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

Exploration of neuroanatomical characteristics to differentiate prodromal Alzheimer's disease from cognitively unimpaired amyloid-positive individuals

Differentiating clinical stages based solely on positive findings from amyloid PET is challenging. We aimed to investigate the neuroanatomical characteristics at the whole-brain level that differentiate prodromal Alzheimer's disease (AD) from cognitively unimpaired amyloid-positive individuals (CU A+) in relation to amyloid deposition and regional atrophy. We included 45 CU A+ participants and 135 participants with amyloid-positive prodromal AD matched 1:3 by age, sex, and education. All participants underwent 18F-florbetaben positron emission tomography and 3D structural T1-weighted magnetic resonance imaging. We compared the standardized uptake value ratios (SUVRs) and volumes in 80 regions of interest (ROIs) between CU A+ and prodromal AD groups using independent t-tests, and employed the least absolute selection and shrinkage operator (LASSO) logistic regression model to identify ROIs associated with prodromal AD in relation to amyloid deposition, regional atrophy, and their interaction. After applying False Discovery Rate correction at < 0.1, there were no differences in global and regional SUVR between CU A+ and prodromal AD groups. Regional volume differences between the two groups were observed in the amygdala, hippocampus, entorhinal cortex, insula, parahippocampal gyrus, and inferior temporal and parietal cortices. LASSO logistic regression model showed significant associations between prodromal AD and atrophy in the entorhinal cortex, inferior parietal cortex, both amygdalae, and left hippocampus. The mean SUVR in the right superior parietal cortex (beta coefficient = 0.0172) and its interaction with the regional volume (0.0672) were also selected in the LASSO model. The mean SUVR in the right superior parietal cortex was associated with an increased likelihood of prodromal AD (Odds ratio [OR] 1.602, p = 0.014), particularly in participants with lower regional volume (OR 3.389, p < 0.001). Only regional volume differences, not amyloid deposition, were observed between CU A+ and prodromal AD. The reduced volume in the superior parietal cortex may play a significant role in the progression to prodromal AD through its interaction with amyloid deposition in that region.

Quantitative Brain Amyloid PET

Since the development of amyloid tracers for PET imaging, there has been interest in quantifying amyloid burden in the brains of patients with Alzheimer disease. Quantitative amyloid PET imaging is poised to become a valuable approach in disease staging, theranostics, monitoring, and as an outcome measure for interventional studies. Yet, there are significant challenges and hurdles to overcome before it can be implemented into widespread clinical practice. On November 17, 2022, the U.S. Food and Drug Administration, Society of Nuclear Medicine and Molecular Imaging, and Medical Imaging and Technology Alliance cosponsored a public workshop comprising experts from academia, industry, and government agencies to discuss the role of quantitative brain amyloid PET imaging in staging, prognosis, and longitudinal assessment of Alzheimer disease. The workshop discussed a range of topics, including available radiopharmaceuticals for amyloid imaging; the methodology, metrics, and analytic validity of quantitative amyloid PET imaging; its use in disease staging, prognosis, and monitoring of progression; and challenges facing the field. This report provides a high-level summary of the presentations and the discussion.

Non-invasive quantification of 18F-florbetaben with total-body EXPLORER PET

BACKGROUND

Kinetic modeling of 18F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic 18F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort.

METHODS

18F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer's disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30 s after injection. Dynamic time-activity curves (TACs) for 110 min were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (VT, Vs) in key brain regions with early amyloid accumulation. Non-displaceable binding potential ([Formula: see text] was also calculated from the multi-reference tissue model (MRTM).

RESULTS

Amyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with [Formula: see text] analysis. [Formula: see text]and VT from kinetic models were correlated (r² = 0.46, P < 2[Formula: see text] with a stronger positive correlation observed in amyloid-positive participants, indicating reliable model fits with the IDIFs. VT from 2TCM was highly correlated ([Formula: see text]= 0.65, P < 2[Formula: see text]) with Logan graphical VT estimation.

CONCLUSION

Non-invasive quantification of amyloid binding from total-body 18F-florbetaben PET data is feasible using aorta IDIFs with high agreement between kinetic distribution volume parameters compared to [Formula: see text]in amyloid-positive and amyloid-negative older individuals.

Non-invasive quantification of 18F-florbetaben with total-body EXPLORER PET

Purpose

Kinetic modeling of 18F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic 18F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort.

Methods

18F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer's disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30 seconds after injection. Dynamic time-activity curves (TACs) for 110 minutes were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (VT, Vs) in key brain regions with early amyloid accumulation. Non-displaceable binding potential (BPND) was also calculated from the multi-reference tissue model (MRTM).

Results

Amyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with BPND analysis. BPND and VT from kinetic models were correlated (r2 = 0.46, P<2e-16) with a stronger positive correlation observed in amyloid-positive participants, indicating reliable model fits with the IDIFs. VT from 2TCM was highly correlated (r2 = 0.65, P< 2e-16) with Logan graphical VT estimation.

Conclusion

Non-invasive quantification of amyloid binding from total-body 18F-florbetaben PET data is feasible using aorta IDIFs with high agreement between kinetic distribution volume parameters compared to BPND in amyloid-positive and negative older individuals.

Alzheimer's Disease Biomarker Detection Using Field Effect Transistor-Based Biosensor

Alzheimer's disease (AD) is closely related to neurodegeneration, leading to dementia and cognitive impairment, especially in people aged > 65 years old. The detection of biomarkers plays a pivotal role in the diagnosis and treatment of AD, particularly at the onset stage. Field-effect transistor (FET)-based sensors are emerging devices that have drawn considerable attention due to their crucial ability to recognize various biomarkers at ultra-low concentrations. Thus, FET is broadly manipulated for AD biomarker detection. In this review, an overview of typical FET features and their operational mechanisms is described in detail. In addition, a summary of AD biomarker detection and the applicability of FET biosensors in this research field are outlined and discussed. Furthermore, the trends and future prospects of FET devices in AD diagnostic applications are also discussed.

Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods

PURPOSE

Amyloid positron emission tomography (PET) with [18F]florbetaben (FBB) is an established tool for detecting Aβ deposition in the brain in vivo based on visual assessment of PET scans. Quantitative measures are commonly used in the research context and allow continuous measurement of amyloid burden. The aim of this study was to demonstrate the robustness of FBB PET quantification.

METHODS

This is a retrospective analysis of FBB PET images from 589 subjects. PET scans were quantified with 15 analytical methods using nine software packages (MIMneuro, Hermes BRASS, Neurocloud, Neurology Toolkit, statistical parametric mapping (SPM8), PMOD Neuro, CapAIBL, non-negative matrix factorization (NMF), AmyloidIQ) that used several metrics to estimate Aβ load (SUVR, centiloid, amyloid load, and amyloid index). Six analytical methods reported centiloid (MIMneuro, standard centiloid, Neurology Toolkit, SPM8 (PET only), CapAIBL, NMF). All results were quality controlled.

RESULTS

The mean sensitivity, specificity, and accuracy were 96.1 ± 1.6%, 96.9 ± 1.0%, and 96.4 ± 1.1%, respectively, for all quantitative methods tested when compared to histopathology, where available. The mean percentage of agreement between binary quantitative assessment across all 15 methods and visual majority assessment was 92.4 ± 1.5%. Assessments of reliability, correlation analyses, and comparisons across software packages showed excellent performance and consistent results between analytical methods.

CONCLUSION

This study demonstrated that quantitative methods using both CE marked software and other widely available processing tools provided comparable results to visual assessments of FBB PET scans. Software quantification methods, such as centiloid analysis, can complement visual assessment of FBB PET images and could be used in the future for identification of early amyloid deposition, monitoring disease progression and treatment effectiveness.

SAM-Support-Based Electrochemical Sensor for Aβ Biomarker Detection of Alzheimer's Disease

Alzheimer's disease has taken the spotlight as a neurodegenerative disease which has caused crucial issues to both society and the economy. Specifically, aging populations in developed countries face an increasingly serious problem due to the increasing budget for patient care and an inadequate labor force, and therefore a solution is urgently needed. Recently, diverse techniques for the detection of Alzheimer's biomarkers have been researched and developed to support early diagnosis and treatment. Among them, electrochemical biosensors and electrode modification proved their effectiveness in the detection of the Aβ biomarker at appropriately low concentrations for practice and point-of-care application. This review discusses the production and detection ability of amyloid beta, an Alzheimer's biomarker, by electrochemical biosensors with SAM support for antibody conjugation. In addition, future perspectives on SAM for the improvement of electrochemical biosensors are also proposed and discussed.

Feasibility evaluation of middle-phase 18F-florbetaben positron emission tomography imaging using centiloid quantification and visual assessment

Background

18F-florbetaben (FBB) positron emission tomography (PET) scan has been widely used in research and routine clinical practice. Most studies used late-phase (scanning from 90 to 110 min after injection) FBB scans to generate beta-amyloid accumulation data. The feasibility of middle-phase scan is seldom discussed. Using the middle-phase data can shorten the patients' waiting between the injection and scan, and hospital can acquire more flexible schedule of routine scan.

