Regional differences in 18F-flutemetamol accumulation between amyloid-positive and -negative brains using high-resolution dedicated head PET scanner.

MRI-free amyloid PET quantification using a deep learning model and white matter reference.

BackgroundAccurate quantification of standardized uptake value ratio (SUVR) in amyloid PET is essential for Alzheimer's disease (AD) diagnosis but typically requires MRI-based segmentation due to subtle uptake differences between gray and white matter.ObjectiveThis study aimed to develop and validate a 3-dimensional deep learning model capable of segmenting these tissues directly from PET images to enable MRI-free SUVR quantification for AD diagnosis.MethodsThis retrospective study included 385 participants who underwent brain amyloid PET and MRI. After excluding 12 data-corrupted cases, 373 subjects were divided into training (n = 318) and test (n = 55) sets. External validation used 625 PET/CT scans from the Alzheimer's Disease Neuroimaging Initiative. Model performance was assessed using Dice coefficients and intersection over union. PET-based SUVRs derived from model-generated masks were compared with MRI-based SUVRs using Spearman correlation, and their diagnostic utility was evaluated by group differences and receiver operating characteristic analysis.ResultsThe model achieved high Dice coefficients for grey matter (GM; 0.785 internal, 0.743 external) and white matter (WM; 0.838 internal, 0.803 external). PET/CT-based SUVR values strongly correlated with MRI references (Spearman's ρ ≥ 0.98, p < 0.001). PET/CT-derived SUVRGM and SUVRGM/WM predicted amyloid status (AUC 0.86 and 0.85, respectively) and cognitive impairment (AUC 0.78).ConclusionsDeep learning-based amyloid PET segmentation enables accurate MRI-free quantification of gray and white matter SUVRs. This approach simplifies clinical workflow while maintaining diagnostic performance comparable to MRI-based methods for AD diagnosis.

18F-flortaucipir PET imaging: Biodistribution in the Japanese population and diagnostic accuracy by Japanese readers.

OBJECTIVE 18F-flortaucipir (Tauvid™) is an 18F-labeled diagnostic positron emission tomography (PET) radiopharmaceutical, which was developed to detect tau pathology in the brain and to estimate the density and/or distribution of aggregated tau neurofibrillary tangles for patients being evaluated for Alzheimer's disease (AD). The objective of this article is to report findings from two studies. The primary objective of the first (dose and biodistribution) study was to investigate the consistency of 18F-flortaucipir PET biodistribution between Japanese and non-Japanese individuals. In the second (reader) study, the comparability of visual reads performed by Japanese and US expert readers who followed the same training program was evaluated. METHODS This article reports findings from two separate studies and datasets. In the dose and biodistribution study, whole-body distribution of 18F-flortaucipir was assessed (N = 9). Standardized uptake value ratios, normalized to the entire cerebellum, were calculated, and whole-body effective dose was calculated using a 73.7 kg bodyweight model. In the reader study (Study A27; I7E-AV-A27), five Japanese physicians visually interpreted 60 PET scans randomly selected from a previous US reader study (Study FR01; NCT03901092). Scan positivity was determined based on increased activity of 18F-flortaucipir in posterolateral temporal, occipital, or parietal/precuneus regions with or without frontal activity. Each scan was visually interpreted by all Japanese readers, who determined whether scans were consistent with an AD or non-AD pattern. Concordance between Japanese and US readers who underwent the same training on the interpretation of 18F-flortaucipir PET images was then evaluated (reader study primary endpoint). RESULTS The biodistribution of 18F-flortaucipir was consistent between Japanese and non-Japanese individuals. When interpreting 18F-flortaucipir PET images to distinguish between AD versus non-AD patterns, Japanese and US readers who underwent the same training showed 100% agreement on the majority reads, with a Cohen's Kappa value of 1. CONCLUSIONS 18F-flortaucipir whole-body biodistribution for Japanese individuals was consistent with that of non-Japanese individuals. After completing the same training, Japanese readers showed high concordance with US readers on the interpretation of 18F-flortaucipir PET images to distinguish between AD and non-AD patterns. Data and scans were from previous studies registered with ClinicalTrials.gov (registration numbers: NCT04474405; NCT03901092).

Amyloid PET Quantitation and Centiloid Thresholds in the Diagnosis of Alzheimer Disease: An Individual Participant Data Meta-Analysis.

