70 results on '"Clifford R. Jack, Jr"'
Search Results
2. Altered structural and functional connectivity in Posterior Cortical Atrophy and Dementia with Lewy bodies
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Neha Atulkumar Singh, Austin W. Goodrich, Jonathan Graff-Radford, Mary M. Machulda, Irene Sintini, Arenn F. Carlos, Carling G. Robinson, Robert I. Reid, Val J. Lowe, Clifford R. Jack, Jr, Ronald C. Petersen, Bradley F. Boeve, Keith A. Josephs, Kejal Kantarci, and Jennifer L. Whitwell
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Resting state functional connectivity ,Diffusion tensor imaging ,Posterior cortical atrophy ,Dementia with Lewy bodies ,Multimodal imaging analysis ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Posterior cortical atrophy (PCA) and dementia with Lewy bodies (DLB) show distinct atrophy and overlapping hypometabolism profiles, but it is unknown how disruptions in structural and functional connectivity compare between these disorders and whether breakdowns in connectivity relate to either atrophy or hypometabolism.Thirty amyloid-positive PCA patients, 24 amyloid-negative DLB patients and 30 amyloid-negative cognitively unimpaired (CU) healthy individuals were recruited at Mayo Clinic, Rochester, MN, and underwent a 3T head MRI, including structural MRI, resting state functional MRI (rsfMRI) and diffusion tensor imaging (DTI) sequences, as well as [18F] fluorodeoxyglucose (FDG) PET. We assessed functional connectivity within and between 12 brain networks using rsfMRI and the CONN functional connectivity toolbox and calculated regional DTI metrics using the Johns Hopkins atlas. Multivariate linear-regression models corrected for multiple comparisons and adjusted for age and sex compared DTI metrics and within-network and between-network functional connectivity across groups. Regional gray-matter volumes and FDG-PET standard uptake value ratios (SUVRs) were calculated and analyzed at the voxel-level using SPM12. We used univariate linear-regression models to investigate the relationship between connectivity measures, gray-matter volume, and FDG-PET SUVR.On DTI, PCA showed degeneration in occipito-parietal white matter, posterior thalamic radiations, splenium of the corpus collosum and sagittal stratum compared to DLB and CU, with greater degeneration in the temporal white matter and the fornix compared to CU. We observed no white-matter degeneration in DLB compared to CU. On rsfMRI, reduced within-network connectivity was present in dorsal and ventral default mode networks (DMN) and the dorsal-attention network in PCA compared to DLB and CU, with reduced within-network connectivity in the visual and sensorimotor networks compared to CU. DLB showed reduced connectivity in the cerebellar network compared to CU. Between-network analysis showed increased connectivity in both cerebellar-to-sensorimotor and cerebellar-to-dorsal attention network connectivity in PCA and DLB. PCA showed reduced anterior DMN-to-cerebellar and dorsal attention-to-sensorimotor connectivity, while DLB showed reduced posterior DMN-to-sensorimotor connectivity compared to CU. PCA showed reduced dorsal DMN-to-visual connectivity compared to DLB. The multimodal analysis revealed weak associations between functional connectivity and volume in PCA, and between functional connectivity and metabolism in DLB.These findings suggest that PCA and DLB have unique connectivity alterations, with PCA showing more widespread disruptions in both structural and functional connectivity; yet some overlap was observed with both disorders showing increased connectivity from the cerebellum.
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- 2024
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3. Speech-language within and between network disruptions in primary progressive aphasia variants
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Neha Singh-Reilly, Hugo Botha, Joseph R. Duffy, Heather M. Clark, Rene L. Utianski, Mary M. Machulda, Jonathan Graff-Radford, Christopher G. Schwarz, Ronald C. Petersen, Val J. Lowe, Clifford R. Jack, Jr, Keith A. Josephs, and Jennifer L. Whitwell
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Resting state fMRI ,Functional connectivity ,Logopenic ,Non-fluent ,Semantic ,PPA ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Primary progressive aphasia (PPA) variants present with distinct disruptions in speech-language functions with little known about the interplay between affected and spared regions within the speech-language network and their interaction with other functional networks.The Neurodegenerative Research Group, Mayo Clinic, recruited 123 patients with PPA (55 logopenic (lvPPA), 44 non-fluent (nfvPPA) and 24 semantic (svPPA)) who were matched to 60 healthy controls. We investigated functional connectivity disruptions between regions within the left-speech-language network (Broca, Wernicke, anterior middle temporal gyrus (aMTG), supplementary motor area (SMA), planum temporale (PT) and parietal operculum (PO)), and disruptions to other networks (visual association, dorsal-attention, frontoparietal and default mode networks (DMN)).Within the speech-language network, multivariate linear regression models showed reduced aMTG-Broca connectivity in all variants, with lvPPA and nfvPPA findings remaining significant after Bonferroni correction. Additional loss in Wernicke-Broca connectivity in nfvPPA, Wernicke-PT connectivity in lvPPA and greater aMTG-PT connectivity in svPPA were also noted. Between-network connectivity findings in all variants showed reduced aMTG-DMN and increased aMTG-dorsal-attention connectivity, with additional disruptions between aMTG-visual association in both lvPPA and svPPA, aMTG-frontoparietal in lvPPA, and Wernicke-DMN breakdown in svPPA.These findings suggest that aMTG connectivity breakdown is a shared feature in all PPA variants, with lvPPA showing more extensive connectivity disruptions with other networks.
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- 2024
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4. Complex relationships of socioeconomic status with vascular and Alzheimer’s pathways on cognition
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Dror Shir, Jonathan Graff-Radford, Angela J. Fought, Timothy G. Lesnick, Scott A. Przybelski, Maria Vassilaki, Val J. Lowe, David S. Knopman, Mary M. Machulda, Ronald C. Petersen, Clifford R. Jack, Jr, Michelle M. Mielke, and Prashanthi Vemuri
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PET imaging ,Amyloid ,Tau ,Cognition ,Vascular health ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Introduction: AD and CVD, which frequently co-occur, are leading causes of age-related cognitive decline. We assessed how demographic factors, socioeconomic status (SES) as indicated by education and occupation, vascular risk factors, and a range of biomarkers associated with both CVD (including white matter hyperintensities [WMH], diffusion MRI abnormalities, infarctions, and microbleeds) and AD (comprising amyloid-PET and tau-PET) collectively influence cognitive function. Methods: In this cross-sectional population study, structural equation models were utilized to understand these associations in 449 participants (mean age (SD) = 74.5 (8.4) years; 56% male; 7.5% cognitively impaired). Results: (1) Higher SES had a protective effect on cognition with mediation through the vascular pathway. (2) The effect of amyloid directly on cognition and through tau was 11-fold larger than the indirect effect of amyloid on cognition through WMH. (3) There is a significant effect of vascular risk on tau deposition. Discussion: The utilized biomarkers captured the impact of CVD and AD on cognition. The overall effect of vascular risk and SES on these biomarkers are complex and need further investigation.
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- 2024
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5. The diamagnetic component map from quantitative susceptibility mapping (QSM) source separation reveals pathological alteration in Alzheimer’s disease-driven neurodegeneration
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Maruf Ahmed, Jingjia Chen, Arvin Arani, Matthew L. Senjem, Petrice M. Cogswell, Clifford R. Jack, Jr., and Chunlei Liu
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Alzheimer's disease ,Quantitative susceptibility mapping ,Neurodegeneration ,DECOMPOSE ,Magnetic susceptibility ,Demyelination ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
A sensitive and accurate imaging technique capable of tracking the disease progression of Alzheimer's Disease (AD) driven amnestic dementia would be beneficial. A currently available method for pathology detection in AD with high accuracy is Positron Emission Tomography (PET) imaging, despite certain limitations such as low spatial resolution, off-targeting error, and radiation exposure. Non-invasive MRI scanning with quantitative magnetic susceptibility measurements can be used as a complementary tool. To date, quantitative susceptibility mapping (QSM) has widely been used in tracking deep gray matter iron accumulation in AD. The present work proposes that by compartmentalizing quantitative susceptibility into paramagnetic and diamagnetic components, more holistic information about AD pathogenesis can be acquired. Particularly, diamagnetic component susceptibility (DCS) can be a powerful indicator for tracking protein accumulation in the gray matter (GM), demyelination in the white matter (WM), and relevant changes in the cerebrospinal fluid (CSF). In the current work, voxel-wise group analysis of the WM and the CSF regions show significantly lower |DCS| (the absolute value of DCS) value for amnestic dementia patients compared to healthy controls. Additionally, |DCS| and τ PET standardized uptake value ratio (SUVr) were found to be associated in several GM regions typically affected by τ deposition in AD. Therefore, we propose that the separated diamagnetic susceptibility can be used to track pathological neurodegeneration in different tissue types and regions of the brain. With the initial evidence, we believe the usage of compartmentalized susceptibility demonstrates substantive potential as an MRI-based technique for tracking AD-driven neurodegeneration.
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- 2023
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6. A face-off of MRI research sequences by their need for de-facing
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Christopher G. Schwarz, Walter K. Kremers, Arvin Arani, Marios Savvides, Robert I. Reid, Jeffrey L. Gunter, Matthew L. Senjem, Petrice M. Cogswell, Prashanthi Vemuri, Kejal Kantarci, David S. Knopman, Ronald C. Petersen, and Clifford R. Jack, Jr.
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De-facing ,De-identification ,Face recognition ,Anonymization ,MRI ,dMRI ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
It is now widely known that research brain MRI, CT, and PET images may potentially be re-identified using face recognition, and this potential can be reduced by applying face-deidentification (“de-facing”) software. However, for research MRI sequences beyond T1-weighted (T1-w) and T2-FLAIR structural images, the potential for re-identification and quantitative effects of de-facing are both unknown, and the effects of de-facing T2-FLAIR are also unknown. In this work we examine these questions (where applicable) for T1-w, T2-w, T2*-w, T2-FLAIR, diffusion MRI (dMRI), functional MRI (fMRI), and arterial spin labelling (ASL) sequences. Among current-generation, vendor-product research-grade sequences, we found that 3D T1-w, T2-w, and T2-FLAIR were highly re-identifiable (96–98%). 2D T2-FLAIR and 3D multi-echo GRE (ME-GRE) were also moderately re-identifiable (44–45%), and our derived T2* from ME-GRE (comparable to a typical 2D T2*) matched at only 10%. Finally, diffusion, functional and ASL images were each minimally re-identifiable (0–8%). Applying de-facing with mri_reface version 0.3 reduced successful re-identification to ≤8%, while differential effects on popular quantitative pipelines for cortical volumes and thickness, white matter hyperintensities (WMH), and quantitative susceptibility mapping (QSM) measurements were all either comparable with or smaller than scan-rescan estimates. Consequently, high-quality de-facing software can greatly reduce the risk of re-identification for identifiable MRI sequences with only negligible effects on automated intracranial measurements. The current-generation echo-planar and spiral sequences (dMRI, fMRI, and ASL) each had minimal match rates, suggesting that they have a low risk of re-identification and can be shared without de-facing, but this conclusion should be re-evaluated if they are acquired without fat suppression, with a full-face scan coverage, or if newer developments reduce the current levels of artifacts and distortion around the face.