Methods

Paired middle-phase (60-80 min) FBB scans and standard (90-110 min) FBB scans were obtained from 27 subjects (12 neurodegenerative dementia, 8 mild cognitive impairment, 3 normal control, and 4 patients not suffering from neurodegenerative dementia). Standardized uptake value ratios (SUVRs) were calculated and converted to centiloid (CL) scale to investigate the impact on image quantification. CL pipeline validation were performed to build an equation converting the middle-phase data into equivalent standard scans. Cohen's kappa of binary interpretation and brain amyloid plaque load (BAPL) score were also used to evaluate the intrareader agreement of the FBB image from the two protocols.

Results

The middle-phase FBB SUVR showed an excellent correlation, which provided a linear regression equation of SUVRFBB60-80 = 0.88 × SUVRFBB90-110 + 0.07, with R2=0.98. The slope of the equation indicated that there was bias between the middle and standard acquisition. This can be converted into the CL scale using CL = 174.68 × SUVR - 166.39. Cohen's kappa of binary interpretation and BAPL score were 1.0 (P<0.0001).

Conclusions

Our findings indicate that the middle-phase FBB protocol is feasible in clinical applications for scans that are at either end of beta-amyloid spectrum, which provides comparable semiquantitative results to standard scan. Patient's waiting time between the injection and scan can be shortened.

International Nuclear Medicine Consensus on the Clinical Use of Amyloid Positron Emission Tomography in Alzheimer's Disease

Alzheimer's disease (AD) is the main cause of dementia, with its diagnosis and management remaining challenging. Amyloid positron emission tomography (PET) has become increasingly important in medical practice for patients with AD. To integrate and update previous guidelines in the field, a task group of experts of several disciplines from multiple countries was assembled, and they revised and approved the content related to the application of amyloid PET in the medical settings of cognitively impaired individuals, focusing on clinical scenarios, patient preparation, administered activities, as well as image acquisition, processing, interpretation and reporting. In addition, expert opinions, practices, and protocols of prominent research institutions performing research on amyloid PET of dementia are integrated. With the increasing availability of amyloid PET imaging, a complete and standard pipeline for the entire examination process is essential for clinical practice. This international consensus and practice guideline will help to promote proper clinical use of amyloid PET imaging in patients with AD.

The RSNA QIBA Profile for Amyloid PET as an Imaging Biomarker for Cerebral Amyloid Quantification

A standardized approach to acquiring amyloid PET images increases their value as disease and drug response biomarkers. Most 18F PET amyloid brain scans often are assessed only visually (per regulatory labels), with a binary decision indicating the presence or absence of Alzheimer disease amyloid pathology. Minimizing technical variance allows precise, quantitative SUV ratios (SUVRs) for early detection of β-amyloid plaques and allows the effectiveness of antiamyloid treatments to be assessed with serial studies. Methods: The Quantitative Imaging Biomarkers Alliance amyloid PET biomarker committee developed and validated a profile to characterize and reduce the variability of SUVRs, increasing statistical power for these assessments. Results: On achieving conformance, sites can justify a claim that brain amyloid burden reflected by the SUVR is measurable to a within-subject coefficient of variation of no more than 1.94% when the same radiopharmaceutical, scanner, acquisition, and analysis protocols are used. Conclusion: This overview explains the claim, requirements, barriers, and potential future developments of the profile to achieve precision in clinical and research amyloid PET imaging.

Cortical Amyloid Burden Relates to Basal Forebrain Volume in Subjective Cognitive Decline

BACKGROUND

Atrophy of cholinergic basal forebrain (BF) nuclei is a frequent finding in magnetic resonance imaging (MRI) volumetry studies that examined patients with prodromal or clinical Alzheimer's disease (AD), but less clear for individuals in earlier stages of the clinical AD continuum.

OBJECTIVE

To examine BF volume reductions in subjective cognitive decline (SCD) participants with AD pathologic changes.

METHODS

The present study compared MRI-based BF volume measurements in age- and sex-matched samples of N = 24 amyloid-positive and N = 24 amyloid-negative SCD individuals, based on binary visual ratings of Florbetaben positron emission tomography (PET) measurements. Additionally, we assessed associations of BF volume with cortical amyloid burden, based on semiquantitative Centiloid (CL) analyses.

RESULTS

Group differences approached significance for BF total volume (p = 0.061) and the Ch4 subregion (p = 0.059) only, showing the expected relative volume reductions for the amyloid-positive subgroup. There were also significant inverse correlations between BF volumes and CL values, which again were most robust for BF total volume and the Ch4 subregion.

CONCLUSIONS

The results are consistent with the hypothesis that amyloid-positive SCD individuals, which are considered to represent a transitional stage on the clinical AD continuum, already show incipient alterations of BF integrity. The negative association with a continuous measure of cortical amyloid burden also suggests that this may reflect an incremental process. Yet, further research is needed to evaluate whether BF changes already emerge at "grey zone" levels of amyloid accumulation, before amyloidosis is reliably detected by PET visual readings.

Assessment of Alzheimer's Disease Imaging Biomarkers in World Trade Center Responders with Cognitive Impairment at Midlife

Purpose  Incidence of early onset neurocognitive dysfunction has been reported in World Trade Center (WTC) responders. Ongoing studies are investigating the underlying etiology, as we are concerned that an underlying risk of neurodegenerative dementia may be occurring because of their stressful and neurotoxic exposures to particulate matter when they responded to the search and rescue efforts on September 11, 2001. The purpose of this study is to report preliminary results from two ongoing positron emission tomography (PET)/magnetic resonance imaging (MRI) imaging studies investigating the presence of Alzheimer's disease (AD) biomarkers, such as β-amyloid, tau, and neurodegeneration, and compare our findings to published norms. Methods  We present findings on 12 WTC responders diagnosed with either cognitive impairment (CI) or mild cognitive impairment (MCI), now at midlife, who underwent PET/MRI brain imaging as part of ongoing studies. Six responders with CI received [ 18 F] florbetaben (FBB) to detect β-amyloidosis and six separate responders with MCI received [ 18 F] flortaucipir (FTP) to detect tauopathy. All 12 responders underwent concomitant MRI scans for gray matter volume analysis of neurodegeneration. Results  PET analysis revealed 50% FBB and 50% of FTP scans were clinically read as positive and that 50% of FTP scans identified as consistent with Braak's stage I or II. Furthermore, one responder identified as centiloid positive for AD. Gray matter volumes from MRI analyses were compared with age/sex-matched norms (Neuroquant), identifying abnormally low cortical volumes in the occipital and temporal lobes, as well as the inferior temporal gyri and the entorhinal cortex. Conclusion  These preliminary results suggest that WTC responders with neurocognitive dysfunction may be at increased risk for a neurodegenerative dementia process as a result of their exposures at September 11, 2001.

The Preventing Alzheimer's with Cognitive Training (PACT) randomized clinical trial

BACKGROUND

To address the rising prevalence of Alzheimer's disease and related dementias, effective interventions that can be widely disseminated are warranted. The Preventing Alzheimer's with Cognitive Training study (PACT) investigates a commercially available computerized cognitive training program targeting improved Useful Field of View Training (UFOVT) performance. The primary goal is to test the effectiveness of UFOVT to reduce incidence of clinically defined mild cognitive impairment (MCI) or dementia with a secondary objective to examine if effects are moderated by plasma β-amyloid level or apolipoprotein E e4 (APOE e4) allele status.

METHODS/DESIGN

This multisite study utilizes a randomized, controlled experimental design with blinded assessors and investigators. Individuals who are 65 years of age and older are recruited from the community. Eligible participants who demonstrate intact cognitive status (Montreal Cognitive Assessment score > 25) are randomized and asked to complete 45 sessions of either a commercially available computerized-cognitive training program (UFOVT) or computerized games across 2.5 years. After three years, participants are screened for cognitive decline. For those demonstrating decline or who are part of a random subsample, a comprehensive neuropsychological assessment is completed. Those who perform below a pre-specified level are asked to complete a clinical evaluation, including an MRI, to ascertain clinical diagnosis of normal cognition, MCI, or dementia. Participants are asked to provide blood samples for analyses of Alzheimer's disease related biomarkers.

DISCUSSION

The PACT study addresses the rapidly increasing prevalence of dementia. Computerized cognitive training may provide a non-pharmaceutical option for reducing incidence of MCI or dementia to improve public health.

REGISTRATION

The PACT study is registered at http://Clinicaltrials.govNCT03848312.

