The Alzheimer's Disease Neuroimaging Initiative and the role and contributions of the Private Partners Scientific Board (PPSB).

The Alzheimer's Disease Neuroimaging Initiative (ADNI) Private Partners Scientific Board (PPSB) encompasses members from industry, biotechnology, diagnostic, and non-profit organizations that have until recently been managed by the Foundation for the National Institutes of Health (FNIH) and provided financial and scientific support to ADNI programs. In this article, we review some of the major activities undertaken by the PPSB, focusing on those supporting the most recently completed National Institute on Aging grant, ADNI3, and the impact it has had on streamlining biomarker discovery and validation in Alzheimer's disease. We also provide a perspective on the gaps that may be filled with future PPSB activities as part of ADNI4 and beyond. HIGHLIGHTS: The Private Partners Scientific board (PPSB) continues to play a key role in enabling several Alzheimer's Disease Neuroimaging Initiative (ADNI) activities. PPSB working groups have led landscape assessments to provide valuable feedback on new technologies, platforms, and methods that may be taken up by ADNI in current or future iterations.

The age-specific comorbidity burden of mild cognitive impairment: a US claims database study.

BACKGROUND: Identifying individuals with mild cognitive impairment (MCI) who are likely to progress to Alzheimer's disease and related dementia disorders (ADRD) would facilitate the development of individualized prevention plans. We investigated the association between MCI and comorbidities of ADRD. We examined the predictive potential of these comorbidities for MCI risk determination using a machine learning algorithm. METHODS: Using a retrospective matched case-control design, 5185 MCI and 15,555 non-MCI individuals aged ≥50 years were identified from MarketScan databases. Predictive models included ADRD comorbidities, age, and sex. RESULTS: Associations between 25 ADRD comorbidities and MCI were significant but weakened with increasing age groups. The odds ratios (MCI vs non-MCI) in 50-64, 65-79, and ≥ 80 years, respectively, for depression (4.4, 3.1, 2.9) and stroke/transient ischemic attack (6.4, 3.0, 2.1). The predictive potential decreased with older age groups, with ROC-AUCs 0.75, 0.70, and 0.66 respectively. Certain comorbidities were age-specific predictors. CONCLUSIONS: The comorbidity burden of MCI relative to non-MCI is age-dependent. A model based on comorbidities alone predicted an MCI diagnosis with reasonable accuracy.

Operationalizing selection criteria for clinical trials in Alzheimer's disease: Biomarker and clinical considerations.

Alzheimer's disease (AD) staging criteria lack standardized, empirical description. Well-defined AD staging criteria are an important consideration in protocol design, influencing a more standardized inclusion/exclusion criteria and defining what constitutes meaningful differentiation among the stages. However, many trials are being designed on the basis of biomarker features and the two need to be coordinated. The Alzheimer's Association Research Roundtable (AARR) Spring 2021 meeting discussed the implementation of preclinical AD staging criteria, and provided recommendations for how they may best be incorporated into clinical trials research. Discussion also included what currently available tools for global clinical trials may best define populations in preclinical AD trials, and if are we able to differentiate preclinical from clinical stages of the disease. Well-defined AD staging criteria are key to improving early detection, diagnostics, clinical trial enrollment, and identifying statistically significant clinical changes, and researchers discussed how emerging blood biomarkers may help with more efficient screening in preclinical stages.

Evaluation of tau deposition using 18F-PI-2620 PET in MCI and early AD subjects-a MissionAD tau sub-study.

