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Background: Neuroimaging studies often quantify tau burden in standardized brain regions to assess Alzheimer disease (AD) progression. However, this method ignores another key biological process in which tau spreads to additional brain regions. We have developed a metric for calculating the extent tau pathology has spread throughout the brain and evaluate the relationship between this metric and tau burden across early stages of AD., Methods: 445 cross-sectional participants (aged ≥ 50) who had MRI, amyloid PET, tau PET, and clinical testing were separated into disease-stage groups based on amyloid positivity and cognitive status (older cognitively normal control, preclinical AD, and symptomatic AD). Tau burden and tau spatial spread were calculated for all participants., Findings: We found both tau metrics significantly elevated across increasing disease stages (p < 0.0001) and as a function of increasing amyloid burden for participants with preclinical (p < 0.0001, p = 0.0056) and symptomatic (p = 0.010, p = 0.0021) AD. An interaction was found between tau burden and tau spatial spread when predicting amyloid burden (p = 0.00013). Analyses of slope between tau metrics demonstrated more spread than burden in preclinical AD (β = 0.59), but then tau burden elevated relative to spread (β = 0.42) once participants had symptomatic AD, when the tau metrics became highly correlated (R = 0.83)., Interpretation: Tau burden and tau spatial spread are both strong biomarkers for early AD but provide unique information, particularly at the preclinical stage. Tau spatial spread may demonstrate earlier changes than tau burden which could have broad impact in clinical trial design., Funding: This research was supported by the Knight Alzheimer Disease Research Center (Knight ADRC, NIH grants P30AG066444, P01AG026276, P01AG003991), Dominantly Inherited Alzheimer Network (DIAN, NIH grants U01AG042791, U19AG03243808, R01AG052550-01A1, R01AG05255003), and the Barnes-Jewish Hospital Foundation Willman Scholar Fund., Competing Interests: Declaration of interests Data collection and sharing for this project was supported by the Dominantly Inherited Alzheimer Network (DIAN, U19-AG032438) funded by the National Institute on Aging (NIA), the Alzheimer's Association (SG-20-690363-DIAN), the German Center for Neurodegenerative Diseases (DZNE), the Queen Square Dementia Biomedical Research Centre and the Medical Research Council Dementias Platform UK (MR/L023784/1 and MR/009076/1). Partial support has also been provided by research and development grants for dementia from the Japan Agency for Medical Research and Development (JP22dk0207049), AMED, the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), Korea Dementia Research Center (KDRC) funded by the Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea (HI21C0066), the Spanish Institute of Health Carlos III (ISCIII), the Canadian Institutes of Health Research (TAD-125697), the Canadian Consortium of Neurodegeneration and Aging, the Brain Canada Foundation, Fonds de Recherche du Québec, and the Raul Carrea Institute for Neurological Research (FLENI). In addition to the acknowledged funding sources for this research, the authors of this manuscript have received financial support from the National Institutes of Health (BMA, TLSB, JH, JCM, CX), National Institute on Aging (AJA, RJB, CC), National Institute of Neurological Disorders and Stroke (RJB), Alzheimer's Association (RJB, CC), DIAN-TU-001 Tau NextGen and OLE (RJB), Biogen (RJB), AbbVie (RJB), Bristol Myers Squibb (RJB), Novartis (RJB), Centene Corporation (RJB), Rainwater Foundation (RJB), Association for Frontotemporal Degeneration FTD Biomarkers Initiative (RJB), BrightFocus Foundation (RJB), Cure Alzheimer's Fund (RJB), Coins for Alzheimer's Research Trust Fund (RJB), Eisai (RJB), The Foundation for Barnes-Jewish Hospital (RJB), TargetALS (RJB), Good Ventures Foundation (RJB), DIAN-TU Pharma Consortium (RJB), Eli Lilly (RJB, TLSB), Avid Radiopharmaceuticals (TLSB), Hoffman-La Roche (RJB), CogState (RJB), Signant (RJB), Siemens (TLSB), and Michael J. Fox Foundation (CC). Travel support was received from Hoffman-La Roche (RJB), Alzheimer's Association Roundtable (RJB), Duke Margolis Alzheimer's Roundtable (RJB), BrightFocus Foundation (RJB), Tau Consortium Investigator's Meeting (RJB), Fondazione Prada (RJB), NAPA Advisory Council on Alzheimer's Research (RJB), and Somalogics (CC). Consultations have been declared for Biogen (TLSB), Eli Lilly (TLSB), Eisai (TLSB), Siemens (TLSB), Bristol Myers Squibb (TLSB), Alector (CC), Circular Genomics (CC), Parabon Nanolabs (JH), Hoffman-La Roche (JH), AlzPath (JH), Prothena (JH), Barcelona Brain Research Center (JCM), Native Alzheimer Disease-Related Resource Center in Minority Aging Research (JCM), and Diadem (CX). Honoraria was received from Korean Dementia Association (RJB), American Neurological Association (RJB), Fondazione Prada (RJB), Weill Cornell Medical College (RJB), Harvard University (RJB), Biogen (TLSB), Eisai (TLSB), Montefiore Grand Rounds NY (JCM), and Tetra-Inst ADRC seminar series Grand Rounds NY (JCM). Patents have been declared for NfL as a marker for ICANs due to CAR-T (BMA), methods for measuring the metabolism of CNS derived biomolecules in vivo (RJB), methods for measuring the metabolism of neutrally derived biomolecules in vivo (RJB), plasma based methods for detecting CNS amyloid disposition (RJB), plasma based methods for determining A-Beta amyloidosis (RJB), methods of treating based on site-specific tau phosphorylation (RJB), and tau kinetic measurements (RJB). Authors participated on advisory boards for VID (BMA), NNTC (BMA), Hoffman-La Roche/Genentech (RJB), Biogen (RJB), UK Dementia Research Institute at University College London (RJB), Stanford University (RJB), Next Generation Translational Proteomics for Alzheimer's and Related Dementias (RJB), C2N Diagnostics (RJB), Eisai (TLSB), Siemens (TLSB), Eli Lilly (TLSB), Bristol Myers Squibb (TLSB), NIH-sponsored external advisor grants (TLSB), NIA-sponsored Caring Bridge and Wall-E (JH), Cure Alzheimer's Fund Research Strategy Council (JCM), Indiana University LEADS Advisory Board (JCM), and FDA Advisory Committee on Imaging Medical Products (CX). Other declared interests include royalties with equity ownership from C2N Diagnostics (RJB), partnering and receiving stock from Circular Genomics (CC), and being the executive director of DIAN (AD). Participation in the ASNR Alzheimer's and ARIA Study Group, QIBA Amyloid PET Working Group, Alzheimer's Association Clinical Tau PET Work Group, and American College of Radiology/AlzNet Work Group (TLSB). Precursors for radiopharmaceuticals and technology transfer were received from Avid Radiopharmaceuticals/Eli Lilly, LMI, and Cerveau/Lantheus (TLSB). Drugs and services were received from Eisai, Janssen, and Hoffman- La Roche for the DIAN-TU Next Generation Trial and DIAN-TU Gantenerumab Open Label Extension (RJB). All other authors have nothing to disclose., (Copyright © 2024. Published by Elsevier B.V.)

