Tissot, Cécile

Abstract Background Tau‐PET tracers are essential for visualizing pathology in Alzheimer's (AD). High detectability to tau is crucial for early detection and monitoring of tau deposition. This study compares the noise to dynamic range ratio (NRR) of [ 18 F]FTP, [ 18 F]MK6240, [ 18 F]PI2620, and [ 18 F]RO948, cross‐sectionally and longitudinally. Methods 460 individuals from the HEAD study (23 cognitively unimpaired (CU) young, 249 CU old and 188 cognitively impaired) underwent [ 18 F]FTP and [ 18 F]MK6240 tau‐PET scans; 94 additionally received [ 18 F]PI2620 and [ 18 F]RO948. A subset of 28 individuals (15 CU and 13 CI) underwent [ 18 F]FTP and [ 18 F]MK6240 follow‐up scans (1.5 ± 0.1 years later). Annual change was measured as [(followup‐baseline)/time between scans]. Noise was calculated as the standard deviation (SD) of CU Aβ‐ participants aged ≤65 (SD CUAβ‐≤65 ). The dynamic range was calculated as the SD across all subjects (SD range ). A lower the NRR (=SD CUAβ‐≤65 /SD range ) indicates more detectability. Analyses were performed at both region‐of‐interest and voxel‐wise levels. Results Across the whole cohort, [ 18 F]MK6240 exhibited lower NRR than [ 18 F]FTP in all regions. Voxel‐wise, differences were most pronounced in the frontal medial temporal regions (Figure 1). Within the four‐tracers subset, [ 18 F]PI2620 and [ 18 F]FTP showed the highest NRR in Braak II, followed by [ 18 F]RO948 and [ 18 F]MK6240. In Braak IV‐VI, [ 18 F]MK6240 consistently demonstrated the lowest values, followed by [ 18 F]PI2620, [ 18 F]FTP and [ 18 F]RO948. Similarly, in metatemporal‐ROI and Braak III, [ 18 F]MK6240 remained the lowest, however followed by [ 18 F]FTP, [ 18 F]PI2620 and [ 18 F]RO948 (Figure 2). Lower [ 18 F]MK6240 NRR was due to larger SD range , while [ 18 F]FTP's lower values stemmed from smaller SD CUAβ‐≤65 . Conversely, high [ 18 F]PI2620 and [ 18 F]RO948 values are driven by larger SD CUAβ‐≤65 . Longitudinal analyses further confirmed that [ 18 F]MK6240 exhibited the lowest NRR across the entire brain, including AD‐related regions, with voxel‐wise differences mainly in the temporal and parietal lobes. Conclusion Tau‐PET tracers exhibit significant variability in detectability. [ 18 F]MK6240 consistently demonstrated lower NRR, implying better detectability across all regions, cross‐sectionally and longitudinally. Despite differences in NRR, [ 18 F]FTP, [ 18 F]RO948 and [ 18 F]PI2620 followed similar pattern. These results provide insights into the differential tracer detectability, helping guide their optimal use in detecting and tracking tau pathology. Ongoing follow‐up scans will further clarify longitudinal tracer detectability and its implications for tau progression in AD.

