Spill-in counts in the quantification of 18F-florbetapir on Aβ-negative subjects: the effect of including white matter in the reference region

Alzheimer's Amyloid Hypothesis and Antibody Therapy: Melting Glaciers?

The amyloid cascade hypothesis for Alzheimer's disease is still alive, although heavily challenged. Effective anti-amyloid immunotherapy would confirm the hypothesis' claim that the protein amyloid-beta is the cause of the disease. Two antibodies, aducanumab and lecanemab, have been approved by the U.S. Food and Drug Administration, while a third, donanemab, is under review. The main argument for the FDA approvals is a presumed therapy-induced removal of cerebral amyloid deposits. Lecanemab and donanemab are also thought to cause some statistical delay in the determination of cognitive decline. However, clinical efficacy that is less than with conventional treatment, selection of amyloid-positive trial patients with non-specific amyloid-PET imaging, and uncertain therapy-induced removal of cerebral amyloids in clinical trials cast doubt on this anti-Alzheimer's antibody therapy and hence on the amyloid hypothesis, calling for a more thorough investigation of the negative impact of this type of therapy on the brain.

FDG PET (and MRI) for Monitoring Immunotherapy in Alzheimer Disease

ABSTRACT

Passive immunotherapy for Alzheimer disease has been tried for over 10 years without success. However, in 2021 and most recently in January 2023, the US Food and Drug Administration granted accelerated approval of 2 antibodies for this purpose, aducanumab and lecanemab. In both cases, the approval was based on a presumed therapy-related removal of amyloid deposits from the brain and, in the case of lecanemab, also some delay in cognitive decline. We question the validity of the evidence for the removal of amyloid in particular as assessed by amyloid PET imaging, believing that what is observed is more likely a large nonspecific amyloid PET signal in the white matter that diminishes during immunotherapy-in line with dose-dependent increases in amyloid-related imaging abnormalities and increased loss of cerebral volume in treated compared with placebo patients. To investigate this further, we recommend repeat FDG PET and MRI in all future immunotherapy trials.

β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3

INTRODUCTION

The Centiloid scale was developed to harmonise the quantification of β-amyloid (Aβ) PET images across tracers, scanners, and processing pipelines. However, several groups have reported differences across tracers and scanners even after centiloid conversion. In this study, we aim to evaluate the impact of different pre and post-processing harmonisation steps on the robustness of longitudinal Centiloid data across three large international cohort studies.

METHODS

All Aβ PET data in AIBL (N = 3315), ADNI (N = 3442) and OASIS3 (N = 1398) were quantified using the MRI-based Centiloid standard SPM pipeline and the PET-only pipeline CapAIBL. SUVR were converted into Centiloids using each tracer's respective transform. Global Aβ burden from pre-defined target cortical regions in Centiloid units were quantified for both raw PET scans and PET scans smoothed to a uniform 8 mm full width half maximum (FWHM) effective smoothness. For Florbetapir, we assessed the performance of using both the standard Whole Cerebellum (WCb) and a composite white matter (WM)+WCb reference region. Additionally, our recently proposed quantification based on Non-negative Matrix Factorisation (NMF) was applied to all spatially and SUVR normalised images. Correlation with clinical severity measured by the Mini-Mental State Examination (MMSE) and effect size, as well as tracer agreement in 11C-PiB-18F-Florbetapir pairs and longitudinal consistency were evaluated.

RESULTS

The smoothing to a uniform resolution partially reduced longitudinal variability, but did not improve inter-tracer agreement, effect size or correlation with MMSE. Using a Composite reference region for 18F-Florbetapir improved inter-tracer agreement, effect size, correlation with MMSE, and longitudinal consistency. The best results were however obtained when using the NMF method which outperformed all other quantification approaches in all metrics used.

CONCLUSIONS

FWHM smoothing has limited impact on longitudinal consistency or outliers. A Composite reference region including subcortical WM should be used for computing both cross-sectional and longitudinal Florbetapir Centiloid. NMF improves Centiloid quantification on all metrics examined.