Diabetes and hypertension are related to amyloid-beta burden in the population-based Rotterdam Study

Higher vascular disease burden increases the likelihood of developing dementia, including Alzheimer's disease. Better understanding the association between vascular risk factors and Alzheimer's disease pathology at the predementia stage is critical for developing effective strategies to delay cognitive decline. In this work, we estimated the impact of six vascular risk factors on the presence and severity of in vivo measured brain amyloid-beta (Aβ) plaques in participants from the population-based Rotterdam Study. Vascular risk factors (hypertension, hypercholesterolaemia, diabetes, obesity, physical inactivity and smoking) were assessed 13 (2004-2008) and 7 years (2009-2014) prior to 18F-florbetaben PET (2018-2021) in 635 dementia-free participants. Vascular risk factors were associated with binary amyloid PET status or continuous PET readouts (standard uptake value ratios, SUVrs) using logistic and linear regression models, respectively, adjusted for age, sex, education, APOE4 risk allele count and time between vascular risk and PET assessment. Participants' mean age at time of amyloid PET was 69 years (range: 60-90), 325 (51.2%) were women and 190 (29.9%) carried at least one APOE4 risk allele. The adjusted prevalence estimates of an amyloid-positive PET status markedly increased with age [12.8% (95% CI 11.6; 14) in 60-69 years versus 35% (36; 40.8) in 80-89 years age groups] and APOE4 allele count [9.7% (8.8; 10.6) in non-carriers versus 38.4% (36; 40.8) to 60.4% (54; 66.8) in carriers of one or two risk allele(s)]. Diabetes 7 years prior to PET assessment was associated with a higher risk of a positive amyloid status [odds ratio (95% CI) = 3.68 (1.76; 7.61), P < 0.001] and higher standard uptake value ratios, indicating more severe Aβ pathology [standardized beta = 0.40 (0.17; 0.64), P = 0.001]. Hypertension was associated with higher SUVr values in APOE4 carriers (mean SUVr difference of 0.09), but not in non-carriers (mean SUVr difference 0.02; P = 0.005). In contrast, hypercholesterolaemia was related to lower SUVr values in APOE4 carriers (mean SUVr difference -0.06), but not in non-carriers (mean SUVr difference 0.02). Obesity, physical inactivity and smoking were not related to amyloid PET measures. The current findings suggest a contribution of diabetes, hypertension and hypercholesterolaemia to the pathophysiology of Alzheimer's disease in a general population of older non-demented adults. As these conditions respond well to lifestyle modification and drug treatment, further research should focus on the preventative effect of early risk management on the development of Alzheimer's disease neuropathology.

Beta amyloid deposition and cognitive decline in Parkinson's disease: a study of the PPMI cohort

The accumulation of beta amyloid in the brain has a complex and poorly understood impact on the progression of Parkinson's disease pathology and much controversy remains regarding its role, specifically in cognitive decline symptoms. Some studies have found increased beta amyloid burden is associated with worsening cognitive impairment in Parkinson's disease, especially in cases where dementia occurs, while other studies failed to replicate this finding. To better understand this relationship, we examined a cohort of 25 idiopathic Parkinson's disease patients and 30 healthy controls from the Parkinson's Progression Marker Initiative database. These participants underwent [¹⁸F]Florbetaben positron emission tomography scans to quantify beta amyloid deposition in 20 cortical regions. We then analyzed this beta amyloid data alongside the longitudinal Montreal Cognitive Assessment scores across 3 years to see how participant's baseline beta amyloid levels affected their cognitive scores prospectively. The first analysis we performed with these data was a hierarchical cluster analysis to help identify brain regions that shared similarity. We found that beta amyloid clusters differently in Parkinson's disease patients compared to healthy controls. In the Parkinson's disease group, increased beta amyloid burden in cluster 2 was associated with worse cognitive ability, compared to deposition in clusters 1 or 3. We also performed a stepwise linear regression where we found an adjusted R² of 0.495 (49.5%) in a model explaining the Parkinson's disease group's Montreal Cognitive Assessment score 1-year post-scan, encompassing the left gyrus rectus, the left anterior cingulate cortex, and the right parietal cortex. Taken together, these results suggest regional beta amyloid deposition alone has a moderate effect on predicting future cognitive decline in Parkinson's disease patients. The patchwork effect of beta amyloid deposition on cognitive ability may be part of what separates cognitive impairment from cognitive sparing in Parkinson's disease. Thus, we suggest it would be more useful to measure beta amyloid burden in specific brain regions rather than using a whole-brain global beta amyloid composite score and use this information as a tool for determining which Parkinson's disease patients are most at risk for future cognitive decline.

Quantification of amyloid PET for future clinical use: a state-of-the-art review

Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.

[18F]THK-5351 PET Patterns in Patients With Alzheimer's Disease and Negative Amyloid PET Findings

Background and Purpose

Alzheimer’s disease (AD) does not always mean amyloid positivity. [¹⁸F]THK-5351 has been shown to be able to detect reactive astrogliosis as well as tau accompanied by neurodegenerative changes. We evaluated the [¹⁸F]THK-5351 retention patterns in positron-emission tomography (PET) and the clinical characteristics of patients clinically diagnosed with AD dementia who had negative amyloid PET findings.

Methods

We performed 3.0-T magnetic resonance imaging, [¹⁸F]THK-5351 PET, and amyloid PET in 164 patients with AD dementia. Amyloid PET was visually scored as positive or negative. [¹⁸F]THK-5351 PET were visually classified as having an intratemporal or extratemporal spread pattern.

Results

The 164 patients included 23 (14.0%) who were amyloid-negative (age 74.9±8.3 years, mean±standard deviation; 9 males, 14 females). Amyloid-negative patients were older, had a higher prevalence of diabetes mellitus, and had better visuospatial and memory functions. The frequency of the apolipoprotein E ε4 allele was higher and the hippocampal volume was smaller in amyloid-positive patients. [¹⁸F]THK-5351 uptake patterns of the amyloid-negative patients were classified into intratemporal spread (n=10) and extratemporal spread (n=13). Neuropsychological test results did not differ significantly between these two groups. The standardized uptake value ratio of [¹⁸F]THK-5351 was higher in the extratemporal spread group (2.01±0.26 vs. 1.61±0.15, p=0.001). After 1 year, Mini Mental State Examination (MMSE) scores decreased significantly in the extratemporal spread group (-3.5±3.2, p=0.006) but not in the intratemporal spread group (-0.5±2.8, p=0.916). The diagnosis remained as AD (n=5, 50%) or changed to other diagnoses (n=5, 50%) in the intratemporal group, whereas it remained as AD (n=8, 61.5%) or changed to frontotemporal dementia (n=4, 30.8%) and other diagnoses (n=1, 7.7%) in the extratemporal spread group.

Conclusions

Approximately 70% of the patients with amyloid-negative AD showed abnormal [¹⁸F]THK-5351 retention. MMSE scores deteriorated rapidly in the patients with an extratemporal spread pattern.

Predictive Scale for Amyloid PET Positivity Based on Clinical and MRI Variables in Patients with Amnestic Mild Cognitive Impairment

The presence of amyloid-β (Aβ) deposition is considered important in patients with amnestic mild cognitive impairment (aMCI), since they can progress to Alzheimer’s disease dementia. Amyloid positron emission tomography (PET) has been used for detecting Aβ deposition, but its high cost is a significant barrier for clinical usage. Therefore, we aimed to develop a new predictive scale for amyloid PET positivity using easily accessible tools. Overall, 161 aMCI patients were recruited from six memory clinics and underwent neuropsychological tests, brain magnetic resonance imaging (MRI), apolipoprotein E (APOE) genotype testing, and amyloid PET. Among the potential predictors, verbal and visual memory tests, medial temporal lobe atrophy, APOE genotype, and age showed significant differences between the Aβ-positive and Aβ-negative groups and were combined to make a model for predicting amyloid PET positivity with the area under the curve (AUC) of 0.856. Based on the best model, we developed the new predictive scale comprising integers, which had an optimal cutoff score ≥ 3. The new predictive scale was validated in another cohort of 98 participants and showed a good performance with AUC of 0.835. This new predictive scale with accessible variables may be useful for predicting Aβ positivity in aMCI patients in clinical practice.

Association between Visceral Adipose Tissue Metabolism and Alzheimer’s Disease Pathology

The visceral adipose tissue (VAT) has been recognized as an endocrine organ, and VAT dysfunction could be a risk factor for Alzheimer’s disease (AD). We aimed to evaluate the association of VAT metabolism with AD pathology. This cross-sectional study included 54 older subjects with cognitive impairment who underwent 2-deoxy-2-[fluorine-18]-fluoro-D-glucose (¹⁸F-FDG) torso positron emission tomography (PET) and ¹⁸F-florbetaben brain PET. ¹⁸F-FDG uptake in VAT on ¹⁸F-FDG PET images was used as a marker of VAT metabolism, and subjects were classified into high and low VAT metabolism groups. A voxel-based analysis revealed that the high VAT metabolism group exhibited a significantly higher cerebral amyloid-β (Aβ) burden than the low VAT metabolism group. In the volume-of-interest analysis, multiple linear regression analyses with adjustment for age, sex, and white matter hyperintensity volume revealed that ¹⁸F-FDG uptake in VAT was significantly associated with the cerebral Aβ burden (β = 0.359, p = 0.007). In conclusion, VAT metabolism was associated with AD pathology in older subjects. Our findings suggest that VAT dysfunction could contribute to AD development.