Abstract Background The 2024 NIA‐AA criteria propose an Alzheimer's disease (AD) staging system based on medial temporal (MT) and neocortical tau burden. However, the optimal strategy to assess tau burden in these regions, which represent distinct phases of AD pathophysiology, remains unclear. Here, we compared tau load and spatial extent of tauopathy (SEOT) as markers of tau burden in participants scanned with [ 18 F]MK6240 and [ 18 F]FTP. We investigated the relationship between these metrics in MT and neocortical regions‐of‐interest (ROIs) and determined which better correlates with AD severity. Method A total of 257 cognitively unimpaired (CU) and 124 Aβ+ cognitively impaired participants (mean age 68.2 years; 58% female) from the HEAD study underwent tau‐PET imaging with both [ 18 F]MK6240 and [ 18 F]FTP. Tau load was quantified using regional SUVR, and SEOT was calculated as the proportion of abnormal voxels relative to young controls. Both metrics were derived from the MT and neocortical ROIs. Spearman's correlations were computed between SUVR and SEOT within the same tracer and across tracers in the same ROIs. We compared rho coefficients to assess whether one metric showed stronger concordance. Additionally, we compared the correlations of SEOT and SUVR with global cognition, cortical thickness, Aβ‐PET load, and plasma pTau‐217. Statistical comparisons were performed using the R package cocor . Result SUVR and SEOT exhibited non‐linear correlations in both MT and neocortical ROIs for both tracers, with SEOT enhancing the correlation between [ 18 F]MK6240 and [ 18 F]FTP in the neocortex ( p <.0001; Figure 1). Both metrics increased with AD severity, with MT SUVR outperforming SEOT in distinguishing Aβ‐ CU from Aβ+ CU individuals, and neocortical SEOT outperforming SUVR in distinguishing Aβ+ MCI from CU (Figure 2). Neocortical SEOT showed stronger correlations with AD severity markers than SUVR for both tracers. MT SEOT was comparable to SUVR, outperforming SUVR only in correlations with MMSE and Aβ‐PET for [ 18 F]FTP (Figure 3). Conclusion Tau extent improves the association of tau‐PET tracers with AD severity, particularly in the neocortex. These findings suggest that tau extent might be a more suitable surrogate marker of tau burden in neocortical regions, offering valuable insights for in vivo staging of tau pathology and clinical trials targeting late‐stage tau pathology.

Abstract Background Variability in meningeal signal has been observed with various tau‐PET tracers. Differences have been observed in sex and age. Furthermore, the potential role of glymphatic clearance in this variability remains unclear. Here we compare meningeal signal of [ 18 F]MK6240 and [ 18 F]FTP tau‐PET tracers in cognitively unimpaired (CU) amyloid‐β‐ (Aβ‐) individuals, in relation to age, sex and glymphatic clearance. Methods 92 CU Aβ‐ (7 CU young [18‐35yo] and 85 CU old) underwent [ 18 F]MK6240 and [ 18 F]FTP tau‐PET scans, structural MRI, and resting‐state functional MRI (rsfMRI). In native space, we defined nine distinct levels representing meningeal regions, organized from those closest to the cortex (1) to those furthest away (9). Glymphatic clearance, measured as gBOLD/CSF coupling, was calculated for each participant; a lower value means a more efficient glymphatic clearance. Associations between meningeal tracer signal and factors such as sex, age, and glymphatic clearance were analyzed using t‐tests and linear regression models. Results All 9 meningeal regions were tested and rendered similar results; we will be showing those for meninges level 2. [ 18 F]MK6240 and [ 18 F]FTP meningeal signal significantly correlated with each other in both sexes (Figure 1). We observed higher [ 18 F]MK6240 meningeal signal in females compared to males while no difference was found for [ 18 F]FTP signal (Figure 2). In females, [ 18 F]MK6240 meningeal signal did not show a significant association with age, whereas in males, a significant relationship was observed. Both males and females exhibited lower [ 18 F]FTP meningeal signal with increasing age (Figure 3A). Additionally, glymphatic clearance was significantly associated with age for females with [ 18 F]MK6240. No significant associations were found in males with [ 18 F]MK6240 or in either sex for [ 18 F]FTP (Figure 3B). Conclusion Our findings demonstrate that meningeal signal of [ 18 F]MK6240 is significantly associated with glymphatic clearance in females, while in males, it is associated with age. In contrast, [ 18 F]FTP signal is primarily influenced by age in both sexes. These results highlight the distinct relationship between [ 18 F]MK6240 signal and glymphatic function in females, while age appears to play a significant role in both males and females for other tracer signal patterns.

