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Background and purposeThe objective of this study was to longitudinally investigate the trajectory of change in 1 H MRS measurements in asymptomatic MAPT mutation carriers who became symptomatic during follow-up, and to determine the time at which the neurochemical alterations accelerated during disease progression.MethodsWe identified eight MAPT mutations carriers who transitioned from asymptomatic to symptomatic disease during follow-up. All participants were longitudinally followed with an average of 7.75 years (range 4-11 years) and underwent two or more single voxel 1 H MRS examinations from the posterior cingulate voxel, with a total of 60 examinations. The rate of longitudinal change for each metabolite was estimated using linear mixed models. A flex point model was used to estimate the flex time point of the change in slope.ResultsThe decrease in the NAA/mI ratio accelerated 2.09 years prior to symptom onset, and continued to decline. A similar trajectory was observed in the presumed glial marker mI/Cr ratio accelerating 1.86 years prior to symptom onset.ConclusionsOur findings support the potential use of longitudinal 1 H MRS for monitoring the neurodegenerative progression in MAPT mutation carriers starting from the asymptomatic stage.

ObjectiveTo determine the frontal lobe proton magnetic resonance spectroscopy (1H MRS) abnormalities in asymptomatic and symptomatic carriers of microtubule-associated protein tau (MAPT) mutations.MethodsWe recruited patients with MAPT mutations from 5 individual families, who underwent single voxel 1H MRS from the medial frontal lobe at 3T (n = 19) from the Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) Study at the Mayo Clinic site. Asymptomatic MAPT mutation carriers (n = 9) had Frontotemporal Lobar Degeneration Clinical Dementia Rating Sum of Boxes (FTLD-CDR SOB) score of zero, and symptomatic MAPT mutation carriers (n = 10) had a median FTLD-CDR SOB score of 5. Noncarriers from healthy first-degree relatives of the patients were recruited as controls (n = 25). The demographic aspects and 1H MRS metabolite ratios were compared by use of the Fisher exact test for sex and linear mixed models to account for within-family correlations. We used Tukey contrasts for pair-wise comparisons.ResultsAsymptomatic MAPT mutation carriers had lower neuronal marker N-acetylaspartate (NAA)/creatine (Cr) (p = 0.001) and lower NAA/myo-inositol (mI) (p = 0.026) than noncarriers after adjustment for age. Symptomatic MAPT mutation carriers had lower NAA/Cr (p = 0.01) and NAA/mI (p = 0.01) and higher mI/Cr (p = 0.02) compared to noncarriers after adjustment for age. Furthermore, NAA/Cr (p = 0.006) and NAA/mI (p < 0.001) ratios decreased, accompanied by an increase in mI/Cr ratio (p = 0.001), as the ages of carriers approached and passed the age at symptom onset.ConclusionFrontal lobe neurochemical alterations measured with 1H MRS precede the symptom onset in MAPT mutation carriers. Frontal lobe 1H MRS is a potential biomarker for early neurodegenerative processes in MAPT mutation carriers.

Level of evidence5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019.

Tensor-Based Morphometry (TBM) allows the automatic mapping of brain changes across time building 3D deformation maps. This technique has been applied for tracking brain degeneration in Alzheimer's and other neurodegenerative diseases with high sensitivity and reliability. Here we applied TBM to quantify changes in brain structure after completing a challenging adaptive cognitive training program based on the n-back task. Twenty-six young women completed twenty-four training sessions across twelve weeks and they showed, on average, large cognitive improvements. High-resolution MRI scans were obtained before and after training. The computed longitudinal deformation maps were analyzed for answering three questions: (a) Are there differential brain structural changes in the training group as compared with a matched control group? (b) Are these changes related to performance differences in the training program? (c) Are standardized changes in a set of psychological factors (fluid and crystallized intelligence, working memory, and attention control) measured before and after training, related to structural changes in the brain? Results showed (a) greater structural changes for the training group in the temporal lobe, (b) a negative correlation between these changes and performance across training sessions (the greater the structural change, the lower the cognitive performance improvements), and (c) negligible effects regarding the psychological factors measured before and after training.