Aquaporin-4 Polymorphisms Are Associated With Cognitive Performance in Parkinson’s Disease

Objective

Aquaporin-4 (AQP4) facilitates a sleep-enhanced interstitial brain waste clearance system. This study was conducted to determine the clinical implication of AQP4 polymorphisms in Parkinson’s disease (PD).

Methods

Three-hundred and eighty-two patients with PD and 180 healthy controls with a mean follow-up time of 66.1 months from the Parkinson’s Progression Marker Initiative study were analyzed. We examined whether AQP4 SNPs were associated with an altered rate of motor or cognitive decline using linear mixed model and Cox regression. We then investigated whether AQP4 SNPs were associated with Aβ burden as measured by 18F Florbetapir standard uptake values. Furthermore, we examined if AQP4 SNPs moderated the association between REM sleep behavior disorder (RBD) and CSF biomarkers.

Results

In patients with PD, AQP4 rs162009 (AA/AG vs. GG) was associated with slower dementia conversion, better performance in letter-number sequencing and symbol digit modalities, lower Aβ deposition in the putamen, anterior cingulum, and frontotemporal areas. In the subgroup of high RBD screening questionnaire score, rs162009 AA/AG had a higher CSF Aβ42 level. rs162009 AA/AG also had better performance in semantic fluency in healthy controls. Besides, rs68006382 (GG/GA vs. AA) was associated with faster progression to mild cognitive impairment, worse performance in letter-number sequencing, semantic fluency, and symbol digit modalities in patients with PD.

Interpretation

Genetic variations of AQP4 and subsequent alterations of glymphatic efficacy might contribute to an altered rate of cognitive decline in PD. AQP4 rs162009 is likely a novel genetic prognostic marker of glymphatic function and cognitive decline in PD.

Patterns of tau pathology identified with 18 F-MK-6240 PET imaging

INTRODUCTION

Positron emission tomography (PET) imaging for neurofibrillary tau allows investigation of the in vivo spatiotemporal progression of Alzheimer's disease (AD) pathology. We evaluated the suitability of 18 F-MK-6240 in a clinical sample and determined the relationships among 18 F-MK-6240 binding, age, cognition, and cerebrospinal fluid (CSF)-based AD biomarkers.

METHODS

Participants (n = 101, 72 ± 9 years, 52% women) underwent amyloid PET, tau PET, structural T1-weighted magnetic resonance imaging, and neuropsychological evaluation. Twenty-one participants had lumbar puncture for CSF measurement of amyloid beta (Aβ)42 , tau, and phosphorylated tau (p-tau).

RESULTS

18 F-MK-6240 recapitulated Braak staging and correlated with CSF tau and p-tau, normalized to Aβ42 . 18 F-MK-6240 negatively correlated with age across Braak regions in amyloid-positive participants, consistent with greater tau pathology in earlier onset AD. Domain-specific, regional patterns of 18 F-MK-6240 binding were associated with reduced memory, executive, and language performance, but only in amyloid-positive participants.

DISCUSSION

18 F-MK-6240 can approximate Braak staging across the AD continuum and provide region-dependent insights into biomarker-based AD models.

Impact of 40 Hz Transcranial Alternating Current Stimulation on Cerebral Tau Burden in Patients with Alzheimer's Disease: A Case Series

BACKGROUND

Alzheimer's disease (AD) is characterized by diffuse amyloid-β (Aβ) and phosphorylated Tau (p-Tau) aggregates as well as neuroinflammation. Exogenously-induced 40 Hz gamma oscillations have been showing to reduce Aβ and p-Tau deposition presumably via microglia activation in AD mouse models.

OBJECTIVE

We aimed to translate preclinical data on gamma-induction in AD patients by means of transcranial alternating current stimulation (tACS).

METHODS

Four participants with mild-to-moderate AD received 1 h of daily 40 Hz (gamma) tACS for 4 weeks (Monday to Friday) targeting the bitemporal lobes (20 h treatment duration). Participant underwent Aβ, p-Tau, and microglia PET imaging with [11C]-PiB, [18F]-FTP, and [11C]-PBR28 respectively, before and after the intervention along with electrophysiological assessment.

RESULTS

No adverse events were reported, and an increase in gamma spectral power on EEG was observed after the treatment. [18F]-FTP PET revealed a significant decrease over 2% of p-Tau burden in 3/4 patients following the tACS treatment, primarily involving the temporal lobe regions targeted by tACS and especially mesial regions (e.g., entorhinal cortex). The amount of intracerebral Aβ as measured by [11C]-PiB was not significantly influenced by tACS, whereas 1/4 reported a significant decrease of microglia activation as measured by [11C]-PBR28.

CONCLUSION

tACS seems to represent a safe and feasible option for gamma induction in AD patients, with preliminary evidence of a possible effect on protein clearance partially mimicking what is observed in animal models. Longer interventions and placebo control conditions are needed to fully evaluate the potential for tACS to slow disease progression.

Relationship between astrocyte reactivity, using novel 11C-BU99008 PET, and glucose metabolism, grey matter volume and amyloid load in cognitively impaired individuals

Post mortem neuropathology suggests that astrocyte reactivity may play a significant role in neurodegeneration in Alzheimer's disease. We explored this in vivo using multimodal PET and MRI imaging. Twenty subjects (11 older, cognitively impaired patients and 9 age-matched healthy controls) underwent brain scanning using the novel reactive astrocyte PET tracer ¹¹C-BU99008, ¹⁸F-FDG and ¹⁸F-florbetaben PET, and T1-weighted MRI. Differences between cognitively impaired patients and healthy controls in regional and voxel-wise levels of astrocyte reactivity, glucose metabolism, grey matter volume and amyloid load were explored, and their relationship to each other was assessed using Biological Parametric Mapping (BPM). Amyloid beta (Aβ)-positive patients showed greater ¹¹C-BU99008 uptake compared to controls, except in the temporal lobe, whilst further increased ¹¹C-BU99008 uptake was observed in Mild Cognitive Impairment subjects compared to those with Alzheimer's disease in the frontal, temporal and cingulate cortices. BPM correlations revealed that regions which showed reduced ¹¹C-BU99008 uptake in Aβ-positive patients compared to controls, such as the temporal lobe, also showed reduced ¹⁸F-FDG uptake and grey matter volume, although the correlations with ¹⁸F-FDG uptake were not replicated in the ROI analysis. BPM analysis also revealed a regionally-dynamic relationship between astrocyte reactivity and amyloid uptake: increased amyloid load in cortical association areas of the temporal lobe and cingulate cortices was associated with reduced ¹¹C-BU99008 uptake, whilst increased amyloid uptake in primary motor and sensory areas (in which amyloid deposition occurs later) was associated with increased ¹¹C-BU99008 uptake. These novel observations add to the hypothesis that while astrocyte reactivity may be triggered by early Aβ-deposition, sustained pro-inflammatory astrocyte reactivity with greater amyloid deposition may lead to astrocyte dystrophy and amyloid-associated neuropathology such as grey matter atrophy and glucose hypometabolism, although the evidence for glucose hypometabolism here is less strong.

Deep learning improves utility of tau PET in the study of Alzheimer's disease

INTRODUCTION

Positron emission tomography (PET) imaging targeting neurofibrillary tau tangles is increasingly used in the study of Alzheimer's disease (AD), but its utility may be limited by conventional quantitative or qualitative evaluation techniques in earlier disease states. Convolutional neural networks (CNNs) are effective in learning spatial patterns for image classification.

METHODS

18F-MK6240 (n = 320) and AV-1451 (n = 446) PET images were pooled from multiple studies. We performed iterations with differing permutations of radioligands, heuristics, and architectures. Performance was compared to a standard region of interest (ROI)-based approach on prediction of memory impairment. We visualized attention of the network to illustrate decision making.

RESULTS

Overall, models had high accuracy (> 80%) with good average sensitivity and specificity (75% and 82%, respectively), and had comparable or higher accuracy to the ROI standard. Visualizations of model attention highlight known characteristics of tau radioligand binding.

DISCUSSION

CNNs could improve tau PET's role in early disease and extend the utility of tau PET across generations of radioligands.

Development of a Low-Molecular-Weight Aβ42 Detection System Using a Enzyme-Linked Peptide Assay

Alzheimer's disease (AD) is a degenerative brain disease that is the most common cause of dementia. The incidence of AD is rapidly rising because of the aging of the world population. Because AD is presently incurable, early diagnosis is very important. The disease is characterized by pathological changes such as deposition of senile plaques and decreased concentration of the amyloid-beta 42 (Aβ42) peptide in the cerebrospinal fluid (CSF). The concentration of Aβ42 in the CSF is a well-studied AD biomarker. The specific peptide probe was screened through four rounds of biopanning, which included the phage display process. The screened peptide showed strong binding affinity in the micromolar range, and the enzyme-linked peptide assay was optimized using the peptide we developed. This diagnostic method showed specificity toward Aβ42 in the presence of other proteins. The peptide-binding site was also estimated using molecular docking analysis. Finally, the diagnostic method we developed could significantly distinguish patients who were classified based on amyloid PET images.