Abstract Background Tau‐PET imaging enables in vivo detection of tau pathology in Alzheimer’s disease (AD), with early detection being critical for tracking disease progression. Here, we compare [ 18 F]FTP and [ 18 F]MK6240 in individuals with low tau burden. Method 450 individuals from the HEAD study (22 cognitively unimpaired (CU) young (CUY), 242 CU old and 186 cognitively impaired (CI)) underwent [ 18 F]FTP and [ 18 F]MK6240 tau‐PET and amyloid‐PET scans. Scans were processed using identical pipelines with inferior cerebellar gray matter as the reference region. Individuals were categorized as low tau if both [ 18 F]FTP and [ 18 F]MK6240 meta‐temporal SUVR were lower than 1.5. For comparison, [ 18 F]MK6240 and [ 18 F]FTP were transformed into one another using linear and non‐linear models; additionally, images were also z‐scored relative to the CUYs. Result Despite cognitive status and amyloid burden, several individuals showed elevated [ 18 F]FTP retention in temporal regions relative to [ 18 F]MK6240. As an example, Figure 1 shows [ 18 F]FTP and [ 18 F]MK6240 in 16 participants (4 per cognitive and amyloid status). Across most subjects with SUVRs<1.5, [ 18 F]FTP presented higher retention in meta‐temporal region as compared to [ 18 F]MK6240, though [ 18 F]MK6240 increased sharply above this threshold (Figure 2). In Figure 3, group‐average images and their transformed counterparts are shown for each group by amyloid and cognitive status, the subset of low‐tau participants in Aβ+ groups are also shown. In low tau groups, [ 18 F]FTP meta‐temporal retention is high in comparison to [ 18 F]MK6240. Additionally, z‐scored [ 18 F]FTP images show broader spread into temporal regions than [ 18 F]MK6240, reinforcing differences in retention. Conclusion [ 18 F]FTP shows meta‐temporal retention not seen with [ 18 F]MK6240 in low tau individuals. This discrepancy persists across transformed and z‐scored images, suggesting that there is a difference in early tracer retention between [ 18 F]FTP and [ 18 F]MK6240. It is unclear if the early [ 18 F]FTP retention is related to early maturity levels of tau or off‐target signal. These findings have important implications for basic understanding of early tau retention, early diagnosis, and biomarker harmonization efforts.

Abstract Background Variability in meningeal signal has been observed with various tau‐PET tracers. Differences have been observed in sex and age. Furthermore, the potential role of glymphatic clearance in this variability remains unclear. Here we compare meningeal signal of [ 18 F]MK6240 and [ 18 F]FTP tau‐PET tracers in cognitively unimpaired (CU) amyloid‐β‐ (Aβ‐) individuals, in relation to age, sex and glymphatic clearance. Methods 92 CU Aβ‐ (7 CU young [18‐35yo] and 85 CU old) underwent [ 18 F]MK6240 and [ 18 F]FTP tau‐PET scans, structural MRI, and resting‐state functional MRI (rsfMRI). In native space, we defined nine distinct levels representing meningeal regions, organized from those closest to the cortex (1) to those furthest away (9). Glymphatic clearance, measured as gBOLD/CSF coupling, was calculated for each participant; a lower value means a more efficient glymphatic clearance. Associations between meningeal tracer signal and factors such as sex, age, and glymphatic clearance were analyzed using t‐tests and linear regression models. Results All 9 meningeal regions were tested and rendered similar results; we will be showing those for meninges level 2. [ 18 F]MK6240 and [ 18 F]FTP meningeal signal significantly correlated with each other in both sexes (Figure 1). We observed higher [ 18 F]MK6240 meningeal signal in females compared to males while no difference was found for [ 18 F]FTP signal (Figure 2). In females, [ 18 F]MK6240 meningeal signal did not show a significant association with age, whereas in males, a significant relationship was observed. Both males and females exhibited lower [ 18 F]FTP meningeal signal with increasing age (Figure 3A). Additionally, glymphatic clearance was significantly associated with age for females with [ 18 F]MK6240. No significant associations were found in males with [ 18 F]MK6240 or in either sex for [ 18 F]FTP (Figure 3B). Conclusion Our findings demonstrate that meningeal signal of [ 18 F]MK6240 is significantly associated with glymphatic clearance in females, while in males, it is associated with age. In contrast, [ 18 F]FTP signal is primarily influenced by age in both sexes. These results highlight the distinct relationship between [ 18 F]MK6240 signal and glymphatic function in females, while age appears to play a significant role in both males and females for other tracer signal patterns.

