The Irony of PET Tau Probe Specificity

A comparison of visual assessment and semi-quantification for the diagnostic and prognostic use of [18F]flortaucipir PET in a memory clinic cohort

PURPOSE

[18F]Flortaucipir PET is a powerful diagnostic and prognostic tool for Alzheimer's disease (AD). Tau status definition is mainly based in the literature on semi-quantitative measures while in clinical settings visual assessment is usually preferred. We compared visual assessment with established semi-quantitative measures to classify subjects and predict the risk of cognitive decline in a memory clinic population.

METHODS

We included 245 individuals from the Geneva Memory Clinic who underwent [18F]flortaucipir PET. Amyloid status was available for 207 individuals and clinical follow-up for 135. All scans were blindly evaluated by three independent raters who visually classified the scans according to Braak stages. Standardized uptake value ratio (SUVR) values were obtained from a global meta-ROI to define tau positivity, and the Simplified Temporo-Occipital Classification (STOC) was applied to obtain semi-quantitatively tau stages. The agreement between measures was tested using Cohen's kappa (k). ROC analysis and linear mixed-effects models were applied to test the diagnostic and prognostic values of tau status and stages obtained with the visual and semi-quantitative approaches.

RESULTS

We found good inter-rater reliability in the visual interpretation of tau Braak stages, independently from the rater's expertise (k>0.68, p<0.01). A good agreement was equally found between visual and SUVR-based classifications for tau status (k=0.67, p<0.01). All tau-assessment modalities significantly discriminated amyloid-positive MCI and demented subjects from others (AUC>0.80) and amyloid-positive from negative subjects (AUC>0.85). Linear mixed-effect models showed that tau-positive individuals presented a significantly faster cognitive decline than the tau-negative group (p<0.01), independently from the classification method.

CONCLUSION

Our results show that visual assessment is reliable for defining tau status and stages in a memory clinic population. The high inter-rater reliability, the substantial agreement, and the similar diagnostic and prognostic performance of visual rating and semi-quantitative methods demonstrate that [18F]flortaucipir PET can be robustly assessed visually in clinical practice.

PET/CT/MRI in Clinical Trials of Alzheimer's Disease

With the advent of PET imaging in 1976, 2-deoxy-2-[18F]fluoro-D-glucose (FDG)-PET became the preferred method for in vivo investigation of cerebral processes, including regional hypometabolism in Alzheimer's disease. With the emergence of amyloid-PET tracers, [11C]Pittsburgh Compound-B in 2004 and later [18F]florbetapir, [18F]florbetaben, and [18F]flumetamol, amyloid-PET has replaced FDG-PET in Alzheimer's disease anti-amyloid clinical trial treatments to ensure "amyloid positivity" as an entry criterion, and to measure treatment-related decline in cerebral amyloid deposits. MRI has been used to rule out other brain diseases and screen for 'amyloid-related imaging abnormalities' (ARIAs) of two kinds, ARIA-E and ARIA-H, characterized by edema and micro-hemorrhage, respectively, and, to a lesser extent, to measure changes in cerebral volumes. While early immunotherapy trials of Alzheimer's disease showed no clinical effects, newer monoclonal antibody trials reported decreases of 27% to 85% in the cerebral amyloid-PET signal, interpreted by the Food and Drug Administration as amyloid removal expected to result in a reduction in clinical decline. However, due to the lack of diagnostic specificity of amyloid-PET tracers, amyloid positivity cannot prevent the inclusion of non-Alzheimer's patients and even healthy subjects in these clinical trials. Moreover, the "decreasing amyloid accumulation" assessed by amyloid-PET imaging has questionable quantitative value in the presence of treatment-related brain damage (ARIAs). Therefore, future Alzheimer's clinical trials should disregard amyloid-PET imaging and focus instead on assessment of regional brain function by FDG-PET and MRI monitoring of ARIAs and brain volume loss in all trial patients.