BACKGROUND: The ability of 18F-PI-2620 PET to measure the spatial distribution of tau pathology in Alzheimer's disease (AD) has been demonstrated in previous studies. The objective of this work was to evaluate tau deposition using 18F-PI-2620 PET in beta-amyloid positive subjects with a diagnosis of mild cognitive impairment (MCI) or mild AD dementia and characterize it with respect to amyloid deposition, cerebrospinal fluid (CSF) assessment, hippocampal volume, and cognition. METHODS: Subjects with a diagnosis of MCI due to AD or mild AD dementia and a visually amyloid-positive 18F-florbetaben PET scan (n=74, 76 ± 7 years, 38 females) underwent a baseline 18F-PI-2620 PET, T1-weighted magnetic resonance imaging (MRI), CSF assessment (Aß42/Aß40 ratio, p-tau, t-tau) (n=22) and several cognitive tests. A 1-year follow-up 18F-PI-2620 PET scans and cognitive assessments were done in 15 subjects. RESULTS: Percentage of visually tau-positive scans increased with amyloid-beta deposition measured in 18F-florbetaben Centiloids (CL) (7.7% (<36 CL), 80% (>83 CL)). 18F-PI-2620 standardized uptake value ratio (SUVR) was correlated with increased 18F-florbetaben CL in several regions of interest. Elevated 18F-PI-2620 SUVR (fusiform gyrus) was associated to high CSF p-tau and t-tau (p=0.0006 and p=0.01, respectively). Low hippocampal volume was associated with increased tau load at baseline (p=0.006 (mesial temporal); p=0.01 (fusiform gyrus)). Significant increases in tau SUVR were observed after 12 months, particularly in the mesial temporal cortex, fusiform gyrus, and inferior temporal cortex (p=0.04, p=0.047, p=0.02, respectively). However, no statistically significant increase in amyloid-beta load was measured over the observation time. The MMSE (Recall score), ADAS-Cog14 (Word recognition score), and CBB (One-card learning score) showed the strongest association with tau deposition at baseline. CONCLUSIONS: The findings support the hypothesis that 18F-PI-2620 PET imaging of neuropathologic tau deposits may reflect underlying neurodegeneration in AD with significant correlations with hippocampal volume, CSF biomarkers, and amyloid-beta load. Furthermore, quantifiable increases in 18F-PI-2620 SUVR over a 12-month period in regions with early tau deposition are consistent with the hypothesis that cortical tau is associated with cognitive impairment. This study supports the utility of 18F-PI-2620 PET to assess tau deposits in an early AD population. Quantifiable tau load and its corresponding increase in early AD cases could be a relevant target engagement marker in clinical trials of anti-amyloid and anti-tau agents. TRIAL REGISTRATION: Data used in this manuscript belong to a tau PET imaging sub-study of the elenbecestat MissionAD Phase 3 program registered in ClinicalTrials.gov ( NCT02956486 ;  NCT03036280 ).

Designing the next-generation clinical care pathway for Alzheimer's disease.

The reconceptualization of Alzheimer's disease (AD) as a clinical and biological construct has facilitated the development of biomarker-guided, pathway-based targeted therapies, many of which have reached late-stage development with the near-term potential to enter global clinical practice. These medical advances mark an unprecedented paradigm shift and requires an optimized global framework for clinical care pathways for AD. In this Perspective, we describe the blueprint for transitioning from the current, clinical symptom-focused and inherently late-stage diagnosis and management of AD to the next-generation pathway that incorporates biomarker-guided and digitally facilitated decision-making algorithms for risk stratification, early detection, timely diagnosis, and preventative or therapeutic interventions. We address critical and high-priority challenges, propose evidence-based strategic solutions, and emphasize that the perspectives of affected individuals and care partners need to be considered and integrated.

Early detection of amyloid load using 18F-florbetaben PET.