Harmonisation of PET imaging features with different amyloid ligands using machine learning-based classifier

PURPOSE

In this study, we used machine learning to develop a new method derived from a ligand-independent amyloid (Aβ) positron emission tomography (PET) classifier to harmonise different Aβ ligands.

METHODS

We obtained 107 paired 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) PET images at the Samsung Medical Centre. To apply the method to FMM ligand, we transferred the previously developed FBB PET classifier to test similar features from the FMM PET images for application to FMM, which in turn developed a ligand-independent Aβ PET classifier. We explored the concordance rates of our classifier in detecting cortical and striatal Aβ positivity. We investigated the correlation of machine learning-based cortical tracer uptake (ML-CTU) values quantified by the classifier between FBB and FMM.

RESULTS

This classifier achieved high classification accuracy (area under the curve = 0.958) even with different Aβ PET ligands. In addition, the concordance rate of FBB and FMM using the classifier (87.5%) was good to excellent, which seemed to be higher than that in visual assessment (82.7%) and lower than that in standardised uptake value ratio cut-off categorisation (93.3%). FBB and FMM ML-CTU values were highly correlated with each other (R = 0.903).

CONCLUSION

Our findings suggested that our novel classifier may harmonise FBB and FMM ligands in the clinical setting which in turn facilitate the biomarker-guided diagnosis and trials of anti-Aβ treatment in the research field.

Screening for cerebral amyloid angiopathy based on serological biomarkers analysis using a dielectrophoretic force-driven biosensor platform

We aimed to analyze plasma amyloid-β (Aβ)_1-40 and Aβ_1-42 using a highly sensitive dielectrophoretic-driven biosensor platform to demonstrate the possibility of precise cerebral amyloid angiopathy (CAA) diagnosis in participants classified according to Aβ-positron emission tomography (PET) positivity and the neuroimaging criteria for CAA. We prospectively recruited 25 people with non-Alzheimer's disease (non-AD) and 19 patients with Alzheimer's disease (AD), which were further classified into the CAA- and CAA+ (possible and probable CAA) groups according to the modified Boston criteria. Patients underwent plasma Aβ analysis using a highly sensitive nano-biosensor platform, Aβ-PET scanning, and detailed neuropsychological testing. As a result, the average signal levels of Aβ_1-42/1-40 differed significantly between the non-AD and AD groups, and the CAA+ group exhibited significantly higher Aβ_1-40 signal levels than the CAA- group in both non-AD and AD groups. The concordance between the Aβ_1-40 signal level and the neuroimaging criteria for CAA was nearly perfect, with areas under the curve of 0.954 (95% confidence interval (CI) 0.856-1.000), 0.969 (0.894-1.000), 0.867 (0.648-1.000), and 1.000 (1.000-1.000) in the non-AD/CAA- vs. non-AD/possible CAA, non-AD/CAA- vs. non-AD/probable CAA, AD/CAA- vs. AD/possible CAA, and AD/CAA- vs. AD/probable CAA groups, respectively. Higher Aβ_1-40 signal levels were significantly associated with the presence of CAA according to regression analyses, and the neuroimaging pattern analysis partly supported this result. Our findings suggest that measuring plasma Aβ_1-40 signal levels using a highly sensitive biosensor platform could be a useful non-invasive CAA diagnostic method.

Quantitative assessment of AD markers using naked eyes: point-of-care testing with paper-based lateral flow immunoassay

Aβ42 is one of the most extensively studied blood and Cerebrospinal fluid (CSF) biomarkers for the diagnosis of symptomatic and prodromal Alzheimer's disease (AD). Because of the heterogeneity and transient nature of Aβ42 oligomers (Aβ42Os), the development of technologies for dynamically detecting changes in the blood or CSF levels of Aβ42 monomers (Aβ42Ms) and Aβ42Os is essential for the accurate diagnosis of AD. The currently commonly used Aβ42 ELISA test kits usually mis-detected the elevated Aβ42Os, leading to incomplete analysis and underestimation of soluble Aβ42, resulting in a comprised performance in AD diagnosis. Herein, we developed a dual-target lateral flow immunoassay (dLFI) using anti-Aβ42 monoclonal antibodies 1F12 and 2C6 for the rapid and point-of-care detection of Aβ42Ms and Aβ42Os in blood samples within 30 min for AD diagnosis. By naked eye observation, the visual detection limit of Aβ42Ms or/and Aβ42Os in dLFI was 154 pg/mL. The test results for dLFI were similar to those observed in the enzyme-linked immunosorbent assay (ELISA). Therefore, this paper-based dLFI provides a practical and rapid method for the on-site detection of two biomarkers in blood or CSF samples without the need for additional expertise or equipment.

Association Between Plasma Amyloid-β and Neuropsychological Performance in Patients With Cognitive Decline

Objective: To investigate the association between plasma amyloid-β (Aβ) levels and neuropsychological performance in patients with cognitive decline using a highly sensitive nano-biosensing platform.

Methods: We prospectively recruited 44 patients with cognitive decline who underwent plasma Aβ analysis, amyloid positron emission tomography (PET) scanning, and detailed neuropsychological tests. Patients were classified into a normal control (NC, n = 25) or Alzheimer’s disease (AD, n = 19) group based on amyloid PET positivity. Multiple linear regression was performed to determine whether plasma Aβ (Aβ₄₀, Aβ₄₂, and Aβ_42/40) levels were associated with neuropsychological test results.

Results: The plasma levels of Aβ_42/40 were significantly different between the NC and AD groups and were the best predictor of amyloid PET positivity by receiver operating characteristic curve analysis [area under the curve of 0.952 (95% confidence interval, 0.892–1.000)]. Although there were significant differences in the neuropsychological performance of cognitive domains (language, visuospatial, verbal/visual memory, and frontal/executive functions) between the NC and AD groups, higher levels of plasma Aβ_42/40 were negatively correlated only with verbal and visual memory performance.

Conclusion: Our results demonstrated that plasma Aβ analysis using a nano-biosensing platform could be a useful tool for diagnosing AD and assessing memory performance in patients with cognitive decline.

Changes in LASSI-L performance over time among older adults with amnestic MCI and amyloid positivity: A preliminary study

There is a pressing need to develop measures that are sensitive to the earliest subtle cognitive changes of Alzheimer's disease (AD) to improve early detection and track disease progression. The Loewenstein-Acevedo Scales of Semantic Interference (LASSI-L) has been shown to successfully discriminate between cognitively unimpaired (CU) older adults and those with amnestic mild cognitive impairment (MCI) and to correlate with total and regional brain amyloid load. The present study investigated how the LASSI-L scores change over time among three distinct diagnostic groups. Eighty-six community-dwelling older adults underwent a baseline evaluation including: a clinical interview, a neuropsychological evaluation, Magnetic Resonance Imaging (MRI), and amyloid Positron Emission Tomography (PET). A follow up evaluation was conducted 12 months later. Initial mean values were calculated using one-way ANOVAs and chi-square analyses. Post-hoc comparisons were conducted using Tukey's Honestly Significant Difference (HSD). A 3 × 2 repeated measures analysis was utilized to examine differences in LASSI-L performance over time. The MCI amyloid positive group demonstrated a significantly greater decline in LASSI-L performance than the MCI amyloid negative and CU groups respectively. The scales that best differentiated the three groups included the Cued A2, which taps into maximum learning capacity, and Cued B2, which assesses the failure to recover from proactive semantic interference. Our findings further support the LASSI-L's discriminative validity.

Astrocyte reactivity with late-onset cognitive impairment assessed in vivo using 11C-BU99008 PET and its relationship with amyloid load

11C-BU99008 is a novel positron emission tomography (PET) tracer that enables selective imaging of astrocyte reactivity in vivo. To explore astrocyte reactivity associated with Alzheimer's disease, 11 older, cognitively impaired (CI) subjects and 9 age-matched healthy controls (HC) underwent 3T magnetic resonance imaging (MRI), 18F-florbetaben and 11C-BU99008 PET. The 8 amyloid (Aβ)-positive CI subjects had higher 11C-BU99008 uptake relative to HC across the whole brain, but particularly in frontal, temporal, medial temporal and occipital lobes. Biological parametric mapping demonstrated a positive voxel-wise neuroanatomical correlation between 11C-BU99008 and 18F-florbetaben. Autoradiography using 3H-BU99008 with post-mortem Alzheimer's brains confirmed through visual assessment that increased 3H-BU99008 binding localised with the astrocyte protein glial fibrillary acid protein and was not displaced by PiB or florbetaben. This proof-of-concept study provides direct evidence that 11C-BU99008 can measure in vivo astrocyte reactivity in people with late-life cognitive impairment and Alzheimer's disease. Our results confirm that increased astrocyte reactivity is found particularly in cortical regions with high Aβ load. Future studies now can explore how clinical expression of disease varies with astrocyte reactivity.

Clinical Characteristic in Primary Progressive Aphasia in Relation to Alzheimer's Disease Biomarkers

BACKGROUND

Primary progressive aphasia (PPA) is associated with amyloid-β (Aβ) pathology. However, clinical feature of PPA based on Aβ positivity remains unclear.

