Unsupervised [18F]Flortaucipir cutoffs for tau positivity and staging in Alzheimer's disease

PURPOSE

Several [18F]Flortaucipir cutoffs have been proposed for tau PET positivity (T+) in Alzheimer's disease (AD), but none were data-driven. The aim of this study was to establish and validate unsupervised T+ cutoffs by applying Gaussian mixture models (GMM).

METHODS

Amyloid negative (A-) cognitively normal (CN) and amyloid positive (A+) AD-related dementia (ADRD) subjects from ADNI (n=269) were included. ADNI (n=475) and Geneva Memory Clinic (GMC) cohorts (n=98) were used for validation. GMM-based cutoffs were extracted for the temporal meta-ROI, and validated against previously published cutoffs and visual rating.

RESULTS

GMM-based cutoffs classified less subjects as T+, mainly in the A- CN (<3.4% vs >28.5%) and A+ CN (<14.5% vs >42.9%) groups and showed higher agreement with visual rating (ICC=0.91 vs ICC<0.62) than published cutoffs.

CONCLUSION

We provided reliable data-driven [18F]Flortaucipir cutoffs for in vivo T+ detection in AD. These cutoffs might be useful to select participants in clinical and research studies.

Image-level trajectory inference of tau pathology using variational autoencoder for Flortaucipir PET

Purpose

Alzheimer’s disease (AD) studies revealed that abnormal deposition of tau spreads in a specific spatial pattern, namely Braak stage. However, Braak staging is based on post mortem brains, each of which represents the cross section of the tau trajectory in disease progression, and numerous studies were reported that do not conform to that model. This study thus aimed to identify the tau trajectory and quantify the tau progression in a data-driven approach with the continuous latent space learned by variational autoencoder (VAE).

Methods

A total of 1080 [¹⁸F]Flortaucipir brain positron emission tomography (PET) images were collected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. VAE was built to compress the hidden features from tau images in latent space. Hierarchical agglomerative clustering and minimum spanning tree (MST) were applied to organize the features and calibrate them to the tau progression, thus deriving pseudo-time. The image-level tau trajectory was inferred by continuously sampling across the calibrated latent features. We assessed the pseudo-time with regard to tau standardized uptake value ratio (SUVr) in AD-vulnerable regions, amyloid deposit, glucose metabolism, cognitive scores, and clinical diagnosis.

Results

We identified four clusters that plausibly capture certain stages of AD and organized the clusters in the latent space. The inferred tau trajectory agreed with the Braak staging. According to the derived pseudo-time, tau first deposits in the parahippocampal and amygdala, and then spreads to the fusiform, inferior temporal lobe, and posterior cingulate. Prior to the regional tau deposition, amyloid accumulates first.

Conclusion

The spatiotemporal trajectory of tau progression inferred in this study was consistent with Braak staging. The profile of other biomarkers in disease progression agreed well with previous findings. We addressed that this approach additionally has the potential to quantify tau progression as a continuous variable by taking a whole-brain tau image into account.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05662-z.

Tau Biomarkers in Dementia: Positron Emission Tomography Radiopharmaceuticals in Tauopathy Assessment and Future Perspective

Abnormal accumulation of Tau protein is closely associated with neurodegeneration and cognitive impairment and it is a biomarker of neurodegeneration in the dementia field, especially in Alzheimer’s disease (AD); therefore, it is crucial to be able to assess the Tau deposits in vivo. Beyond the fluid biomarkers of tauopathy described in this review in relationship with the brain glucose metabolic patterns, this review aims to focus on tauopathy assessment by using Tau PET imaging. In recent years, several first-generation Tau PET tracers have been developed and applied in the dementia field. Common limitations of first-generation tracers include off-target binding and subcortical white-matter uptake; therefore, several institutions are working on developing second-generation Tau tracers. The increasing knowledge about the distribution of first- and second-generation Tau PET tracers in the brain may support physicians with Tau PET data interpretation, both in the research and in the clinical field, but an updated description of differences in distribution patterns among different Tau tracers, and in different clinical conditions, has not been reported yet. We provide an overview of first- and second-generation tracers used in ongoing clinical trials, also describing the differences and the properties of novel tracers, with a special focus on the distribution patterns of different Tau tracers. We also describe the distribution patterns of Tau tracers in AD, in atypical AD, and further neurodegenerative diseases in the dementia field.