BACKGROUND: A low amount and extent of Aß deposition at early stages of Alzheimer's disease (AD) may limit the use of previously developed pathology-proven composite SUVR cutoffs. This study aims to characterize the population with earliest abnormal Aß accumulation using 18F-florbetaben PET. Quantitative thresholds for the early (SUVRearly) and established (SUVRestab) Aß deposition were developed, and the topography of early Aß deposition was assessed. Subsequently, Aß accumulation over time, progression from mild cognitive impairment (MCI) to AD dementia, and tau deposition were assessed in subjects with early and established Aß deposition. METHODS: The study population consisted of 686 subjects (n = 287 (cognitively normal healthy controls), n = 166 (subjects with subjective cognitive decline (SCD)), n = 129 (subjects with MCI), and n = 101 (subjects with AD dementia)). Three categories in the Aß-deposition continuum were defined based on the developed SUVR cutoffs: Aß-negative subjects, subjects with early Aß deposition ("gray zone"), and subjects with established Aß pathology. RESULTS: SUVR using the whole cerebellum as the reference region and centiloid (CL) cutoffs for early and established amyloid pathology were 1.10 (13.5 CL) and 1.24 (35.7 CL), respectively. Cingulate cortices and precuneus, frontal, and inferior lateral temporal cortices were the regions showing the initial pathological tracer retention. Subjects in the "gray zone" or with established Aß pathology accumulated more amyloid over time than Aß-negative subjects. After a 4-year clinical follow-up, none of the Aß-negative or the gray zone subjects progressed to AD dementia while 91% of the MCI subjects with established Aß pathology progressed. Tau deposition was infrequent in those subjects without established Aß pathology. CONCLUSIONS: This study supports the utility of using two cutoffs for amyloid PET abnormality defining a "gray zone": a lower cutoff of 13.5 CL indicating emerging Aß pathology and a higher cutoff of 35.7 CL where amyloid burden levels correspond to established neuropathology findings. These cutoffs define a subset of subjects characterized by pre-AD dementia levels of amyloid burden that precede other biomarkers such as tau deposition or clinical symptoms and accelerated amyloid accumulation. The determination of different amyloid loads, particularly low amyloid levels, is useful in determining who will eventually progress to dementia. Quantitation of amyloid provides a sensitive measure in these low-load cases and may help to identify a group of subjects most likely to benefit from intervention. TRIAL REGISTRATION: Data used in this manuscript belong to clinical trials registered in ClinicalTrials.gov ( NCT00928304 , NCT00750282 , NCT01138111 , NCT02854033 ) and EudraCT (2014-000798-38).

Validation of a spatial normalization method using a principal component derived adaptive template for [18F]florbetaben PET.

Quantification may help in the context of amyloid-ß positron emission tomography (PET). Quantification typically requires that PET images be spatially normalized, a process that can be subject to bias. We herein aimed to test whether a principal component approach (PCA) previously applied to [18F]flutemetamol PET extends to [18F]florbetaben. PCA was applied to [18F]florbetaben PET data for 132 subjects (70 Alzheimer dementia, 62 controls) and used to generate an adaptive synthetic template. Spatial normalization of [18F]florbetaben data using this approach was compared to that achieved using SPM12's magnetic resonance (MR) imaging driven algorithm. The two registration methods showed high agreement and minimal difference in standardized uptake value ratios (SUVR) (R2 = 0.997 using cerebellum as reference region and 0.996 using the pons). Our method allows for robust and accurate registration of [18F]florbetaben images to template space, without the need for an MR image, and may prove of value in clinical and research settings.

Tau PET imaging with 18F-PI-2620 in Patients with Alzheimer Disease and Healthy Controls: A First-in-Humans Study.

18F-PI-2620 is a PET tracer with high binding affinity for aggregated tau, a key pathologic feature of Alzheimer disease (AD) and other neurodegenerative disorders. Preclinically, 18F-PI-2620 binds to both 3-repeat and 4-repeat tau isoforms. The purpose of this first-in-humans study was to evaluate the ability of 18F-PI-2620 to detect tau pathology in AD patients using PET imaging, as well as to assess the safety and tolerability of this new tau PET tracer. Methods: Participants with a clinical diagnosis of probable AD and healthy controls (HCs) underwent dynamic 18F-PI-2620 PET imaging for 180 min. 18F-PI-2620 binding was assessed visually and quantitatively using distribution volume ratios (DVR) estimated from noninvasive tracer kinetics and SUV ratio (SUVR) measured at different time points after injection, with the cerebellar cortex as the reference region. Time-activity curves and SUVR were assessed in AD and HC subjects, as well as DVR and SUVR correlations and effect size (Cohen's d) over time. Results:18F-PI-2620 showed peak brain uptake around 5 min after injection and fast washout from nontarget regions. In AD subjects, focal asymmetric uptake was evident in temporal and parietal lobes, precuneus, and posterior cingulate cortex. DVR and SUVR in these regions were significantly higher in AD subjects than in HCs. Very low background signal was observed in HCs. 18F-PI-2620 administration was safe and well tolerated. SUVR time-activity curves in most regions and subjects achieved a secular equilibrium after 40 min after injection. A strong correlation (R2 > 0.93) was found between noninvasive DVR and SUVR for all imaging windows starting at more than 30 min after injection. Similar effect sizes between AD and HC groups were obtained across the different imaging windows. 18F-PI-2620 uptake in neocortical regions significantly correlated with the degree of cognitive impairment. Conclusion: Initial clinical data obtained in AD and HC subjects demonstrated a high image quality and excellent signal-to-noise ratio of 18F-PI-2620 PET for imaging tau deposition in AD subjects. Noninvasive quantification using DVR and SUVR for 30-min imaging windows between 30 and 90 min after injection-for example, 45-75 min-provides robust and significant discrimination between AD and HC subjects. 18F-PI-2620 uptake in expected regions correlates strongly with neurocognitive performance.