Investigating Tau and Amyloid Tracer Skull Binding in Studies of Alzheimer Disease

Off-target binding of [18F]flortaucipir (FTP) can complicate quantitative PET analyses. An underdiscussed off-target region is the skull. Here, we characterize how often FTP skull binding occurs, its influence on estimates of Alzheimer disease pathology, its potential drivers, and whether skull uptake is a stable feature across time and tracers. Methods: In 313 cognitively normal and mildly impaired participants, CT scans were used to define a skull mask. This mask was used to quantify FTP skull uptake. Skull uptake of the amyloid-β PET tracers [18F]florbetapir and [11C]Pittsburgh compound B (n = 152) was also assessed. Gaussian mixture modeling defined abnormal levels of skull binding for each tracer. We examined the relationship of continuous bone uptake to known off-target binding in the basal ganglia and choroid plexus as well as skull density measured from the CT. Finally, we examined the confounding effect of skull binding on pathologic quantification. Results: We found that 50 of 313 (∼16%) FTP scans had high levels of skull signal. Most were female (n = 41, 82%), and in women, lower skull density was related to higher FTP skull signal. Visual reads by a neuroradiologist revealed a significant relationship with hyperostosis; however, only 21% of women with high skull binding were diagnosed with hyperostosis. FTP skull signal did not substantially correlate with other known off-target regions. Skull uptake was consistent over longitudinal FTP scans and across tracers. In amyloid-β-negative, but not -positive, individuals, FTP skull binding impacted quantitative estimates in temporal regions. Conclusion: FTP skull binding is a stable, participant-specific phenomenon and is unrelated to known off-target regions. Effects were found primarily in women and were partially related to lower bone density. The presence of [11C]Pittsburgh compound B skull binding suggests that defluorination does not fully explain FTP skull signal. As signal in skull bone can impact quantitative analyses and differs across sex, it should be explicitly addressed in studies of aging and Alzheimer disease.

Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation

Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegenerative disease research, opening avenues for molecular diagnosis in vivo. However, few have been approved for clinical use. Understanding the neurobiological basis of PET signal validation remains problematic because it requires a large-scale, voxel-to-voxel correlation between PET and (immuno) histological signals. Large dimensionality of whole human brains, tissue deformation impacting co-registration, and computing requirements to process terabytes of information preclude proper validation. We developed a computational pipeline to identify and segment particles of interest in billion-pixel digital pathology images to generate quantitative, 3D density maps. The proposed convolutional neural network for immunohistochemistry samples, IHCNet, is at the pipeline's core. We have successfully processed and immunostained over 500 slides from two whole human brains with three phospho-tau antibodies (AT100, AT8, and MC1), spanning several terabytes of images. Our artificial neural network estimated tau inclusion from brain images, which performs with ROC AUC of 0.87, 0.85, and 0.91 for AT100, AT8, and MC1, respectively. Introspection studies further assessed the ability of our trained model to learn tau-related features. We present an end-to-end pipeline to create terabytes-large 3D tau inclusion density maps co-registered to MRI as a means to facilitate validation of PET tracers.

Amyloid and Tau in Alzheimer's Disease: Biomarkers or Molecular Targets for Therapy? Are We Shooting the Messenger?

Alzheimer's disease is a neuropsychiatric disorder with devastating clinical and socioeconomic consequences. Since the original description of the neuropathological correlates of the disorder, neuritic plaques and neurofibrillary tangles have been presumed to be critical to the underlying pathophysiology of the illness. The authors review the clinical and neuropathological origins of Alzheimer's disease and trace the evolution of modern biomarkers from their historical roots. They describe how technological innovations such as neuroimaging and biochemical assays have been used to measure and quantify key proteins and lipids in the brain, cerebrospinal fluid, and blood and advance their role as biomarkers of Alzheimer's disease. Together with genomics, these approaches have led to the development of a thematic and focused science in the area of degenerative disorders. The authors conclude by drawing distinctions between legitimate biomarkers of disease and molecular targets for therapeutic intervention and discuss future approaches to this complex neurobehavioral illness.

