A new integrated dual time-point amyloid PET/MRI data analysis method

Diagnostic performance of molecular imaging methods in predicting the progression from mild cognitive impairment to dementia: an updated systematic review

PURPOSE

Epidemiological and logistical reasons are slowing the clinical validation of the molecular imaging biomarkers in the initial stages of neurocognitive disorders. We provide an updated systematic review of the recent advances (2017-2022), highlighting methodological shortcomings.

METHODS

Studies reporting the diagnostic accuracy values of the molecular imaging techniques (i.e., amyloid-, tau-, [18F]FDG-PETs, DaT-SPECT, and cardiac [123I]-MIBG scintigraphy) in predicting progression from mild cognitive impairment (MCI) to dementia were selected according to the Preferred Reporting Items for a Systematic Review and Meta-Analysis (PRISMA) method and evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Main eligibility criteria were as follows: (1) ≥ 50 subjects with MCI, (2) follow-up ≥ 3 years, (3) gold standard: progression to dementia or diagnosis on pathology, and (4) measures of prospective accuracy.

RESULTS

Sensitivity (SE) and specificity (SP) in predicting progression to dementia, mainly to Alzheimer's dementia were 43-100% and 63-94% for [18F]FDG-PET and 64-94% and 48-93% for amyloid-PET. Longitudinal studies were lacking for less common disorders (Dementia with Lewy bodies-DLB and Frontotemporal lobe degeneration-FTLD) and for tau-PET, DaT-SPECT, and [123I]-MIBG scintigraphy. Therefore, the accuracy values from cross-sectional studies in a smaller sample of subjects (n > 20, also including mild dementia stage) were chosen as surrogate outcomes. DaT-SPECT showed 47-100% SE and 71-100% SP in differentiating Lewy body disease (LBD) from non-LBD conditions; tau-PET: 88% SE and 100% SP in differentiating DLB from Posterior Cortical Atrophy. [123I]-MIBG scintigraphy differentiated LBD from non-LBD conditions with 47-100% SE and 71-100% SP.

CONCLUSION

Molecular imaging has a moderate-to-good accuracy in predicting the progression of MCI to Alzheimer's dementia. Longitudinal studies are sparse in non-AD conditions, requiring additional efforts in these settings.

Data-driven analysis of regional brain metabolism in behavioral frontotemporal dementia and late-onset primary psychiatric diseases with frontal lobe syndrome: A PET/MRI study

Late-onset primary psychiatric disease (PPD) and behavioral frontotemporal dementia (bvFTD) present with a similar frontal lobe syndrome. We compare brain glucose metabolism in bvFTD and late-onset PPD and investigate the metabolic correlates of cognitive and behavioral disturbances through FDG-PET/MRI. We studied 37 bvFTD and 20 late-onset PPD with a mean clinical follow-up of three years. At baseline evaluation, metabolism of the dorsolateral, ventrolateral, orbitofrontal regions and caudate could classify the patients with a diagnostic accuracy of 91% (95% CI: 0.81-0.98%). 45% of PPD showed low-grade hypometabolism in the anterior cingulate and/or parietal regions. Frontal lobe metabolism was normal in 32% of genetic bvFTD and bvFTD with motor neuron signs. Hypometabolism of the frontal and caudate regions could help in distinguishing bvFTD from PPD, except in cases with motor neuron signs and/or genetic bvFTD for which brain metabolism may be less informative.

Pediatric Imaging Using PET/MR Imaging

PET/MR imaging is a one-stop shop technique for pediatric diseases allowing not only an accurate clinical assessment of tumors at staging and restaging but also the diagnosis of neurologic, inflammatory, and infectious diseases in complex cases. Moreover, applying PET kinetic analyses and sequences such as diffusion-weighted imaging as well as quantitative analysis investigating the relationship between disease metabolic activity and cellularity can be applied. Complex radiomics analysis can also be performed.