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- 2023
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7. Cross–scanner harmonization methods for structural MRI may need further work: A comparison study
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Robel K. Gebre, Matthew L. Senjem, Sheelakumari Raghavan, Christopher G. Schwarz, Jeffery L. Gunter, Ekaterina I. Hofrenning, Robert I. Reid, Kejal Kantarci, Jonathan Graff-Radford, David S. Knopman, Ronald C. Petersen, Clifford R. Jack, Jr, and Prashanthi Vemuri
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Deep learning ,Structural MRI ,Scan harmonization ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
The clinical usefulness MRI biomarkers for aging and dementia studies relies on precise brain morphological measurements; however, scanner and/or protocol variations may introduce noise or bias. One approach to address this is post-acquisition scan harmonization. In this work, we evaluate deep learning (neural style transfer, CycleGAN and CGAN), histogram matching, and statistical (ComBat and LongComBat) methods. Participants who had been scanned on both GE and Siemens scanners (cross-sectional participants, known as Crossover (n = 113), and longitudinally scanned participants on both scanners (n = 454)) were used. The goal was to match GE MPRAGE (T1-weighted) scans to Siemens improved resolution MPRAGE scans. Harmonization was performed on raw native and preprocessed (resampled, affine transformed to template space) scans. Cortical thicknesses were measured using FreeSurfer (v.7.1.1). Distributions were checked using Kolmogorov-Smirnov tests. Intra-class correlation (ICC) was used to assess the degree of agreement in the Crossover datasets and annualized percent change in cortical thickness was calculated to evaluate the Longitudinal datasets. Prior to harmonization, the least agreement was found at the frontal pole (ICC = 0.72) for the raw native scans, and at caudal anterior cingulate (0.76) and frontal pole (0.54) for the preprocessed scans. Harmonization with NST, CycleGAN, and HM improved the ICCs of the preprocessed scans at the caudal anterior cingulate (>0.81) and frontal poles (>0.67). In the Longitudinal raw native scans, over- and under-estimations of cortical thickness were observed due to the changing of the scanners. ComBat matched the cortical thickness distributions throughout but was not able to increase the ICCs or remove the effects of scanner changeover in the Longitudinal datasets. CycleGAN and NST performed slightly better to address the cortical thickness variations between scanner change. However, none of the methods succeeded in harmonizing the Longitudinal dataset. CGAN was the worst performer for both datasets. In conclusion, the performance of the methods was overall similar and region dependent. Future research is needed to improve the existing approaches since none of them outperformed each other in terms of harmonizing the datasets at all ROIs. The findings of this study establish framework for future research into the scan harmonization problem.
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- 2023
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8. Spatial patterns of elevated magnetic susceptibility in progressive apraxia of speech
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Ryota Satoh, Arvin Arani, Matthew L. Senjem, Joseph R. Duffy, Heather M. Clark, Rene L. Utianski, Hugo Botha, Mary M. Machulda, Clifford R. Jack, Jr, Jennifer L. Whitwell, and Keith A. Josephs
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Apraxia of speech ,Progressive apraxia of speech ,Magnetic resonance imaging ,Quantitative susceptibility mapping ,Iron ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Purpose: Progressive apraxia of speech (PAOS) is a neurodegenerative disorder affecting the planning or programming of speech. Little is known about its magnetic susceptibility profiles indicative of biological processes such as iron deposition and demyelination. This study aims to clarify (1) the pattern of susceptibility in PAOS patients, (2) the susceptibility differences between the phonetic (characterized by predominance of distorted sound substitutions and additions) and prosodic (characterized by predominance of slow speech rate and segmentation) subtypes of PAOS, and (3) the relationships between susceptibility and symptom severity. Methods: Twenty patients with PAOS (nine phonetic and eleven prosodic subtypes) were prospectively recruited and underwent a 3 Tesla MRI scan. They also underwent detailed speech, language, and neurological evaluations. Quantitative susceptibility maps (QSM) were reconstructed from multi-echo gradient echo MRI images. Region of interest analysis was conducted to estimate susceptibility coefficients in several subcortical and frontal regions. We compared susceptibility values between PAOS and an age-matched control group and performed a correlation analysis between susceptibilities and an apraxia of speech rating scale (ASRS) phonetic and prosodic feature ratings. Results: The magnetic susceptibility of PAOS was statistically greater than that of controls in subcortical regions (left putamen, left red nucleus, and right dentate nucleus) (p
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- 2023
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9. Face recognition from research brain PET: An unexpected PET problem
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Christopher G. Schwarz, Walter K. Kremers, Val J. Lowe, Marios Savvides, Jeffrey L. Gunter, Matthew L. Senjem, Prashanthi Vemuri, Kejal Kantarci, David S. Knopman, Ronald C. Petersen, and Clifford R. Jack, Jr.
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Face recognition ,De-facing ,De-identification ,Anonymization ,PET/CT ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
It is well known that de-identified research brain images from MRI and CT can potentially be re-identified using face recognition; however, this has not been examined for PET images. We generated face reconstruction images of 182 volunteers using amyloid, tau, and FDG PET scans, and we measured how accurately commercial face recognition software (Microsoft Azure's Face API) automatically matched them with the individual participants’ face photographs. We then compared this accuracy with the same experiments using participants’ CT and MRI. Face reconstructions from PET images from PET/CT scanners were correctly matched at rates of 42% (FDG), 35% (tau), and 32% (amyloid), while CT were matched at 78% and MRI at 97-98%. We propose that these recognition rates are high enough that research studies should consider using face de-identification (“de-facing”) software on PET images, in addition to CT and structural MRI, before data sharing. We also updated our mri_reface de-identification software with extended functionality to replace face imagery in PET and CT images. Rates of face recognition on de-faced images were reduced to 0-4% for PET, 5% for CT, and 8% for MRI. We measured the effects of de-facing on regional amyloid PET measurements from two different measurement pipelines (PETSurfer/FreeSurfer 6.0, and one in-house method based on SPM12 and ANTs), and these effects were small: ICC values between de-faced and original images were > 0.98, biases were
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- 2022
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10. Response to 'On the reproducibility of quantitative susceptibility mapping and its potential as a clinical biomarker: A comment on Cogswell et al. 2021'
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Petrice M. Cogswell, Heather J. Wiste, Stephen D. Weigand, Terry M. Therneau, and Clifford R. Jack, Jr
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Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Published
- 2022
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11. TDP-43-associated atrophy in brains with and without frontotemporal lobar degeneration
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Marina Buciuc, Peter R. Martin, Nirubol Tosakulwong, Melissa E. Murray, Leonard Petrucelli, Matthew L. Senjem, Anthony J. Spychalla, David S. Knopman, Bradley F. Boeve, Ronald C. Petersen, Joseph E. Parisi, R. Ross Reichard, Dennis W. Dickson, Clifford R. Jack, Jr., Jennifer L. Whitwell, and Keith A. Josephs
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Alzheimer’s disease ,TDP-43 ,MRI ,LATE ,Old age FTLD ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Transactive response DNA-binding protein of ∼43 kDa (TDP-43), a primary pathologic substrate in tau-negative frontotemporal lobar degeneration (FTLD), is also often found in the brains of elderly individuals without FTLD and is a key player in the process of neurodegeneration in brains with and without FTLD. It is unknown how rates and trajectories of TDP-43-associated brain atrophy compare between these two groups. Additionally, non-FTLD TDP-43 inclusions are not homogeneous and can be divided into two morphologic types: type-α and neurofibrillary tangle-associated type-β. Therefore, we explored whether neurodegeneration also varies due to the morphologic type. In this longitudinal retrospective study of 293 patients with 843 MRI scans spanning over ∼10 years, we used a Bayesian hierarchical linear model to quantify similarities and differences between the non-FTLD TDP-43 (type-α/type-β) and FTLD-TDP (n = 68) in both regional volume at various timepoints before death and annualized rate of atrophy. Since Alzheimer’s disease (AD) is a frequent co-pathology in non-FTLD TDP-43, we further divided types α/β based on presence/absence of intermediate-high likelihood AD: AD-TDP type-β (n = 90), AD-TDP type-α (n = 104), and Pure-TDP (n = 31, all type-α). FTLD-TDP was associated with faster atrophy rates in the inferior temporal lobe and temporal pole compared to all non-FTLD TDP-43 groups. The atrophy rate in the frontal lobe was modulated by age with younger FTLD-TDP having the fastest rates. Older FTLD-TDP showed a limbic predominant pattern of neurodegeneration. AD-TDP type-α showed faster rates of hippocampal atrophy and smaller volumes of amygdala, temporal pole, and inferior temporal lobe compared to AD-TDP type-β. Pure-TDP was associated with slowest rates and less atrophy in all brain regions. The results suggest that there are differences and similarities in longitudinal brain volume loss between FTLD-TDP and non-FTLD TDP-43. Within FTLD-TDP age plays a role in which brain regions are the most affected. Additionally, brain atrophy regional rates also vary by non-FTLD TDP-43 type.
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- 2022
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12. Distinct brain iron profiles associated with logopenic progressive aphasia and posterior cortical atrophy
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Neha Atulkumar Singh, Arvin Arani, Jonathan Graff-Radford, Matthew L. Senjem, Peter R. Martin, Mary M. Machulda, Christopher G. Schwarz, Yunhong Shu, Petrice M. Cogswell, David S. Knopman, Ronald C. Petersen, Val J. Lowe, Clifford R. Jack, Jr., Keith A. Josephs, and Jennifer L. Whitwell
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Quantitative susceptibility mapping ,Brain iron deposition ,Atypical Alzheimer’s disease ,Logopenic progressive aphasia ,Posterior cortical atrophy ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Quantitative susceptibility mapping (QSM) can detect iron distribution in the brain by estimating local tissue magnetic susceptibility properties at every voxel. Iron deposition patterns are well studied in typical Alzheimer’s disease (tAD), but little is known about these patterns in atypical clinical presentations of AD such as logopenic progressive aphasia (LPA) and posterior cortical atrophy (PCA). Seventeen PCA patients and eight LPA patients were recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, and underwent MRI that included a five-echo gradient echo sequence for calculation of QSM. Mean QSM signal was extracted from gray and white matter for regions-of-interest across the brain using the Mayo Clinic Adult Lifespan Template. Bayesian hierarchical models were fit per-region and per-hemisphere to compare PCA, LPA, 63 healthy controls, and 20 tAD patients. Strong evidence (posterior probability > 0.99) was observed for greater susceptibility in the middle occipital gyrus and amygdala in both LPA and PCA, and in the right inferior parietal, inferior temporal, and angular gyri in PCA and the caudate and substantia nigra in LPA compared to controls. Moderate evidence for greater susceptibility (posterior probability > 0.90) was also observed in the inferior occipital gyrus, precuneus, putamen and entorhinal cortex in both LPA and PCA, along with superior frontal gyrus in PCA and inferior temporal gyri, insula and basal ganglia in LPA, when compared to controls. Between phenotypic comparisons, LPA had greater susceptibility in the caudate, hippocampus, and posterior cingulate compared to PCA, while PCA showed greater susceptibility in the right superior frontal and middle temporal gyri compared to LPA. Both LPA and PCA showed moderate and strong evidence for greater susceptibility than tAD, particularly in medial and lateral parietal regions, while tAD showed greater susceptibility in the hippocampus and basal ganglia. This study proposes the possibility of unique iron profiles existing between LPA and PCA within cortical and subcortical structures. These changes match well with the disease-related changes of the clinical phenotypes, suggesting that QSM could be an informative candidate marker to study iron deposition in these patients.