Effect of Shortening the Scan Duration on Quantitative Accuracy of [18F]Flortaucipir Studies

PURPOSE

Dynamic positron emission tomography (PET) protocols allow for accurate quantification of [18F]flortaucipir-specific binding. However, dynamic acquisitions can be challenging given the long required scan duration of 130 min. The current study assessed the effect of shorter scan protocols for [18F]flortaucipir on its quantitative accuracy.

PROCEDURES

Two study cohorts with Alzheimer's disease (AD) patients and healthy controls (HC) were included. All subjects underwent a 130-min dynamic [18F]flortaucipir PET scan consisting of two parts (0-60/80-130 min) post-injection. Arterial sampling was acquired during scanning of the first cohort only. For the second cohort, a second PET scan was acquired within 1-4 weeks of the first PET scan to assess test-retest repeatability (TRT). Three alternative time intervals were explored for the second part of the scan: 80-120, 80-110 and 80-100 min. Furthermore, the first part of the scan was also varied: 0-50, 0-40 and 0-30 min time intervals were assessed. The gap in the reference TACs was interpolated using four different interpolation methods: population-based input function 2T4k_VB (POP-IP_2T4k_VB), cubic, linear and exponential. Regional binding potential (BPND) and relative tracer delivery (R1) values estimated using simplified reference tissue model (SRTM) and/or receptor parametric mapping (RPM). The different scan protocols were compared to the respective values estimated using the original scan acquisition. In addition, TRT of the RPM BPND and R1 values estimated using the optimal shortest scan duration was also assessed.

RESULTS

RPM BPND and R1 obtained using 0-30/80-100 min scan and POP-IP_2T4k_VB reference region interpolation had an excellent correlation with the respective parametric values estimated using the original scan duration (r2 > 0.95). The TRT of RPM BPND and R1 using the shortest scan duration was - 1 ± 5 % and - 1 ± 6 % respectively.

CONCLUSIONS

This study demonstrated that [18F]flortaucipir PET scan can be acquired with sufficient quantitative accuracy using only 50 min of dual-time-window scanning time.

A multicenter comparison of [18F]flortaucipir, [18F]RO948, and [18F]MK6240 tau PET tracers to detect a common target ROI for differential diagnosis

PURPOSE

This study aims to determine whether comparable target regions of interest (ROIs) and cut-offs can be used across [18F]flortaucipir, [18F]RO948, and [18F]MK6240 tau positron emission tomography (PET) tracers for differential diagnosis of Alzheimer's disease (AD) dementia vs either cognitively unimpaired (CU) individuals or non-AD neurodegenerative diseases.

METHODS

A total of 1755 participants underwent tau PET using either [18F]flortaucipir (n = 975), [18F]RO948 (n = 493), or [18F]MK6240 (n = 287). SUVR values were calculated across four theory-driven ROIs and several tracer-specific data-driven (hierarchical clustering) regions of interest (ROIs). Diagnostic performance and cut-offs for ROIs were determined using receiver operating characteristic analyses and the Youden index, respectively.

RESULTS

Comparable diagnostic performance (area under the receiver operating characteristic curve [AUC]) was observed between theory- and data-driven ROIs. The theory-defined temporal meta-ROI generally performed very well for all three tracers (AUCs: 0.926-0.996). An SUVR value of approximately 1.35 was a common threshold when using this ROI.

CONCLUSION

The temporal meta-ROI can be used for differential diagnosis of dementia patients with [18F]flortaucipir, [18F]RO948, and [18F]MK6240 tau PET with high accuracy, and that using very similar cut-offs of around 1.35 SUVR. This ROI/SUVR cut-off can also be applied across tracers to define tau positivity.

Automated production of [18F]Flortaucipir for PET imaging of tauopathies

Radiotracer [¹⁸F]Flortaucipir is an FDA-approved diagnostic agent for PET imaging of density and distribution of abnormal tau protein deposition (tauopathies) in Alzheimer's disease. A high-yield automated method for routine GMP-compliant [¹⁸F]Flortaucipir production is desired to meet increasing clinical need. In this work, we reported an automated radiosynthesis of [¹⁸F]Flortaucipir in a RNplus Research module and the quality control (QC) tests for human use under full GMP compliance. Briefly, automated radiosynthesis of [¹⁸F]Flortaucipir was processed via nucleophilic radiofluorination of precursor AV1622 and followed by acid hydrolysis in a RNplus Research module, which included the radiosynthesis, semi-preparative high-performance liquid chromatography (HPLC) purification, and the final formulation via solid phase extraction (SPE). The final products were obtained in non-decay corrected radiochemical yields of 14.8-16.6% (n = 3) within total synthesis time of 55 min. The radiochemical purities of [¹⁸F]Flortaucipir were > 99.9% and the molar activities were 247.9-384.8 GBq/µmol at end of synthesis. The results of QC tests met all the specifications for human use. In conclusion, [¹⁸F]Flortaucipir was reproducibly achieved with desired radiochemical yield and high radiochemical purity and molar activity. Three GMP compliant validation runs and QC results demonstrated the efficacy of this method for automated production of [¹⁸F]Flortaucipir for human use.