Introduction: Amyloidosis, including cerebral amyloid angiopathy, and markers of small vessel disease (SVD) vary across dominantly inherited Alzheimer's disease (DIAD) presenilin-1 (PSEN1) mutation carriers. We investigated how mutation position relative to codon 200 (pre-/postcodon 200) influences these pathologic features and dementia at different stages., Methods: Individuals from families with known PSEN1 mutations (n = 393) underwent neuroimaging and clinical assessments. We cross-sectionally evaluated regional Pittsburgh compound B-positron emission tomography uptake, magnetic resonance imaging markers of SVD (diffusion tensor imaging-based white matter injury, white matter hyperintensity volumes, and microhemorrhages), and cognition., Results: Postcodon 200 carriers had lower amyloid burden in all regions but worse markers of SVD and worse Clinical Dementia Rating ® scores compared to precodon 200 carriers as a function of estimated years to symptom onset. Markers of SVD partially mediated the mutation position effects on clinical measures., Discussion: We demonstrated the genotypic variability behind spatiotemporal amyloidosis, SVD, and clinical presentation in DIAD, which may inform patient prognosis and clinical trials., Highlights: Mutation position influences Aβ burden, SVD, and dementia. PSEN1 pre-200 group had stronger associations between Aβ burden and disease stage. PSEN1 post-200 group had stronger associations between SVD markers and disease stage. PSEN1 post-200 group had worse dementia score than pre-200 in late disease stage. Diffusion tensor imaging-based SVD markers mediated mutation position effects on dementia in the late stage., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual's point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of 'sporadic' AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers., (© 2023. The Author(s).)