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- 2022
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13. Relationships between β-amyloid and tau in an elderly population: An accelerated failure time modelww
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Terry M. Therneau, Ph.D., David S. Knopman, M.D., Val J. Lowe, M.D., Hugo Botha, M.B., Ch.B., Jonathan Graff-Radford, M.D., David T. Jones, M.D., Prashanthi Vemuri, Ph.D., Michelle M. Mielke, Ph.D., Christopher G. Schwarz, Ph.D., Matthew L. Senjem, M.S., Jeffrey L. Gunter, Ph.D., Ronald C. Petersen, M.D., Ph.D., and Clifford R. Jack, Jr, M.D.
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Alzheimer's disease ,Modeling ,Progression ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Using positron emission tomography (PET)-derived amyloid and tau measurements from 1,495 participants, we explore the evolution of these values over time via an accelerated failure time (AFT) model. The AFT model assumes a shared pattern of progression, but one which is shifted earlier or later in time for each individual; an individual's time shift for amyloid and for tau are assumed to be linked. The resulting pattern for each outcome consists of an earlier indolent phase followed by sharp progression of the accumulation rate. APOE ε4 shifts the amyloid curve leftward (earlier) by 6.1 years, and the tau curve leftward by 2.6 years. Female sex shifts the amyloid curve leftward by 2.4 years and the tau curve leftward by 2.6 years. Per-person shifts (i.e., the individual's deviation from the population mean) for the onset of amyloid accumulation ranged from 13 years earlier to 13 years later (10th to 90th percentile) than average and 11 years earlier to 14 years later for tau, with an estimated correlation of 0.49. The average delay between amyloid increase and tau increase was 13.3 years.
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- 2021
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14. Selecting software pipelines for change in flortaucipir SUVR: Balancing repeatability and group separation
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Christopher G. Schwarz, Terry M. Therneau, Stephen D. Weigand, Jeffrey L. Gunter, Val J. Lowe, Scott A. Przybelski, Matthew L. Senjem, Hugo Botha, Prashanthi Vemuri, Kejal Kantarci, Bradley F. Boeve, Jennifer L. Whitwell, Keith A. Josephs, Ronald C. Petersen, David S. Knopman, and Clifford R. Jack, Jr
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AV-1451 ,Flortaucipir ,Tau PET ,Partial volume correction ,PVC ,GTM ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Since tau PET tracers were introduced, investigators have quantified them using a wide variety of automated methods. As longitudinal cohort studies acquire second and third time points of serial within-person tau PET data, determining the best pipeline to measure change has become crucial. We compared a total of 415 different quantification methods (each a combination of multiple options) according to their effects on a) differences in annual SUVR change between clinical groups, and b) longitudinal measurement repeatability as measured by the error term from a linear mixed-effects model. Our comparisons used MRI and Flortaucipir scans of 97 Mayo Clinic study participants who clinically either: a) were cognitively unimpaired, or b) had cognitive impairments that were consistent with Alzheimer's disease pathology. Tested methods included cross-sectional and longitudinal variants of two overarching pipelines (FreeSurfer 6.0, and an in-house pipeline based on SPM12), three choices of target region (entorhinal, inferior temporal, and a temporal lobe meta-ROI), five types of partial volume correction (PVC) (none, two-compartment, three-compartment, geometric transfer matrix (GTM), and a tau-specific GTM variant), seven choices of reference region (cerebellar crus, cerebellar gray matter, whole cerebellum, pons, supratentorial white matter, eroded supratentorial WM, and a composite of eroded supratentorial WM, pons, and whole cerebellum), two choices of region masking (GM or GM and WM), and two choices of statistic (voxel-wise mean vs. median). Our strongest findings were: 1) larger temporal-lobe target regions greatly outperformed entorhinal cortex (median sample size estimates based on a hypothetical clinical trial were 520–526 vs. 1740); 2) longitudinal processing pipelines outperformed cross-sectional pipelines (median sample size estimates were 483 vs. 572); and 3) reference regions including supratentorial WM outperformed traditional cerebellar and pontine options (median sample size estimates were 370 vs. 559). Altogether, our results favored longitudinally SUVR methods and a temporal-lobe meta-ROI that includes adjacent (juxtacortical) WM, a composite reference region (eroded supratentorial WM + pons + whole cerebellum), 2-class voxel-based PVC, and median statistics.
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- 2021
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15. CSF dynamics as a predictor of cognitive progression
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Petrice M. Cogswell, Stephen D. Weigand, Heather J. Wiste, Jeffrey L. Gunter, Jonathan Graff-Radford, David T. Jones, Christopher G. Schwarz, Matthew L. Senjem, David S. Knopman, Ronald C. Petersen, and Clifford R. Jack, Jr
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Disproportionately enlarged subarachnoid-space hydrocephalus ,MRI ,Cognitive impairment ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Disproportionately enlarged subarachnoid-space hydrocephalus (DESH), characterized by tight high convexity CSF spaces, ventriculomegaly, and enlarged Sylvian fissures, is thought to be an indirect marker of a CSF dynamics disorder. The clinical significance of DESH with regard to cognitive decline in a community setting is not yet well defined. The goal of this work is to determine if DESH is associated with cognitive decline. Participants in the population-based Mayo Clinic Study of Aging (MCSA) who met the following criteria were included: age ≥ 65 years, 3T MRI, and diagnosis of cognitively unimpaired or mild cognitive impairment at enrollment as well as at least one follow-up visit with cognitive testing. A support vector machine based method to detect the DESH imaging features on T1-weighted MRI was used to calculate a “DESH score”, with positive scores indicating a more DESH-like imaging pattern. For the participants who were cognitively unimpaired at enrollment, a Cox proportional hazards model was fit with time defined as years from enrollment to first diagnosis of mild cognitive impairment or dementia, or as years to last known cognitively unimpaired diagnosis for those who did not progress. Linear mixed effects models were fit among all participants to estimate annual change in cognitive z scores for each domain (memory, attention, language, and visuospatial) and a global z score. For all models, covariates included age, sex, education, APOE genotype, cortical thickness, white matter hyperintensity volume, and total intracranial volume. The hazard of progression to cognitive impairment was an estimated 12% greater for a DESH score of +1 versus −1 (HR 1.12, 95% CI 0.97–1.31, p = 0.11). Global and attention cognition declined 0.015 (95% CI 0.005–0.025) and 0.016 (95% CI 0.005–0.028) z/year more, respectively, for a DESH score of +1 vs −1 (p = 0.01 and p = 0.02), with similar, though not statistically significant DESH effects in the other cognitive domains. Imaging features of disordered CSF dynamics are an independent predictor of subsequent cognitive decline in the MCSA, among other well-known factors including age, cortical thickness, and APOE status. Therefore, since DESH contributes to cognitive decline and is present in the general population, identifying individuals with DESH features may be important clinically as well as for selection in clinical trials.
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- 2021
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16. Changing the face of neuroimaging research: Comparing a new MRI de-facing technique with popular alternatives
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Christopher G. Schwarz, Walter K. Kremers, Heather J. Wiste, Jeffrey L. Gunter, Prashanthi Vemuri, Anthony J. Spychalla, Kejal Kantarci, Aaron P. Schultz, Reisa A. Sperling, David S. Knopman, Ronald C. Petersen, and Clifford R. Jack, Jr.
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Face Recognition ,De-Facing ,De-Identification ,Anonymization ,Reliability ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Recent advances in automated face recognition algorithms have increased the risk that de-identified research MRI scans may be re-identifiable by matching them to identified photographs using face recognition. A variety of software exist to de-face (remove faces from) MRI, but their ability to prevent face recognition has never been measured and their image modifications can alter automated brain measurements. In this study, we compared three popular de-facing techniques and introduce our mri_reface technique designed to minimize effects on brain measurements by replacing the face with a population average, rather than removing it. For each technique, we measured 1) how well it prevented automated face recognition (i.e. effects on exceptionally-motivated individuals) and 2) how it altered brain measurements from SPM12, FreeSurfer, and FSL (i.e. effects on the average user of de-identified data). Before de-facing, 97% of scans from a sample of 157 volunteers were correctly matched to photographs using automated face recognition. After de-facing with popular software, 28-38% of scans still retained enough data for successful automated face matching. Our proposed mri_reface had similar performance with the best existing method (fsl_deface) at preventing face recognition (28-30%) and it had the smallest effects on brain measurements in more pipelines than any other, but these differences were modest.