Partial Volume Correction Increases the Sensitivity of 18F-Florbetapir-Positron Emission Tomography for the Detection of Early Stage Amyloidosis

Purpose: To test whether correcting for unspecific signal from the cerebral white matter increases the sensitivity of amyloid-PET for early stages of cerebral amyloidosis.

Methods: We analyzed 18F-Florbetapir-PET and cerebrospinal fluid (CSF) Aβ42 data from 600 older individuals enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI), including people with normal cognition, mild cognitive impairment (MCI), and Alzheimer’s disease (AD) dementia. We determined whether three compartmental partial volume correction (PVC-3), explicitly modeling signal spill-in from white matter, significantly improved the association of CSF Aβ42 levels with global 18F-Florbetapir-PET values compared with standard processing without PVC (non-PVC) and a widely used two-compartmental PVC method (PVC-2). In additional voxel-wise analyses, we determined the sensitivity of PVC-3 compared with non-PVC and PVC-2 for detecting early regional amyloid build-up as modeled by decreasing CSF Aβ42 levels. For replication, we included an independent sample of 43 older individuals with subjective memory complaints from the INveStIGation of AlzHeimer’s PredicTors cohort (INSIGHT-preAD study).

Results: In the ADNI sample, PVC-3 18F-Florbetapir-PET values normalized to whole cerebellum signal showed significantly stronger associations with CSF Aβ42 levels than non-PVC or PVC-2, particularly in the lower range of amyloid levels. These effects were replicated in the INSIGHT-preAD sample. PVC-3 18F-Florbetapir-PET data detected regional amyloid build-up already at higher (less abnormal) CSF Aβ42 levels than non-PVC or PVC-2 data.

Conclusion: A PVC approach that explicitly models unspecific white matter binding improves the sensitivity of amyloid-PET for identifying the earliest stages of cerebral amyloid pathology which has implications for future primary prevention trials.

18F-florbetapir PET as a marker of myelin integrity across the Alzheimer's disease spectrum

Purpose

Recent evidence suggests that PET imaging with amyloid-β (Aβ) tracers can be used to assess myelin integrity in cerebral white matter (WM). Alzheimer’s disease (AD) is characterized by myelin changes that are believed to occur early in the disease course. Nevertheless, the extent to which demyelination, as measured with Aβ PET, contributes to AD progression remains unexplored.

Methods

Participants with concurrent ¹⁸F-florbetapir (FBP) PET, MRI, and cerebrospinal fluid (CSF) examinations were included (241 cognitively normal, 347 Aβ-positive cognitively impaired, and 207 Aβ-negative cognitively impaired subjects). A subset of these participants had also available diffusion tensor imaging (DTI) images (n = 195). We investigated cross-sectional associations of FBP retention in the white matter (WM) with MRI-based markers of WM degeneration, AD clinical progression, and fluid biomarkers. In longitudinal analyses, we used linear mixed models to assess whether FBP retention in normal-appearing WM (NAWM) predicted progression of WM hyperintensity (WMH) burden and clinical decline.

Results

In AD-continuum individuals, FBP retention in NAWM was (1) higher compared with WMH regions, (2) associated with DTI-based measures of WM integrity, and (3) associated with longitudinal progression of WMH burden. FBP uptake in WM decreased across the AD continuum and with increasingly abnormal CSF biomarkers of AD. Furthermore, FBP retention in the WM was associated with large-calibre axon degeneration as reflected by abnormal plasma neurofilament light chain levels. Low FBP uptake in NAWM predicted clinical decline in preclinical and prodromal AD, independent of demographics, global cortical Aβ, and WMH burden. Most of these associations were also observed in Aβ-negative cognitively impaired individuals.

Conclusion

These results support the hypothesis that FBP retention in the WM is myelin-related. Demyelination levels progressed across the AD continuum and were associated with clinical progression at early stages, suggesting that this pathologic process might be a relevant degenerative feature in the disease course.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05493-y.