Off-target binding of [ 18 F]flortaucipir (FTP) can complicate quantitative PET analyses. An underdiscussed off-target region is the skull. Here, we characterize how often FTP skull binding occurs, its influence on estimates of Alzheimer disease pathology, its potential drivers, and whether skull uptake is a stable feature across time and tracers. Methods: In 313 cognitively normal and mildly impaired participants, CT scans were used to define a skull mask. This mask was used to quantify FTP skull uptake. Skull uptake of the amyloid-β PET tracers [ 18 F]florbetapir and [ 11 C]Pittsburgh compound B ( n = 152) was also assessed. Gaussian mixture modeling defined abnormal levels of skull binding for each tracer. We examined the relationship of continuous bone uptake to known off-target binding in the basal ganglia and choroid plexus as well as skull density measured from the CT. Finally, we examined the confounding effect of skull binding on pathologic quantification. Results: We found that 50 of 313 (∼16%) FTP scans had high levels of skull signal. Most were female ( n = 41, 82%), and in women, lower skull density was related to higher FTP skull signal. Visual reads by a neuroradiologist revealed a significant relationship with hyperostosis; however, only 21% of women with high skull binding were diagnosed with hyperostosis. FTP skull signal did not substantially correlate with other known off-target regions. Skull uptake was consistent over longitudinal FTP scans and across tracers. In amyloid-β-negative, but not -positive, individuals, FTP skull binding impacted quantitative estimates in temporal regions. Conclusion: FTP skull binding is a stable, participant-specific phenomenon and is unrelated to known off-target regions. Effects were found primarily in women and were partially related to lower bone density. The presence of [ 11 C]Pittsburgh compound B skull binding suggests that defluorination does not fully explain FTP skull signal. As signal in skull bone can impact quantitative analyses and differs across sex, it should be explicitly addressed in studies of aging and Alzheimer disease., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

The apolipoprotein E ( APOE ) ε4 allele is strongly linked with cerebral β-amyloidosis, but its relationship with tauopathy is less established. We investigated the relationship between APOE ε4 carrier status, regional amyloid-β (Aβ), magnetic resonance imaging (MRI) volumetrics, tau positron emission tomography (PET), APOE messenger RNA (mRNA) expression maps, and cerebrospinal fluid phosphorylated tau (CSF ptau 181 ). Three hundred fifty participants underwent imaging, and 270 had ptau 181 . We used computational models to evaluate the main effect of APOE ε4 carrier status on regional neuroimaging values and then the interaction of ε4 status and global Aβ on regional tau PET and brain volumes as well as CSF ptau 181 . Separately, we also examined the additional interactive influence of sex. We found that, for the same degree of Aβ burden, APOE ε4 carriers showed greater tau PET signal relative to noncarriers in temporal regions, but no interaction was present for MRI volumes or CSF ptau 181 . This potentiation of tau aggregation irrespective of sex occurred in brain regions with high APOE mRNA expression, suggesting local vulnerabilities to tauopathy. There were greater effects of APOE genotype in females, although the interactive sex effects did not strongly mirror mRNA expression. Pathology is not homogeneously expressed throughout the brain but mirrors underlying biological patterns such as gene expression.