Non-invasive Standardised Uptake Value for Verification of the Use of Previously Validated Reference Region for [18F]Flortaucipir and [18F]Florbetapir Brain PET Studies

Purpose

The simplified reference tissue model (SRTM) is commonly applied for the quantification of brain positron emission tomography (PET) studies, particularly because it avoids arterial cannulation. SRTM requires a validated reference region which is obtained by baseline-blocking or displacement studies. Once a reference region is validated, the use should be verified for each new subject. This verification normally requires volume of distribution (V_T) of a reference region. However, performing dynamic scanning and arterial sampling is not always possible, specifically in elderly subjects and in advanced disease stages. The aim of this study was to investigate the use of non-invasive standardised uptake value (SUV) approaches, in comparison to V_T, as a verification of the previously validated grey matter cerebellum reference region for [¹⁸F]flortaucipir and [¹⁸F]florbetapir PET imaging in Alzheimer’s disease (AD) patients and controls.

Procedures

Dynamic 130-min [¹⁸F]flortaucipir PET scans obtained from nineteen subjects (10 AD patients) and 90-min [¹⁸F]florbetapir dynamic scans obtained from fourteen subjects (8 AD patients) were included. Regional V_T’s were estimated for both tracers and were considered the standard verification of the previously validated reference region. Non-invasive SUVs corrected for body weight (SUV_BW), lean body mass (SUL), and body surface area (SUV_BSA) were obtained by using later time intervals of the dynamic scans. Simulations were also performed to assess the effect of flow and specific binding (BP_ND) on the SUVs.

Results

A low SUV corresponded well with a low V_T for both [¹⁸F]flortaucipir and [¹⁸F]florbetapir. Simulation confirmed that SUVs were only slightly affected by flow changes and that increases in SUV were predominantly determined by the presence of specific binding.

Conclusions

In situations where dynamic scanning and arterial sampling is not possible, a low SUV_{(80–100 min)} for [¹⁸F]flortaucipir and a low SUV_{(50–70 min)} for [¹⁸F]florbetapir may be used as indication for absence of specific binding in the grey matter cerebellum reference region.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11307-020-01572-y.

Test-retest repeatability of [18F]Flortaucipir PET in Alzheimer's disease and cognitively normal individuals

The aim of this study was to investigate the test-retest (TRT) repeatability of various parametric quantification methods for [18F]Flortaucipir positron emission tomography (PET). We included eight subjects with dementia or mild cognitive impairment due to Alzheimer's disease and six cognitively normal subjects. All underwent two 130-min dynamic [18F]Flortaucipir PET scans within 3 ± 1 weeks. Data were analyzed using reference region models receptor parametric mapping (RPM), simplified reference tissue method 2 (SRTM2) and reference logan (RLogan), as well as standardized uptake value ratios (SUVr, time intervals 40-60, 80-100 and 110-130 min post-injection) with cerebellar gray matter as reference region. We obtained distribution volume ratio or SUVr, first for all brain regions and then in three tau-specific regions-of-interest (ROIs). TRT repeatability (%) was defined as |retest-test|/(average (test + retest)) × 100. For all methods and across ROIs, TRT repeatability ranged from (median (IQR)) 0.84% (0.68-2.15) to 6.84% (2.99-11.50). TRT repeatability was good for all reference methods used, although semi-quantitative models (i.e. SUVr) performed marginally worse than quantitative models, for instance TRT repeatability of RPM: 1.98% (0.78-3.58) vs. SUVr80-100: 3.05% (1.28-5.52), p < 0.001. Furthermore, for SUVr80-100 and SUVr110-130, with higher average SUVr, more variation was observed. In conclusion, while TRT repeatability was good for all models used, quantitative methods performed slightly better than semi-quantitative methods.