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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 (slope0.8). 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

Background: The lack of standardization of intensity normalization methods and its unknown effect on the quantification output is recognized as a major drawback for the harmonization of brain FDG-PET quantification protocols. The aim of this work is the ground truth-based evaluation of different intensity normalization methods on brain FDG-PET quantification output. Methods: Realistic FDG-PET images were generated using Monte Carlo simulation from activity and attenuation maps directly derived from 25 healthy subjects (adding theoretical relative hypometabolisms on 6 regions of interest and for 5 hypometabolism levels). Single-subject statistical parametric mapping (SPM) was applied to compare each simulated FDG-PET image with a healthy database after intensity normalization based on reference regions methods such as the brain stem (RRBS), cerebellum (RRC) and the temporal lobe contralateral to the lesion (RRTL), and data-driven methods, such as proportional scaling (PS), histogram-based method (HN) and iterative versions of both methods (iPS and iHN). The performance of these methods was evaluated in terms of the recovery of the introduced theoretical hypometabolic pattern and the appearance of unspecific hypometabolic and hypermetabolic findings. Results: Detected hypometabolic patterns had significantly lower volumes than the introduced hypometabolisms for all intensity normalization methods particularly for slighter reductions in metabolism . Among the intensity normalization methods, RRC and HN provided the largest recovered hypometabolic volumes, while the RRBS showed the smallest recovery. In general, data-driven methods overcame reference regions and among them, the iterative methods overcame the non-iterative ones. Unspecific hypermetabolic volumes were similar for all methods, with the exception of PS, where it became a major limitation (up to 250 cm3) for extended and intense hypometabolism. On the other hand, unspecific hypometabolism was similar far all methods, and usually solved with appropriate clustering. Conclusions: Our findings showed that the inappropriate use of intensity normalization methods can provide remarkable bias in the detected hypometabolism and it represents a serious concern in terms of false positives. Based on our findings, we recommend the use of histogram-based intensity normalization methods. Reference region methods performance was equivalent to data-driven methods only when the selected reference region is large and stable.

Abstract Objective This study investigated early, real‐world outcomes with cenobamate (CNB) in a large series of patients with highly drug‐resistant epilepsy within a Spanish Expanded Access Program (EAP). Method This was a multicenter, retrospective, observational study in 14 hospitals. Inclusion criteria were age ≥18 years, focal seizures, and EAP authorization. Data were sourced from patient clinical records. Primary effectiveness endpoints included reductions (100%, ≥90%, ≥75%, and ≥50%) or worsening in seizure frequency at 3‐, 6‐, and 12‐month visits and at the last visit. Safety endpoints included rates of adverse events (AEs) and AEs leading to discontinuation. Results The study included 170 patients. At baseline, median epilepsy duration was 26 years and median number of seizures/month was 11.3. The median number of prior antiseizure medications (ASMs) and concomitant ASMs were 12 and 3, respectively. Mean CNB dosages/day were 176 mg, 200 mg, and 250 mg at 3, 6, and 12 months. Retention rates were 98.2%, 94.5%, and 87% at 3, 6, and 12 months. At last available visit, the rate of seizure freedom was 13.3%; ≥90%, ≥75%, and ≥50% responder rates were 27.9%, 45.5%, and 63%, respectively. There was a significant reduction in the number of seizures per month (mean: 44.6%; median: 66.7%) between baseline and the last visit (P