Objective: To determine the characteristics of participants with amyloid-related imaging abnormalities (ARIA) in a trial of gantenerumab or solanezumab in dominantly inherited Alzheimer disease (DIAD)., Methods: 142 DIAD mutation carriers received either gantenerumab SC (n = 52), solanezumab IV (n = 50), or placebo (n = 40). Participants underwent assessments with the Clinical Dementia Rating® (CDR®), neuropsychological testing, CSF biomarkers, β-amyloid positron emission tomography (PET), and magnetic resonance imaging (MRI) to monitor ARIA. Cross-sectional and longitudinal analyses evaluated potential ARIA-related risk factors., Results: Eleven participants developed ARIA-E, including 3 with mild symptoms. No ARIA-E was reported under solanezumab while gantenerumab was associated with ARIA-E compared to placebo (odds ratio [OR] = 9.1, confidence interval [CI][1.2, 412.3]; p = 0.021). Under gantenerumab, APOE-ɛ4 carriers were more likely to develop ARIA-E (OR = 5.0, CI[1.0, 30.4]; p = 0.055), as were individuals with microhemorrhage at baseline (OR = 13.7, CI[1.2, 163.2]; p = 0.039). No ARIA-E was observed at the initial 225 mg/month gantenerumab dose, and most cases were observed at doses >675 mg. At first ARIA-E occurrence, all ARIA-E participants were amyloid-PET+, 60% were CDR >0, 60% were past their estimated year to symptom onset, and 60% had also incident ARIA-H. Most ARIA-E radiologically resolved after dose adjustment and developing ARIA-E did not significantly increase odds of trial discontinuation. ARIA-E was more frequently observed in the occipital lobe (90%). ARIA-E severity was associated with age at time of ARIA-E., Interpretation: In DIAD, solanezumab was not associated with ARIA. Gantenerumab dose over 225 mg increased ARIA-E risk, with additional risk for individuals APOE-ɛ4(+) or with microhemorrhage. ARIA-E was reversible on MRI in most cases, generally asymptomatic, without additional risk for trial discontinuation. ANN NEUROL 2022;92:729-744., (© 2022 The Authors. Annals of Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Although often unmeasured in studies of cognition, many older adults possess Alzheimer disease (AD) pathologies such as beta-amyloid (Aβ) deposition, despite being asymptomatic. We were interested in examining whether the behavior-structure relationship observed in later life was altered by the presence of preclinical AD pathology. A total of 511 cognitively unimpaired adults completed magnetic resonance imaging and three attentional control tasks; a subset (n = 396) also underwent Aβ-positron emissions tomography. A vertex-wise model was conducted to spatially represent the relationship between cortical thickness and average attentional control accuracy, while moderation analysis examined whether Aβ deposition impacted this relationship. First, we found that reduced cortical thickness in temporal, medial- and lateral-parietal, and dorsolateral prefrontal cortex, predicted worse performance on the attention task composite. Subsequent moderation analyses observed that levels of Aβ significantly influence the relationship between cortical thickness and attentional control. Our results support the hypothesis that preclinical AD, as measured by Aβ deposition, is partially driving what would otherwise be considered general aging in a cognitively normal adult population., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Purpose: Recent studies have shown that standard compartmental models using plasma input or the cerebellum reference tissue input are generally not reliable for quantifying tau burden in dynamic 18 F-flortaucipir PET studies of Alzheimer disease. So far, the optimal reference region for estimating 18 F-flortaucipir delivery and specific tau binding has yet to be determined. The objective of the study is to improve 18 F-flortaucipir brain tau PET quantification using a spatially constrained kinetic model with dual reference tissues., Methods: Participants were classified as either cognitively normal (CN) or cognitively impaired (CI) based on clinical assessment. T1-weighted structural MRI and 105-min dynamic 18 F-flortaucipir PET scans were acquired for each participant. Using both a simplified reference tissue model (SRTM2) and Logan plot with either cerebellum gray matter or centrum semiovale (CS) white matter as the reference tissue, we estimated distribution volume ratios (DVRs) and the relative transport rate constant R 1 for region of interest-based (ROI) and voxelwise-based analyses. Conventional linear regression (LR) and LR with spatially constrained (LRSC) parametric imaging algorithms were then evaluated. Noise-induced bias in the parametric images was compared to estimates from ROI time activity curve-based kinetic modeling. We finally evaluated standardized uptake value ratios at early phase (SUVR EP , 0.7-2.9 min) and late phase (SUVR LP , 80-105 min) to approximate R 1 and DVR, respectively., Results: The percent coefficients of variation of R 1 and DVR estimates from SRTM2 with spatially constrained modeling were comparable to those from the Logan plot and SUVRs. The SRTM2 using CS reference tissue with LRSC reduced noise-induced underestimation in the LR generated DVR images to negligible levels (< 1%). Inconsistent overestimation of DVR in the SUVR LP only occurred using the cerebellum reference tissue-based measurements. The CS reference tissue-based DVR and SUVR LP , and cerebellum-based SUVR EP and R 1 provided higher Cohen's effect size d to detect increased tau deposition and reduced relative tracer transport rate in CI individuals., Conclusion: Using a spatially constrained kinetic model with dual reference tissues significantly improved quantification of relative perfusion and tau binding. Cerebellum and CS are the suggested reference tissues to estimate R 1 and DVR, respectively, for dynamic 18 F-flortaucipir PET studies. Cerebellum-based SUVR EP and CS-based SUVR LP may be used to simplify 18 F-flortaucipir PET study., (© 2021. Springer-Verlag GmbH Germany, part of Springer Nature.)