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- 2021
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17. Associations of quantitative susceptibility mapping with Alzheimer's disease clinical and imaging markers
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Petrice M. Cogswell, Heather J. Wiste, Matthew L. Senjem, Jeffrey L. Gunter, Stephen D. Weigand, Christopher G. Schwarz, Arvin Arani, Terry M. Therneau, Val J. Lowe, David S. Knopman, Hugo Botha, Jonathan Graff-Radford, David T. Jones, Kejal Kantarci, Prashanthi Vemuri, Bradley F Boeve, Michelle M. Mielke, Ronald C. Petersen, and Clifford R. Jack, Jr
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Quantitative susceptibility mapping ,Beta amyloid PET ,Tau PET ,Alzheimer's disease ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Altered iron metabolism has been hypothesized to be associated with Alzheimer's disease pathology, and prior work has shown associations between iron load and beta amyloid plaques. Quantitative susceptibility mapping (QSM) is a recently popularized MR technique to infer local tissue susceptibility secondary to the presence of iron as well as other minerals. Greater QSM values imply greater iron concentration in tissue. QSM has been used to study relationships between cerebral iron load and established markers of Alzheimer's disease, however relationships remain unclear. In this work we study QSM signal characteristics and associations between susceptibility measured on QSM and established clinical and imaging markers of Alzheimer's disease. The study included 421 participants (234 male, median age 70 years, range 34–97 years) from the Mayo Clinic Study of Aging and Alzheimer's Disease Research Center; 296 (70%) had a diagnosis of cognitively unimpaired, 69 (16%) mild cognitive impairment, and 56 (13%) amnestic dementia. All participants had multi-echo gradient recalled echo imaging, PiB amyloid PET, and Tauvid tau PET. Variance components analysis showed that variation in cortical susceptibility across participants was low. Linear regression models were fit to assess associations with regional susceptibility. Expected increases in susceptibility were found with older age and cognitive impairment in the deep and inferior gray nuclei (pallidum, putamen, substantia nigra, subthalamic nucleus) (betas: 0.0017 to 0.0053 ppm for a 10 year increase in age, p = 0.03 to
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- 2021
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18. Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease
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Aylin Dincer, Brian A. Gordon, Amrita Hari-Raj, Sarah J. Keefe, Shaney Flores, Nicole S. McKay, Angela M. Paulick, Kristine E. Shady Lewis, Rebecca L. Feldman, Russ C. Hornbeck, Ricardo Allegri, Beau M. Ances, Sarah B. Berman, Adam M. Brickman, William S. Brooks, David M. Cash, Jasmeer P. Chhatwal, Martin R. Farlow, Christian la Fougère, Nick C. Fox, Michael J. Fulham, Clifford R. Jack, Jr., Nelly Joseph-Mathurin, Celeste M. Karch, Athene Lee, Johannes Levin, Colin L. Masters, Eric M. McDade, Hwamee Oh, Richard J. Perrin, Cyrus Raji, Stephen P. Salloway, Peter R. Schofield, Yi Su, Victor L. Villemagne, Qing Wang, Michael W. Weiner, Chengjie Xiong, Igor Yakushev, John C. Morris, Randall J. Bateman, and Tammie L.S. Benzinger
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Alzheimer disease ,Autosomal dominant Alzheimer disease ,Preclinical ,Cortical signature ,Amyloid ,Cortical thickness ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals.We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir.To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume.We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.
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- 2020
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19. 18F-FDG PET-CT pattern in idiopathic normal pressure hydrocephalus
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Ryan A. Townley, Hugo Botha, Jonathan Graff-Radford, Bradley F. Boeve, Ronald C. Petersen, Matthew L. Senjem, David S. Knopman, Val Lowe, Clifford R. Jack, Jr, and David T. Jones
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Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Background: Idiopathic normal pressure hydrocephalus (iNPH) is an important and treatable cause of neurologic impairment. Diagnosis is complicated due to symptoms overlapping with other age related disorders. The pathophysiology underlying iNPH is not well understood. We explored FDG-PET abnormalities in iNPH patients in order to determine if FDG-PET may serve as a biomarker to differentiate iNPH from common neurodegenerative disorders. Methods: We retrospectively compared 18F-FDG PET-CT imaging patterns from seven iNPH patients (mean age 74 ± 6 years) to age and sex matched controls, as well as patients diagnosed with clinical Alzheimer's disease dementia (AD), Dementia with Lewy Bodies (DLB) and Parkinson's Disease Dementia (PDD), and behavioral variant frontotemporal dementia (bvFTD). Partial volume corrected and uncorrected images were reviewed separately. Results: Patients with iNPH, when compared to controls, AD, DLB/PDD, and bvFTD, had significant regional hypometabolism in the dorsal striatum, involving the caudate and putamen bilaterally. These results remained highly significant after partial volume correction. Conclusions: In this study, we report a FDG-PET pattern of hypometabolism in iNPH involving the caudate and putamen with preserved cortical metabolism. This pattern may differentiate iNPH from degenerative diseases and has the potential to serve as a biomarker for iNPH in future studies. These findings also further our understanding of the pathophysiology underlying the iNPH clinical presentation. Keywords: FDG-PET, Normal pressure hydrocephalus, Hypometabolism, Caudate, Biomarker
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- 2018
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20. Disrupted functional connectivity in primary progressive apraxia of speech
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Hugo Botha, Rene L. Utianski, Jennifer L. Whitwell, Joseph R. Duffy, Heather M. Clark, Edythe A. Strand, Mary M. Machulda, Nirubol Tosakulwong, David S. Knopman, Ronald C. Petersen, Clifford R. Jack, Jr, Keith A. Josephs, and David T. Jones
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Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Apraxia of speech is a motor speech disorder thought to result from impaired planning or programming of articulatory movements. It can be the initial or only manifestation of a degenerative disease, termed primary progressive apraxia of speech (PPAOS). The aim of this study was to use task-free functional magnetic resonance imaging (fMRI) to assess large-scale brain network pathophysiology in PPAOS. Twenty-two PPAOS participants were identified from a prospective cohort of degenerative speech and language disorders patients. All participants had a comprehensive, standardized evaluation including an evaluation by a speech-language pathologist, examination by a behavioral neurologist and a multimodal imaging protocol which included a task-free fMRI sequence. PPAOS participants were age and sex matched to amyloid-negative, cognitively normal participants with a 1:2 ratio. We chose a set of hypothesis driven, predefined intrinsic connectivity networks (ICNs) from a large, out of sample independent component analysis and then used them to initialize a spatiotemporal dual regression to estimate participant level connectivity within these ICNs. Specifically, we evaluated connectivity within the speech and language, face and hand sensorimotor, left working memory, salience, superior parietal, supramarginal, insular and deep gray ICNs in a multivariate manner. The spatial maps for each ICN were then compared between PPAOS and control participants. We used clinical measures of apraxia of speech severity to assess for clinical-connectivity correlations for regions found to differ between PPAOS and control participants. Compared to controls, PPAOS participants had reduced connectivity of the right supplementary motor area and left posterior temporal gyrus to the rest of the speech and language ICN. The connectivity of the right supplementary motor area correlated negatively with an articulatory error score. PPAOS participants also had reduced connectivity of the left supplementary motor area to the face sensorimotor ICN, between the left lateral prefrontal cortex and the salience ICN and between the left temporal-occipital junction and the left working memory ICN. The latter connectivity correlated with the apraxia of speech severity rating scale, although the finding did not survive correction for multiple comparisons. Increased connectivity was noted in PPAOS participants between the dorsal posterior cingulate and the left working memory ICN. Our results support the importance of the supplementary motor area in the pathophysiology of PPAOS, which appears to be disconnected from speech and language regions. Supplementary motor area connectivity may serve as a biomarker of degenerative apraxia of speech severity. Keywords: Apraxia of speech, Functional connectivity, Intrinsic connectivity networks
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- 2018
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21. Comparison of [18F]Flutemetamol and [11C]Pittsburgh Compound-B in cognitively normal young, cognitively normal elderly, and Alzheimer's disease dementia individuals
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Val J. Lowe, Emily Lundt, David Knopman, Matthew L. Senjem, Jeffrey L. Gunter, Christopher G. Schwarz, Bradley J. Kemp, Clifford R. Jack, Jr, and Ronald C. Petersen
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Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Background: Understanding the variation in uptake between different amyloid PET tracers is important to appropriately interpret data using different amyloid tracers. Therefore, we compared the uptake differences in [18F]Flutemetamol (FMT) and [11C]PiB (PiB) PET in the same people. Methods: Structural MRI, FMT PET and PiB PET were each performed in 30 young cognitively normal (yCN), 31 elderly cognitively normal (eCN) and 21 Alzheimer's disease dementia (AD) participants. PiB and FMT images for each participant were compared quantitatively using voxel- and region-based analyses. Region of interest (ROI) analyses included comparisons of grey matter (GM) regions as well as white matter (WM) regions. Regional comparisons of each tracer between different groups and comparisons of the two modalities within the different groups were performed. To compare mean SUVr between modalities, and between diagnostic groups, we used paired t-tests and Student's t-test, respectively. We also compared the ability of the two tracers to discriminate between diagnostic groups using AUROC estimates. The effect of using different normalization regions on SUVr values was also evaluated. Results: Both FMT and PiB showed greater uptake throughout GM structures in AD vs. eCN or yCN. In all dual-modality group comparisons (FMT vs. PiB in yCN, eCN, and AD), greater WM uptake was seen with FMT vs. PiB. In yCN and eCN greater diffuse GM uptake was seen with FMT vs. PiB. When comparing yCN to eCN within each tracer, greater WM uptake was seen in eCN vs yCN. Conclusions: Flutemetamol and PiB show similar topographical GM uptake in AD and CN participants and the tracers show comparable group discrimination. Greater WM accumulation with FMT suggests that quantitative differences vs. PiB will be apparent when using WM or GM as a reference region. Both imaging tracers demonstrate increased WM uptake in older people. These findings suggest that using different amyloid tracers or different methods of analyses in serial brain imaging in an individual may result in artifactual amyloid change measurements. Clinical use of several amyloid tracers in the same patient will have challenges that need to be carefully considered.
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- 2017
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22. Longitudinal tau-PET uptake and atrophy in atypical Alzheimer's disease
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Irene Sintini, Peter R. Martin, Jonathan Graff-Radford, Matthew L. Senjem, Christopher G. Schwarz, Mary M. Machulda, Anthony J. Spychalla, Daniel A. Drubach, David S. Knopman, Ronald C. Petersen, Val J. Lowe, Clifford R. Jack, Jr, Keith A. Josephs, and Jennifer L. Whitwell
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Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
The aims of this study were: to examine regional rates of change in tau-PET uptake and grey matter volume in atypical Alzheimer's disease (AD); to investigate the role of age in such changes; to describe multimodal regional relationships between tau accumulation and atrophy. Thirty atypical AD patients underwent baseline and one-year follow-up MRI, [18F]AV-1451 PET and PiB PET. Region- and voxel-level rates of tau accumulation and grey matter atrophy relative to cognitively unimpaired individuals, and the influence of age on such rates, were assessed. Univariate and multivariate analyses were performed between baseline measurements and rates of change, between baseline tau and atrophy, and between the two rates of change. Regional patterns of change in tau and volume differed, with highest rates of tau accumulation in frontal lobe and highest rates of atrophy in temporoparietal regions. Age had a negative effect on disease progression, predominantly on tau, with younger patients having a more rapid accumulation. Baseline tau uptake and regions of tau accumulation were disconnected, with high baseline tau uptake across the cortex correlated with high rates of tau accumulation in frontal and sensorimotor regions. In contrast, baseline volume and atrophy were locally related in the occipitoparietal regions. Higher tau uptake at baseline was locally related to higher rates of atrophy in frontal and occipital lobes. Tau accumulation rates positively correlated with rates of atrophy. In summary, our study showed that tau accumulation and atrophy presented different regional patterns in atypical AD, with tau spreading into the frontal lobes while atrophy remains in temporoparietal and occipital cortex, suggesting a temporal disconnect between protein deposition and neurodegeneration. Keywords: Longitudinal tau-PET, Atrophy, Atypical AD, Multimodal imaging
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- 2019
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23. Automated detection of imaging features of disproportionately enlarged subarachnoid space hydrocephalus using machine learning methods
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Nathaniel B. Gunter, Christopher G. Schwarz, Jonathan Graff-Radford, Jeffrey L. Gunter, David T. Jones, Neill R. Graff-Radford, Ronald C. Petersen, David S. Knopman, and Clifford R. Jack, Jr.