Graph Models of Pathology Spread in Alzheimer's Disease: An Alternative to Conventional Graph Theoretic Analysis

Background: Graph theory and connectomics are new techniques for uncovering disease-induced changes in the brain's structural network. Most prior studied have focused on network statistics as biomarkers of disease. However, an emerging body of work involves exploring how the network serves as a conduit for the propagation of disease factors in the brain and has successfully mapped the functional and pathological consequences of disease propagation. In Alzheimer's disease (AD), progressive deposition of misfolded proteins amyloid and tau is well-known to follow fiber projections, under a "prion-like" trans-neuronal transmission mechanism, through which misfolded proteins cascade along neuronal pathways, giving rise to network spread. Methods: In this review, we survey the state of the art in mathematical modeling of connectome-mediated pathology spread in AD. Then we address several open questions that are amenable to mathematically precise parsimonious modeling of pathophysiological processes, extrapolated to the whole brain. We specifically identify current formal models of how misfolded proteins are produced, aggregate, and disseminate in brain circuits, and attempt to understand how this process leads to stereotyped progression in Alzheimer's and other related diseases. Conclusion: This review serves to unify current efforts in modeling of AD progression that together have the potential to explain observed phenomena and serve as a test-bed for future hypothesis generation and testing in silico. Impact statement Graph theory is a powerful new approach that is transforming the study of brain processes. There do not exist many focused reviews of the subfield of graph modeling of how Alzheimer's and other dementias propagate within the brain network, and how these processes can be mapped mathematically. By providing timely and topical review of this subfield, we fill a critical gap in the community and present a unified view that can serve as an in silico test-bed for future hypothesis generation and testing. We also point to several open and unaddressed questions and controversies that future practitioners can tackle.

Evaluation of a visual interpretation method for tau-PET with 18F-flortaucipir

INTRODUCTION

Positron emission tomography targeting tau (tau-PET) is a promising diagnostic tool for the identification of Alzheimer's disease (AD). Currently available data rely on quantitative measures, and a visual interpretation method, critical for clinical translation, is needed.

METHODS

We developed a visual interpretation method for 18F-flortaucipir tau-PET and tested it on 274 individuals (cognitively normal controls, patients with mild cognitive impairment [MCI], AD dementia, and non-AD diagnoses). Two readers interpreted 18F-flortaucipir PET using two complementary indices: a global visual score and a visual distribution pattern.

RESULTS

Global visual scores were reliable, correlated with global cortical 18F-flortaucipir standardized uptake value ratio (SUVR) and were associated with clinical diagnosis and amyloid status. The AD-like 18F-flortaucipir pattern had good sensitivity and specificity to identify amyloid-positive patients with AD dementia or MCI.

DISCUSSION

This 18F-flortaucipir visual rating scheme is associated with SUVR quantification, clinical diagnosis, and amyloid status, and constitutes a promising approach to tau measurement in clinical settings.

Chronic Traumatic Encephalopathy: A Comparison with Alzheimer's Disease and Frontotemporal Dementia

The clinical diagnosis of chronic traumatic encephalopathy (CTE) is challenging due to heterogeneous clinical presentations and overlap with other neurodegenerative dementias. Depending on the clinical presentation, the differential diagnosis of CTE includes Alzheimer's disease (AD), behavioral variant frontotemporal dementia (bvFTD), Parkinson's disease, amyotrophic lateral sclerosis, primary mood disorders, posttraumatic stress disorder, and psychotic disorders. The aim of this article is to compare the clinical aspects, genetics, fluid biomarkers, imaging, treatment, and pathology of CTE to those of AD and bvFTD. A detailed clinical evaluation, neurocognitive assessment, and structural brain imaging can inform the differential diagnosis, while molecular biomarkers can help exclude underlying AD pathology. Prospective studies that include clinicopathological correlations are needed to establish tools that can more accurately determine the cause of neuropsychiatric decline in patients at risk for CTE.