Evaluation of Dosimetry, Quantitative Methods, and Test-Retest Variability of 18F-PI-2620 PET for the Assessment of Tau Deposits in the Human Brain.

18F-PI-2620 is a next-generation tau PET tracer that has demonstrated ability to image the spatial distribution of suspected tau pathology. The objective of this study was to assess the tracer biodistribution, dosimetry, and quantitative methods of 18F-PI-2620 in the human brain. Full kinetic modeling to quantify tau load was investigated. Noninvasive kinetic modeling and semiquantitative methods were evaluated against the full tracer kinetics. Finally, the reproducibility of PET measurements from test and retest scans was assessed. Methods: Three healthy controls (HCs) and 4 Alzheimer disease (AD) subjects underwent 2 dynamic PET scans, including arterial sampling. Distribution volume ratio (DVR) was estimated using full tracer kinetics (reversible 2-tissue-compartment [2TC] model and Logan graphical analysis [LGA]) and noninvasive kinetic models (noninvasive LGA [NI-LGA] and the multilinear reference tissue model [MRTM2]). SUV ratio (SUVR) was determined at different imaging windows after injection. The correlation between DVR and SUVR, effect size (Cohen's d), and test-retest variability (TRV) were evaluated. Additionally, 6 HCs received 1 tracer administration and underwent whole-body PET for dosimetry calculation. Organ doses and the whole-body effective dose were calculated using OLINDA 2.0. Results: A strong correlation was found across different kinetic models (R2 > 0.97) and between DVR(2TC) and SUVR between 30 and 90 min, with an R2 of more than 0.95. Secular equilibrium was reached at around 40 min after injection in most regions and subjects. TRV and effect size for SUVR across different regions were similar at 30-60 min (TRV, 3.8%; Cohen's d, 3.80), 45-75 min (TRV, 4.3%; Cohen's d, 3.77) and 60-90 min (TRV, 4.9%; Cohen's d, 3.73) and increased at later time points. Elimination was via the hepatobiliary and urinary systems. The whole-body effective dose was 33.3 ± 2.1 µSv/MBq for an adult female and 33.1 ± 1.4 µSv/MBq for an adult male, with a 1.5-h urinary bladder voiding interval. Conclusion:18F-PI-2620 exhibits fast kinetics, suitable dosimetry, and low TRV. DVR measured using the 2TC model with arterial sampling correlated strongly with DVR measured by NI-LGA, MRTM2, and SUVR. SUVR can be used for 18F-PI-2620 PET quantification of tau deposits, avoiding arterial blood sampling. Static 18F-PI-2620 PET scans between 45 and 75 min after injection provide excellent quantification accuracy, a large effect size, and low TRV.

Comparison of 18F-florbetaben quantification results using the standard Centiloid, MR-based, and MR-less CapAIBL® approaches: Validation against histopathology.

