isensee et al. 2021), was trained on manual segmentations from only 3 brain hemispheres to obtain automated segmentations of 4 subcortical structures (caudate, putamen, globus pallidus, thalamus) across 38 subjects spanning Alzheimer's Disease (AD), Lewy Body Disease (LBD), FTLD‐TDP, 4R tauopathies and miscellaneous tauopathies (Figure 1, Table 1). Subcortical volumes were extracted from automated segmentations. Cerebral cortical volume was computed via cortical segmentation method in Khandelwal et al. 2021. Regional volumes were evaluated via likelihood ratio tests (Figure 2), adjusted for covariates (age, sex and intracranial volume from in vivo MRI) and multiple tests. Separately, correlations were computed between subcortical volumes, cortical thicknesses at 18 landmark locations and neuropathological ratings (Khandelwal et al. 2021, Wisse et al. 2021, Figure 3). Result The pipeline validated regional volumetric relationships in neurodegeneration. Global cortex volume did not significantly differ among disease groups (Figure 2). Compared to AD, FTLD‐TDP had significantly lower putamen and thalamus volumes while 4R tauopathies had reduced putamen and caudate volumes ( P ’s 〈 0.05, adjusted for covariates/multiple comparisons). Before multiple tests correction, there were decreased covariate‐adjusted volumes in globus pallidus and caudate in FTLD‐TDP and thalamus in 4R tauopathy relative to AD. Subcortical volumes correlated with each other ( P ’s 〈 0.05) but not with cortical thickness, with trends in motor cortex (Figure 3). Subcortical volumes also trended with local tau pathology (Figure 4). Conclusion Our ex vivo neuroimaging framework differentiates subcortical atrophy patterns in FTLD‐TDP and 4R tauopathies compared to AD, highlighting utility in ex vivo imaging for diagnosing and investigating neurodegeneration.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2201940-6
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  • 7
    In: Alzheimer's & Dementia, Wiley, Vol. 18, No. S6 ( 2022-12)
    Abstract: Tau pathology in the medial temporal lobe (MTL) is closely linked to neurodegeneration, and is an early pathological change associated with Alzheimer’s disease (AD). MRI measures of MTL neurodegeneration have proven to be sensitive to change during preclinical AD. Current measures are confounded by the presence of non‐AD pathologies (e.g., TDP‐43, ageing). Here, we combine ex vivo imaging with histopathological ratings of tau and TDP‐43 to identify fine‐grained MTL atrophy patterns specific to tau. Such an analysis could be used to define MTL “hotspots” where in vivo measures of neurodegeneration are expected to be strongly associated with tau, potentially enabling the development of biomarkers that are more effective during early AD clinical trials. Method Ex vivo MRI scans (0.2x0.2x0.2mm 3 , 9.4T) of human MTL specimens were combined using a customized registration approach to construct a 3D atlas. Using serial histology available in a subset of specimens (n = 11), MTL subregions in the atlas were labelled based on cytoarchitecture (Ravikumar et al., 2021) (Figure 1A). To perform thickness analysis, 29 specimens containing a primary diagnosis of AD or primary age‐related tauopathy were registered to the atlas (13 specimens were registered to the atlas during atlas construction, and 16 were registered to the atlas after it was constructed) (Figure 1B, Table 1). Using histopathology measures of tau and TDP‐43 pathology (based on contralateral sampling), we investigated the association between tau and thickness by fitting a linear model (with age/TDP‐43 as covariates) at each point along the MTL and SRLM surface. Result Pointwise thickness analysis reveals significant atrophy patterns in the transentorhinal region and SRLM. When excluding age from the model, stronger tau associations are observed in the SRLM, entorhinal cortex, and extending further towards Brodmann Area 35 (Figure 2). Conclusion Our findings are consistent with early Braak stages but suggest that covarying for age may be obscuring some associations due to tau since age and tau burden have a highly correlated relationship (Figure 3). In future work, quantitative maps of NFT burden will be mapped from serial pathology images into atlas space, allowing us to characterize NFT distribution in 3D (Yushkevich et al., 2021).