Multi-Modal Signatures of Tau Pathology, Neuronal Fiber Integrity, and Functional Connectivity in Traumatic Brain Injury

[¹⁸F]AV-1451 (aka ¹⁸F-Flortaucipir, [¹⁸F]T807) was developed for positron-emission tomography (PET) imaging of paired helical filaments of hyperphosphorylated tau, which are of interest in a range of neuropathologies, including traumatic brain injury (TBI). Magnetic resonance imaging (MRI) techniques like diffusion tensor imaging (DTI) and resting state functional connectivity assess structural and functional characteristics of the brain, complementing the molecular information that can be obtained by PET. The goal herein was to explore the utility of such multi-modal imaging in a case series based on a population of TBI subjects. This study probes the interrelationship between tau deposition, white matter integrity, and gray matter functional connectivity across the spectrum of TBI. Nineteen subjects (11 controls, five former contact sports athletes, one automotive accident, and two with military-related injury) underwent [¹⁸F]AV-1451 PET and magnetic resonance scanning procedures. [¹⁸F]AV-1451 distribution volume ratio (DVR) was estimated using the Logan method and the cerebellum as a reference region. Diffusion tractography images and fractional anisotropy (FA) images were generated using diffusion toolkit and FSL. Resting-state functional MRI (fMRI) analysis was based on a graph theory metric, namely weighted degree centrality. TBI subjects showed greater heterogeneity in [¹⁸F]AV-1451 DVR when compared with control subjects. In a subset of TBI subjects, areas with high [¹⁸F]AV-1451 binding corresponded with increased FA and diminished white matter tract density in DTI. Functional MRI results exhibited an increase in functional connectivity, particularly among local connections, in the areas where tau aggregates were more prevalent. In a case series of a diverse group of TBI subjects, brain regions with elevated tau burden exhibited increased functional connectivity as well as decreased white matter integrity. These findings portray molecular, microstructural, and functional corollaries of TBI that spatially coincide and can be measured in the living human brain using noninvasive neuroimaging techniques.

The Value of In Vitro Binding as Predictor of In Vivo Results: A Case for [18F]FDDNP PET

PURPOSE

Caution is warranted when in vitro results of biomarkers labeled with tritium were perfunctorily used to criticize in vivo data and conclusions derived with the same tracers labeled with positron emitters and positron emission tomography (PET). This concept is illustrated herein with the PET utilization of [¹⁸F]FDDNP, a biomarker used for in vivo visualization of β-amyloid and tau protein neuroaggregates in humans, later contradicted by in vitro data reported with [³H]FDDNP. In this investigation, we analyze the multiple factors involved in the experimental design of the [³H]FDDNP in vitro study that led to the erroneous interpretation of results.

PROCEDURE

The present work describes full details on the synthesis, characterization, purity, and kinetics of radiolytic stability of [³H]FDDNP. The optimal in vitro conditions for detecting tau and β-amyloid protein aggregates using macroscopic and microscopic autoradiography with both [¹⁸F]FDDNP and [³H]FDDNP are also presented. Macroscopic autoradiography determinations were performed with [³H]FDDNP of verified purity using established methods described previously in the literature.

RESULTS

The autoradiographic results using phosphate buffered saline (PBS) with less than 1 % EtOH and pure, freshly prepared [³H]FDDNP compared with the earlier reported data using [³H]FDDNP of undetermined purity and PBS in 10 % EtOH demonstrate the critical importance of rigorous experimental design for meaningful in vitro determinations. [¹⁸F]FDDNP binding to both amyloid plaques and neurofibrillary tangles was confirmed by amyloid and tau immunohistochemical stains of adjacent tissues.

CONCLUSIONS

This work illustrates the sensitivity of in vitro techniques to various experimental conditions and underscores that conclusions obtained from translational in vitro to in vivo determinations must always be performed with extreme care to avoid wrong interpretations that can be perpetuated and assumed without further analysis.

Effect of Off-Target Binding on 18F-Flortaucipir Variability in Healthy Controls Across the Life Span