INTRODUCTION: 18F-florbetaben is currently approved for the visual rule out of ß-amyloid (Aß) pathology. It is also used for recruitment and as an outcome measure in therapeutic trials, requiring accurate and reproducible quantification of Aß burden in the brain. METHODS: Data from eighty-eight subjects (52 male subjects, aged 79.8 ± 10.6 years) who underwent antemortem 18F-florbetaben positron emission tomography scan and magnetic resonance imaging less than a year before neuropathological assessment at autopsy were evaluated. Image analysis was performed using the standard Centiloid (CL) statistical parametric mapping approach and CapAIBL®. Imaging results were compared against autopsy data. RESULTS: Against combined Bielschowsky silver staining and immunohistochemistry histopathological scores, statistical parametric mapping had 96% sensitivity, 96% specificity, and 95% accuracy, whereas magnetic resonance-less CapAIBL standardized uptake value ratioWhole Cerebellum had 94% sensitivity, 96% specificity, and 95% accuracy. Based on the combined histopathological scores, a CL threshold band of 19 ± 7 CL was determined. DISCUSSION: Quantification of 18F-florbetaben positron emission tomography scans using magnetic resonance-based and magnetic resonance-less CapAIBL® approaches showed high agreement, establishing a pathology-based threshold in CL.

ß-Amyloid accumulation in the human brain after one night of sleep deprivation.

The effects of acute sleep deprivation on ß-amyloid (Aß) clearance in the human brain have not been documented. Here we used PET and 18F-florbetaben to measure brain Aß burden (ABB) in 20 healthy controls tested after a night of rested sleep (baseline) and after a night of sleep deprivation. We show that one night of sleep deprivation, relative to baseline, resulted in a significant increase in Aß burden in the right hippocampus and thalamus. These increases were associated with mood worsening following sleep deprivation, but were not related to the genetic risk (APOE genotype) for Alzheimer's disease. Additionally, baseline ABB in a range of subcortical regions and the precuneus was inversely associated with reported night sleep hours. APOE genotyping was also linked to subcortical ABB, suggesting that different Alzheimer's disease risk factors might independently affect ABB in nearby brain regions. In summary, our findings show adverse effects of one-night sleep deprivation on brain ABB and expand on prior findings of higher Aß accumulation with chronic less sleep.

Validation of Noninvasive Tracer Kinetic Analysis of 18F-Florbetaben PET Using a Dual-Time-Window Acquisition Protocol.

Accurate amyloid PET quantification is necessary for monitoring amyloid-ß accumulation and response to therapy. Currently, most of the studies are analyzed using the static SUV ratio (SUVR) approach because of its simplicity. However, this approach may be influenced by changes in cerebral blood flow (CBF) or radiotracer clearance. Full tracer kinetic models require arterial blood sampling and dynamic image acquisition. The objectives of this work were, first, to validate a noninvasive kinetic modeling approach for 18F-florbetaben PET using an acquisition protocol with the best compromise between quantification accuracy and simplicity and, second, to assess the impact of CBF changes and radiotracer clearance on SUVRs and noninvasive kinetic modeling data in 18F-florbetaben PET. Methods: Using data from 20 subjects (10 patients with probable Alzheimer dementia and 10 healthy volunteers), the nondisplaceable binding potential (BPND) obtained from the full kinetic analysis was compared with the SUVR and with noninvasive tracer kinetic methods (simplified reference tissue model and multilinear reference tissue model 2). Various approaches using shortened or interrupted acquisitions were compared with the results of the full acquisition (0-140 min). Simulations were performed to assess the effect of CBF and radiotracer clearance changes on SUVRs and noninvasive kinetic modeling outputs. Results: An acquisition protocol using time windows of 0-30 and 120-140 min with appropriate interpolation of the missing time points provided the best compromise between patient comfort and quantification accuracy. Excellent agreement was found between BPND obtained using the full protocol and BPND obtained using the dual-window protocol (for multilinear reference tissue model 2, BPND [dual-window] = 0.01 + 1.00·BPND [full], R2 = 0.97; for simplified reference tissue model, BPND [dual-window] = 0.05 + 0.92·BPND [full], R2 = 0.93). Simulations showed a limited impact of CBF and radiotracer clearance changes on multilinear reference tissue model parameters and SUVR. Conclusion: This study demonstrated accurate noninvasive kinetic modeling of 18F-florbetaben PET data using a dual-window acquisition, thus providing a good compromise between quantification accuracy, scan duration, and patient burden. The influence of CBF and radiotracer clearance changes on amyloid-ß load estimates was small. For most clinical research applications, the SUVR approach is appropriate. However, for longitudinal studies in which maximum quantification accuracy is desired, this noninvasive dual-window acquisition with kinetic analysis is recommended.