Complex biological systems are organized across various spatiotemporal scales with particular scientific disciplines dedicated to the study of each scale (e.g. genetics, molecular biology and cognitive neuroscience). When considering disease pathophysiology, one must contemplate the scale at which the disease process is being observed and how these processes impact other levels of organization. Historically Alzheimer's disease has been viewed as a disease of abnormally aggregated proteins by pathologists and molecular biologists and a disease of clinical symptoms by neurologists and psychologists. Bridging the divide between these scales has been elusive, but the study of brain networks appears to be a pivotal inroad to accomplish this task. In this study, we were guided by an emerging systems-based conceptualization of Alzheimer's disease and investigated changes in brain networks across the disease spectrum. The default mode network has distinct subsystems with unique functional-anatomic connectivity, cognitive associations, and responses to Alzheimer's pathophysiology. These distinctions provide a window into the systems-level pathophysiology of Alzheimer's disease. Using clinical phenotyping, metadata, and multimodal neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative, we characterized the pattern of default mode network subsystem connectivity changes across the entire disease spectrum (n = 128). The two main findings of this paper are (i) the posterior default mode network fails before measurable amyloid plaques and appears to initiate a connectivity cascade that continues throughout the disease spectrum; and (ii) high connectivity between the posterior default mode network and hubs of high connectivity (many located in the frontal lobe) is associated with amyloid accumulation. These findings support a system model best characterized by a cascading network failure--analogous to cascading failures seen in power grids triggered by local overloads proliferating to downstream nodes eventually leading to widespread power outages, or systems failures. The failure begins in the posterior default mode network, which then shifts processing burden to other systems containing prominent connectivity hubs. This model predicts a connectivity 'overload' that precedes structural and functional declines and recasts the interpretation of high connectivity from that of a positive compensatory phenomenon to that of a load-shifting process transiently serving a compensatory role. It is unknown whether this systems-level pathophysiology is the inciting event driving downstream molecular events related to synaptic activity embedded in these systems. Possible interpretations include that the molecular-level events drive the network failure, a pathological interaction between the network-level and the molecular-level, or other upstream factors are driving both.

Alzheimer's disease (AD) researchers commonly use MRI as a quantitative measure of disease severity. Historically, hippocampal volume has been favored. Recently, "AD signature" measurements of gray matter (GM) volumes or cortical thicknesses have gained attention. Here, we systematically evaluate multiple thickness- and volume-based candidate-methods side-by-side, built using the popular FreeSurfer, SPM, and ANTs packages, according to the following criteria: (a) ability to separate clinically normal individuals from those with AD; (b) (extent of) correlation with head size, a nuisance covariatel (c) reliability on repeated scans; and (d) correlation with Braak neurofibrillary tangle stage in a group with autopsy. We show that volume- and thickness-based measures generally perform similarly for separating clinically normal from AD populations, and in correlation with Braak neurofibrillary tangle stage at autopsy. Volume-based measures are generally more reliable than thickness measures. As expected, volume measures are highly correlated with head size, while thickness measures are generally not. Because approaches to statistically correcting volumes for head size vary and may be inadequate to deal with this underlying confound, and because our goal is to determine a measure which can be used to examine age and sex effects in a cohort across a large age range, we thus recommend thickness-based measures. Ultimately, based on these criteria and additional practical considerations of run-time and failure rates, we recommend an AD signature measure formed from a composite of thickness measurements in the entorhinal, fusiform, parahippocampal, mid-temporal, inferior-temporal, and angular gyrus ROIs using ANTs with input segmentations from SPM12.

