rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data

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.

Highly accurate blood test for Alzheimer's disease is similar or superior to clinical cerebrospinal fluid tests

With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-β (Aβ) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aβ42/40 and p-tau181/Aβ42. The primary and secondary outcomes were detection of brain Aβ or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aβ PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aβ PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.

Impact of simulated reduced injected dose on the assessment of amyloid PET scans

PURPOSE

To investigate the impact of reduced injected doses on the quantitative and qualitative assessment of the amyloid PET tracers [18F]flutemetamol and [18F]florbetaben.

METHODS

Cognitively impaired and unimpaired individuals (N = 250, 36% Aβ-positive) were included and injected with [18F]flutemetamol (N = 175) or [18F]florbetaben (N = 75). PET scans were acquired in list-mode (90-110 min post-injection) and reduced-dose images were simulated to generate images of 75, 50, 25, 12.5 and 5% of the original injected dose. Images were reconstructed using vendor-provided reconstruction tools and visually assessed for Aβ-pathology. SUVRs were calculated for a global cortical and three smaller regions using a cerebellar cortex reference tissue, and Centiloid was computed. Absolute and percentage differences in SUVR and CL were calculated between dose levels, and the ability to discriminate between Aβ- and Aβ + scans was evaluated using ROC analyses. Finally, intra-reader agreement between the reduced dose and 100% images was evaluated.

RESULTS

At 5% injected dose, change in SUVR was 3.72% and 3.12%, with absolute change in Centiloid 3.35CL and 4.62CL, for [18F]flutemetamol and [18F]florbetaben, respectively. At 12.5% injected dose, percentage change in SUVR and absolute change in Centiloid were < 1.5%. AUCs for discriminating Aβ- from Aβ + scans were high (AUC ≥ 0.94) across dose levels, and visual assessment showed intra-reader agreement of > 80% for both tracers.

CONCLUSION

This proof-of-concept study showed that for both [18F]flutemetamol and [18F]florbetaben, adequate quantitative and qualitative assessments can be obtained at 12.5% of the original injected dose. However, decisions to reduce the injected dose should be made considering the specific clinical or research circumstances.

Correlation Between Amyloid PET Imaging and Discordant Cerebrospinal Fluid Biomarkers Results in Patients with Suspected Alzheimer's Disease

BACKGROUND

Although the concordance between cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers and amyloid-PET findings is well known, there are no data regarding the concordance of amyloid-PET with inconclusive CSF values of amyloid-β (Aβ)1 - 42 and p-tau for the diagnosis of AD.

OBJECTIVE

To investigate the relationship between the amyloid-PET results with discordant AD biomarkers values in CSF (Aβ1 - 42+/p-tau-or Aβ1 - 42-/p-tau+).

METHODS

An observational retrospective study, including 62 patients with mild cognitive impairment (32/62) or dementia (30/62), suspicious of AD who had undergone a lumbar puncture to determine CSF AD biomarkers, and presented discordant values in CSF between Aβ1 - 42 and p-tau (Aβ1 - 42+/p-tau-or Aβ1 - 42-/p-tau+). All of them, underwent an amyloid-PET with 18F-Florbetaben. An extensive neuropsychological testing as part of their diagnostic process (MMSE and TMA-93), was performed, and it was also obtained the Global Deterioration Scale.

RESULTS

Comparing the discordant CSF results of each patient with the cerebral amyloid-PET results, we found that in the group with Aβ1 - 42+ and p-tau-CSF values, the amyloid-PET was positive in 51.2% and negative in 48.8% of patients, while in the group with Aβ1 - 42-and p-Tau+ CSF values, the amyloid-PET was positive in 52.6% of patients and negative in 47.4% of them. No significant association was found (p = 0.951) between the results of amyloid-PET and the two divergent groups in CSF.

CONCLUSIONS

No significant relationship was observed between the results of discordant AD biomarkers in CSF and the result of amyloid-PET. No trend in amyloid-PET results was observed in relation to CSF biomarker values.

Brain health registry updates: An online longitudinal neuroscience platform

INTRODUCTION

Remote, internet-based methods for recruitment, screening, and longitudinally assessing older adults have the potential to facilitate Alzheimer's disease (AD) clinical trials and observational studies.

METHODS

The Brain Health Registry (BHR) is an online registry that includes longitudinal assessments including self- and study partner-report questionnaires and neuropsychological tests. New initiatives aim to increase inclusion and engagement of commonly underincluded communities using digital, community-engaged research strategies. New features include multilingual support and biofluid collection capabilities.