Patient and Caregiver Assessment of the Benefits From the Clinical Use of Amyloid PET Imaging.

INTRODUCTION: Few studies to date have explored patient and caregiver views on the clinical use of amyloid positron emission tomography (PET). METHODS: A 7-item questionnaire assessing patient and caregiver views (510 total respondents) toward amyloid PET imaging was advertised broadly through alz.org/trialmatch. RESULTS: We received 510 unique responses from 48 US states, 2 Canadian provinces, the Dominican Republic, and Greece. Both patients and caregivers indicated that they would want to receive amyloid imaging if offered the opportunity. Over 88% of respondents had a positive response (∼10% with neutral and 2% with negative responses) to whether amyloid PET should be offered routinely and be reimbursed. Such information was felt to be useful for long-term legal, financial, and health care planning. Respondents identifying with early age cognitive decline (younger than 65 y) were more likely to explore options for disability insurance (P=0.03). Responders from the Midwest were more likely to utilize information from amyloid imaging for legal planning (P=0.02), disability insurance (P=0.02), and life insurance (P=0.04) than other US regions. DISCUSSION: Patients and caregivers supported the use of amyloid PET imaging in clinical practice and felt that the information would provide significant benefits particularly in terms of future planning.

18F-Florbetaben PET beta-amyloid binding expressed in Centiloids.

PURPOSE: The Centiloid (CL) method enables quantitative values from Aß-amyloid (Aß) imaging to be expressed in a universal unit providing pathological, diagnostic and prognostic thresholds in clinical practice and research and allowing integration of multiple tracers and methods. The method was developed for 11C-PiB scans with zero CL set as the average in young normal subjects and 100 CL the average in subjects with mild Alzheimer's disease (AD). The method allows derivation of equations to convert the uptake value of any tracer into the same standard CL units but first requires head-to-head comparison with 11C-PiB results. We derived the equation to express 18F-florbetaben (FBB) binding in CL units. METHODS: Paired PiB and FBB PET scans were obtained in 35 subjects. including ten young normal subjects aged under 45 years (33 ± 8 years). FBB images were acquired from 90 to 110 min after injection. Spatially normalized images were analysed using the standard CL method (SPM8 coregistration of PET data to MRI data and the MNI-152 atlas) and standard CL regions (cortex and whole cerebellum downloaded from http://www.gaain.org ). RESULTS: FBB binding was strongly correlated with PiB binding (R 2 = 0.96, SUVRFBB = 0.61 × SUVRPiB + 0.39). The equation to derive CL values from FBB SUVR was CL units = 153.4 × SUVRFBB - 154.9. The CL value in the young normal subjects was -1.08 ± 6.81 for FBB scans compared to -0.32 ± 3.48 for PiB scans, giving a variance ratio of 1.96 (SDFBB CL/SDPiB CL). CONCLUSIONS: 18F-FBB binding is strongly correlated with PiB binding and FBB results can now be expressed in CL units.

Optimized classification of 18F-Florbetaben PET scans as positive and negative using an SUVR quantitative approach and comparison to visual assessment.

