Partial volume correction in longitudinal tau PET studies: is it really needed?

BACKGROUND

[18F]flortaucipir (FTP) tau PET quantification is known to be affected by non-specific binding in off-target regions. Although partial volume correction (PVC) techniques partially account for this effect, their inclusion may also introduce noise and variability into the quantification process. While the impact of these effects has been studied in cross-sectional designs, the benefits and drawbacks of PVC on longitudinal FTP studies is still under scrutiny. The aim of this work was to study the performance of the most common PVC techniques for longitudinal FTP imaging.

METHODS

A cohort of 247 individuals from the Alzheimer's Disease Neuroimaging Initiative with concurrent baseline FTP-PET, amyloid-beta (Aβ) PET and structural MRI, as well as with follow-up FTP-PET and MRI were included in the study. FTP-PET scans were corrected for partial volume effects using Meltzer's, a simple and popular analytical PVC, and both the region-based voxel-wise (RBV) and the iterative Yang (iY) corrections. FTP SUVR values and their longitudinal rates of change were calculated for regions of interest (ROI) corresponding to Braak Areas I-VI, for a temporal meta-ROI and for regions typically displaying off-target FTP binding (caudate, putamen, pallidum, thalamus, choroid plexus, hemispheric white matter, cerebellar white matter, and cerebrospinal fluid). The longitudinal correlation between binding in off-target and target ROIs was analysed for the different PVCs. Additionally, group differences in longitudinal FTP SUVR rates of change between Aβ-negative (A-) and Aβ-positive (A+), and between cognitively unimpaired (CU) and cognitively impaired (CI) individuals, were studied. Finally, we compared the ability of different partial-volume-corrected baseline FTP SUVRs to predict longitudinal brain atrophy and cognitive decline.

RESULTS

Among off-target ROIs, hemispheric white matter showed the highest correlation with longitudinal FTP SUVR rates from cortical target ROIs (R2=0.28-0.82), with CSF coming in second (R2=0.28-0.42). Application of voxel-wise PVC techniques minimized this correlation, with RBV performing best (R2=0.00-0.07 for hemispheric white matter). PVC also increased group differences between CU and CI individuals in FTP SUVR rates of change across all target regions, with RBV again performing best (No PVC: Cohen's d = 0.26-0.66; RBV: Cohen's d = 0.43-0.74). These improvements were not observed for differentiating A- from A+ groups. Additionally, voxel-wise PVC techniques strengthened the correlation between baseline FTP SUVR and longitudinal grey matter atrophy and cognitive decline.

CONCLUSION

Quantification of longitudinal FTP SUVR rates of change is affected by signal from off-target regions, especially the hemispheric white matter and the CSF. Voxel-wise PVC techniques significantly reduce this effect. PVC provided a significant but modest benefit for tasks involving the measurement of group-level longitudinal differences. These findings are particularly relevant for the estimations of sample sizes and analysis methodologies of longitudinal group studies.

Advancing Tau-PET quantification in Alzheimer's disease with machine learning: introducing THETA, a novel tau summary measure

Alzheimer's disease (AD) exhibits spatially heterogeneous 3R/4R tau pathology distributions across participants, making it a challenge to quantify extent of tau deposition. Utilizing Tau-PET from three independent cohorts, we trained and validated a machine learning model to identify visually positive Tau-PET scans from regional SUVR values and developed a novel summary measure, THETA, that accounts for heterogeneity in tau deposition. The model for identification of tau positivity achieved a balanced test accuracy of 95% and accuracy of ≥87% on the validation datasets. THETA captured heterogeneity of tau deposition, had better association with clinical measures, and corresponded better with visual assessments in comparison with the temporal meta-region-of-interest Tau-PET quantification methods. Our novel approach aids in identification of positive Tau-PET scans and provides a quantitative summary measure, THETA, that effectively captures the heterogeneous tau deposition seen in AD. The application of THETA for quantifying Tau-PET in AD exhibits great potential.

Increased Medial Temporal Tau Positron Emission Tomography Uptake in the Absence of Amyloid-β Positivity

Importance

An increased tau positron emission tomography (PET) signal in the medial temporal lobe (MTL) has been observed in older individuals in the absence of amyloid-β (Aβ) pathology. Little is known about the longitudinal course of this condition, and its association with Alzheimer disease (AD) remains unclear.