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Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Objective: Create an automated classifier for imaging characteristics of disproportionately enlarged subarachnoid space hydrocephalus (DESH), a neuroimaging phenotype of idiopathic normal pressure hydrocephalus (iNPH). Methods: 1597 patients from the Mayo Clinic Study of Aging (MCSA) were reviewed for imaging characteristics of DESH. One core feature of DESH, the presence of tightened sulci in the high-convexities (THC), was used as a surrogate for the presence of DESH as the expert clinician-defined criterion on which the classifier was trained. Anatomical MRI scans were automatically segmented for cerebrospinal fluid (CSF) and overlaid with an atlas of 123 named sulcal regions. The volume of CSF in each sulcal region was summed and normalized to total intracranial volume. Area under the receiver operating characteristic curve (AUROC) values were computed for each region individually, and these values determined feature selection for the machine learning model. Due to class imbalance in the data (72 selected scans out of 1597 total scans) adaptive synthetic sampling (a technique which generates synthetic examples based on the original data points) was used to balance the data. A support vector machine model was then trained on the regions selected. Results: Using the automated classification model, we were able to classify scans for tightened sulci in the high convexities, as defined by the expert clinician, with an AUROC of about 0.99 (false negative ≈ 2%, false positive ≈ 5%). Ventricular volumes were among the classifier's most discriminative features but are not specific for DESH. The inclusion of regions outside the ventricles allowed specificity from atrophic neurodegenerative diseases that are also accompanied by ventricular enlargement. Conclusion: Automated detection of tight high convexity, a key imaging feature of DESH, is possible by using support vector machine models with selected sulcal CSF volumes as features. Keywords: Normal pressure ydrocephalus, Disproportionately enlarged subarachnoid hydrocephalus, Support vector machines, Computer-aided diagnosis, Tight high-convexity
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- 2019
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24. ApoE4 effects on automated diagnostic classifiers for mild cognitive impairment and Alzheimer's disease
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Liana G. Apostolova, Kristy S. Hwang, Omid Kohannim, David Avila, David Elashoff, Clifford R. Jack, Jr., Leslie Shaw, John Q. Trojanowski, Michael W. Weiner, and Paul M. Thompson
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Alzheimer's disease ,Abeta ,Tau ,Hippocampus atrophy ,ADNI ,Diagnosis ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Biomarkers are the only feasible way to detect and monitor presymptomatic Alzheimer's disease (AD). No single biomarker can predict future cognitive decline with an acceptable level of accuracy. In addition to designing powerful multimodal diagnostic platforms, a careful investigation of the major sources of disease heterogeneity and their influence on biomarker changes is needed. Here we investigated the accuracy of a novel multimodal biomarker classifier for differentiating cognitively normal (NC), mild cognitive impairment (MCI) and AD subjects with and without stratification by ApoE4 genotype. 111 NC, 182 MCI and 95 AD ADNI participants provided both structural MRI and CSF data at baseline. We used an automated machine-learning classifier to test the ability of hippocampal volume and CSF Aβ, t-tau and p-tau levels, both separately and in combination, to differentiate NC, MCI and AD subjects, and predict conversion. We hypothesized that the combined hippocampal/CSF biomarker classifier model would achieve the highest accuracy in differentiating between the three diagnostic groups and that ApoE4 genotype will affect both diagnostic accuracy and biomarker selection. The combined hippocampal/CSF classifier performed better than hippocampus-only classifier in differentiating NC from MCI and NC from AD. It also outperformed the CSF-only classifier in differentiating NC vs. AD. Our amyloid marker played a role in discriminating NC from MCI or AD but not for MCI vs. AD. Neurodegenerative markers contributed to accurate discrimination of AD from NC and MCI but not NC from MCI. Classifiers predicting MCI conversion performed well only after ApoE4 stratification. Hippocampal volume and sex achieved AUC = 0.68 for predicting conversion in the ApoE4-positive MCI, while CSF p-tau, education and sex achieved AUC = 0.89 for predicting conversion in ApoE4-negative MCI. These observations support the proposed biomarker trajectory in AD, which postulates that amyloid markers become abnormal early in the disease course while markers of neurodegeneration become abnormal later in the disease course and suggests that ApoE4 could be at least partially responsible for some of the observed disease heterogeneity.
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- 2014
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25. Molecular Targeting of Alzheimer's Amyloid Plaques for Contrast-Enhanced Magnetic Resonance Imaging
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Joseph F. Poduslo, Thomas M. Wengenack, Geoffry L. Curran, Thomas Wisniewski, Einar M. Sigurdsson, Slobodon I. Macura, Bret J. Borowski, and Clifford R. Jack, Jr.
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Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Smart molecular probes for both diagnostic and therapeutic purposes are expected to provide significant advances in clinical medicine and biomedical research. We describe such a probe that targets β-amyloid plaques of Alzheimer's disease and is detectable by magnetic resonance imaging (MRI) because of contrast imparted by gadolinium labeling. Three properties essential for contrast enhancement of β-amyloid plaques on MRI exist in this smart molecular probe, putrescine–gadolinium–amyloid-β peptide: (1) transport across the blood–brain barrier following intravenous injection conferred by the polyamine moiety, (2) binding to plaques with molecular specificity by putrescine–amyloid-β, and (3) magnetic resonance imaging contrast by gadolinium. MRI was performed on ex vivo tissue specimens at 7 T at a spatial resolution approximating plaque size (62.5 μm3), in order to prove the concept that the probe, when administered intravenously, can selectively enhance plaques. The plaque-to-background tissue contrast-to-noise ratio, which was precisely correlated with histologically stained plaques, was enhanced more than nine-fold in regions of cortex and hippocampus following intravenous administration of this probe in AD transgenic mice. Continuing engineering efforts to improve spatial resolution are underway in MRI, which may enable in vivo imaging at the resolution of individual plaques with this or similar contrast probes. This could enable early diagnosis and also provide a direct measure of the efficacy of anti-amyloid therapies currently being developed.
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- 2002
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26. Spectral graph theory and graph energy metrics show evidence for the alzheimer's disease disconnection syndrome in APOE-4 risk gene carriers.
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Madelaine Daianu, Adam Mezher, Neda Jahanshad, Derrek P. Hibar, Talia M. Nir, Clifford R. Jack Jr., Michael W. Weiner, Matt A. Bernstein, and Paul M. Thompson
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- 2015
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27. Power Estimates for Voxel-Based Genetic Association Studies Using Diffusion Imaging.
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Neda Jahanshad, Peter V. Kochunov, David C. Glahn, John Blangero, Thomas E. Nichols, Katie L. McMahon, Greig I. de Zubicaray, Nicholas G. Martin, Margaret J. Wright, Clifford R. Jack Jr., Matt A. Bernstein, Michael W. Weiner, Arthur W. Toga, and Paul M. Thompson
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- 2013
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28. Disrupted Brain Connectivity in Alzheimer's Disease: Effects of Network Thresholding.
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Madelaine Daianu, Emily L. Dennis, Neda Jahanshad, Talia M. Nir, Arthur W. Toga, Clifford R. Jack Jr., Michael W. Weiner, and Paul M. Thompson
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- 2013
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29. Bivariate Genome-Wide Association Study of Genetically Correlated Neuroimaging Phenotypes from DTI and MRI through a Seemingly Unrelated Regression Model.
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Neda Jahanshad, Priya Bhatt, Derrek P. Hibar, Julio Villalon, Talia M. Nir, Arthur W. Toga, Clifford R. Jack Jr., Matt A. Bernstein, Michael W. Weiner, Katie McMahon, Greig I. de Zubicaray, Nicholas G. Martin, Margaret J. Wright, and Paul M. Thompson
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- 2013
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30. Mapping Dynamic Changes in Ventricular Volume onto Baseline Cortical Surfaces in Normal Aging, MCI, and Alzheimer's Disease.
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Sarah K. Madsen, Boris Gutman, Shantanu H. Joshi, Arthur W. Toga, Clifford R. Jack Jr., Michael W. Weiner, and Paul M. Thompson
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- 2013
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31. Understanding atrophy trajectories in alzheimer's disease using association rules on MRI images.
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György J. Simon, Peter W. Li, Clifford R. Jack Jr., and Prashanthi Vemuri
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- 2011
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32. Tau Polygenic Risk Scoring: a Cost-Effective Aid for Prognostic Counseling in Alzheimer’s Disease
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Vijay K. Ramanan, Michael G. Heckman, Timothy G. Lesnick, Scott A. Przybelski, Elliot J. Cahn, Matthew L. Kosel, Melissa E. Murray, Michelle M. Mielke, Hugo Botha, Jonathan Graff-Radford, David T. Jones, Val J. Lowe, Mary M. Machulda, Clifford R. Jack Jr, David S. Knopman, Ronald C. Petersen, Owen A. Ross, and Prashanthi Vemuri
- Subjects
Counseling ,Cellular and Molecular Neuroscience ,Amyloid ,Alzheimer Disease ,Cost-Benefit Analysis ,Apolipoprotein E4 ,Humans ,tau Proteins ,Neurology (clinical) ,Prognosis ,Article ,Pathology and Forensic Medicine ,Aged - Abstract
Tau deposition is one of two hallmark features of biologically defined Alzheimer's disease (AD) and is more closely related to cognitive decline than amyloidosis. Further, not all amyloid-positive individuals develop tauopathy, resulting in wide heterogeneity in clinical outcomes across the population with AD. We hypothesized that a polygenic risk score (PRS) based on tau PET (tau PRS) would capture the aggregate inherited susceptibility/resistance architecture influencing tau accumulation, beyond solely the measurement of amyloid-β burden. Leveraging rich multimodal data from a population-based sample of older adults, we found that this novel tau PRS was a strong surrogate of tau PET deposition and captured a significant proportion of the variance in tau PET levels as compared with amyloid PET burden, APOE (apolipoprotein E) ε4 (the most common risk allele for AD), and a non-APOE PRS of clinical case-control AD risk variants. In independent validation samples, the tau PRS was associated with cerebrospinal fluid phosphorylated tau levels in one cohort and with postmortem Braak neurofibrillary tangle stage in another. We also observed an association of the tau PRS with longitudinal cognitive trajectories, including a statistical interaction of the tau PRS with amyloid burden on cognitive decline. Although additional study is warranted, these findings demonstrate the potential utility of a tau PRS for capturing the collective genetic background influencing tau deposition in the general population. In the future, a tau PRS could be leveraged for cost-effective screening and risk stratification to guide trial enrollment and clinical interventions in AD.