INTRODUCTION: Standardized uptake value ratios (SUVRs) calculated from cerebral cortical areas can be used to categorize 18F-Florbetaben (FBB) PET scans by applying appropriate cutoffs. The objective of this work was first to generate FBB SUVR cutoffs using visual assessment (VA) as standard of truth (SoT) for a number of reference regions (RR) (cerebellar gray matter (GCER), whole cerebellum (WCER), pons (PONS), and subcortical white matter (SWM)). Secondly, to validate the FBB PET scan categorization performed by SUVR cutoffs against the categorization made by post-mortem histopathological confirmation of the Aß presence. Finally, to evaluate the added value of SUVR cutoff categorization to VA. METHODS: SUVR cutoffs were generated for each RR using FBB scans from 143 subjects who were visually assessed by 3 readers. SUVR cutoffs were validated in 78 end-of life subjects using VA from 8 independent blinded readers (3 expert readers and 5 non-expert readers) and histopathological confirmation of the presence of neuritic beta-amyloid plaques as SoT. Finally, the number of correctly or incorrectly classified scans according to pathology results using VA and SUVR cutoffs was compared. RESULTS: Composite SUVR cutoffs generated were 1.43 (GCER), 0.96 (WCER), 0.78 (PONS) and 0.71 (SWM). Accuracy values were high and consistent across RR (range 83-94% for histopathology, and 85-94% for VA). SUVR cutoff performed similarly as VA but did not improve VA classification of FBB scans read either by expert readers or the majority read but provided higher accuracy than some non-expert readers. CONCLUSION: The accurate scan classification obtained in this study supports the use of VA as SoT to generate site-specific SUVR cutoffs. For an elderly end of life population, VA and SUVR cutoff categorization perform similarly in classifying FBB scans as Aß-positive or Aß-negative. These results emphasize the additional contribution that SUVR cutoff classification may have compared with VA performed by non-expert readers.

Optimal Reference Region to Measure Longitudinal Amyloid-ß Change with 18F-Florbetaben PET.

Accurate measurement of changes in amyloid-ß (Aß) deposition over time is important in longitudinal studies, particularly in anti-Aß therapeutic trials. To achieve this, the optimal reference region (RR) must be selected to reduce variance of Aß PET measurements, allowing early detection of treatment efficacy. The aim of this study was to determine the RR that allows earlier detection of subtle Aß changes using 18F-florbetaben PET. Methods: Forty-five patients with mild cognitive impairment (mean age ± SD, 72.69 ± 6.54 y; 29 men/16 women) who underwent up to 3 18F-florbetaben scans were included. Baseline scans were visually classified as high (Aß+) or low (Aß-) amyloid. Six cortical regions were quantified using a standardized region-of-interest atlas applied to the spatially normalized gray matter image obtained from segmentation of the baseline T1-weighted volumetric MRI. Four RRs (cerebellar gray matter [CGM], whole cerebellum [WCER], pons, and subcortical white matter [SWM]) were studied. The SUV ratio (SUVR) for each RR was calculated by dividing cortex activity by RR activity, with a composite SUVR averaged over 6 cortical regions. SUVR increase from baseline to 1 and 2 y, and percentage Aß deposition per year, were assessed across Aß+ and Aß- groups. Results: SUVs for any RR were not significantly different over time. Percentage Aß accumulation per year derived from composite SUVR was 0.10 ± 1.72 (Aß-) and 1.36 ± 1.98 (Aß+) (P = 0.02) for CGM and 0.13 ± 1.47 and 1.32 ± 1.75 (P = 0.01), respectively, for WCER. Compared with baseline, the composite SUVR increase in Aß+ scans was significantly larger than in Aß- scans at 1 y (P = 0.04 [CGM]; P = 0.03 [WCER]) and 2 y (P = 0.02 [CGM]; P = 0.01 [WCER]) using these 2 RRs. Significant SUVR changes using the pons as the RR were detected only at 2 y (P = 0.46 [1 y], P = 0.001 [2 y]). SUVR using the SWM as the RR showed no significant differences at either follow-up (P = 0.39 [1 y], P = 0.09 [2 y]). Conclusion: RR selection influences reliable early measurement of Aß changes over time. Compared with SWM and pons, which do not fulfil the RR requirements and have limited sensitivity to detect Aß changes, cerebellar RRs are recommended for 18F-florbetaben PET because they allow earlier detection of Aß accumulation.

Advances in Aß plaque detection and the value of knowing: overcoming challenges to improving patient outcomes in Alzheimer's disease.