RESULTS

BHR includes > 100,000 participants. BHR has made over 259,000 referrals resulting in 25,997 participants enrolled in 30 aging and AD studies. In addition, 28,278 participants are coenrolled in BHR and other studies with data linkage among studies. Data have been shared with 28 investigators. Recent efforts have facilitated the enrollment and engagement of underincluded ethnocultural communities.

DISCUSSION

The major advantages of the BHR approach are scalability and accessibility. Challenges include compliance, retention, cohort diversity, and generalizability.

HIGHLIGHTS

Brain Health Registry (BHR) is an online, longitudinal platform of > 100,000 members. BHR made > 259,000 referrals, which enrolled 25,997 participants in 32 studies. New efforts increased enrollment and engagement of underincluded communities in BHR. The major advantages of the BHR approach are scalability and accessibility. BHR provides a unique adjunct for clinical neuroscience research.

Blood β-synuclein is related to amyloid PET positivity in memory clinic patients

INTRODUCTION

β-synuclein is an emerging blood biomarker to study synaptic degeneration in Alzheimer´s disease (AD), but its relation to amyloid-β (Αβ) pathology is unclear.

METHODS

We investigated the association of plasma β-synuclein levels with [18F] flutemetamol positron emission tomography (PET) in patients with AD dementia (n = 51), mild cognitive impairment (MCI-Aβ+ n = 18, MCI- Aβ- n = 30), non-AD dementias (n = 22), and non-demented controls (n = 5).

RESULTS

Plasma β-synuclein levels were higher in Aβ+ (AD dementia, MCI-Aβ+) than in Aβ- subjects (non-AD dementias, MCI-Aβ-) with good discrimination of Aβ+ from Aβ- subjects and prediction of Aβ status in MCI individuals. A positive correlation between plasma β-synuclein and Aβ PET was observed in multiple cortical regions across all lobes.

DISCUSSION

Plasma β-synuclein demonstrated discriminative properties for Aβ PET positive and negative subjects. Our data underline that β-synuclein is not a direct marker of Aβ pathology and suggest different longitudinal dynamics of synaptic degeneration versus amyloid deposition across the AD continuum.

HIGHLIGHTS

Blood and CSF β-synuclein levels are higher in Aβ+ than in Aβ- subjects. Blood β-synuclein level correlates with amyloid PET positivity in multiple regions. Blood β-synuclein predicts Aβ status in MCI individuals.

Longitudinal amyloid and tau PET imaging in Alzheimer's disease: A systematic review of methodologies and factors affecting quantification

Deposition of amyloid and tau pathology can be quantified in vivo using positron emission tomography (PET). Accurate longitudinal measurements of accumulation from these images are critical for characterizing the start and spread of the disease. However, these measurements are challenging; precision and accuracy can be affected substantially by various sources of errors and variability. This review, supported by a systematic search of the literature, summarizes the current design and methodologies of longitudinal PET studies. Intrinsic, biological causes of variability of the Alzheimer's disease (AD) protein load over time are then detailed. Technical factors contributing to longitudinal PET measurement uncertainty are highlighted, followed by suggestions for mitigating these factors, including possible techniques that leverage shared information between serial scans. Controlling for intrinsic variability and reducing measurement uncertainty in longitudinal PET pipelines will provide more accurate and precise markers of disease evolution, improve clinical trial design, and aid therapy response monitoring.

Evaluation of novel data-driven metrics of amyloid β deposition for longitudinal PET studies

PURPOSE

Positron emission tomography (PET) provides in vivo quantification of amyloid-β (Aβ) pathology. Established methods for assessing Aβ burden can be affected by physiological and technical factors. Novel, data-driven metrics have been developed to account for these sources of variability. We aimed to evaluate the performance of four of these amyloid PET metrics against conventional techniques, using a common set of criteria.

METHODS

Three cohorts were used for evaluation: Insight 46 (N=464, [18F]florbetapir), AIBL (N=277, [18F]flutemetamol), and an independent test-retest data (N=10, [18F]flutemetamol). Established metrics of amyloid tracer uptake included the Centiloid (CL) and where dynamic data was available, the non-displaceable binding potential (BPND). The four data-driven metrics computed were the amyloid load (Aβ load), the Aβ-PET pathology accumulation index (Aβ index), the Centiloid derived from non-negative matrix factorisation (CLNMF), and the amyloid pattern similarity score (AMPSS). These metrics were evaluated using reliability and repeatability in test-retest data, associations with BPND and CL, variability of the rate of change and sample size estimates to detect a 25% slowing in Aβ accumulation.