OBJECTIVE

We aimed to assess the prevalence of Aβ positivity in patients with PPA and compare the clinical characteristics of patients with Aβ-positive (A+) and Aβ-negative (A-) PPA. Further, we applied Aβ and tau classification system (AT system) in patients with PPA for whom additional information of in vivo tau biomarker was available.

METHODS

We recruited 110 patients with PPA (41 semantic [svPPA], 27 non-fluent [nfvPPA], 32 logopenic [lvPPA], and 10 unclassified [ucPPA]) who underwent Aβ-PET imaging at multi centers. The extent of language impairment and cortical atrophy were compared between the A+ and A-PPA subgroups using general linear models.

RESULTS

The prevalence of Aβ positivity was highest in patients with lvPPA (81.3%), followed by ucPPA (60.0%), nfvPPA (18.5%), and svPPA (9.8%). The A+ PPA subgroup manifested cortical atrophy mainly in the left superior temporal/inferior parietal regions and had lower repetition scores compared to the A-PPA subgroup. Further, we observed that more than 90% (13/14) of the patients with A+ PPA had tau deposition.

CONCLUSION

Our findings will help clinicians understand the patterns of language impairment and cortical atrophy in patients with PPA based on Aβ deposition. Considering that most of the A+ PPA patents are tau positive, understanding the influence of Alzheimer's disease biomarkers on PPA might provide an opportunity for these patients to participate in clinical trials aimed for treating atypical Alzheimer's disease.

Machine Learning for the Prediction of Amyloid Positivity in Amnestic Mild Cognitive Impairment

BACKGROUND

Amyloid-β (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is important for predicting conversion to Alzheimer's disease. However, Aβ evaluation through Aβ positron emission tomography (PET) is limited due to high cost and safety issues.

OBJECTIVE

We therefore aimed to develop and validate prediction models of Aβ positivity for aMCI using optimal interpretable machine learning (ML) approaches utilizing multimodal markers.

METHODS

We recruited 529 aMCI patients from multiple centers who underwent Aβ PET. We trained ML algorithms using a training cohort (324 aMCI from Samsung medical center) with two-phase modelling: model 1 included age, gender, education, diabetes, hypertension, apolipoprotein E genotype, and neuropsychological test scores; model 2 included the same variables as model 1 with additional MRI features. We used four-fold cross-validation during the modelling and evaluated the models on an external validation cohort (187 aMCI from the other centers).

RESULTS

Model 1 showed good accuracy (area under the receiver operating characteristic curve [AUROC] 0.837) in cross-validation, and fair accuracy (AUROC 0.765) in external validation. Model 2 led to improvement in the prediction performance with good accuracy (AUROC 0.892) in cross validation compared to model 1. Apolipoprotein E genotype, delayed recall task scores, and interaction between cortical thickness in the temporal region and hippocampal volume were the most important predictors of Aβ positivity.

CONCLUSION

Our results suggest that ML models are effective in predicting Aβ positivity at the individual level and could help the biomarker-guided diagnosis of prodromal AD.

Salivary lactoferrin is associated with cortical amyloid-beta load, cortical integrity, and memory in aging

BACKGROUND

Aging is associated with declining protective immunity and persistent low-grade inflammatory responses, which significantly contribute to Alzheimer's disease (AD) pathogenesis. Detecting aging-related cerebral vulnerability associated with deterioration of the immune system requires from non-invasive biomarkers able to detect failures in the brain-immunity connection. Reduced levels of salivary lactoferrin (sLF), an iron-binding protein with immunomodulatory activity, have been related to AD diagnosis. However, it remains unknown whether decreased sLF is associated with increased cortical amyloid-beta (Aβ) load and/or with loss of cortical integrity in normal aging.

METHODS

Seventy-four cognitively normal older adults (51 females) participated in the study. We applied multiple linear regression analyses to assess (i) whether sLF is associated with cortical Aβ load measured by 18F-Florbetaben (FBB)-positron emission tomography (PET), (ii) whether sLF-related variations in cortical thickness and cortical glucose metabolism depend on global Aβ burden, and (iii) whether such sLF-related cortical abnormalities moderate the relationship between sLF and cognition.

RESULTS

sLF was negatively associated with Aβ load in parieto-temporal regions. Moreover, sLF was related to thickening of the middle temporal cortex, increased FDG uptake in the posterior cingulate cortex, and poorer memory. These associations were stronger in individuals showing the highest Aβ burden.

CONCLUSIONS

sLF levels are sensitive to variations in cortical Aβ load, structural and metabolic cortical abnormalities, and subclinical memory impairment in asymptomatic older adults. These findings provide support for the use of sLF as a non-invasive biomarker of cerebral vulnerability in the general aging population.

Dual-phase 18F-florbetaben PET provides cerebral perfusion proxy along with beta-amyloid burden in Alzheimer's disease

BACKGROUND

This study investigated changes in brain perfusion and Aβ burden according to the progression of Alzheimer's disease (AD) by using a dual-phase ¹⁸F-florbetaben (FBB) PET protocol.

METHODS

Sixty subjects, including 12 with Aβ-negative normal cognition (Aβ^-NC), 32 with Aβ-positive mild cognitive impairment (Aβ⁺MCI), and 16 with Aβ-positive AD (Aβ⁺AD), were enrolled. A dynamic PET scan was obtained in the early phase (0-10 min, eFBB) and delayed phase (90-110 min, dFBB), which were then averaged into a single frame, respectively. In addition to the averaged eFBB, an R1 parametric map was calculated from the eFBB scan based on a simplified reference tissue model (SRTM). Between-group regional and voxel-wise analyses of the images were performed. The associations between cognitive profiles and PET-derived parameters were investigated.

RESULTS

Both the R1 and eFBB perfusion reductions in the cortical regions were not significantly different between the Aβ^-NC and Aβ⁺MCI groups, while they were significantly reduced from the Aβ⁺MCI to Aβ⁺AD groups in regional and voxel-wise analyses. However, cortical Aβ depositions on dFBB were not significantly different between the Aβ⁺MCI and Aβ⁺AD groups. There were strong positive correlations between the R1 and eFBB images in regional and voxel-wise analyses. Both perfusion components showed significant correlations with general and specific cognitive profiles.

CONCLUSION

The results of this study demonstrated the feasibility of dual-phase ¹⁸F-FBB PET to evaluate different trajectories of dual biomarkers for neurodegeneration and Aβ burden over the course of AD. In addition, both eFBB and SRTM-based R1 can provide robust indices of brain perfusion.

MRI-Visible Perivascular Spaces in the Centrum Semiovale Are Associated with Brain Amyloid Deposition in Patients with Alzheimer Disease-Related Cognitive Impairment

BACKGROUND AND PURPOSE

The association of perivascular spaces in the centrum semiovale with amyloid accumulation among patients with Alzheimer disease-related cognitive impairment is unknown. We evaluated this association in patients with Alzheimer disease-related cognitive impairment and β-amyloid deposition, assessed with [¹⁸F] florbetaben PET/CT.

MATERIALS AND METHODS

MR imaging and [¹⁸F] florbetaben PET/CT images of 144 patients with Alzheimer disease-related cognitive impairment were retrospectively evaluated. MR imaging-visible perivascular spaces were rated on a 4-point visual scale: a score of ≥3 or <3 indicated a high or low degree of MR imaging-visible perivascular spaces, respectively. Amyloid deposition was evaluated using the brain β-amyloid plaque load scoring system.

RESULTS

Compared with patients negative for β-amyloid, those positive for it were older and more likely to have lower cognitive function, a diagnosis of Alzheimer disease, white matter hyperintensity, the Apolipoprotein E ε4 allele, and a high degree of MR imaging-visible perivascular spaces in the centrum semiovale. Multivariable analysis, adjusted for age and Apolipoprotein E status, revealed that a high degree of MR imaging-visible perivascular spaces in the centrum semiovale was independently associated with β-amyloid positivity (odds ratio, 2.307; 95% CI, 1.036-5.136; P = .041).

CONCLUSIONS

A high degree of MR imaging-visible perivascular spaces in the centrum semiovale independently predicted β-amyloid positivity in patients with Alzheimer disease-related cognitive impairment. Thus, MR imaging-visible perivascular spaces in the centrum semiovale are associated with amyloid pathology of the brain and could be an indirect imaging marker of amyloid burden in patients with Alzheimer disease-related cognitive impairment.

Identifying novel genetic variants for brain amyloid deposition: a genome-wide association study in the Korean population

Background

Genome-wide association studies (GWAS) have identified a number of genetic variants for Alzheimer’s disease (AD). However, most GWAS were conducted in individuals of European ancestry, and non-European populations are still underrepresented in genetic discovery efforts. Here, we performed GWAS to identify single nucleotide polymorphisms (SNPs) associated with amyloid β (Aβ) positivity using a large sample of Korean population.