NiftyPAD - Novel Python Package for Quantitative Analysis of Dynamic PET Data

Current PET datasets are becoming larger, thereby increasing the demand for fast and reproducible processing pipelines. This paper presents a freely available, open source, Python-based software package called NiftyPAD, for versatile analyses of static, full or dual-time window dynamic brain PET data. The key novelties of NiftyPAD are the analyses of dual-time window scans with reference input processing, pharmacokinetic modelling with shortened PET acquisitions through the incorporation of arterial spin labelling (ASL)-derived relative perfusion measures, as well as optional PET data-based motion correction. Results obtained with NiftyPAD were compared with the well-established software packages PPET and QModeling for a range of kinetic models. Clinical data from eight subjects scanned with four different amyloid tracers were used to validate the computational performance. NiftyPAD achieved [Formula: see text] correlation with PPET, with absolute difference [Formula: see text] for linearised Logan and MRTM2 methods, and [Formula: see text] correlation with QModeling, with absolute difference [Formula: see text] for basis function based SRTM and SRTM2 models. For the recently published SRTM ASL method, which is unavailable in existing software packages, high correlations with negligible bias were observed with the full scan SRTM in terms of non-displaceable binding potential ([Formula: see text]), indicating reliable model implementation in NiftyPAD. Together, these findings illustrate that NiftyPAD is versatile, flexible, and produces comparable results with established software packages for quantification of dynamic PET data. It is freely available ( https://github.com/AMYPAD/NiftyPAD ), and allows for multi-platform usage. The modular setup makes adding new functionalities easy, and the package is lightweight with minimal dependencies, making it easy to use and integrate into existing processing pipelines.

A comparison of advanced semi-quantitative amyloid PET analysis methods

PURPOSE

To date, there is no consensus on how to semi-quantitatively assess brain amyloid PET. Some approaches use late acquisition alone (e.g., ELBA, based on radiomic features), others integrate the early scan (e.g., TDr, which targets the area of maximum perfusion) and structural imaging (e.g., WMR, that compares kinetic behaviour of white and grey matter, or SI based on the kinetic characteristics of the grey matter alone). In this study SUVr, ELBA, TDr, WMR, and SI were compared. The latter - the most complete one - provided the reference measure for amyloid burden allowing to assess the efficacy and feasibility in clinical setting of the other approaches.

METHODS

We used data from 85 patients (aged 44-87) who underwent dual time-point PET/MRI acquisitions. The correlations with SI were computed and the methods compared with the visual assessment. Assuming SUVr, ELBA, TDr, and WMR to be independent measures, we linearly combined them to obtain more robust indices. Finally, we investigated possible associations between each quantifier and age in amyloid-negative patients.

RESULTS

Each quantifier exhibited excellent agreement with visual assessment and strong correlation with SI (average AUC = 0.99, ρ = 0.91). Exceptions to this were observed for subcortical regions with ELBA and WMR (ρ_ELBA = 0.44, ρ_WMR = 0.70). The linear combinations showed better performances than the individual methods. Significant associations were observed between TDr, WMR, SI, and age in amyloid-negative patients (p < 0.05).

CONCLUSION

Among the other methods, TDr came closest to the reference with less implementation complexity. Moreover, this study suggests that combining independent approaches gives better results than the individual procedure, so efforts should focus on multi-classifier systems for amyloid PET. Finally, the ability of techniques integrating blood perfusion to depict age-related variations in amyloid load in amyloid-negative subjects demonstrates the goodness of the estimate.

Quantification of Brain β-Amyloid Load in Parkinson's Disease With Mild Cognitive Impairment: A PET/MRI Study

Background

Mild cognitive impairment in Parkinson's disease (PD-MCI) is associated with faster cognitive decline and conversion to dementia. There is uncertainty about the role of β-amyloid (Aβ) co-pathology and its contribution to the variability in PD-MCI profile and cognitive progression.

Objective

To study how presence of Aβ affects clinical and cognitive manifestations as well as regional brain volumes in PD-MCI.

Methods

Twenty-five PD-MCI patients underwent simultaneous PET/3T-MRI with [¹⁸F]flutemetamol and a clinical and neuropsychological examination allowing level II diagnosis. We tested pairwise differences in motor, clinical, and cognitive features with Mann–Whitney U test. We calculated [¹⁸F]flutemetamol (FMM) standardized uptake value ratios (SUVR) in striatal and cortical ROIs, and we performed a univariate linear regression analysis between the affected cognitive domains and the mean SUVR. Finally, we investigated differences in cortical and subcortical brain regional volumes with magnetic resonance imaging (MRI).