RESULTS

All metrics showed good reliability. Aβ load, Aβ index and CLNMF were strong associated with the BPND. The associations with CL suggest that cross-sectional measures of CLNMF, Aβ index and Aβ load are robust across studies. Sample size estimates for secondary prevention trial scenarios were the lowest for CLNMF and Aβ load compared to the CL.

CONCLUSION

Among the novel data-driven metrics evaluated, the Aβ load, the Aβ index and the CLNMF can provide comparable performance to more established quantification methods of Aβ PET tracer uptake. The CLNMF and Aβ load could offer a more precise alternative to CL, although further studies in larger cohorts should be conducted.

Profiling of plasma biomarkers in the context of memory assessment in a tertiary memory clinic

Plasma biomarkers have shown promising performance in research cohorts in discriminating between different stages of Alzheimer's disease (AD). Studies in clinical populations are necessary to provide insights on the clinical utility of plasma biomarkers before their implementation in real-world settings. Here we investigated plasma biomarkers (glial fibrillary acidic protein (GFAP), tau phosphorylated at 181 and 231 (pTau181, pTau231), amyloid β (Aβ) 42/40 ratio, neurofilament light) in 126 patients (age = 65 ± 8) who were admitted to the Clinic for Cognitive Disorders, at Karolinska University Hospital. After extensive clinical assessment (including CSF analysis), patients were classified as: mild cognitive impairment (MCI) (n = 75), AD (n = 25), non-AD dementia (n = 16), no dementia (n = 9). To refine the diagnosis, patients were examined with [¹⁸F]flutemetamol PET (Aβ-PET). Aβ-PET images were visually rated for positivity/negativity and quantified in Centiloid. Accordingly, 68 Aβ+ and 54 Aβ- patients were identified. Plasma biomarkers were measured using single molecule arrays (SIMOA). Receiver-operated curve (ROC) analyses were performed to detect Aβ-PET+ using the different biomarkers. In the whole cohort, the Aβ-PET centiloid values correlated positively with plasma GFAP, pTau231, pTau181, and negatively with Aβ42/40 ratio. While in the whole MCI group, only GFAP was associated with Aβ PET centiloid. In ROC analyses, among the standalone biomarkers, GFAP showed the highest area under the curve discriminating Aβ+ and Aβ- compared to other plasma biomarkers. The combination of plasma biomarkers via regression was the most predictive of Aβ-PET, especially in the MCI group (prior to PET, n = 75) (sensitivity = 100%, specificity = 82%, negative predictive value = 100%). In our cohort of memory clinic patients (mainly MCI), the combination of plasma biomarkers was sensitive in ruling out Aβ-PET negative individuals, thus suggesting a potential role as rule-out tool in clinical practice.

Air pollution is associated with faster cognitive decline in Alzheimer's disease

OBJECTIVE

Although chronic exposure to air pollution is associated with an increased risk of dementia in normal elderlies, the effect of chronic exposure to air pollution on the rates of cognitive decline in Alzheimer's disease (AD) has not been elucidated.

METHODS

In this longitudinal study, a total of 269 patients with mild cognitive impairment or early dementia due to AD with the evidence of brain β-amyloid deposition were followed-up for a mean period of 4 years. Five-year normalized hourly cumulative exposure value of each air pollutant, such as carbon monoxide (CO), nitrogen dioxide (NO2 ), sulfur dioxide (SO2 ), and particulate matter (PM2.5 and PM10 ), was computed based on nationwide air pollution database. The effects of chronic exposure to air pollution on longitudinal cognitive decline rate were evaluated using linear mixed models.

RESULTS

Higher chronic exposure to SO2 was associated with a faster decline in memory score, whereas chronic exposure to CO, NO2 , and PM10 were not associated with the rate of cognitive decline. Higher chronic exposure to PM2.5 was associated with a faster decline in visuospatial score in apolipoprotein E ε4 carriers. These effects remained significant even after adjusting for potential confounders.

INTERPRETATION

Our findings suggest that chronic exposure to SO2 and PM2.5 is associated with faster clinical progression in AD.