ObjectiveOur primary objective was to compare the performance of unaccelerated vs. accelerated structural MRI for measuring disease progression using serial scans in Alzheimer's disease (AD).MethodsWe identified cognitively normal (CN), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI) and AD subjects from all available Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects with usable pairs of accelerated and unaccelerated scans. There were a total of 696 subjects with baseline and 3 month scans, 628 subjects with baseline and 6 month scans and 464 subjects with baseline and 12 month scans available. We employed the Symmetric Diffeomorphic Image Normalization method (SyN) for normalization of the serial scans to obtain tensor based morphometry (TBM) maps which indicate the structural changes between pairs of scans. We computed a TBM-SyN summary score of annualized structural changes over 31 regions of interest (ROIs) that are characteristically affected in AD. TBM-SyN scores were computed using accelerated and unaccelerated scan pairs and compared in terms of agreement, group-wise discrimination, and sample size estimates for a hypothetical therapeutic trial.ResultsWe observed a number of systematic differences between TBM-SyN scores computed from accelerated and unaccelerated pairs of scans. TBM-SyN scores computed from accelerated scans tended to have overall higher estimated values than those from unaccelerated scans. However, the performance of accelerated scans was comparable to unaccelerated scans in terms of discrimination between clinical groups and sample sizes required in each clinical group for a therapeutic trial. We also found that the quality of both accelerated vs. unaccelerated scans were similar.ConclusionsAccelerated scanning protocols reduce scan time considerably. Their group-wise discrimination and sample size estimates were comparable to those obtained with unaccelerated scans. The two protocols did not produce interchangeable TBM-SyN estimates, so it is arguably important to use either accelerated pairs of scans or unaccelerated pairs of scans throughout the study duration.

Stable MR acquisition is essential for reliable measurement of brain atrophy in longitudinal studies. One attractive recent advance in MRI is to speed up acquisition using parallel imaging (e.g. reducing volumetric T1-weighted acquisition scan times from around 9 to 5 min). In some studies, a decision to change to an accelerated acquisition may have been deliberately taken, while in others repeat scans may occasionally be accidentally acquired with an accelerated acquisition. In ADNI, non-accelerated and accelerated scans were acquired in the same scanning session on each individual. We investigated the impact on brain atrophy as measured by k-means normalized boundary shift integral (KN-BSI) and deformation-based morphometry when changing from non-accelerated to accelerated MRI acquisitions over a 12-month interval using scans of 422 subjects from ADNI. KN-BSIs were calculated using both a non-accelerated baseline scan and non-accelerated 12-month scans (i.e. consistent acquisition), and a non-accelerated baseline scan and an accelerated 12-month scan (i.e. changed acquisition). Fluid-based non-rigid registration was also performed on those scans to estimate the brain atrophy rate. We found that the effect on KN-BSI and fluid-based non-rigid registration depended on the scanner manufacturer. For KN-BSI, in Philips and Siemens scanners, the change had very little impact on the measured atrophy rate (increase of 0.051% in Philips and -0.035% in Siemens from consistent acquisition to changed acquisition), whereas, in GE, the change caused a mean reduction of 0.65% in the brain atrophy rate. This is likely due to the difference in tissue contrast between gray matter and cerebrospinal fluid in the non-accelerated and accelerated scans in GE, which uses IR-FSPGR instead of MP-RAGE. For fluid-based non-rigid registration, the change caused a mean increase of 0.29% in the brain atrophy rate in the changed acquisition compared with consistent acquisition in Philips, whereas in GE and Siemens, the change had less impact on the mean atrophy rate (increase of 0.18% in GE and 0.049% in Siemens). Moving from non-accelerated baseline scans to accelerated scans for follow-up may have surprisingly little effect on computed atrophy rates depending on the exact sequence details and the scanner manufacturer; even accidentally inconsistent scans of this nature may still be useful.