Objective: To investigate the inherent clinical risks associated with the presence of cerebral microhemorrhages (CMHs) or cerebral microbleeds and characterize individuals at high risk for developing hemorrhagic amyloid-related imaging abnormality (ARIA-H), we longitudinally evaluated families with dominantly inherited Alzheimer disease (DIAD)., Methods: Mutation carriers (n = 310) and noncarriers (n = 201) underwent neuroimaging, including gradient echo MRI sequences to detect CMHs, and neuropsychological and clinical assessments. Cross-sectional and longitudinal analyses evaluated relationships between CMHs and neuroimaging and clinical markers of disease., Results: Three percent of noncarriers and 8% of carriers developed CMHs primarily located in lobar areas. Carriers with CMHs were older, had higher diastolic blood pressure and Hachinski ischemic scores, and more clinical, cognitive, and motor impairments than those without CMHs. APOE ε4 status was not associated with the prevalence or incidence of CMHs. Prevalent or incident CMHs predicted faster change in Clinical Dementia Rating although not composite cognitive measure, cortical thickness, hippocampal volume, or white matter lesions. Critically, the presence of 2 or more CMHs was associated with a significant risk for development of additional CMHs over time (8.95 ± 10.04 per year)., Conclusion: Our study highlights factors associated with the development of CMHs in individuals with DIAD. CMHs are a part of the underlying disease process in DIAD and are significantly associated with dementia. This highlights that in participants in treatment trials exposed to drugs, which carry the risk of ARIA-H as a complication, it may be challenging to separate natural incidence of CMHs from drug-related CMHs., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

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 (n ADRC  = 381; n DIAN  = 145), preclinical (n ADRC  = 153; n DIAN  = 76), and cognitively impaired (n ADRC  = 54; n DIAN  = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11 C-Pittsburgh compound B or 18 F-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., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Introduction: Quantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B-based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design., Methods: Pittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter-individual variability of the two tracers were compared using multivariate linear models both cross-sectionally and longitudinally., Results: Global amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers., Discussion: Although the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers.

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.

Amyloid imaging is a valuable tool for research and diagnosis in dementing disorders. Successful use of this tool is limited by the lack of a common standard in the quantification of amyloid imaging data. The Centiloid approach was recently proposed to address this problem and in this work, we report our implementation of this approach and evaluate the impact of differences in underlying image analysis methodologies using both cross-sectional and longitudinal datasets. The Centiloid approach successfully converts quantitative amyloid burden measurements into a common Centiloid scale (CL) and comparable dynamic range. As expected, the Centiloid values derived from different analytical approaches inherit some of the inherent benefits and drawbacks of the underlying approaches, and these differences result in statistically significant ( p  < 0.05) differences in the variability and group mean values. Because of these differences, even after expression in CL, the 95% specificity amyloid positivity thresholds derived from different analytic approaches varied from 5.7 CL to 11.9 CL, and the reliable worsening threshold varied from -2.0 CL to 11.0 CL. Although this difference is in part due to the dependency of the threshold determination methodology on the statistical characteristics of the measurements. When amyloid measurements obtained from different centers are combined for analysis, one should not expect Centiloid conversion to eliminate all the differences in amyloid burden measurements due to variabilities in underlying acquisition protocols and analysis techniques.