Software compatibility analysis for quantitative measures of [18F]flutemetamol amyloid PET burden in mild cognitive impairment

RATIONALE

Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods.

METHODS

Composite SUVr using the pons as the reference region was generated from [¹⁸F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVr_pons was applied. Quantitative results from MIM Software's MIMneuro, Syntermed's NeuroQ, Hermes Medical Solutions' BRASS and GE Healthcare's CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores.

RESULTS

Using an Aβ positivity threshold of ≥ 0.6 SUVr_pons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss') and individual software pairings (Cohen's), were ≥ 0.9 signifying "almost perfect" inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957-0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r² = 0.98).

CONCLUSION

Using an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [¹⁸F]flutemetamol amyloid PET with a ≥ 0.6 SUVr_pons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.

Quantification of amyloid beta and tau PET without a structural MRI

INTRODUCTION

Relying on magnetic resonance imaging (MRI) for quantification of positron emission tomography (PET) images may limit generalizability of the results. We evaluated several MRI-free approaches for amyloid beta (Aβ) and tau PET quantification relative to MRI-dependent quantification cross-sectionally and longitudinally.

METHODS

We compared baseline MRI-free and MRI-dependent measurements of Aβ PET ([18F]florbetapir [FBP], N = 1290, [18F]florbetaben [FBB], N = 290) and tau PET ([18F]flortaucipir [FTP], N = 768) images with respect to continuous and dichotomous agreement, effect sizes of Aβ+ impaired versus Aβ- unimpaired groups, and longitudinal standardized uptake value ratio (SUVR) slopes in a subset of individuals.

RESULTS

The best-performing MRI-free approaches had high continuous and dichotomous agreement with MRI-dependent SUVRs for Aβ PET and temporal flortaucipir (R² ≥0.95; ± agreement ≥92%) and for Alzheimer's disease-related effect sizes; agreement was slightly lower for entorhinal flortaucipir and longitudinal slopes.

DISCUSSION

There is no consistent loss of baseline or longitudinal AD-related signal with MRI-free Aβ and tau PET image quantification.

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.

Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer's disease

Objective

Although beta-amyloid (Aβ) positron emission tomography (PET) images are interpreted visually as positive or negative, approximately 10% are judged as equivocal in Alzheimer’s disease. Therefore, we aimed to develop an automated semi-quantitative analysis technique using ¹⁸F-flutemetamol PET images without anatomical images.

Methods

Overall, 136 cases of patients administered ¹⁸F-flutemetamol were enrolled. Of 136 cases, five PET images each with the highest and lowest values of standardized uptake value ratio (SUVr) of cerebral cortex-to-pons were used to create positive and negative templates. Using these templates, PET images of the remaining 126 cases were standardized, and SUVr images were produced with the pons as a reference region. The mean of SUVr values in the volume of interest delineated on the cerebral cortex was compared to those in the CortexID Suite (GE Healthcare). Furthermore, centiloid (CL) values were calculated for the 126 cases using data from the Centiloid Project (http://www.gaain.org/centiloid-project) and both templates. ¹⁸F-flutemetamol-PET was interpreted visually as positive/negative based on Aβ deposition in the cortex. However, the criterion "equivocal" was added for cases with focal or mild Aβ accumulation that were difficult to categorize. Optimal cutoff values of SUVr and CL maximizing sensitivity and specificity for Aβ detection were determined by receiver operating characteristic (ROC) analysis using the visual evaluation as a standard of truth.

Results

SUVr calculated by our method and CortexID were highly correlated (R² = 0.9657). The 126 PET images comprised 84 negative and 42 positive cases of Aβ deposition by visual evaluation, of which 11 and 10 were classified as equivocal, respectively. ROC analyses determined the optimal cutoff values, sensitivity, and specificity for SUVr as 0.544, 89.3%, and 92.9%, respectively, and for CL as 12.400, 94.0%, and 92.9%, respectively. Both semi-quantitative analyses showed that 12 and 9 of the 21 equivocal cases were negative and positive, respectively, under the optimal cutoff values.

Conclusions

This semi-quantitative analysis technique using ¹⁸F-flutemetamol-PET calculated SUVr and CL automatically without anatomical images. Moreover, it objectively and homogeneously interpreted positive or negative Aβ burden in the brain as a supplemental tool for the visual reading of equivocal cases in routine clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12149-022-01769-x.