The Alzheimer's Disease Neuroimaging Initiative recently implemented accelerated T1-weighted structural imaging to reduce scan times. Faster scans may reduce study costs and patient attrition by accommodating people who cannot tolerate long scan sessions. However, little is known about how scan acceleration affects the power to detect longitudinal brain change. Using tensor-based morphometry, no significant difference was detected in numerical summaries of atrophy rates from accelerated and nonaccelerated scans in subgroups of patients with Alzheimer's disease, early or late mild cognitive impairment, or healthy controls over a 6- and 12-month scan interval. Whole-brain voxelwise mapping analyses revealed some apparent regional differences in 6-month atrophy rates when comparing all subjects irrespective of diagnosis (n = 345). No such whole-brain difference was detected for the 12-month scan interval (n = 156). Effect sizes for structural brain changes were not detectably different in accelerated versus nonaccelerated data. Scan acceleration may influence brain measures but has minimal effects on tensor-based morphometry-derived atrophy measures, at least over the 6- and 12-month intervals examined here.

INTRODUCTION: Patients with dementia with Lewy bodies (DLB) may have Alzheimers disease (AD) pathology that can be detected by plasma biomarkers. Our objective was to evaluate plasma biomarkers of AD and their association with positron emission tomography (PET) biomarkers of amyloid and tau deposition in the continuum of DLB, starting from prodromal stages of the disease. METHODS: The cohort included patients with isolated rapid eye movement (REM) sleep behavior disorder (iRBD), mild cognitive impairment with Lewy bodies (MCI‐LB), or DLB, with a concurrent blood draw and PET scans. RESULTS: Abnormal levels of plasma glial fibrillary acidic protein (GFAP) were found at the prodromal stage of MCI‐LB in association with increased amyloid PET. Abnormal levels of plasma phosphorylated tau (p‐tau)‐181 and neurofilament light (NfL) were found at the DLB stage. Plasma p‐tau‐181 showed the highest accuracy in detecting abnormal amyloid and tau PET in patients with DLB. DISCUSSION: The range of AD co‐pathology can be detected with plasma biomarkers in the DLB continuum, particularly with plasma p‐tau‐181 and GFAP. [ABSTRACT FROM AUTHOR]

Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models. [ABSTRACT FROM AUTHOR]

INTRODUCTION: The timing of plasma biomarker changes is not well understood. The goal of this study was to evaluate the temporal co‐evolution of plasma and positron emission tomography (PET) Alzheimer's disease (AD) biomarkers. METHODS: We included 1408 Mayo Clinic Study of Aging and Alzheimer's Disease Research Center participants. An accelerated failure time (AFT) model was fit with amyloid beta (Aβ) PET, tau PET, plasma p‐tau217, p‐tau181, and glial fibrillary acidic protein (GFAP) as endpoints. RESULTS: Individual timing of plasma p‐tau progression was strongly associated with Aβ PET and GFAP progression. In the population, GFAP became abnormal first, then Aβ PET, plasma p‐tau, and tau PET temporal meta‐regions of interest when applying cut points based on young, cognitively unimpaired participants. DISCUSSION: Plasma p‐tau is a stronger indicator of a temporally linked response to elevated brain Aβ than of tau pathology. While Aβ deposition and a rise in GFAP are upstream events associated with tau phosphorylation, the temporal link between p‐tau and Aβ PET was the strongest. Highlights: Plasma p‐tau progression was more strongly associated with Aβ than tau PET.Progression on plasma p‐tau was associated with Aβ PET and GFAP progression.P‐tau181 and p‐tau217 become abnormal after Aβ PET and before tau PET.GFAP became abnormal first, before plasma p‐tau and Aβ PET. [ABSTRACT FROM AUTHOR]