Methods

One thousand four hundred seventy-four participants of Korean ancestry were recruited from multicenters in South Korea. Discovery dataset consisted of 1190 participants (383 with cognitively unimpaired [CU], 330 with amnestic mild cognitive impairment [aMCI], and 477 with AD dementia [ADD]) and replication dataset consisted of 284 participants (46 with CU, 167 with aMCI, and 71 with ADD). GWAS was conducted to identify SNPs associated with Aβ positivity (measured by amyloid positron emission tomography). Aβ prediction models were developed using the identified SNPs. Furthermore, bioinformatics analysis was conducted for the identified SNPs.

Results

In addition to APOE, we identified nine SNPs on chromosome 7, which were associated with a decreased risk of Aβ positivity at a genome-wide suggestive level. Of these nine SNPs, four novel SNPs (rs73375428, rs2903923, rs3828947, and rs11983537) were associated with a decreased risk of Aβ positivity (p < 0.05) in the replication dataset. In a meta-analysis, two SNPs (rs7337542 and rs2903923) reached a genome-wide significant level (p < 5.0 × 10⁻⁸). Prediction performance for Aβ positivity increased when rs73375428 were incorporated (area under curve = 0.75; 95% CI = 0.74–0.76) in addition to clinical factors and APOE genotype. Cis-eQTL analysis demonstrated that the rs73375428 was associated with decreased expression levels of FGL2 in the brain.

Conclusion

The novel genetic variants associated with FGL2 decreased risk of Aβ positivity in the Korean population. This finding may provide a candidate therapeutic target for AD, highlighting the importance of genetic studies in diverse populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-021-00854-z.

The relationship of semantic intrusions to different etiological subtypes of MCI and cognitively healthy older adults

INTRODUCTION

There is increasing evidence that susceptibility to proactive semantic interference (PSI) and the failure to recover from PSI (frPSI) as evidenced by intrusion errors may be early cognitive markers of both preclinical and prodromal Alzheimer's disease (AD).

METHODS

One hundred forty-five participants were administered extensive clinical and neuropsychological evaluations including the Loewenstein-Acevedo Scales for Semantic Interference and Learning (LASSI-L), a sensitive cognitive stress test measuring PSI and frPSI. Participants also underwent structural magnetic resonance imaging (MRI) and amyloid positron emission tomography/computed tomography (PET/CT) imaging.

RESULTS

PSI and frPSI errors were much more prevalent in the mild cognitive impairment (MCI)-AD (amyloid positive) group than the other diagnostic groups. The number of intrusion errors observed across the other MCI groups without amyloid pathology and those with normal cognition were comparable.

DISCUSSION

Semantic intrusion errors on the LASSI-L occur much less frequently in persons who have different types of non-AD-related MCI and may be used as an early cognitive marker of prodromal AD.

The Role of Free and Cued Selective Reminding Test in Predicting [18F]Florbetaben PET Results in Mild Cognitive Impairment and Mild Dementia

BACKGROUND

Free and Cued Selective Reminding Test (FCSRT) is a reliable cognitive marker for Alzheimer's disease (AD), and the identification of neuropsychological tests sensitive to the early signs of AD pathology is crucial both in research and clinical practice.

OBJECTIVE

The study aimed to ascertain the ability of FCSRT in predicting the amyloid load as determined from amyloid PET imaging (Amy-PET) in patients with cognitive disorders.

METHODS

For our purpose, 79 patients (71 MCI, 8 mild dementia) underwent a complete workup for dementia, including the FCSRT assessment and a [18F]florbetaben PET scan. FCSRT subitem scores were used as predictors in different binomial regression models.

RESULTS

Immediate free recall and delayed free recall were the best predictors overall in the whole sample; whereas in patients <76 years, all models further improved with immediate total recall (ITR) and Index of Sensitivity of Cueing (ISC) resulting the most accurate in anticipating Amy-PET results, with a likelihood of being Amy-PET positive greater than 85% for ITR and ISC scores of less than 25 and 0.5, respectively.

CONCLUSION

FCSRT proved itself to be a valid tool in dementia diagnosis, also being able to correlate with amyloid pathology. The possibility to predict Amy-PET results through a simple and reliable neuropsychological test might be helpful for clinicians in the dementia field, adding value to a paper and pencil tool compared to most costly biomarkers.

The Use, Standardization, and Interpretation of Brain Imaging Data in Clinical Trials of Neurodegenerative Disorders

Imaging biomarkers play a wide-ranging role in clinical trials for neurological disorders. This includes selecting the appropriate trial participants, establishing target engagement and mechanism-related pharmacodynamic effect, monitoring safety, and providing evidence of disease modification. In the early stages of clinical drug development, evidence of target engagement and/or downstream pharmacodynamic effect-especially with a clear relationship to dose-can provide confidence that the therapeutic candidate should be advanced to larger and more expensive trials, and can inform the selection of the dose(s) to be further tested, i.e., to "de-risk" the drug development program. In these later-phase trials, evidence that the therapeutic candidate is altering disease-related biomarkers can provide important evidence that the clinical benefit of the compound (if observed) is grounded in meaningful biological changes. The interpretation of disease-related imaging markers, and comparability across different trials and imaging tools, is greatly improved when standardized outcome measures are defined. This standardization should not impinge on scientific advances in the imaging tools per se but provides a common language in which the results generated by these tools are expressed. PET markers of pathological protein aggregates and structural imaging of brain atrophy are common disease-related elements across many neurological disorders. However, PET tracers for pathologies beyond amyloid β and tau are needed, and the interpretability of structural imaging can be enhanced by some simple considerations to guard against the possible confound of pseudo-atrophy. Learnings from much-studied conditions such as Alzheimer's disease and multiple sclerosis will be beneficial as the field embraces rarer diseases.

Early detection of amyloid load using 18F-florbetaben PET

BACKGROUND

A low amount and extent of Aβ 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 Aβ accumulation using ¹⁸F-florbetaben PET. Quantitative thresholds for the early (SUVR_early) and established (SUVR_estab) Aβ deposition were developed, and the topography of early Aβ deposition was assessed. Subsequently, Aβ accumulation over time, progression from mild cognitive impairment (MCI) to AD dementia, and tau deposition were assessed in subjects with early and established Aβ 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 Aβ-deposition continuum were defined based on the developed SUVR cutoffs: Aβ-negative subjects, subjects with early Aβ deposition ("gray zone"), and subjects with established Aβ 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 Aβ pathology accumulated more amyloid over time than Aβ-negative subjects. After a 4-year clinical follow-up, none of the Aβ-negative or the gray zone subjects progressed to AD dementia while 91% of the MCI subjects with established Aβ pathology progressed. Tau deposition was infrequent in those subjects without established Aβ 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 Aβ 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).

Restoration of amyloid PET images obtained with short-time data using a generative adversarial networks framework

Our purpose in this study is to evaluate the clinical feasibility of deep-learning techniques for F-18 florbetaben (FBB) positron emission tomography (PET) image reconstruction using data acquired in a short time. We reconstructed raw FBB PET data of 294 patients acquired for 20 and 2 min into standard-time scanning PET (PET_20m) and short-time scanning PET (PET_2m) images. We generated a standard-time scanning PET-like image (sPET_20m) from a PET_2m image using a deep-learning network. We did qualitative and quantitative analyses to assess whether the sPET_20m images were available for clinical applications. In our internal validation, sPET_20m images showed substantial improvement on all quality metrics compared with the PET_2m images. There was a small mean difference between the standardized uptake value ratios of sPET_20m and PET_20m images. A Turing test showed that the physician could not distinguish well between generated PET images and real PET images. Three nuclear medicine physicians could interpret the generated PET image and showed high accuracy and agreement. We obtained similar quantitative results by means of temporal and external validations. We can generate interpretable PET images from low-quality PET images because of the short scanning time using deep-learning techniques. Although more clinical validation is needed, we confirmed the possibility that short-scanning protocols with a deep-learning technique can be used for clinical applications.

Abnormal Regional and Global Connectivity Measures in Subjective Cognitive Decline Depending on Cerebral Amyloid Status

BACKGROUND

Amyloid-β accumulation was found to alter precuneus-based functional connectivity (FC) in mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia, but its impact is less clear in subjective cognitive decline (SCD), which in combination with AD pathologic change is theorized to correspond to stage 2 of the Alzheimer's continuum in the 2018 NIA-AA research framework.

OBJECTIVE

This study addresses how amyloid pathology relates to resting-state fMRI FC in SCD, especially focusing on the precuneus.

METHODS

From the DELCODE cohort, two groups of 24 age- and gender-matched amyloid-positive (SCDAβ+) and amyloidnegative SCD (SCDβ-) patients were selected according to visual [18F]-Florbetaben (FBB) PET readings, and studied with resting-state fMRI. Local (regional homogeneity [ReHo], fractional amplitude of low-frequency fluctuations [fALFF]) and global (degree centrality [DC], precuneus seed-based FC) measures were compared between groups. Follow-up correlation analyses probed relationships of group differences with global and precuneal amyloid load, as measured by FBB standard uptake value ratios (SUVR=⫖FBB).