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- 2022
33. Causal Structure Discovery Identifies Risk Factors and Early Brain Markers Related to Evolution of White Matter Hyperintensities
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Xinpeng Shen, Sheelakumari Raghavan, Scott A. Przybelski, Timothy G. Lesnick, Sisi Ma, Robert I. Reid, Jonathan Graff-Radford, Michelle M. Mielke, David S. Knopman, Ronald C. Petersen, Clifford R. Jack Jr., György J. Simon, and Prashanthi Vemuri
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Adult ,Aged, 80 and over ,Cognitive Neuroscience ,Brain ,Middle Aged ,Magnetic Resonance Imaging ,White Matter ,Diffusion Tensor Imaging ,Neurology ,Risk Factors ,Hypertension ,Humans ,Radiology, Nuclear Medicine and imaging ,Female ,Neurology (clinical) ,Biomarkers ,Aged - Abstract
Our goal was to understand the complex relationship between age, sex, midlife risk factors, and early white matter changes measured by diffusion tensor imaging (DTI) and their role in the evolution of longitudinal white matter hyperintensities (WMH). We identified 1564 participants (1396 cognitively unimpaired, 151 mild cognitive impairment and 17 dementia participants) with age ranges of 30-90 years from the population-based sample of Mayo Clinic Study of Aging. We used computational causal structure discovery and regression analyses to evaluate the predictors of WMH and DTI, and to ascertain the mediating effect of DTI on WMH. We further derived causal graphs to understand the complex interrelationships between midlife protective factors, vascular risk factors, diffusion changes, and WMH. Older age, female sex, and hypertension were associated with higher baseline and progression of WMH as well as DTI measures (P ≤ 0.003). The effects of hypertension and sex on WMH were partially mediated by microstructural changes measured on DTI. Higher midlife physical activity was predictive of lower WMH through a direct impact on better white matter tract integrity as well as an indirect effect through reducing the risk of hypertension by lowering BMI. This study identified key risks factors, early brain changes, and pathways that may lead to the evolution of WMH.
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- 2022
34. Differential effect of dementia etiology on cortical stiffness as assessed by MR elastography
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KowsalyaDevi Pavuluri, Jonathan M. Scott, John Huston III, Richard L. Ehman, Armando Manduca, Clifford R. Jack Jr, Rodolfo Savica, Bradley F. Boeve, Kejal Kantarci, Ronald C. Petersen, David S. Knopman, and Matthew C. Murphy
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Neurology ,Cognitive Neuroscience ,Radiology, Nuclear Medicine and imaging ,Neurology (clinical) - Published
- 2023
35. Practical algorithms for amyloid β probability in subjective or mild cognitive impairment
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Nancy Maserejian, Shijia Bian, Wenting Wang, Judith Jaeger, Jeremy A. Syrjanen, Jeremiah Aakre, Clifford R. Jack Jr., Michelle M. Mielke, Feng Gao, and Alzheimer's Disease Neuroimaging Initiative and the AIBL research team
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Amyloid ,Population ,Decision tree ,Feature selection ,Disease ,lcsh:Geriatrics ,AIBL ,lcsh:RC346-429 ,03 medical and health sciences ,Diagnostic Assessment and Prognosis ,0302 clinical medicine ,Neuroimaging ,ADNI ,Medicine ,MCSA ,Cognitive decline ,education ,lcsh:Neurology. Diseases of the nervous system ,030304 developmental biology ,0303 health sciences ,education.field_of_study ,Recall ,business.industry ,Biomarker ,Alzheimer's disease ,Immediate recall ,Algorithm ,lcsh:RC952-954.6 ,Psychiatry and Mental health ,APOE ε4 ,Biomarker (medicine) ,Neurology (clinical) ,business ,030217 neurology & neurosurgery - Abstract
Introduction Practical algorithms predicting the probability of amyloid pathology among patients with subjective cognitive decline or mild cognitive impairment may help clinical decisions regarding confirmatory biomarker testing for Alzheimer's disease. Methods Algorithm feature selection was conducted with Alzheimer's Disease Neuroimaging Initiative and Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing data. Probability algorithms were developed in Alzheimer's Disease Neuroimaging Initiative using nested cross-validation accompanied by stratified subsampling to obtain 1000 internally validated decision trees. Semi-independent validation was conducted using Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing. Independent external validation was conducted in the population-based Mayo Clinic Study of Aging. Results Two algorithms were developed using age and normalized immediate recall z-scores, with or without apolipoprotein E e4 carrier status. Both algorithms had robust performance across data sets and when substituting different recall memory tests. Discussion The statistical framework resulted in robust probability estimation. Application of these algorithms may assist in clinical decision-making for further testing to diagnose amyloid pathology.
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- 2019
36. Deep learning identifies brain structures that predict cognition and explain heterogeneity in cognitive aging
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Krishnakant V. Saboo, Chang Hu, Yogatheesan Varatharajah, Scott A. Przybelski, Robert I. Reid, Christopher G. Schwarz, Jonathan Graff-Radford, David S. Knopman, Mary M. Machulda, Michelle M. Mielke, Ronald C. Petersen, Paul M. Arnold, Gregory A. Worrell, David T. Jones, Clifford R. Jack Jr, Ravishankar K. Iyer, and Prashanthi Vemuri
- Subjects
Aging ,Cognition ,Deep Learning ,Neurology ,Cognitive Aging ,Cognitive Neuroscience ,Brain ,Humans ,Cognitive Dysfunction ,Magnetic Resonance Imaging ,Aged - Abstract
Specific brain structures (gray matter regions and white matter tracts) play a dominant role in determining cognitive decline and explain the heterogeneity in cognitive aging. Identification of these structures is crucial for screening of older adults at risk of cognitive decline. Using deep learning models augmented with a model-interpretation technique on data from 1432 Mayo Clinic Study of Aging participants, we identified a subset of brain structures that were most predictive of individualized cognitive trajectories and indicative of cognitively resilient vs. vulnerable individuals. Specifically, these structures explained why some participants were resilient to the deleterious effects of elevated brain amyloid and poor vascular health. Of these, medial temporal lobe and fornix, reflective of age and pathology-related degeneration, and corpus callosum, reflective of inter-hemispheric disconnection, accounted for 60% of the heterogeneity explained by the most predictive structures. Our results are valuable for identifying cognitively vulnerable individuals and for developing interventions for cognitive decline.
- Published
- 2021
37. Amyloid-PET and ¹⁸F-FDG-PET in the diagnostic investigation of Alzheimer's disease and other dementia
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Gaël Chételat, Javier Arbizu, Henryk Barthel, Valentina Garibotto, Ian Law, Silvia Morbelli, Elsmarieke van de Giessen, Federica Agosta, Frederik Barkhof, David J Brooks, Maria C Carrillo, Bruno Dubois, Anders M Fjell, Giovanni B Frisoni, Oskar Hansson, Karl Herholz, Brian F Hutton, Clifford R Jack Jr, Adriaan A Lammertsma, Susan M Landau, Satoshi Minoshima, Flavio Nobili, Agneta Nordberg, Rik Ossenkoppele, Wim J G Oyen, Daniela Perani, Gil D Rabinovici, Philip Scheltens, Victor L Villemagne, Henrik Zetterberg, and Alexander Drzezga
- Abstract
Various biomarkers are available to support the diagnosis of neurodegenerative diseases in clinical and research settings. Among the molecular imaging biomarkers, amyloid-PET, which assesses brain amyloid deposition, and18F-fluorodeoxyglucose (18F-FDG) PET, which assesses glucose metabolism, provide valuable and complementary information. However, uncertainty remains regarding the optimal timepoint, combination, and an order in which these PET biomarkers should be used in diagnostic evaluations because conclusive evidence is missing. Following an expert panel discussion, we reached an agreement on the specific use of the individual biomarkers, based on available evidence and clinical expertise. We propose a diagnostic algorithm with optimal timepoints for these PET biomarkers, also taking into account evidence from other biomarkers, for early and differential diagnosis of neurodegenerative diseases that can lead to dementia. We propose three main diagnostic pathways with distinct biomarker sequences, in which amyloid-PET and18F-FDG-PET are placed at different positions in the order of diagnostic evaluations, depending on clinical presentation. We hope that this algorithm can support diagnostic decision making in specialist clinical settings with access to these biomarkers and might stimulate further research towards optimal diagnostic strategies.
- Published
- 2020
38. Utility of perfusion PET measures to assess neuronal injury in Alzheimer's disease
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Nelly Joseph‐Mathurin, Yi Su, Tyler M. Blazey, Mateusz Jasielec, Andrei Vlassenko, Karl Friedrichsen, Brian A. Gordon, Russ C. Hornbeck, Lisa Cash, Beau M. Ances, Thomas Veale, David M. Cash, Adam M. Brickman, Virginia Buckles, Nigel J. Cairns, Carlos Cruchaga, Alison Goate, Clifford R. Jack Jr., Celeste Karch, William Klunk, Robert A. Koeppe, Daniel S. Marcus, Richard Mayeux, Eric McDade, James M. Noble, John Ringman, Andrew J. Saykin, Paul M. Thompson, Chengjie Xiong, John C. Morris, Randall J. Bateman, Tammie L.S. Benzinger, and Dominantly Inherited Alzheimer Network
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FDG ,PiB ,Neuroimaging ,Perfusion scanning ,Disease ,lcsh:Geriatrics ,lcsh:RC346-429 ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,Neuronal injury ,0302 clinical medicine ,medicine ,Dementia ,lcsh:Neurology. Diseases of the nervous system ,medicine.diagnostic_test ,business.industry ,Disease progression ,Alzheimer's disease ,medicine.disease ,3. Good health ,Perfusion ,Radiation exposure ,lcsh:RC952-954.6 ,Psychiatry and Mental health ,Positron emission tomography ,Neurology (clinical) ,Nuclear medicine ,business ,030217 neurology & neurosurgery - Abstract
Introduction 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is commonly used to estimate neuronal injury in Alzheimer's disease (AD). Here, we evaluate the utility of dynamic PET measures of perfusion using 11 C-Pittsburgh compound B (PiB) to estimate neuronal injury in comparison to FDG PET. Methods FDG, early frames of PiB images, and relative PiB delivery rate constants (PiB-R1) were obtained from 110 participants from the Dominantly Inherited Alzheimer Network. Voxelwise, regional cross-sectional, and longitudinal analyses were done to evaluate the correlation between images and estimate the relationship of the imaging biomarkers with estimated time to disease progression based on family history. Results Metabolism and perfusion images were spatially correlated. Regional PiB-R1 values and FDG, but not early frames of PiB images, significantly decreased in the mutation carriers with estimated year to onset and with increasing dementia severity. Discussion Hypometabolism estimated by PiB-R1 may provide a measure of brain perfusion without increasing radiation exposure.
- Published
- 2018
39. Full 3D Rigid Body Automatic Motion Correction of MRI Images.
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Yi Su, Armando Manduca, Clifford R. Jack Jr., E. Brian Welch, and Richard L. Ehman
- Published
- 2001
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40. Spherical Navigator Echoes for Full 3-D Rigid Body Motion Measurement in MRI.
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E. Brian Welch, Armando Manduca, Roger C. Grimm, Heidi A. Ward, and Clifford R. Jack Jr.