ObjectiveTo determine structural MRI and digital microscopic characteristics of REM sleep behavior disorder in individuals with low-, intermediate-, and high-likelihood dementia with Lewy bodies (DLB) at autopsy.MethodsPatients with autopsy-confirmed low-, intermediate-, and high-likelihood DLB, according to the probability statement recommended by the third report of the DLB Consortium, and antemortem MRI, were identified (n = 75). The clinical history was assessed for presence (n = 35) and absence (n = 40) of probable REM sleep behavior disorder (pRBD), and patients' antemortem MRIs were compared using voxel-based morphometry. Pathologic burdens of phospho-tau, β-amyloid, and α-synuclein were measured in regions associated with early neuropathologic involvement, the hippocampus and amygdala.ResultspRBD was present in 21 patients (60%) with high-likelihood, 12 patients (34%) with intermediate-likelihood, and 2 patients (6%) with low-likelihood DLB. Patients with pRBD were younger, more likely to be male (p ≤ 0.001), and had a more frequent neuropathologic diagnosis of diffuse (neocortical) Lewy body disease. In the hippocampus and amygdala, phospho-tau and β-amyloid burden were lower in patients with pRBD compared with those without pRBD (p < 0.01). α-Synuclein burden did not differ in the hippocampus, but trended in the amygdala. Patients without pRBD had greater atrophy of temporoparietal cortices, hippocampus, and amygdala (p < 0.001) than those with pRBD; atrophy of the hippocampus (p = 0.005) and amygdala (p = 0.02) were associated with greater phospho-tau burdens in these regions.ConclusionPresence of pRBD is associated with a higher likelihood of DLB and less severe Alzheimer-related pathology in the medial temporal lobes, whereas absence of pRBD is characterized by Alzheimer-like atrophy patterns on MRI and increased phospho-tau burden.

BackgroundPrevalence and risk factors for focal hemosiderin deposits are important considerations when planning amyloid-modifying trials for treatment and prevention of Alzheimer's disease (AD).MethodsSubjects were cognitively normal (n = 171), early-mild cognitive impairment (MCI) (n = 240), late-MCI (n = 111), and AD (n = 40) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Microhemorrhages and superficial siderosis were assessed at baseline and on all available MRIs at 3, 6, and 12 months. β-amyloid load was assessed with (18)F-florbetapir positron emission tomography.ResultsPrevalence of superficial siderosis was 1% and prevalence of microhemorrhages was 25% increasing with age (P < .001) and β-amyloid load (P < .001). Topographic densities of microhemorrhages were highest in the occipital lobes and lowest in the deep/infratentorial regions. A greater number of microhemorrhages at baseline was associated with a greater annualized rate of additional microhemorrhages by last follow-up (rank correlation = 0.49; P < .001).ConclusionsFocal hemosiderin deposits are relatively common in the ADNI cohort and are associated with β-amyloid load.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) three-dimensional T1-weighted magnetic resonance imaging (MRI) acquisitions provide a rich data set for developing and testing analysis techniques for extracting structural endpoints. To promote greater rigor in analysis and meaningful comparison of different algorithms, the ADNI MRI Core has created standardized analysis sets of data comprising scans that met minimum quality control requirements. We encourage researchers to test and report their techniques against these data. Standard analysis sets of volumetric scans from ADNI-1 have been created, comprising screening visits, 1-year completers (subjects who all have screening, 6- and 12-month scans), 2-year annual completers (screening, 1-year and 2-year scans), 2-year completers (screening, 6-months, 1-year, 18-months [mild cognitive impaired (MCI) only], and 2-year scans), and complete visits (screening, 6-month, 1-year, 18-month [MCI only], 2-year, and 3-year [normal and MCI only] scans). As the ADNI-GO/ADNI-2 data become available, updated standard analysis sets will be posted regularly.