Importance Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I2 = 80%). Conclusions and Relevance In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

Diffuse glioma perfusion quantification with ASL and DSC: a head-to-head comparison with 15O-H2O PET

Background and purpose Arterial spin labeling (ASL) is a non-invasive alternative to dynamic susceptibility contrast (DSC) for measuring cerebral blood flow (CBF), even though both methods measure slightly different contrast. This study compares ASL and DSC MRI with the gold-standard measurement 15O-H2O PET in gliomas. Methods Eight patients (age 40.5 ± 17.0 years, 3 women) with grade 2–4 gliomas were scanned at 3T MRI with ASL and DSC, and at PET using a 15O-H2O PET tracer. Quantitative comparison was performed in contralateral normal-appearing tissue, and in tumors with and without normalization to contralateral tissue. The mean voxel-wise relative error (MRE) was calculated for PET-ASL and PET-DSC. The MRE difference between ASL and DSC was evaluated using a t-test (p < 0.05 after Bonferroni correction). Results ASL showed superior (p<0.001) voxel-wise agreement with PET (MRE 26.8%) in the normal-appearing tissue compared with DSC (MRE 33.8%). While the tumor maximum CBF normalized to contralateral gray matter comparison with PET did not differ between (p=0.5) ASL (MRE 23.2%) and DSC (MRE 22.0%), voxel-wise agreement was better (p<0.001) for ASL (MRE 27.2%) than for DSC (MRE 35.0%). Visually, ASL overestimated CBF near larger arteries, and DSC underestimated CBF in non-enhancing tumors with tiny capillaries. Conclusion While neither ASL nor DSC is fully comparable to 15O-H2O PET in all tumors, ASL presents a viable non-invasive alternative to DSC for glioma imaging. These findings encourage future studies to investigate the extent to which the combination of ASL and DSC can measure complementary tumor hemodynamics.

Integrated PET/MRI for the evaluation of gray matter atrophy and metabolic changes in idiopathic Parkinson’s disease

Background The underlying mechanisms linking structural and metabolic alterations of idiopathic Parkinson’s disease (IPD) remain poorly understood. Utilizing integrated PET/MR for its precise spatial correlation, this study investigated the temporal relationship between gray matter (GM) atrophy and reduced FDG SUVR (RFS) across IPD stages to provide insights for early diagnosis. Methods This prospective study recruited 90 IPD patients stratified by Hoehn-Yahr (H-Y) stage into mild, moderate, and severe groups, alongside 30 age-matched healthy controls (HC). All participants underwent integrated 18F-FDG PET/MR imaging. SPM was used to extract the GM volume (VGM) and standardized uptake value ratio for each brain region. Group differences were analyzed with one-way ANOVA and Bonferroni tests. Spearman correlation analysis was utilized to evaluate the associations of both VGM and metabolic changes with H-Y staging. Individual Z-scores for VGM and metabolic alterations were calculated, and their relationship was examined using Spearman/Pearson correlation, followed by paired t-tests to compare their differences. Result With disease progression, GM atrophy and RFS in IPD patients gradually extend from focal to widespread patterns. A characteristic pattern of cerebral hypermetabolism was observed in IPD. H-Y stage demonstrated a significant inverse correlation with the extent of both brain GM atrophy (affecting 82 out of 90 regions) and RFS (affecting 20 regions). Conversely, it was positively correlated with hypermetabolism in regions including the sensorimotor cortex, amygdala, and globus pallidus. Moderate correlations between atrophy and RFS were confined to the left inferior parietal lobule (r = 0.619, p < 0.001) and superior temporal gyrus of the temporal pole (r = 0.612, p < 0.001) only in severe group. In early stages, the number of regions where RFS predominated over atrophy (57 regions) substantially exceeded those where atrophy was more severe (1 region). In late stages, the number of regions with more pronounced atrophy than RFS (25 regions) surpassed that of regions where RFS was dominant (12 regions). Conclusion Widespread RFS predominates during early stages, whereas structural atrophy gradually becomes the dominant imaging feature as the disease advances. These alterations are significantly correlated with disease severity, underscoring the potential of multimodal imaging biomarkers for the early diagnosis of IPD and monitor its progression.

Sources of Variability in Normative Cerebral [18F]FDG-PET imaging