RESULTS

ReHo was significantly higher (voxel-wise p < 0.01, cluster-level p < 0.05) in the bilateral precuneus for SCDAβ+patients, whereas fALFF was not altered between groups. Relatively higher precuneus-based FC with occipital areas (but no altered DC) was observed in SCDAβ+ patients. In this latter cluster, precuneus-occipital FC correlated positively with global (SCDAβ+) and precuneus SUVRFBB (both groups).

CONCLUSION

While partial confounding influences due to a higher APOE ε4 carrier ratio among SCDAβ+ patients cannot be excluded, exploratory results indicate functional alterations in the precuneus hub region that were related to amyloid-β load, highlighting incipient pathology in stage 2 of the AD continuum.

Elucidating the Risk Factors for Progression from Amyloid-Negative Amnestic Mild Cognitive Impairment to Dementia

BACKGROUND

Amyloid PET allows for the assessment of amyloid β status in the brain, distinguishing true Alzheimer's disease from Alzheimer's disease-mimicking conditions. Around 15-20% of patients with clinically probable Alzheimer's disease have been found to have no significant Alzheimer's pathology on amyloid PET. However, a limited number of studies had been conducted on this subpopulation in terms of clinical progression.

OBJECTIVE

We investigated the risk factors that could affect the progression to dementia in patients with amyloid-negative amnestic mild cognitive impairment (MCI).

METHODS

This study was a single-institutional, retrospective cohort study of patients over the age of 50 with amyloid-negative amnestic MCI who visited the memory clinic of Asan Medical Center with a follow-up period of more than 36 months. All participants underwent brain magnetic resonance imaging (MRI), detailed neuropsychological testing, and fluorine-18[F18]-florbetaben amyloid PET.

RESULTS

During the follow-up period, 39 of 107 patients progressed to dementia from amnestic MCI. In comparison with the stationary group, the progressed group had a more severe impairment in verbal and visual episodic memory function and hippocampal atrophy, which showed an Alzheimer's diseaselike pattern despite the lack of evidence for significant Alzheimer's disease pathology. Voxel-based morphometric MRI analysis revealed that the progressed group had a reduced gray matter volume in the bilateral cerebellar cortices, right temporal cortex, and bilateral insular cortices.

CONCLUSION

Considering the lack of evidence of amyloid pathology, clinical progression of these subpopulation may be caused by other neuropathologies such as TDP-43, abnormal tau or alpha synuclein that lead to neurodegeneration independent of amyloid-driven pathway. Further prospective studies incorporating biomarkers of Alzheimer's disease-mimicking dementia are warranted.

Olfactory Impairment Is Related to Tau Pathology and Neuroinflammation in Alzheimer's Disease

BACKGROUND

Olfactory impairment is evident in Alzheimer's disease (AD); however, its precise relationships with clinical biomarker measures of tau pathology and neuroinflammation are not well understood.

OBJECTIVE

To determine if odor identification performance measured with the University of Pennsylvania Smell Identification Test (UPSIT) is related to in vivo measures of tau pathology and neuroinflammation.

METHODS

Cognitively normal and cognitively impaired participants were selected from an established research cohort of adults aged 50 and older who underwent neuropsychological testing, brain MRI, and amyloid PET. Fifty-four participants were administered the UPSIT. Forty-one underwent 18F-MK-6240 PET (measuring tau pathology) and fifty-three underwent 11C-PBR28 PET (measuring TSPO, present in activated microglia). Twenty-three participants had lumbar puncture to measure CSF concentrations of total tau (t-tau), phosphorylated tau (p-tau), and amyloid-β (Aβ42).

RESULTS

Low UPSIT performance was associated with greater18F-MK-6240 binding in medial temporal cortex, hippocampus, middle/inferior temporal gyri, inferior parietal cortex, and posterior cingulate cortex (p < 0.05). Similar relationships were seen for 11C-PBR28. These relationships were primarily driven by amyloid-positive participants. Lower UPSIT performance was associated with greater CSF concentrations of t-tau and p-tau (p < 0.05). Amyloid status and cognitive status exhibited independent effects on UPSIT performance (p < 0.01).

CONCLUSION

Olfactory identification deficits are related to extent of tau pathology and neuroinflammation, particularly in those with amyloid pathophysiology. The independent association of amyloid-positivity and cognitive impairment with odor identification suggests that low UPSIT performance may be a marker for AD pathophysiology in cognitive normal individuals, although impaired odor identification is associated with both AD and non-AD related neurodegeneration.NCT Registration Numbers: NCT03373604; NCT02831283.

Concordance in detecting amyloid positivity between 18F-florbetaben and 18F-flutemetamol amyloid PET using quantitative and qualitative assessments

We aimed to quantitatively and qualitatively assess whether there is a discrepancy in detecting amyloid beta (Aβ) positivity between 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) positron emission tomography (PET). We obtained paired FBB and FMM PET images from 107 participants. Three experts visually quantified the Aβ deposition as positive or negative. Quantitative assessment was performed using global cortical standardized uptake value ratio (SUVR) with the whole cerebellum as the reference region. Inter-rater agreement was excellent for FBB and FMM. The concordance rates between FBB and FMM were 94.4% (101/107) for visual assessment and 98.1% (105/107) for SUVR cut-off categorization. Both FBB and FMM showed high agreement rates between visual assessment and SUVR positive or negative categorization (93.5% in FBB and 91.2% in FMM). When the two ligands were compared based on SUVR cut-off categorization as standard of truth, although not statistically significant, the false-positive rate was higher in FMM (9.1%) than in FBB (1.8%) (p = 0.13). Our findings suggested that both FBB and FMM had excellent agreement when used to quantitatively and qualitatively evaluate Aβ deposits, thus, combining amyloid PET data associated with the use of different ligands from multi-centers is feasible.

Biomarker Localization, Analysis, Visualization, Extraction, and Registration (BLAzER) Methodology for Research and Clinical Brain PET Applications

BACKGROUND

Tools for efficient evaluation of amyloid- and tau-PET images are needed in both clinical and research settings.

OBJECTIVE

This study was designed to validate a semi-automated image analysis methodology, called Biomarker Localization, Analysis, Visualization, Extraction, and Registration (BLAzER). We tested BLAzER using two different segmentation platforms, FreeSurfer (FS) and Neuroreader (NR), for regional brain PET quantification in participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset.

METHODS

127 amyloid-PET and 55 tau-PET studies with volumetric MRIs were obtained from ADNI. The BLAzER methodology utilizes segmentation of MR images by FS or NR, then visualizes and quantifies regional brain PET data using FDA-cleared software (MIM), enabling quality control to ensure optimal registration and to detect segmentation errors.

RESULTS

BLAzER analysis required ∼5 min plus segmentation time. BLAzER using FS segmentation showed strong agreement with ADNI for global amyloid-PET standardized uptake value ratios (SUVRs) (r = 0.9922, p < 0.001) and regional tau-PET SUVRs across all Braak staging regions (r > 0.97, p < 0.001) with high inter-operator reproducibility (ICC > 0.97) and nearly identical dichotomization as amyloid-positive or -negative (2 discrepant cases out of 127). Comparing FS versus NR segmentation with BLAzER, global SUVRs were strongly correlated for amyloid-PET (r = 0.9841, p < 0.001), but were systematically higher (4% on average) with NR, likely due to more inclusion of white matter with NR-defined regions.

CONCLUSIONS

BLAzER provides an efficient methodology for regional brain PET quantification. FDA-cleared components and visualization of registration reduce barriers between research and clinical applications.

PET amyloid in normal aging: direct comparison of visual and automatic processing methods

Assessment of amyloid deposits is a critical step for the identification of Alzheimer disease (AD) signature in asymptomatic elders. Whether the different amyloid processing methods impacts on the quality of clinico-radiological correlations is still unclear. We directly compared in 155 elderly controls with extensive neuropsychological testing at baseline and 4.5 years follow-up three approaches: (i) operator-dependent standard visual reading, (ii) operator-independent automatic SUVR with four different reference regions, and (iii) novel operator and region of reference-independent automatic Aβ-index. The coefficient of variance was used to examine inter-individual variability for each processing method. Using visually-established amyloid positivity as the gold standard, the area under the receiver operating characteristic curve (ROC) was computed. Linear regression models were used to assess the association between changes in continuous cognitive score and amyloid uptake values. In SUVR analyses, the coefficient of variance varied from 1.718 to 1.762 according to the area of reference and was of − 3.045 for the Aβ-index method. Compared to the visual rating, Aβ-index method showed the largest area under the ROC curve [0.9568 (95% CI 0.9252, 0.98833)]. The best cut-off score was of − 0.3359 with sensitivity and specificity values of 0.97 and 0.83, respectively. Only the Aß-index was related to more severe decrement of cognitive performances [regression coefficient: 9.103 (95% CI 1.148, 17.058)]. The Aβ-index is considered as preferred option in asymptomatic elders, since it is operator-independent, avoids the selection of reference area, is closer to established visual scoring and correlates with the evolution of cognitive performances.