Introduction: Structural magnetic resonance imaging is a marker of gray matter health and decline that is sensitive to impaired cognition and Alzheimer's disease pathology. Prior work has shown that both amyloid β (Aβ) and tau biomarkers are related to cortical thinning, but it is unclear what unique influences they have on the brain., Methods: Aβ pathology was measured with [ 18 F] AV-45 (florbetapir) positron emission tomography (PET) and tau was assessed with [ 18 F] AV-1451 (flortaucipir) PET in a population of 178 older adults, of which 123 had longitudinal magnetic resonance imaging assessments (average of 5.7 years) that preceded the PET acquisitions., Results: In cross-sectional analyses, greater tau PET pathology was associated with thinner cortices. When examined independently in longitudinal models, both Aβ and tau were associated with greater antecedent loss of gray matter. However, when examined in a combined model, levels of tau, but not Aβ, were still highly related to change in cortical thickness., Discussion: Measures of tau PET are strongly related to gray matter atrophy and likely mediate relationships between Aβ and gray matter.

Background: Models of Alzheimer's disease propose a sequence of amyloid β (Aβ) accumulation, hypometabolism, and structural decline that precedes the onset of clinical dementia. These pathological features evolve both temporally and spatially in the brain. In this study, we aimed to characterise where in the brain and when in the course of the disease neuroimaging biomarkers become abnormal., Methods: Between Jan 1, 2009, and Dec 31, 2015, we analysed data from mutation non-carriers, asymptomatic carriers, and symptomatic carriers from families carrying gene mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) enrolled in the Dominantly Inherited Alzheimer's Network. We analysed 11 C-Pittsburgh Compound B ( 11 C-PiB) PET, 18 F-Fluorodeoxyglucose ( 18 F-FDG) PET, and structural MRI data using regions of interest to assess change throughout the brain. We estimated rates of biomarker change as a function of estimated years to symptom onset at baseline using linear mixed-effects models and determined the earliest point at which biomarker trajectories differed between mutation carriers and non-carriers. This study is registered at ClinicalTrials.gov (number NCT00869817) FINDINGS: 11 C-PiB PET was available for 346 individuals (162 with longitudinal imaging), 18 F-FDG PET was available for 352 individuals (175 with longitudinal imaging), and MRI data were available for 377 individuals (201 with longitudinal imaging). We found a sequence to pathological changes, with rates of Aβ deposition in mutation carriers being significantly different from those in non-carriers first (across regions that showed a significant difference, at a mean of 18·9 years [SD 3·3] before expected onset), followed by hypometabolism (14·1 years [5·1] before expected onset), and lastly structural decline (4·7 years [4·2] before expected onset). This biomarker ordering was preserved in most, but not all, regions. The temporal emergence within a biomarker varied across the brain, with the precuneus being the first cortical region for each method to show divergence between groups (22·2 years before expected onset for Aβ accumulation, 18·8 years before expected onset for hypometabolism, and 13·0 years before expected onset for cortical thinning)., Interpretation: Mutation carriers had elevations in Aβ deposition, reduced glucose metabolism, and cortical thinning compared with non-carriers which preceded the expected onset of dementia. Accrual of these pathologies varied throughout the brain, suggesting differential regional and temporal vulnerabilities to Aβ, metabolic decline, and structural atrophy, which should be taken into account when using biomarkers in a clinical setting as well as designing and evaluating clinical trials., Funding: US National Institutes of Health, the German Center for Neurodegenerative Diseases, and the Medical Research Council Dementias Platform UK., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

[This corrects the article DOI: 10.1371/journal.pone.0152082.].

Amyloid imaging plays an important role in the research and diagnosis of dementing disorders. Substantial variation in quantitative methods to measure brain amyloid burden exists in the field. The aim of this work is to investigate the impact of methodological variations to the quantification of amyloid burden using data from the Dominantly Inherited Alzheimer's Network (DIAN), an autosomal dominant Alzheimer's disease population. Cross-sectional and longitudinal [11C]-Pittsburgh Compound B (PiB) PET imaging data from the DIAN study were analyzed. Four candidate reference regions were investigated for estimation of brain amyloid burden. A regional spread function based technique was also investigated for the correction of partial volume effects. Cerebellar cortex, brain-stem, and white matter regions all had stable tracer retention during the course of disease. Partial volume correction consistently improves sensitivity to group differences and longitudinal changes over time. White matter referencing improved statistical power in the detecting longitudinal changes in relative tracer retention; however, the reason for this improvement is unclear and requires further investigation. Full dynamic acquisition and kinetic modeling improved statistical power although it may add cost and time. Several technical variations to amyloid burden quantification were examined in this study. Partial volume correction emerged as the strategy that most consistently improved statistical power for the detection of both longitudinal changes and across-group differences. For the autosomal dominant Alzheimer's disease population with PiB imaging, utilizing brainstem as a reference region with partial volume correction may be optimal for current interventional trials. Further investigation of technical issues in quantitative amyloid imaging in different study populations using different amyloid imaging tracers is warranted.