SimPET-An open online platform for the Monte Carlo simulation of realistic brain PET data. Validation for 18 F-FDG scans

Purpose

SimPET (www.sim‐pet.org) is a free cloud‐based platform for the generation of realistic brain positron emission tomography (PET) data. In this work, we introduce the key features of the platform. In addition, we validate the platform by performing a comparison between simulated healthy brain FDG‐PET images and real healthy subject data for three commercial scanners (GE Advance NXi, GE Discovery ST, and Siemens Biograph mCT).

Methods

The platform provides a graphical user interface to a set of automatic scripts taking care of the code execution for the phantom generation, simulation (SimSET), and tomographic image reconstruction (STIR). We characterize the performance using activity and attenuation maps derived from PET/CT and MRI data of 25 healthy subjects acquired with a GE Discovery ST. We then use the created maps to generate synthetic data for the GE Discovery ST, the GE Advance NXi, and the Siemens Biograph mCT. The validation was carried out by evaluating Bland‐Altman differences between real and simulated images for each scanner. In addition, SPM voxel‐wise comparison was performed to highlight regional differences. Examples for amyloid PET and for the generation of ground‐truth pathological patients are included.

Results

The platform can be efficiently used for generating realistic simulated FDG‐PET images in a reasonable amount of time. The validation showed small differences between SimPET and acquired FDG‐PET images, with errors below 10% for 98.09% (GE Discovery ST), 95.09% (GE Advance NXi), and 91.35% (Siemens Biograph mCT) of the voxels. Nevertheless, our SPM analysis showed significant regional differences between the simulated images and real healthy patients, and thus, the use of the platform for converting control subject databases between different scanners requires further investigation.

Conclusions

The presented platform can potentially allow scientists in clinical and research settings to perform MC simulation experiments without the need for high‐end hardware or advanced computing knowledge and in a reasonable amount of time.

Reduced [18F]flortaucipir retention in white matter hyperintensities compared to normal-appearing white matter

PURPOSE

Recent research has suggested the use of white matter (WM) reference regions for longitudinal tau-PET imaging. However, tau tracers display affinity for the β-sheet structure formed by myelin, and thus WM lesions might influence tracer retention. Here, we explored whether the tau-sensitive tracer [¹⁸F]flortaucipir shows reduced retention in WM hyperintensities (WMH) and how this retention changes over time.

METHODS

We included 707 participants from the Alzheimer's Disease Neuroimaging Initiative with available [¹⁸F]flortaucipir-PET and structural and FLAIR MRI scans. WM segments and WMH were automatically delineated in the structural MRI and FLAIR scans, respectively. [¹⁸F]flortaucipir standardized uptake value ratios (SUVR) of WMH and normal-appearing WM (NAWM) were calculated using the inferior cerebellar grey matter as reference region, and a 3-mm erosion was applied to the combined NAWM and WMH masks to avoid partial volume effects. Longitudinal [¹⁸F]flortaucipir SUVR changes in NAWM and WMH were estimated using linear mixed models. The percent variance of WM-referenced cortical [¹⁸F]flortaucipir SUVRs explained by longitudinal changes in the WM reference region was estimated with the R² coefficient.

RESULTS

Compared to NAWM, WMH areas displayed significantly reduced [¹⁸F]flortaucipir SUVR, independent of cognitive impairment or Aβ status (mean difference = 0.14 SUVR, p < 0.001). Older age was associated with lower [¹⁸F]flortaucipir SUVR in both NAWM (- 0.002 SUVR/year, p = 0.005) and WMH (- 0.004 SUVR/year, p < 0.001). Longitudinally, [¹⁸F]flortaucipir SUVR decreased in NAWM (- 0.008 SUVR/year, p = 0.03) and even more so in WMH (- 0.02 SUVR/year, p < 0.001). Between 17% and 66% of the variance of longitudinal changes in cortical WM-referenced [¹⁸F]flortaucipir SUVRs were explained by longitudinal changes in the reference region.

CONCLUSIONS

[¹⁸F]flortaucipir retention in the WM decreases over time and is influenced by the presence of WMH, supporting the hypothesis that [¹⁸F]flortaucipir retention in the WM is partially myelin-dependent. These findings have implications for the use of WM reference regions for [¹⁸F]flortaucipir-PET imaging.