Results

There were 8 Aβ+ and 17 Aβ- PD-MCI. They did not differ for age, disease duration, clinical, motor, behavioral, and global cognition scores. PD-MCI-Aβ+ showed worse performance in the overall executive domain (p = 0.037). Subcortical ROIs analysis showed significant Aβ deposition in PD-MCI-Aβ+ patients in the right caudal and rostral middle frontal cortex, in precuneus, in left paracentral and pars triangularis (p < 0.0001), and bilaterally in the putamen (p = 0.038). Cortical regions with higher amyloid load correlated with worse executive performances (p < 0.05). Voxel-based morphometry (VBM) analyses showed no between groups differences.

Conclusions

Presence of cerebral Aβ worsens executive functions, but not motor and global cognitive abilities in PD-MCI, and it is not associated with middle-temporal cortex atrophy. These findings, together with the observation of significant proportion of PD-MCI-Aβ-, suggest that Aβ may not be the main pathogenetic determinant of cognitive deterioration in PD-MCI, but it would rather aggravate deficits in domains vulnerable to Parkinson primary pathology.

The contribution of beta-amyloid to dementia in Lewy body diseases: a 1-year follow-up study

Dementia in Lewy Body Diseases (Parkinson’s disease and dementia with Lewy Bodies) affects progression of disabilities, quality of life and well-being. Understanding its pathogenetic mechanisms is critical to properly implement disease-modifying strategies. It has been hypothesized that synuclein- and amyloid-pathology act synergistically aggravating cognitive decline in elderly patients but their precise contribution to dementia is debated. In this study, we aimed at exploring if presence of amyloid deposits influences clinical, cognitive and neuroanatomical correlates of mental decline in a cohort of 40 Parkinson’s disease patients with normal cognition (n = 5), mild cognitive impairment (n = 22), and dementia (n = 13) as well as in Dementia with Lewy Bodies (n = 10). Patients underwent simultaneous 3 T PET/MRI with [¹⁸F]-flutemetamol and were assessed with an extensive baseline motor and neuropsychological examination, which allowed level II diagnosis of mild cognitive impairment and dementia. The role of amyloid positivity on each cognitive domain, and on the rate of conversion to dementia at 1-year follow-up was explored. A Kaplan Meier and the Log Rank (Mantel–Cox) test were used to assess the pairwise differences in time-to-develop dementia in Parkinson’s disease patients with and without significant amyloidosis. Furthermore, the presence of an Alzheimer’s dementia-like morphological pattern was evaluated using visual and automated assessment of T₁-weighted and T₂-weighted MRI images. We observed similar percentage of amyloid deposits in Parkinson’s disease dementia and dementia with Lewy Bodies cohorts (50% in each group) with an overall prevalence of 34% of significant amyloid depositions in Lewy Body Diseases. PET amyloid positivity was associated with worse global cognition (Montreal Cognitive Assessment and Mini Mental State Examination), executive and language difficulties. At 12-month follow-up, amyloid positive Parkinson’s disease patients were more likely to have become demented than those without amyloidosis. Moreover, there was no difference in the presence of an Alzheimer’s disease-like atrophy pattern and in vascular load (at Fazekas scale) between Lewy Body Diseases with and without significant amyloid deposits. Our findings suggest that in Lewy Body Diseases, amyloid deposition enhances cognitive deficits, particularly attention-executive and language dysfunctions. However, the large number of patients without significant amyloid deposits among our cognitively impaired patients indicates that synuclein pathology itself plays a critical role in the development of dementia in Lewy Body Diseases.

A kinetics-based approach to amyloid PET semi-quantification

PURPOSE

To develop and validate a semi-quantification method (time-delayed ratio, TDr) applied to amyloid PET scans, based on tracer kinetics information.

METHODS

The TDr method requires two static scans per subject: one early (~ 0-10 min after the injection) and one late (typically 50-70 min or 90-100 min after the injection, depending on the tracer). High perfusion regions are delineated on the early scan and applied onto the late scan. A SUVr-like ratio is calculated between the average intensities in the high perfusion regions and the late scan hotspot. TDr was applied to a naturalistic multicenter dataset of 143 subjects acquired with [¹⁸F]florbetapir. TDr values are compared to visual evaluation, cortical-cerebellar SUVr, and to the geometrical semi-quantification method ELBA. All three methods are gauged versus the heterogeneity of the dataset.