Measuring early tau accumulation is important in studying aging and Alzheimer disease and is only as accurate as the signal-to-noise ratio of the tracer. Along with aggregated tau in the form of neurofibrillary tangles, ¹⁸F-flortaucipir has been reported to bind to neuromelanin, monoamine oxidase, calcifications, iron, leptomeningeal melanocytes, and microhemorrages. Although ¹⁸F-flortaucipir successfully differentiates healthy controls (HCs) from subjects with Alzheimer disease, variability exists in the cortical signal in amyloid-negative HCs. We aimed to explore the relationship between off-target binding signal and variability in the cortical signal in HCs. Methods: Subjects (n = 139) received ¹¹C-Pittsburgh compound B (PIB) and ¹⁸F-flortaucipir PET scans and a magnetization-prepared rapid gradient echo MRI scan. PET frames were realigned and coregistered to the MR images, which were segmented using FreeSurfer. In amyloid-negative HCs (n = 90; age range, 21-94 y), 7 nonspecific or off-target binding regions were considered: caudate, pallidum, putamen, thalamus, cerebellar white matter, hemispheric white matter, and choroid plexus. These regions of interest were assigned to 3 similarly behaving groups using principle components analysis, exploratory factor analysis, and Pearson correlations for caudate, putamen, and pallidum (also correlated with age); thalamus and white matter; and choroid plexus. In amyloid-negative HCs with ¹¹C-PIB and ¹⁸F-flortaucipir scans, correlations were calculated between white and gray matter before and after partial-volume correction. Results: The correlation between white and gray matter disappeared after partial-volume correction in ¹¹C-PIB (r ² = 0) but persisted for ¹⁸F-flortaucipir (r ² = 0.27), demonstrating that the correlation between white and gray matter signal in ¹⁸F-flortaucipir is not solely due to partial-volume effects. A linear regression showed that off-target signal from putamen and thalamus together explained 64% of the variability in the cortical signal in amyloid-negative HCs (not seen in amyloid-positive HCs). Variability in amyloid-negative HCs but not amyloid-positive HCs correlated with white matter signal (unrelated to partial-volume effects) and age-related off-target signal (possibly related to iron load). Conclusion: The noise in the ¹⁸F-flortaucipir measurement could pose challenges when studying early tau accumulation.

In vivo evidence for pre-symptomatic neuroinflammation in a MAPT mutation carrier

Neuroinflammation occurs in frontotemporal dementia, however its timing relative to protein aggregation and neuronal loss is unknown. Using positron emission tomography and magnetic resonance imaging to quantify these processes in a pre‐symptomatic carrier of the 10 + 16 MAPT mutation, we show microglial activation in frontotemporal regions, despite a lack of protein aggregation or atrophy in these areas. The distribution of microglial activation better discriminated the carrier from controls than did protein aggregation at this pre‐symptomatic disease stage. Our findings suggest an early role for microglial activation in frontotemporal dementia. Longitudinal studies are needed to explore the causality of this pathophysiological association.

Detection and quantification of beta cells by PET imaging: why clinical implementation has never been closer

In this issue of Diabetologia, Alavi and Werner ( https://doi.org/10.1007/s00125-018-4676-1 ) criticise the attempts to use positron emission tomography (PET) for in vivo imaging of pancreatic beta cells, which they consider as 'futile'. In support of this strong statement, they point out the limitations of PET imaging, which they believe render beta cell mass impossible to estimate using this method. In our view, the Alavi and Werner presentation of the technical limitations of PET imaging does not reflect the current state of the art, which leads them to questionable conclusions towards the feasibility of beta cell imaging using this approach. Here, we put forward arguments in favour of continuing the development of innovative technologies enabling in vivo imaging of pancreatic beta cells and concisely present the current state of the art regarding putative technical limitations of PET imaging. Indeed, far from being a 'futile' effort, we demonstrate that beta cell imaging is now closer than ever to becoming a long-awaited clinical reality.

Futility of attempts to detect and quantify beta cells by PET imaging in the pancreas: why it is time to abandon the approach

In this commentary, we describe the limitations of positron emission tomography (PET) in visualising and characterising beta cell mass in the native pancreas in healthy individuals and those diagnosed with diabetes. Imaging with PET requires a large mass of targeted cells or other structures in the range of approximately 8-10 cm³. Since islets occupy only 1% of the pancreatic volume and are dispersed throughout the organ, it is our view that uptake of PET tracers, including [¹⁸F]fluoropropyl-(+)-dihydrotetrabenazine, in islets cannot be successfully detected by current imaging modalities. Therefore, we dispute the feasibility of PET imaging for the detection of loss of beta cells in the native pancreas in individuals with diabetes. However, we believe this novel approach can be successfully employed to visualise beta cell mass in individuals with hyperinsulinism and transplanted islets.