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2201940-6
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  • 8
    In: Neurobiology of Aging, Elsevier BV, Vol. 98 ( 2021-02), p. 231-241
    Type of Medium: Online Resource
    ISSN: 0197-4580
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 1498414-3
    SSG: 12
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  • 9
    In: Alzheimer's & Dementia, Wiley, Vol. 16, No. S4 ( 2020-12)
    Abstract: Structural magnetic resonance imaging (MRI) biomarkers are important for early detection of Alzheimer’s Disease (AD). However, atrophy measures can be confounded by changes due to aging and comorbid non‐AD neurodegenerative pathologies. Linking postmortem MRI of the medial temporal lobe (MTL) to histopathology may identify focal patterns of change associated specifically with early AD. We implemented a pipeline of high‐resolution MRI of MTL specimens and serial histopathology imaging [REF]. However, the task of extracting the intact MTL specimen such that it fits into the MRI coil requires anatomical expertise and has proven error prone. Here we present an algorithm to automatically create 3D printed molds guiding MTL extraction. Method INPUTS: 7T MRI scan of a formalin‐fixed hemisphere in which the hemisphere, MTL ROI and optional second ROI to be spared during cutting (e.g. frontal lobe) have been segmented using ITK‐SNAP semi‐automatic segmentation tools. OUTPUTS: Two 3D printed molds with slits that guide cutting. Mold 1 holds the whole hemisphere, guiding four cuts orthogonal to the midsagittal plane (Figure 1). Mold 2 holds the extracted tissue block, guiding three subsequent longitudinal cuts that trim the tissue to fit into a 50mm cylindrical holder (Figure 2). The positioning of the cuts can be specified interactively by the user using ITK‐SNAP (translating and rotating 3D images representing cutting planes) or automatically by optimizing (using Powell’s method) energy functions that minimize the volume of the final piece of tissue under multiple constraints (see Figures 3 and 4). Result The algorithm with interactively positioned cut planes was used in four hemispheres; the automated version in one (Figure 5). For each MRI scan, the MTL was intact. By contrast, retrospective review revealed cutting errors in 48% of manually cut specimens. Conclusion Our image‐guided approach reduces errors and dependence on anatomical expertise; allows more tissue to be spared from each brain donation; and enables postmortem imaging at a larger scale. It is not limited to the MTL and could be of interest to brain banks and AD research centers involved in postmortem imaging.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2201940-6
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  • 10
    In: Alzheimer's & Dementia, Wiley, Vol. 18, No. S5 ( 2022-12)
    Abstract: Ex vivo magnetic resonance imaging (MRI) enables detailed characterization of neuroanatomy (Augustinack et al. 2013), such as hippocampal subfields in the medial temporal lobe (MTL) (Yushkevich et al. 2021, Ravikumar et al. 2021). However, automated cortical segmentation methods in ex vivo MRI are not well developed due to limited data availability and heterogeneity in scanners and acquisition. Here, we investigate a deep learning framework to parcellate the cortical mantle, compute thickness and link them with neuropathology ratings across 16 cortical regions in 7 Tesla MRIs of 38 ex vivo brain specimens spanning Alzheimer Disease and Related Dementias. Method A deep learning method, nnU‐Net (Isensee et al. 2021), was trained on manually segmented 3D image patches (Figure 1C) to obtain automated cortical segmentations across 38 subjects (Table 1). We identified 16 landmarks (Figure 1A) for localized quantitative signatures of cortical morphometry and used the pipeline in Wisse et al. 2021 to measure local thickness (Figure 1B). Associations were computed between cortical thickness from manual and automated segmentations via Pearson’s correlation and average fixed‐raters Intra‐class Correlation Coefficient (ICC) for 16 locations (Figure 3). We also correlated thickness from both automated and manual segmentations with neuropathological ratings of tau and neuronal loss in corresponding contralateral regions and global Braak staging (Figures 4 and 5). Result Figure 2 depicts cortical mantle segmentation across brain hemispheres. Figure 3 shows good agreement between ground truth and automated thickness, with 15 regions with significant associations (p 〈 0.05) and 8 regions having r 〉 0.6. We observe high ICC scores with 9 regions where ICC 〉 0.7, confirming that automated segmentations accurately measure thickness. Figure 4 shows significant correlations between thickness and Tau ratings for Brodmann Area 35 (BA35) and midfrontal regions and trends between neuronal loss and thickness in entorhinal cortex (ERC), anterior temporal pole and anterior insula. Figure 5 shows significant correlations between thickness and Braak staging in ventrolateral temporal cortex and ERC, with trends in other regions. Conclusion Our automated ex vivo neuroimaging framework accurately segments the cortical mantle, provides thickness measurements that concur with user‐supervised thickness and links morphometry with underlying neurodegeneration, thus suggesting the strengths of ex vivo MRI.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2201940-6
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