ObjectiveTo characterize the shape of the trajectories of Alzheimer disease biomarkers as a function of Mini-Mental State Examination (MMSE) score.Design and settingLongitudinal registries from the Mayo Clinic and the Alzheimer's Disease Neuroimaging Initiative.PatientsTwo different samples (n = 343 and n = 598) were created that spanned the cognitive spectrum from normal to Alzheimer disease dementia. Subgroup analyses were performed in members of both cohorts (n = 243 and n = 328) who were amyloid positive at baseline.Main outcome measuresThe shape of biomarker trajectories as a function of MMSE score, adjusted for age, was modeled and described as baseline (cross-sectional) and within-subject longitudinal effects. Biomarkers evaluated were cerebrospinal fluid (CSF) Aβ42 and tau levels, amyloid and fluorodeoxyglucose positron emission tomography imaging, and structural magnetic resonance imaging.ResultsBaseline biomarker values generally worsened (ie, nonzero slope) with lower baseline MMSE score. Baseline hippocampal volume, amyloid positron emission tomography, and fluorodeoxyglucose positron emission tomography values plateaued (ie, nonlinear slope) with lower MMSE score in 1 or more analyses. Longitudinally, within-subject rates of biomarker change were associated with worsening MMSE score. Nonconstant within-subject rates (deceleration) of biomarker change were found in only 1 model.ConclusionsBiomarker trajectory shapes by MMSE score were complex and were affected by interactions with age and APOE status. Nonlinearity was found in several baseline effects models. Nonconstant within-subject rates of biomarker change were found in only 1 model, likely owing to limited within-subject longitudinal follow-up. Creating reliable models that describe the full trajectories of Alzheimer disease biomarkers will require significant additional longitudinal data in individual participants.

The purpose of this study was to use serial imaging to gain insight into the sequence of pathologic events in Alzheimer's disease, and the clinical features associated with this sequence. We measured change in amyloid deposition over time using serial (11)C Pittsburgh compound B (PIB) positron emission tomography and progression of neurodegeneration using serial structural magnetic resonance imaging. We studied 21 healthy cognitively normal subjects, 32 with amnestic mild cognitive impairment and 8 with Alzheimer's disease. Subjects were drawn from two sources--ongoing longitudinal registries at Mayo Clinic, and the Alzheimer's disease Neuroimaging Initiative (ADNI). All subjects underwent clinical assessments, MRI and PIB studies at two time points, approximately one year apart. PIB retention was quantified in global cortical to cerebellar ratio units and brain atrophy in units of cm(3) by measuring ventricular expansion. The annual change in global PIB retention did not differ by clinical group (P = 0.90), and although small (median 0.042 ratio units/year overall) was greater than zero among all subjects (P < 0.001). Ventricular expansion rates differed by clinical group (P < 0.001) and increased in the following order: cognitively normal (1.3 cm(3)/year) < amnestic mild cognitive impairment (2.5 cm(3)/year) < Alzheimer's disease (7.7 cm(3)/year). Among all subjects there was no correlation between PIB change and concurrent change on CDR-SB (r = -0.01, P = 0.97) but some evidence of a weak correlation with MMSE (r =-0.22, P = 0.09). In contrast, greater rates of ventricular expansion were clearly correlated with worsening concurrent change on CDR-SB (r = 0.42, P < 0.01) and MMSE (r =-0.52, P < 0.01). Our data are consistent with a model of typical late onset Alzheimer's disease that has two main features: (i) dissociation between the rate of amyloid deposition and the rate of neurodegeneration late in life, with amyloid deposition proceeding at a constant slow rate while neurodegeneration accelerates and (ii) clinical symptoms are coupled to neurodegeneration not amyloid deposition. Significant plaque deposition occurs prior to clinical decline. The presence of brain amyloidosis alone is not sufficient to produce cognitive decline, rather, the neurodegenerative component of Alzheimer's disease pathology is the direct substrate of cognitive impairment and the rate of cognitive decline is driven by the rate of neurodegeneration. Neurodegeneration (atrophy on MRI) both precedes and parallels cognitive decline. This model implies a complimentary role for MRI and PIB imaging in Alzheimer's disease, with each reflecting one of the major pathologies, amyloid dysmetabolism and neurodegeneration.