RESULTS

TDr shows excellent agreement with respect to the binary visual assessment (AUC = 0.99) and significantly correlates with both validated semi-quantification methods, reaching a Pearson correlation coefficient of 0.86 with respect to ELBA.

CONCLUSIONS

TDr is an alternative approach to previously validated ones (SUVr and ELBA). It requires minimal image processing; it is independent on predefined regions of interest and does not require MR registration. Besides, it takes advantage on the availability of early scans which are becoming common practice while imposing a negligible added patient discomfort.

Brain Amyloid Contribution to Cognitive Dysfunction in Early-Stage Parkinson's Disease: The PPMI Dataset

BACKGROUND

The pathological processes underlying cognitive impairment in Parkinson's disease (PD) are heterogeneous and the contribution of cerebral amyloid deposits is poorly defined, particularly in the early stages of the disease.

OBJECTIVE

To investigate regional [18F]florbetaben binding to amyloid-β (Aβ) and its contribution to cognitive dysfunction in early stage PD.

METHODS

A multicenter cohort of 48 PD patients from the Parkinson's Progression Marker Initiative (PPMI) underwent [18F]florbetaben positron emission tomography (PET) scanning. Clinical features, including demographic characteristics, motor severity, cerebrospinal fluid (CSF), and cognitive testing were systematically assessed according to the PPMI study protocol. For the purpose of this study, we analyzed various neuropsychological tests assessing all cognitive functions.

RESULTS

There were 10/48 (21%) amyloid positive PD patients (PDAβ+). Increased [18F]florbetaben uptake in widespread cortical and subcortical regions was associated with poorer performance on global cognition, as assessed by Montreal Cognitive Assessment (MoCA), and impaired performance on Symbol Digit Modality test (SDMT). Further, we found that PDAβ+ patients had higher CSF total-tau/Aβ1 - 42 (p = 0.001) and phosphorylated-tau/Aβ1 - 42 in (p = 0.002) compared to amyloid-negative PD.

CONCLUSION

These findings suggest that multiple disease processes are associated with PD cognitive impairment and amyloid deposits may be observed already in early stages. However, prevalence of amyloid positivity is in the range of literature age-matched control population. Increased cortical and subcortical amyloid is associated with poor performance in attentive-executive domains while cognitive deficits at MoCA and SDMT may identify amyloid-related dysfunction in early PD.

Sleep-Cognition Hypothesis In maritime Pilots, what is the effect of long-term work-related poor sleep on cognition and amyloid accumulation in healthy middle-aged maritime pilots: methodology of a case-control study

INTRODUCTION

Evidence indicates a bidirectional relationship between poor sleep and Alzheimer's disease (AD). While AD may lead to disruption of normal sleep, poor sleep in itself may play a causal role in the development of AD by influencing the production and/or clearance of the amyloid-beta (Aβ) protein. This led to the hypothesis that extended periods (>10 years) of sleep loss could lead to Aβ accumulation with subsequent cognitive AD-related decline. This manuscript describes the methodology of the SCHIP study, a cohort study in maritime pilots that aims at investigating the relationship between prolonged work-related sleep loss, cognitive function and amyloid accumulation among healthy middle-aged maritime pilots, to test the hypothesis that prolonged sleep loss increases the risk of AD-related cognitive decline.

METHODS

Our study sample consists of a group of healthy middle-aged maritime pilots (n=20), who have been exposed to highly irregular work schedules for more than 15 years. The maritime pilots will be compared to a group of healthy, age and education-matched controls (n=20) with normal sleep. Participants will complete 10 days of actigraphy (Actiwatch 2, Philips Respironics) combined with a sleep-wake diary. They will undergo one night of polysomnography, followed by comprehensive assessment of cognitive function. Additionally, participants will undergo amyloid positron emission tomography-CT to measure brain amyloid accumulation and MRI to investigate atrophy and vascular changes.

ANALYSIS

All analyses will be performed using IBM SPSS V.20.0 (SPSS). We will perform independent samples t-tests to compare all outcome parameters.