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- 2001
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41. Relationship Between Risk Factors and Brain Reserve in Late Middle Age: Implications for Cognitive Aging
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Bryan J. Neth, Jonathan Graff-Radford, Michelle M. Mielke, Scott A. Przybelski, Timothy G. Lesnick, Christopher G. Schwarz, Robert I. Reid, Matthew L. Senjem, Val J. Lowe, Mary M. Machulda, Ronald C. Petersen, Clifford R. Jack Jr., David S. Knopman, and Prashanthi Vemuri
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0301 basic medicine ,Aging ,Cognitive Neuroscience ,Population ,multimodal imaging ,Corpus callosum ,lcsh:RC321-571 ,03 medical and health sciences ,0302 clinical medicine ,brain reserve ,Neuroimaging ,Fractional anisotropy ,Medicine ,Effects of sleep deprivation on cognitive performance ,education ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,resilience ,Cognitive reserve ,Original Research ,2. Zero hunger ,education.field_of_study ,dynamic ,business.industry ,cognitive aging ,Cognition ,030104 developmental biology ,Posterior cingulate ,business ,030217 neurology & neurosurgery ,Clinical psychology ,Neuroscience - Abstract
Background Brain reserve can be defined as the individual variation in the brain structural characteristics that later in life are likely to modulate cognitive performance. Late midlife represents a point in aging where some structural brain imaging changes have become manifest but the effects of cognitive aging are minimal, and thus may represent an ideal opportunity to determine the relationship between risk factors and brain imaging biomarkers of reserve. Objective We aimed to assess neuroimaging measures from multiple modalities to broaden our understanding of brain reserve, and the late midlife risk factors that may make the brain vulnerable to age related cognitive disorders. Methods We examined multimodal [structural and diffusion Magnetic Resonance Imaging (MRI), FDG PET] neuroimaging measures in 50-65 year olds to examine the associations between risk factors (Intellectual/Physical Activity: education-occupation composite, physical, and cognitive-based activity engagement; General Health Factors: presence of cardiovascular and metabolic conditions (CMC), body mass index, hemoglobin A1c, smoking status (ever/never), CAGE Alcohol Questionnaire (>2, yes/no), Beck Depression Inventory score), brain reserve measures [Dynamic: genu corpus callosum fractional anisotropy (FA), posterior cingulate cortex FDG uptake, superior parietal cortex thickness, AD signature cortical thickness; Static: intracranial volume], and cognition (global, memory, attention, language, visuospatial) from a population-based sample. We quantified dynamic proxies of brain reserve (cortical thickness, glucose metabolism, microstructural integrity) and investigated various protective/risk factors. Results Education-occupation was associated with cognition and total intracranial volume (static measure of brain reserve), but was not associated with any of the dynamic neuroimaging biomarkers. In contrast, many general health factors were associated with the dynamic neuroimaging proxies of brain reserve, while most were not associated with cognition in this late middle aged group. Conclusion Brain reserve, as exemplified by the four dynamic neuroimaging features studied here, is itself at least partly influenced by general health status in midlife, but may be largely independent of education and occupation.
- Published
- 2019
42. Population-Based Prevalence of Infarctions on 3D Fluid-Attenuated Inversion Recovery (FLAIR) Imaging.
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Cogswell, Petrice M., Aakre, Jeremiah A., Castillo, Anna M., Knopman, David S., Kantarci, Kejal, Rabinstein, Alejandro A., Petersen, Ronald C., Jack, Clifford R., Mielke, Michelle M., Vemuri, Prashanthi, Graff-Radford, Jonathan, Clifford, R Jack Jr, and Jack, Clifford R Jr
- Abstract
Objectives: To report population-based, age-specific prevalence of infarctions as identified via 3D fluid-attenuated inversion recovery (FLAIR) imaging.Materials and Methods: Participants without dementia in the Mayo Clinic Study of Aging (MCSA), a population-based study in Olmsted County, MN, age 50-89 who underwent 3D FLAIR imaging between 2017 and 2020 were included. Infarctions per participant were determined via visual interpretation. Inter- and intra-reader reliability were calculated. Infarction prevalence on 3D FLAIR was derived by standardization to the Olmsted County population and was compared to that previously reported on 2D FLAIR imaging.Results: Among 580 participants (mean age 71 years, 46% female) the prevalence (95% confidence interval) of any infarction was 5.0% (0.0%-9.9%) at age 50-59 years and 38.8% (28.6%-49.0%) at 80-89 years. In addition to increasing with age, the prevalence varied by sex and type of infarction. Prevalence estimates of cortical infarcts were 0.9% (0.0%-2.7%) at age 50-59 years and 20.2% (10.7%-29.7%) at 80-89 years and lacunar infarcts 4.1% (0.0%-8.8%) at age 50-59 years and 31.2% (21.5%-41.0%) at 80-89 years. Prevalence estimates of any infarction by sex were: men, 8.7% (0.0%-18.7%) at 50-59 years and 54.9% (41.0%-68.8%) at 80-89 years and women, 2.4% (0.0%-7.3%) at age 50-59 years and 27.3% (12.9%-41.7%) at 80-89 years. Intra- and inter- reader reliability were very good (kappa = 0.85 and 0.82, respectively). After adjusting for age, sex and education, individuals imaged with 3D FLAIR were 1.5 times (95% CI 1.2-1.8, p<0.001) more likely to be identified as positive for infarction compared to those imaged with 2D FLAIR.Conclusions: Infarction prevalence increases with age and is greater in men than women. Infarction prevalence on 3D FLAIR imaging, which has become more widely implemented as an alternative to 2D FLAIR over the past several years, will be a useful reference in future work. [ABSTRACT FROM AUTHOR]- Published
- 2022
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43. NODDI in gray matter is a sensitive marker of aging and early AD changes
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Xi Yu, Scott A. Przybelski, Robert I. Reid, Timothy G. Lesnick, Sheelakumari Raghavan, Jonathan Graff‐Radford, Val J. Lowe, Kejal Kantarci, David S. Knopman, Ronald C. Petersen, Clifford R. Jack Jr., and Prashanthi Vemuri
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brain aging ,diffusion magnetic resonance imaging ,early Alzheimer's disease dementia ,neurite orientation dispersion and density imaging ,Neurology. Diseases of the nervous system ,RC346-429 ,Geriatrics ,RC952-954.6 - Abstract
Abstract INTRODUCTION Age‐related and Alzheimer's disease (AD) dementia–related neurodegeneration impact brain health. While morphometric measures from T1‐weighted scans are established biomarkers, they may be less sensitive to earlier changes. Neurite orientation dispersion and density imaging (NODDI), offering biologically meaningful interpretation of tissue microstructure, may be an advanced brain health biomarker. METHODS We contrasted regional gray matter NODDI and morphometric evaluations concerning their correlation with (1) age, (2) clinical diagnosis stage, and (3) tau pathology as assessed by AV1451 positron emission tomography. RESULTS Our study hypothesizes that NODDI measures are more sensitive to aging and early AD changes than morphometric measures. One NODDI output, free water fraction (FWF), showed higher sensitivity to age‐related changes, generally better effect sizes in separating mild cognitively impaired from cognitively unimpaired participants, and stronger associations with regional tau deposition than morphometric measures. DISCUSSION These findings underscore NODDI's utility in capturing early neurodegenerative changes and enhancing our understanding of aging and AD. Highlights Neurite orientation dispersion and density imaging can serve as an effective brain health biomarker for aging and early Alzheimer's disease (AD). Free water fraction has higher sensitivity to normal brain aging. Free water fraction has stronger associations with early AD and regional tau deposition.
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- 2024
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44. Performance of the Lumipulse plasma Aβ42/40 and pTau181 immunoassays in the detection of amyloid pathology
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Daniel J. Figdore, Heather J. Wiste, Joshua A. Bornhorst, Randall J. Bateman, Yan Li, Jonathan Graff‐Radford, David S. Knopman, Prashanthi Vemuri, Val J. Lowe, Clifford R. Jack Jr, Ronald C. Petersen, and Alicia Algeciras‐Schimnich
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Alzheimer's disease blood biomarkers ,amyloid beta ,amyloid‐PET ,Aβ42/Aβ40 ,plasma pTau ,pTau181 ,Neurology. Diseases of the nervous system ,RC346-429 ,Geriatrics ,RC952-954.6 - Abstract
Abstract INTRODUCTION This study evaluated the performance of the Lumipulse plasma beta‐amyloid (Aβ) 42/40 and pTau181 compared to other assays to detect an abnormal amyloid‐positron emission tomography (PET). METHODS Plasma samples from cognitively unimpaired (N = 179) and MCI/AD dementia (N = 36) individuals were retrospectively evaluated. Plasma Aβ42/40 and pTau181 were measured using the Lumipulse and Simoa immunoassays. An immunoprecipitation mass spectrometry (IP‐MS) assay for plasma Aβ42/40 was also evaluated. Amyloid‐PET status was the outcome measure. RESULTS Lumipulse and IP‐MS Aβ42/40 exhibited the highest diagnostic accuracy for detecting an abnormal amyloid‐PET (areas under the curve [AUCs] of 0.81 and 0.84, respectively). The Lumipulse and Simoa pTau181 assays exhibited lower performance (AUCs of 0.74 and 0.72, respectively). The Simoa Aβ42/40 assay demonstrated the lowest diagnostic accuracy (AUC 0.57). Combining Aβ42/40 and pTau181 did not significantly improve performance over Aβ42/40 alone for Lumipulse (AUC 0.83) or over pTau181 alone for Simoa (AUC 0.71) DISCUSSION The Lumipulse Aβ42/40 assay showed similar performance to the IP‐MS Aβ42/40 assay for detection of an abnormal amyloid‐PET; and both assays performed better than the two p‐tau181 immunoassays. The Simoa Aβ42/Aβ40 assay was the least accurate at predicting an abnormal amyloid‐PET status. Highlights Lumipulse plasma Aβ42/Aβ40 AUC for abnormal amyloid‐PET detection was 0.81. This performance was comparable to previously reported IP‐MS and higher than Simoa. Performance of Alzheimer's disease blood biomarkers varies between assays.