Objective

To study the pathologic and clinical course of older individuals with PET-evidenced MTL tau deposition (TMTL+) in the absence of Aβ pathology (A-), and the association of this condition with the AD continuum.

Design, Setting, and Participants

A multicentric, observational, longitudinal cohort study was conducted using pooled data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Harvard Aging Brain Study (HABS), and the AVID-A05 study, collected between July 2, 2015, and August 23, 2021. Participants in the ADNI, HABS, and AVID-A05 studies (N = 1093) with varying degrees of cognitive performance were deemed eligible if they had available tau PET, Aβ PET, and magnetic resonance imaging scans at baseline. Of these, 128 participants did not meet inclusion criteria based on Aβ PET and tau PET biomarker profiles (A+ TMTL-).

Exposures

Tau and Aβ PET, magnetic resonance imaging, cerebrospinal fluid biomarkers, and cognitive assessments.

Main Outcomes and Measures

Cross-sectional and longitudinal measures for tau and Aβ PET, cortical atrophy, cognitive scores, and core AD cerebrospinal fluid biomarkers (Aβ42/40 and tau phosphorylated at threonine 181 p-tau181 available in a subset).

Results

Among the 965 individuals included in the study, 503 were women (52.1%) and the mean (SD) age was 73.9 (8.1) years. A total of 51% of A- individuals and 78% of A+ participants had increased tau PET signal in the entorhinal cortex (TMTL+) compared with healthy younger (aged <39 years) controls. Compared with A- TMTL-, A- TMTL+ participants showed statistically significant, albeit moderate, longitudinal (mean [SD], 1.83 [0.84] years) tau PET increases that were largely limited to the temporal lobe, whereas those with A+ TMTL+ showed faster and more cortically widespread tau PET increases. In contrast to participants with A+ TMTL+, those with A- TMTL+ did not show any noticeable Aβ accumulation over follow-up (mean [SD], 2.36 [0.76] years). Complementary cerebrospinal fluid analysis confirmed longitudinal p-tau181 increases in A- TMTL+ in the absence of increased Aβ accumulation. Participants with A- TMTL+ had accelerated MTL atrophy, whereas those with A+ TMTL+ showed accelerated atrophy in widespread temporoparietal brain regions. Increased MTL tau PET uptake in A- individuals was associated with cognitive decline, but at a significantly slower rate compared with A+ TMTL+.

Conclusions and Relevance

In this study, individuals with A- TMTL+ exhibited progressive tau accumulation and neurodegeneration, but these processes were comparably slow, remained largely restricted to the MTL, were associated with only subtle changes in global cognitive performance, and were not accompanied by detectable accumulation of Aβ biomarkers. These data suggest that individuals with A- TMTL+ are not on a pathologic trajectory toward AD.

Impact of spill-in counts from off-target regions on [18F]Flortaucipir PET quantification

BACKGROUND

[¹⁸F]Flortaucipir (FTP) PET quantification is usually hindered by spill-in counts from off-target binding (OFF) regions. The present work aims to provide an in-depth analysis of the impact of OFF in FTP PET quantification, as well as to identify optimal partial volume correction (PVC) strategies to minimize this problem.

METHODS

309 amyloid-beta (Aβ) negative cognitively normal subjects were included in the study. Additionally, 510 realistic FTP images with different levels of OFF were generated using Monte Carlo simulation (MC). Images were corrected for PVC using both a simple two-compartment and a multi-region method including OFF regions. FTP standardized uptake value ratio (SUVR) was quantified in Braak Areas (BA), the hippocampus (which was not included in Braak I/II) and different OFF regions (caudate, putamen, pallidum, thalamus, choroid plexus (ChPlex), cerebellar white matter (cerebWM), hemispheric white matter (hemisWM) and cerebrospinal fluid (CSF)) using the lower portion of the cerebellum as a reference region. The correlations between OFF and cortical SUVRs were studied both in real and in simulated PET images, with and without PVC.