ETHICS AND DISSEMINATION

The study protocol was approved by our institutional ethical review board (NL55712.091.16, file number 2016-2337) and will be performed according to Good Clinical Practice rules. Data and results will be published in 2020.

Optimized dual-time-window protocols for quantitative [18F]flutemetamol and [18F]florbetaben PET studies

Background

A long dynamic scanning protocol may be required to accurately measure longitudinal changes in amyloid load. However, such a protocol results in a lower patient comfort and scanning efficiency compared to static scans. A compromise can be achieved by implementing dual-time-window protocols. This study aimed to optimize these protocols for quantitative [¹⁸F]flutemetamol and [¹⁸F]florbetaben studies.

Methods

Rate constants for subjects across the Alzheimer’s disease spectrum (i.e., non-displaceable binding potential (BP_ND) in the range 0.02–0.77 and 0.02–1.04 for [¹⁸F]flutemetamol and [¹⁸F]florbetaben, respectively) were established based on clinical [¹⁸F]flutemetamol (N = 6) and [¹⁸F]florbetaben (N = 20) data, and used to simulate tissue time-activity curves (TACs) of 110 min using a reference tissue and plasma input model. Next, noise was added (N = 50) and data points corresponding to different intervals were removed from the TACs, ranging from 0 (i.e., 90–90 = full-kinetic curve) to 80 (i.e., 10–90) minutes, creating a dual-time-window. Resulting TACs were fitted using the simplified reference tissue method (SRTM) to estimate the BP_ND, outliers (≥ 1.5 × BP_ND max) were removed and the bias was assessed using the distribution volume ratio (DVR = BP_ND + 1). To this end, acceptability curves, which display the fraction of data below a certain bias threshold, were generated and the area under those curves were calculated.

Results

[¹⁸F]Flutemetamol and [¹⁸F]florbetaben data demonstrated an increased bias in amyloid estimate for larger intervals and higher noise levels. An acceptable bias (≤ 3.1%) in DVR could be obtained with all except the 10–90 and 20–90-min intervals. Furthermore, a reduced fraction of acceptable data and most outliers were present for these two largest intervals (maximum percentage outliers 48 and 32 for [¹⁸F]flutemetamol and [¹⁸F]florbetaben, respectively).

Conclusions

The length of the interval inversely correlates with the accuracy of the BP_ND estimates. Consequently, a dual-time-window protocol of 0–30 and 90–110 min (=maximum of 60 min interval) allows for accurate estimation of BP_ND values for both tracers.

[¹⁸F]flutemetamol: EudraCT 2007-000784-19, registered 8 February 2007, [¹⁸F]florbetaben: EudraCT 2006-003882-15, registered 2006.

Electronic supplementary material

The online version of this article (10.1186/s13550-019-0499-4) contains supplementary material, which is available to authorized users.

PET/MRI Hybrid Systems

Over the last decade, the combination of PET and MRI in one system has proven to be highly successful in basic preclinical research, as well as in clinical research. Nowadays, PET/MRI systems are well established in preclinical imaging and are progressing into clinical applications to provide further insights into specific diseases, therapeutic assessments, and biological pathways. Certain challenges in terms of hardware had to be resolved concurrently with the development of new techniques to be able to reach the full potential of both combined techniques. This review provides an overview of these challenges and describes the opportunities that simultaneous PET/MRI systems can exploit in comparison with stand-alone or other combined hybrid systems. New approaches were developed for simultaneous PET/MRI systems to correct for attenuation of 511 keV photons because MRI does not provide direct information on gamma photon attenuation properties. Furthermore, new algorithms to correct for motion were developed, because MRI can accurately detect motion with high temporal resolution. The additional information gained by the MRI can be employed to correct for partial volume effects as well. The development of new detector designs in combination with fast-decaying scintillator crystal materials enabled time-of-flight detection and incorporation in the reconstruction algorithms. Furthermore, this review lists the currently commercially available systems both for preclinical and clinical imaging and provides an overview of applications in both fields. In this regard, special emphasis has been placed on data analysis and the potential for both modalities to evolve with advanced image analysis tools, such as cluster analysis and machine learning.

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

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