Error propagation analysis of seven partial volume correction algorithms for [18F]THK-5351 brain PET imaging

BACKGROUND

Novel partial volume correction (PVC) algorithms have been validated by assuming ideal conditions of image processing; however, in real clinical PET studies, the input datasets include error sources which cause error propagation to the corrected outcome.

METHODS

We aimed to evaluate error propagations of seven PVCs algorithms for brain PET imaging with [¹⁸F]THK-5351 and to discuss the reliability of those algorithms for clinical applications. In order to mimic brain PET imaging of [¹⁸F]THK-5351, pseudo-observed SUVR images for one healthy adult and one adult with Alzheimer's disease were simulated from individual PET and MR images. The partial volume effect of pseudo-observed PET images were corrected by using Müller-Gärtner (MG), the geometric transfer matrix (GTM), Labbé (LABBE), regional voxel-based (RBV), iterative Yang (IY), structural functional synergy for resolution recovery (SFS-RR), and modified SFS-RR algorithms with incorporation of error sources in the datasets for PVC processing. Assumed error sources were mismatched FWHM, inaccurate image-registration, and incorrectly segmented anatomical volume. The degree of error propagations in ROI values was evaluated by percent differences (%diff) of PV-corrected SUVR against true SUVR.

RESULTS

Uncorrected SUVRs were underestimated against true SUVRs (- 15.7 and - 53.7% in hippocampus for HC and AD conditions), and application of each PVC algorithm reduced the %diff. Larger FWHM mismatch led to larger %diff of PVC-SUVRs against true SUVRs for all algorithms. Inaccurate image registration showed systematic propagation for most algorithms except for SFS-RR and modified SFS-RR. Incorrect segmentation of the anatomical volume only resulted in error propagations in limited local regions.

CONCLUSIONS

We demonstrated error propagation by numerical simulation of THK-PET imaging. Error propagations of 7 PVC algorithms for brain PET imaging with [¹⁸F]THK-5351 were significant. Robust algorithms for clinical applications must be carefully selected according to the study design of clinical PET data.

Intensity normalization methods in brain FDG-PET quantification

BACKGROUND

The lack of standardization of intensity normalization methods and its unknown effect on the quantification output is recognized as a major drawback for the harmonization of brain FDG-PET quantification protocols. The aim of this work is the ground truth-based evaluation of different intensity normalization methods on brain FDG-PET quantification output.

METHODS

Realistic FDG-PET images were generated using Monte Carlo simulation from activity and attenuation maps directly derived from 25 healthy subjects (adding theoretical relative hypometabolisms on 6 regions of interest and for 5 hypometabolism levels). Single-subject statistical parametric mapping (SPM) was applied to compare each simulated FDG-PET image with a healthy database after intensity normalization based on reference regions methods such as the brain stem (RRBS), cerebellum (RRC) and the temporal lobe contralateral to the lesion (RRTL), and data-driven methods, such as proportional scaling (PS), histogram-based method (HN) and iterative versions of both methods (iPS and iHN). The performance of these methods was evaluated in terms of the recovery of the introduced theoretical hypometabolic pattern and the appearance of unspecific hypometabolic and hypermetabolic findings.

RESULTS

Detected hypometabolic patterns had significantly lower volumes than the introduced hypometabolisms for all intensity normalization methods particularly for slighter reductions in metabolism . Among the intensity normalization methods, RRC and HN provided the largest recovered hypometabolic volumes, while the RRBS showed the smallest recovery. In general, data-driven methods overcame reference regions and among them, the iterative methods overcame the non-iterative ones. Unspecific hypermetabolic volumes were similar for all methods, with the exception of PS, where it became a major limitation (up to 250 cm³) for extended and intense hypometabolism. On the other hand, unspecific hypometabolism was similar far all methods, and usually solved with appropriate clustering.

CONCLUSIONS

Our findings showed that the inappropriate use of intensity normalization methods can provide remarkable bias in the detected hypometabolism and it represents a serious concern in terms of false positives. Based on our findings, we recommend the use of histogram-based intensity normalization methods. Reference region methods performance was equivalent to data-driven methods only when the selected reference region is large and stable.