Abstract Background Tau‐PET tracers are essential for visualizing pathology in Alzheimer’s (AD). High detectability to tau is crucial for early detection and monitoring of tau deposition. This study compares the noise to dynamic range ratio (NRR) of [ 18 F]FTP, [ 18 F]MK6240, [ 18 F]PI2620, and [ 18 F]RO948, cross‐sectionally and longitudinally. Methods 460 individuals from the HEAD study (23 cognitively unimpaired (CU) young, 249 CU old and 188 cognitively impaired) underwent [ 18 F]FTP and [ 18 F]MK6240 tau‐PET scans; 94 additionally received [ 18 F]PI2620 and [ 18 F]RO948. A subset of 28 individuals (15 CU and 13 CI) underwent [ 18 F]FTP and [ 18 F]MK6240 follow‐up scans (1.5 ± 0.1 years later). Annual change was measured as [(followup‐baseline)/time between scans]. Noise was calculated as the standard deviation (SD) of CU Aβ‐ participants aged ≤65 (SD CUAβ‐≤65 ). The dynamic range was calculated as the SD across all subjects (SD range ). A lower the NRR (=SD CUAβ‐≤65 /SD range ) indicates more detectability. Analyses were performed at both region‐of‐interest and voxel‐wise levels. Results Across the whole cohort, [ 18 F]MK6240 exhibited lower NRR than [ 18 F]FTP in all regions. Voxel‐wise, differences were most pronounced in the frontal medial temporal regions (Figure 1). Within the four‐tracers subset, [ 18 F]PI2620 and [ 18 F]FTP showed the highest NRR in Braak II, followed by [ 18 F]RO948 and [ 18 F]MK6240. In Braak IV‐VI, [ 18 F]MK6240 consistently demonstrated the lowest values, followed by [ 18 F]PI2620, [ 18 F]FTP and [ 18 F]RO948. Similarly, in metatemporal‐ROI and Braak III, [ 18 F]MK6240 remained the lowest, however followed by [ 18 F]FTP, [ 18 F]PI2620 and [ 18 F]RO948 (Figure 2). Lower [ 18 F]MK6240 NRR was due to larger SD range , while [ 18 F]FTP's lower values stemmed from smaller SD CUAβ‐≤65 . Conversely, high [ 18 F]PI2620 and [ 18 F]RO948 values are driven by larger SD CUAβ‐≤65 . Longitudinal analyses further confirmed that [ 18 F]MK6240 exhibited the lowest NRR across the entire brain, including AD‐related regions, with voxel‐wise differences mainly in the temporal and parietal lobes. Conclusion Tau‐PET tracers exhibit significant variability in detectability. [ 18 F]MK6240 consistently demonstrated lower NRR, implying better detectability across all regions, cross‐sectionally and longitudinally. Despite differences in NRR, [ 18 F]FTP, [ 18 F]RO948 and [ 18 F]PI2620 followed similar pattern. These results provide insights into the differential tracer detectability, helping guide their optimal use in detecting and tracking tau pathology. Ongoing follow‐up scans will further clarify longitudinal tracer detectability and its implications for tau progression in AD.