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- 2024
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45. Interactions Between Neuropsychiatric Symptoms and Alzheimer's Disease Neuroimaging Biomarkers in Predicting Longitudinal Cognitive Decline
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Anna Pink, Janina Krell‐Roesch, Jeremy A. Syrjanen, Luke R. Christenson, Val J. Lowe, Prashanthi Vemuri, Julie A. Fields, Gorazd B. Stokin, Walter K. Kremers, Eugene L. Scharf, Clifford R. Jack Jr., David S. Knopman, Ronald C. Petersen, Maria Vassilaki, and Yonas E. Geda
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Psychiatry ,RC435-571 - Abstract
Objective To examine interactions between Neuropsychiatric symptoms (NPS) with Pittsburgh Compound B (PiB) and fluorodeoxyglucose positron emission tomography (FDG‐PET) in predicting cognitive trajectories. Methods We conducted a longitudinal study in the setting of the population‐based Mayo Clinic Study of Aging in Olmsted County, MN, involving 1581 cognitively unimpaired (CU) persons aged ≥50 years (median age 71.83 years, 54.0% males, 27.5% APOE ɛ4 carriers). NPS at baseline were assessed using the Neuropsychiatric Inventory Questionnaire (NPI‐Q). Brain glucose hypometabolism was defined as a SUVR ≤ 1.47 (measured by FDG‐PET) in regions typically affected in Alzheimer's disease. Abnormal cortical amyloid deposition was measured using PiB‐PET (SUVR ≥ 1.48). Neuropsychological testing was done approximately every 15 months, and we calculated global and domain‐specific (memory, language, attention, and visuospatial skills) cognitive z‐scores. We ran linear mixed‐effect models to examine the associations and interactions between NPS at baseline and z‐scored PiB‐ and FDG‐PET SUVRs in predicting cognitive z‐scores adjusted for age, sex, education, and previous cognitive testing. Results Individuals at the average PiB and without NPS at baseline declined over time on cognitive z‐scores. Those with increased PiB at baseline declined faster (two‐way interaction), and those with increased PiB and NPS declined even faster (three‐way interaction). We observed interactions between time, increased PiB and anxiety or irritability indicating accelerated decline on global z‐scores, and between time, increased PiB and several NPS (e.g., agitation) showing faster domain‐specific decline, especially on the attention domain. Conclusions NPS and increased brain amyloid deposition synergistically interact in accelerating global and domain‐specific cognitive decline among CU persons at baseline.
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- 2023
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46. Association of raloxifene and tamoxifen therapy with cognitive performance, odds of mild cognitive impairment, and brain MRI markers of neurodegeneration
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Firat Kara, Christine M. Lohse, Anna M. Castillo, Nirubol Tosakulwong, Timothy G. Lesnick, Clifford R. Jack Jr, Ronald C. Petersen, Janet E. Olson, Fergus J. Couch, Kathryn J. Ruddy, Kejal Kantarci, and Michelle M. Mielke
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breast cancer ,cognitive performance ,cross‐sectional ,MCI ,raloxifene ,tamoxifen ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract The aim of this cross‐sectional study was to examine whether a history of selective estrogen receptor modifiers (SERMs), tamoxifen and raloxifene, use was associated with cognitive performance, odds of mild cognitive impairment (MCI), or magnetic resonance imaging (MRI) markers of neurodegeneration associated with Alzheimer's disease. We included women with prior history of breast cancer or no prior history of any cancer at enrollment in the Mayo Clinic Study of Aging (MCSA). This information was abstracted using the Rochester Epidemiology Project medical‐linkage system. Logistic regression was used to examine associations of SERMs with odds of MCI. Linear regression models were used to examine associations of SERMs with cognitive z‐scores (Memory, Executive Function, Language, Visuospatial Skills, Global Cognition), and MRI markers. Among 2840 women aged 50 and older in the MCSA, 151 had a history of breast cancer, and 42 (28%) of these had a history of tamoxifen treatment. A total of 2235 women had no prior history of any cancer, and 76 (3%) of these had a history of raloxifene use. No significant associations between tamoxifen use and cognition, or odds of MCI were observed among women with a history of breast cancer after adjusting for confounders. Similarly, raloxifene use was not significantly associated with cognition, or odds of MCI in women without a history of cancer after adjusting for confounders. We did not find significant associations between the use of either SERM and MRI markers. Use of tamoxifen or raloxifene was not significantly associated with cognition in postmenopausal women.
- Published
- 2023
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47. Plasma‐derived biomarkers of Alzheimer's disease and neuropsychiatric symptoms: A community‐based study
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Janina Krell‐Roesch, Isabella Zaniletti, Jeremy A. Syrjanen, Walter K. Kremers, Alicia Algeciras‐Schimnich, Jeffrey L. Dage, Argonde C. vanHarten, Julie A. Fields, David S. Knopman, Clifford R. Jack Jr, Ronald C. Petersen, Maria Vassilaki, and Yonas E. Geda
- Subjects
Alzheimer's disease ,neuropsychiatric symptoms ,plasma biomarkers ,Neurology. Diseases of the nervous system ,RC346-429 ,Geriatrics ,RC952-954.6 - Abstract
Abstract INTRODUCTION We examined associations between plasma‐derived biomarkers of Alzheimer's disease (AD) and neuropsychiatric symptoms (NPS) in community‐dwelling older adults. METHODS Cross‐sectional study involving 1005 persons ≥50 years of age (mean 74 years, 564 male, 118 cognitively impaired), who completed plasma‐derived biomarker (amyloid beta 42 [Aβ42]/Aβ40, phosphorylated tau 181 [p‐tau181], p‐tau217, total tau [t‐tau], neurofilament light [NfL]), and NPS assessment. RESULTS P‐tau181 (odds ratio [OR] 2.06, 95% confidence interval [CI] 1.41–3.00, p
- Published
- 2023
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48. Effects of de-facing software mri_reface on utility of imaging biomarkers used in Alzheimer’s disease research
- Author
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Christopher G. Schwarz, Walter K. Kremers, Stephen D. Weigand, Carl M. Prakaashana, Matthew L. Senjem, Scott A. Przybelski, Val J. Lowe, Jeffrey L. Gunter, Kejal Kantarci, Prashanthi Vemuri, Jonathan Graff-Radford, Ronald C. Petersen, David S. Knopman, and Clifford R. Jack Jr.
- Subjects
De-facing ,De-identification ,Face recognition ,Anonymization ,Alzheimer’s disease ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Brain imaging research studies increasingly use “de-facing” software to remove or replace facial imagery before public data sharing. Several works have studied the effects of de-facing software on brain imaging biomarkers by directly comparing automated measurements from unmodified vs de-faced images, but most research brain images are used in analyses of correlations with cognitive measurements or clinical statuses, and the effects of de-facing on these types of imaging-to-cognition correlations has not been measured. In this work, we focused on brain imaging measures of amyloid (A), tau (T), neurodegeneration (N), and vascular (V) measures used in Alzheimer’s Disease (AD) research. We created a retrospective sample of participants from three age- and sex-matched clinical groups (cognitively unimpaired, mild cognitive impairment, and AD dementia, and we performed region- and voxel-wise analyses of: hippocampal volume (N), white matter hyperintensity volume (V), amyloid PET (A), and tau PET (T) measures, each from multiple software pipelines, on their ability to separate cognitively defined groups and their degrees of correlation with age and Clinical Dementia Rating (CDR)–Sum of Boxes (CDR-SB). We performed each of these analyses twice: once with unmodified images and once with images de-faced with leading de-facing software mri_reface, and we directly compared the findings and their statistical strengths between the original vs. the de-faced images. Analyses with original and with de-faced images had very high agreement. There were no significant differences between any voxel-wise comparisons. Among region-wise comparisons, only three out of 55 correlations were significantly different between original and de-faced images, and these were not significant after correction for multiple comparisons. Overall, the statistical power of the imaging data for AD biomarkers was almost identical between unmodified and de-faced images, and their analyses results were extremely consistent.
- Published
- 2023
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49. Deep learning identifies brain structures that predict cognition and explain heterogeneity in cognitive aging
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Krishnakant V. Saboo, Chang Hu, Yogatheesan Varatharajah, Scott A. Przybelski, Robert I. Reid, Christopher G. Schwarz, Jonathan Graff-Radford, David S. Knopman, Mary M. Machulda, Michelle M. Mielke, Ronald C. Petersen, Paul M. Arnold, Gregory A. Worrell, David T. Jones, Clifford R. Jack Jr, Ravishankar K. Iyer, and Prashanthi Vemuri
- Subjects
Cognitive heterogeneity ,Brain reserve ,Deep learning ,Cognitive aging ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Specific brain structures (gray matter regions and white matter tracts) play a dominant role in determining cognitive decline and explain the heterogeneity in cognitive aging. Identification of these structures is crucial for screening of older adults at risk of cognitive decline. Using deep learning models augmented with a model-interpretation technique on data from 1432 Mayo Clinic Study of Aging participants, we identified a subset of brain structures that were most predictive of individualized cognitive trajectories and indicative of cognitively resilient vs. vulnerable individuals. Specifically, these structures explained why some participants were resilient to the deleterious effects of elevated brain amyloid and poor vascular health. Of these, medial temporal lobe and fornix, reflective of age and pathology-related degeneration, and corpus callosum, reflective of inter-hemispheric disconnection, accounted for 60% of the heterogeneity explained by the most predictive structures. Our results are valuable for identifying cognitively vulnerable individuals and for developing interventions for cognitive decline.
- Published
- 2022
- Full Text
- View/download PDF
50. MRI and flortaucipir relationships in Alzheimer's phenotypes are heterogeneous
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Keith A. Josephs, Nirubol Tosakulwong, Jonathan Graff‐Radford, Stephen D. Weigand, Marina Buciuc, Mary M. Machulda, David T. Jones, Christopher G. Schwarz, Matthew L. Senjem, Nilufer Ertekin‐Taner, Kejal Kantarci, Bradley F. Boeve, David S. Knopman, Clifford R. Jack Jr, Ronald C. Petersen, Val J. Lowe, and Jennifer L. Whitwell
- Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Abstract Objective To assess the relationships between MRI volumetry and [18F]flortaucipir PET of typical and atypical clinical phenotypes of Alzheimer’s disease, by genarian (age by decade). Methods Five‐hundred and sixty‐four participants including those with typical (n = 86) or atypical (n = 80) Alzheimer’s dementia and normal controls (n = 398) underwent apolipoprotein E genotyping, MRI, flortaucipir, and 11C‐PiB; all 166 Alzheimer’s participants were beta‐amyloid positive and all controls were beta‐amyloid negative. Grey matter volume and flortaucipir standard uptake value ratios were calculated for hippocampus, entorhinal cortex, and neocortex. Ratios of hippocampal‐to‐neocortical and entorhinal‐to‐neocortical volume and flortaucipir uptake were also calculated. Linear regression models assessed relationships among regional volume, flortaucipir uptake, and ratios and phenotypes, within three genarians (50–59, 60–69, and 70+). Voxel‐level analyses were also performed. Results For 50–59 greater medial temporal atrophy and flortaucipir uptake was observed in the typical compared with atypical phenotype. The typical phenotype also showed greater frontal neocortex uptake with the voxel‐level analysis. For 60–69 and 70+ there was greater hippocampal volume loss in the typical compared with atypical phenotype while only the 60–69, but not the 70+ group, showed a difference in hippocampal flortaucipir uptake. We also observed a pattern for higher neocortical flortaucipir uptake to correlate with younger age decade for both phenotypes. Interpretation MRI volumetry versus flortaucipir PET relationships differ across Alzheimer’s clinical phenotypes, and also within phenotype across age decades. This suggests that there is potential risk of masked effects by not accounting for genarian in participants with beta‐amyloid and tau‐positive biomarker defined Alzheimer’s disease.
- Published
- 2020
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