RESULTS

In-vivo, we found correlations between all OFF and target regions, especially strong for the hemisWM (slope>0.63, R²>0.4). All the correlations were attenuated but remained significant after applying PVC, except for the ChPlex. In MC simulations, the hemisWM and CSF were the main contributors to PVE in all BA (slopes 0.15-0.26 and 0.13-0.21 respectively). The hemisWM (slope=0.2), as well as the ChPlex (slope=0.02), influenced SUVRs in the hippocampus. The CerebWM was negatively correlated with all target regions (slope<-0.02, R²>0.8). While no other correlations between OFF and target regions were found, hemisWM was correlated with all OFF regions but the cerebWM (slopes 0.06-0.33). HemisWM correlations attenuated (slopes<0.06) when applying two-compartment PVC, but the hippocampus-ChPlex and the cerebWM correlations required more complex PVC with dedicated compartments for these regions. In-vivo, PVC removed a notably higher fraction of the correlation between OFF regions found to be affected by PVE in the simulation studies and BA (≈50%) than for OFF regions not affected by PVE (16%).

CONCLUSION

HemisWM is the main driver of spill-in effects in FTP PET, affecting both target regions and the rest of OFF regions. PVC successfully reduces PVE, even when using a simple two-compartment method. Despite PVC, non-zero correlations were still observed between target and OFF regions in vivo, which suggests the existence of biological or tracer-related contributions to these correlations.

Non-invasive Spatial Mapping of Frequencies in Atrial Fibrillation: Correlation With Contact Mapping

Introduction: Regional differences in activation rates may contribute to the electrical substrates that maintain atrial fibrillation (AF), and estimating them non-invasively may help guide ablation or select anti-arrhythmic medications. We tested whether non-invasive assessment of regional AF rate accurately represents intracardiac recordings.

Methods: In 47 patients with AF (27 persistent, age 63 ± 13 years) we performed 57-lead non-invasive Electrocardiographic Imaging (ECGI) in AF, simultaneously with 64-pole intracardiac signals of both atria. ECGI was reconstructed by Tikhonov regularization. We constructed personalized 3D AF rate distribution maps by Dominant Frequency (DF) analysis from intracardiac and non-invasive recordings.

Results: Raw intracardiac and non-invasive DF differed substantially, by 0.54 Hz [0.13 – 1.37] across bi-atrial regions (R² = 0.11). Filtering by high spectral organization reduced this difference to 0.10 Hz (cycle length difference of 1 – 11 ms) [0.03 – 0.42] for patient-level comparisons (R² = 0.62), and 0.19 Hz [0.03 – 0.59] and 0.20 Hz [0.04 – 0.61] for median and highest DF, respectively. Non-invasive and highest DF predicted acute ablation success (p = 0.04).

Conclusion: Non-invasive estimation of atrial activation rates is feasible and, when filtered by high spectral organization, provide a moderate estimate of intracardiac recording rates in AF. Non-invasive technology could be an effective tool to identify patients who may respond to AF ablation for personalized therapy.

Automatic quality electrogram assessment improves phase-based reentrant activity identification in atrial fibrillation

Identification of reentrant activity driving atrial fibrillation (AF) is increasingly important to ablative therapies. The goal of this work is to study how the automatically-classified quality of the electrograms (EGMs) affects reentrant AF driver localization. EGMs from 259 AF episodes obtained from 29 AF patients were recorded using 64-poles basket catheters and were manually classified according to their quality. An algorithm capable of identifying signal quality was developed using time and spectral domain parameters. Electrical reentries were identified in 3D phase maps using phase transform and were compared with those obtained with a 2D activation-based method. Effect of EGM quality was studied by discarding 3D phase reentries detected in regions with low-quality EGMs. Removal of reentries identified by 3D phase analysis in regions with low-quality EGMs improved its performance, increasing the area under the ROC curve (AUC) from 0.69 to 0.80. The EGMs quality classification algorithm showed an accurate performance for EGM classification (AUC 0.94) and reentry detection (AUC 0.80). Automatic classification of EGM quality based on time and spectral signal parameters is feasible and accurate, avoiding the manual labelling. Discard of reentries identified in regions with automatically-detected poor-quality EGMs improved the specificity of the 3D phase-based method for AF driver identification.