AbstractBackgroundTau‐PET tracers have been used to diagnose and stage Alzheimer’s disease. However, different tau tracers present distinct patterns of binding throughout the brain, challenging the harmonization of their results. We hypothesize that the choice of a reference region can impact the harmonization of the tau‐PET standardized uptake value ratio (SUVR). In this context, we aimed to explore how different cerebellar reference regions impact the association between [18F]Flortaucipir and [18F]MK‐6240 SUVR values.MethodWe studied 185 individuals across the aging and AD spectrum with head‐to‐head Flortaucipir and MK‐6240 tau PET (HEAD Study). SUVRs were processed to a common 8mm FWHM using 15 different reference regions defined in the spatially unbiased atlas template of the cerebellum (SUIT) (Diedrichsen, 2009). Regression models investigated the association between Flortaucipir and MK‐6240 using multiple combinations of reference regions. R2 statistic was used to estimate goodness‐of‐fitting.Result225 combinations of associations Flortaucipir and MK‐6240 SUVR were tested, where the SUVRs are not necessarily quantified using the same reference region. Figure 1 presents the top 25 strongest and 25 weakest associations, ordered based on the coefficient of determination (R²). Flortaucipir and MK‐6240 exhibited the most robust associations when the inferior cerebellar gray matter or Crus I were employed for SUVR determination (R2=0.89, Figure 1‐2). Conversely, combinations incorporating the fastigial region consistently yielded weaker associations between the two tracers (R2<0.70, Figure 1‐2).ConclusionInterestingly, we showed that the inferior cerebellum, when used for both tracers, serves as a robust reference region for determining the most similar SUVRs for Flortaucipir and MK‐6240. Notably, these two regions have been commonly utilized in previous studies involving these tau tracers. Our results imply that the inferior cerebellum could be the optimal reference region for research aimed at harmonizing tau PET tracers using statistical scales.

AbstractBackgroundDifferences between on‐ and off‐target retention characteristics between [18F]MK6240 and [18F]Flortaucipir (FTP) complicate the harmonization across tracers. Our objective here was to separate the impact of the reference region by evaluating correlations between [18F]MK6240 (MK) and [18F]FTP standard uptake values (SUVs).MethodParticipants (Figure 1, n=90) received an amyloid‐β (Aβ) PET scan ([11C]PIB or [18F]NAV4694) and two tau‐PET scans: [18F]MK (90‐110 minutes post‐injection) and [18F]FTP (80‐100 minutes post‐injection). For all PET scans, the individual frames were realigned, averaged, and co‐registered to a Freesurfer 7.1‐segmented T1‐MPRAGE. SUVs were calculated in the reference region (inferior cerebellar gray), on‐target regions (entorhinal cortex, hippocampus, Braak III, Braak IV, Braak V, Braak VI) and off‐target regions (caudate, pallidum, putamen, thalamus, cerebellar white matter, choroid plexus, meninges, eroded white matter). We examined correlations between [18F]MK and [18F]FTP SUV values as a function of Aβ status, as well as their associations with age.ResultAll correlations (Figure 2) were significant at p<0.001. The interaction with Aβ status was significant for hippocampus, BraakIII‐V and the metatemporal region. In Aβ+ participants, [18F]FTP and [18F]MK6240 have similar SUVs in on‐target regions with a slope close to 1 except for in hippocampus and Braak VI. However, [18F]FTP SUVs, on average, were greater than [18F]MK SUVs in Aβ+ and Aβ‐ subjects in the reference region and all off‐target regions except for meninges, and in Aβ‐ subjects in the on‐target regions. Age correlated with [18F]FTP SUVs in Aβ‐ subjects in all regions (except the reference region, Braak VI and meninges) and [18F]MK SUVs in putamen and pallidum, but this correlation was only significant (p<0.01) when young and old subjects were included.ConclusionDespite [18F]MK’s higher affinity for tau and SUVR dynamic range being twice that of [18F]FTP, the SUVs in on‐target regions are similar. The higher [18F]FTP signal in the reference region appears to be the contributing factor to the lower dynamic range. The higher [18F]FTP signal in on‐target regions for Aβ‐ subjects may reflect the presence of off‐target signals in these subjects. Taking off‐target signals into account should improve correlations between the two tracers, especially when measuring the earliest deposition of tau.