Clinical diagnosis of Alzheimer's disease (AD) can be challenging as numerous diseases mimic the characteristics of AD. In this light, recent guidelines developed by different associations and working groups point out the need for biomarkers to support AD diagnosis. This paper discusses 18F-labeled radiotracers (which are indicated for PET imaging of the brain) and ongoing clinical studies that aim to generate new evidence for the usage of amyloid imaging. In addition to their relatively long half-life, these agents are known for their high sensitivity and high negative predictive values for detection of neuritic Aß plaques. Comparisons with other biomarkers are provided and implications of diagnostic disclosures discussed. Finally, recent data from clinical trials underscore the importance of amyloid PET for detecting, quantifying and monitoring Aß plaque deposits.

Perspective: The Alzheimer's Disease Neuroimaging Initiative and the role and contributions of the Private Partner Scientific Board (PPSB).

The Alzheimer's Disease Neuroimaging Initiative (ADNI) Private Partner Scientific Board (PPSB) is comprised of representatives of private, for-profit entities (including pharmaceutical, biotechnology, diagnostics, imaging companies, and imaging contract research organizations), and nonprofit organizations that provide financial and scientific support to ADNI through the Foundation for the National Institutes of Health. The PPSB serves as an independent, open, and precompetitive forum in which all private sector and not-for-profit partners in ADNI can collaborate, share information, and offer scientific and private-sector perspectives and expertise on issues relating to the ADNI project. In this article, we review and highlight the role, activities, and contributions of the PPSB within the ADNI project, and provide a perspective on remaining unmet needs and future directions.

The influence of biological and technical factors on quantitative analysis of amyloid PET: Points to consider and recommendations for controlling variability in longitudinal data.

In vivo imaging of amyloid burden with positron emission tomography (PET) provides a means for studying the pathophysiology of Alzheimer's and related diseases. Measurement of subtle changes in amyloid burden requires quantitative analysis of image data. Reliable quantitative analysis of amyloid PET scans acquired at multiple sites and over time requires rigorous standardization of acquisition protocols, subject management, tracer administration, image quality control, and image processing and analysis methods. We review critical points in the acquisition and analysis of amyloid PET, identify ways in which technical factors can contribute to measurement variability, and suggest methods for mitigating these sources of noise. Improved quantitative accuracy could reduce the sample size necessary to detect intervention effects when amyloid PET is used as a treatment end point and allow more reliable interpretation of change in amyloid burden and its relationship to clinical course.

Surgery and brain atrophy in cognitively normal elderly subjects and subjects diagnosed with mild cognitive impairment.

BACKGROUND: Structural magnetic resonance imaging is used to longitudinally monitor the progression of Alzheimer disease from its presymptomatic to symptomatic phases. Using magnetic resonance imaging data from the Alzheimer's Disease Neuroimaging Initiative, we tested the hypothesis that surgery would impact brain parameters associated with progression of dementia. METHODS: Brain images from the neuroimaging initiative database were used to study normal volunteer subjects and patients with mild cognitive impairment for the age group 55 to 90 inclusive. We compared changes in regional brain anatomy for three visits that defined two intervisit intervals for a surgical cohort (n = 41) and a propensity matched nonsurgical control cohort (n = 123). The first interval for the surgical cohort contained the surgical date. Regional brain volumes were determined with Freesurfer and quantitatively described with J-image software (University of California at San Francisco, San Francisco, California). Statistical analysis used Repeated Measures ANCOVA (SPSS, v.18.0; Chicago, IL). RESULTS: We found that surgical patients, during the first follow-up interval (5-9 months), but not subsequently, had increased rates of atrophy for cortical gray matter and hippocampus, and lateral ventricle enlargement, as compared with nonsurgical controls. A composite score of five cognitive tests during this interval showed reduced performance for surgical patients with mild cognitive impairment. CONCLUSIONS: Elderly subjects after surgery experienced an increased rate of brain atrophy during the initial evaluation interval, a time associated with enhanced risk for postoperative cognitive dysfunction. Although there was no difference in atrophy rate by diagnosis, subjects with mild cognitive impairment suffered greater subsequent cognitive effects.