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Cecile, Tissot

Mayo Clinic

Lawrence Berkeley National Laboratory

Citations 2

In vivo detectability of tau‐PET tracers in Alzheimer's disease
Cecile, Tissot, Rahmouni, Nesrine, Tsai, Hsin‐Yeh, Therriault, Joseph, Macedo, Arthur, Servaes, Stijn, Stevenson, J. K. M. ller, Ziontz, Jacob , Liu, Peiwei, Gordon, Brian A., Pascual, Belen, Lowe, Val J. , Soleimani‐Meigooni, David, Oh, Hwamee, Klunk, William E, Rosa‐Neto, Pedro, Jagust, William J., Pascoal, Tharick A, Baker, Suzanne L. , Tissot, Cécile , Rahmouni, Nesrine , Therriault, Joseph , Macedo, Arthur C. , Servaes, Stijn , Stevenson, Jenna , Lussier, Firoza Zubeida , Trudel, Lydia , Gordon, Brian A. , Pascual, Belén , Soleimani‐Meigooni, David N. , Oh, Hwamee , Klunk, William E. , Rosa-Neto, Pedro , Jagust, William J. , Pascoal, Tharick Ali

Alzheimer's & Dementia | January 9, 2026 | Volume: 21 | Issue: S2 | Pages: No page available

10.1002/alz70856_106041 Get It

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.
Tau Spatial Extent Outperforms Tau Load as a Marker of Neocortical Tau Burden: Head‐to‐head evidence from [18F]MK6240 and [18F]FTP PET
Macedo, Arthur, Rahmouni, Nesrine, Lussier, Firoza Z, Cecile, Tissot, Bezgin, Gleb, Therriault, Joseph, Servaes, Stijn, Hosseini, Seyyed Ali, Hall, Brandon J, Chan, Tevy , Aumont, Etienne, Ferreira, Pamela C.L., Bellaver, Bruna, Povala, Guilherme, Amaral, Lívia , Pascual, Belen, Gordon, Brian A., Lowe, Val J. , Oh, Hwamee, Soleimani‐Meigooni, David, Fortea, Juan M., Baker, Suzanne L. , Pascoal, Tharick A, Rosa‐Neto, Pedro, Macedo, Arthur C. , Rahmouni, Nesrine , Lussier, Firoza Zubeida , Tissot, Cécile , Bezgin, Gleb , Therriault, Joseph , Servaes, Stijn , Hosseini, Seyyed Ali , Hall, Brandon J. , Aumont, Étienne , Ferreira, Pâmela C.L. , Bellaver, Bruna , Povala, Guilherme , Bauer‐Negrini, Guilherme , Pascual, Belén , Gordon, Brian A. , Oh, Hwamee , Soleimani‐Meigooni, David N. , Fortea, Juan , Pascoal, Tharick Ali , Rosa-Neto, Pedro

Alzheimer's & Dementia | January 8, 2026 | Volume: 21 | Issue: S2 | Pages: No page available

10.1002/alz70856_105999 Get It

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.