Amyloid PET imaging is an indispensable tool widely used in the investigation, diagnosis and monitoring of Alzheimer's disease (AD). Currently, a reference region based approach is used as the mainstream quantification technique for amyloid imaging. This approach assumes the reference region is amyloid free and has the same tracer influx and washout kinetics as the regions of interest. However, this assumption may not always be valid. The goal of this work is to evaluate an amyloid imaging quantification technique that uses arterial region of interest as the reference to avoid potential bias caused by specific binding in the reference region. 21 participants, age 58 and up, underwent Pittsburgh compound B (PiB) PET imaging and MR imaging including a time-of-flight (TOF) MR angiography (MRA) scan and a structural scan. FreeSurfer based regional analysis was performed to quantify PiB PET data. Arterial input function was estimated based on coregistered TOF MRA using a modeling based technique. Regional distribution volume (VT) was calculated using Logan graphical analysis with estimated arterial input function. Kinetic modeling was also performed using the estimated arterial input function as a way to evaluate PiB binding (DVRkinetic) without a reference region. As a comparison, Logan graphical analysis was also performed with cerebellar cortex as reference to obtain DVRREF. Excellent agreement was observed between the two distribution volume ratio measurements (r>0.89, ICC>0.80). The estimated cerebellum VT was in line with literature reported values and the variability of cerebellum VT in the control group was comparable to reported variability using arterial sampling data. This study suggests that image-based arterial input function is a viable approach to quantify amyloid imaging data, without the need of arterial sampling or a reference region. This technique can be a valuable tool for amyloid imaging, particularly in population where reference normalization may not be accurate.

Amyloid imaging is a valuable tool for research and diagnosis in dementing disorders. As positron emission tomography (PET) scanners have limited spatial resolution, measured signals are distorted by partial volume effects. Various techniques have been proposed for correcting partial volume effects, but there is no consensus as to whether these techniques are necessary in amyloid imaging, and, if so, how they should be implemented. We evaluated a two-component partial volume correction technique and a regional spread function technique using both simulated and human Pittsburgh compound B (PiB) PET imaging data. Both correction techniques compensated for partial volume effects and yielded improved detection of subtle changes in PiB retention. However, the regional spread function technique was more accurate in application to simulated data. Because PiB retention estimates depend on the correction technique, standardization is necessary to compare results across groups. Partial volume correction has sometimes been avoided because it increases the sensitivity to inaccuracy in image registration and segmentation. However, our results indicate that appropriate PVC may enhance our ability to detect changes in amyloid deposition., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Major imaging biomarkers of Alzheimer's disease include amyloid deposition [imaged with [(11)C]Pittsburgh compound B (PiB) PET], altered glucose metabolism (imaged with [(18)F]fluro-deoxyglucose PET), and structural atrophy (imaged by MRI). Recently we published the initial subset of imaging findings for specific regions in a cohort of individuals with autosomal dominant Alzheimer's disease. We now extend this work to include a larger cohort, whole-brain analyses integrating all three imaging modalities, and longitudinal data to examine regional differences in imaging biomarker dynamics. The anatomical distribution of imaging biomarkers is described in relation to estimated years from symptom onset. Autosomal dominant Alzheimer's disease mutation carrier individuals have elevated PiB levels in nearly every cortical region 15 y before the estimated age of onset. Reduced cortical glucose metabolism and cortical thinning in the medial and lateral parietal lobe appeared 10 and 5 y, respectively, before estimated age of onset. Importantly, however, a divergent pattern was observed subcortically. All subcortical gray-matter regions exhibited elevated PiB uptake, but despite this, only the hippocampus showed reduced glucose metabolism. Similarly, atrophy was not observed in the caudate and pallidum despite marked amyloid accumulation. Finally, before hypometabolism, a hypermetabolic phase was identified for some cortical regions, including the precuneus and posterior cingulate. Additional analyses of individuals in which longitudinal data were available suggested that an accelerated appearance of volumetric declines approximately coincides with the onset of the symptomatic phase of the disease.