AbstractBackgroundThe association between [18F]Flortaucipir (FTP) and [18F]MK6240, two commonly used tau‐PET tracers in Alzheimer’s disease (AD), varies due to distinct binding properties and off‐target signal regions. Our study aims to elucidate the biological factors influencing this association and evaluate the applicability of a common equation across different on‐target regions.Method113 individuals from the HEAD dataset (11 young, 58 cognitively unimpaired elderly, and 44 cognitively impaired) underwent [18F]MK6240, [18F]FTP and Aβ‐PET scans. Images were processed using the inferior cerebellar grey (CG) as the reference region, with subjects categorized by Aβ status. Stepwise linear fitting identified off‐target (OFF) regions impacting tracer associations within the whole cortex, Braak and temporal‐meta regions of interest (ROIs). OFF regions included were a composite mask (pallidum, putamen, caudate ‐ PPC) to address collinearity in subcortical nuclei, as well as the region with the greatest partial volume effects (PVE) on the ROI (meninges, choroid plexus, and the hotspot medial to entorhinal cortices (EC)). Akaike information criteria (AIC) analyses tested linear models with various off‐target regions.ResultPPC and PVE regions influenced tracer association in on‐target regions. PPC binding is associated with age. PPC and meninges retention, along with Aβ status interaction, demonstrated the best model fit for the whole cortex (Figure 1). Weighting factors derived from the whole cortex model were applied to Braak regions and temporal meta‐ROI. Braak III‐VI and temporal‐meta ROI showed optimal models including OFF regions and Aβ status interaction (Figure 2). Forcing the whole equation gave optimal results. For Braak I (EC), adding the OFF covariates only was the best model. For Braak II (hippocampus), the best model included OFF regions and the interaction with Aβ status (Figure 2). Forcing the whole cortex equation onto Braak I and Braak II yielded suboptimal fits.ConclusionHarmonizing tau‐PET tracers involves considering significant covariates. Integrating meningeal and age‐related off‐target regions enhances [18F]MK6240 and [18F]FTP association in on‐target regions, further improved by Aβ status inclusion. While the whole cortex model may not suit early ROI, it proves effective for Braak III and beyond. Creating an equation for tracer translation necessitates incorporating meningeal and subnuclei off‐target retention.

AbstractBackgroundTau‐PET tracers allow for in vivo Braak staging of individuals in the Alzheimer’s disease (AD) continuum. The impact of tracers’ characteristics for Braak staging using tau‐PET remains unclear. Therefore, we performed a head‐to‐head comparison of Braak staging using first‐ and second‐generation tau‐PET tracers.MethodWe assessed 51 cognitively unimpaired (CU) and 49 cognitively impaired participants (mean [SD] age 69.4 [7.5] years) with at least two tau‐PET ligands ([18F]MK6240, [18F]AV1451, and/or [18F]RO948) at McGill University, as part of the HEAD study. We calculated standardized uptake value ratios (SUVR) in Braak‐like regions of interest (ROI) for each ligand and investigated their association using Spearman’s correlation. Thresholds defined the presence of tauopathy in each Braak ROI, which was used to assign a Braak stage to each participant. Finally, we assessed the agreement between the Braak staging provided by each tracer, both for the traditional (using separate Braak stages – 0, I, II, III, IV, V, and VI) and simplified (using joint Braak stages – 0, I‐II, III‐IV, and V‐VI) frameworks.ResultIn all Braak ROIs, we found positive correlations between the SUVR values of the three tracers (Figure 1). The strongest correlation was between [18F]MK6240 and [18F]RO948 in Braak II (r=0.94), and the weakest between [18F]AV1451 and [18F]RO948 in VI (r=0.51). Inter‐tracer agreement regarding the latest stage of abnormality was substantial or nearly perfect between pairs of tracers but moderate between the three tracers (Figure 2A). The simplified framework presented greater agreement compared to traditional Braak staging, except between [18F]MK6240 and [18F]RO948. At the ROI level, the lowest agreements were observed for Braak II and I‐II, when [18F]MK6240 and [18F]RO948 were compared to [18F]AV1451 (Figure 2B‐C). [18F]AV1451 had the highest probability of overestimating the Braak stage assigned by [18F]MK6240 and by [18F]RO948, especially at earlier stages (Figure 3).ConclusionThe ligands presented moderate to nearly perfect agreement for in vivo staging of AD severity. Off‐target binding of [18F]AV1451 to the choroid plexus might explain disagreements at early stages. Overall, slight improvements in agreements were achieved with the simplified framework, as observed in histopathological staging.