Johnson, Derek R.

Abstract Introduction Quantitative interpretation of pediatric brain [ 18 F]-FDG PET is limited by the lack of age-matched normative reference databases, despite substantial developmental variation in cerebral glucose metabolism. This study aimed to construct a large-scale normative pediatric [ 18 F]-FDG PET database and develop an age-specific z-score mapping framework for quantitative evaluation of pediatric epilepsy. Method Pediatric brain PET data were retrospectively derived from clinically acquired whole-body or dedicated [ 18 F]-FDG PET examinations in participants 0–19 years of age without neurologic disease or visible brain abnormalities. A total of 417 PET scans from 341 participants were stratified into five developmental age groups: infancy, early childhood, middle childhood/school age, adolescence, and late adolescence. SUVR maps were generated using whole-brain atlas and brainstem reference regions. Voxel-wise t-test analyses were performed to characterize age- and sex-related metabolic differences. Age-specific voxel-wise mean and standard deviation maps were generated from the normative cohort and used to calculate age-matched hypometabolic z-score maps in 14 pediatric patients with epilepsy. The resulting abnormalities were qualitatively evaluated for concordance with epileptogenic findings identified on clinical MRI and/or PET by expert image review. Results Voxel-wise analyses demonstrated prominent age-dependent SUVR differences, particularly between infancy and older age groups. With whole-brain atlas normalization, older children showed progressively higher relative SUVR in cortical and cerebellar gray matter regions, whereas infancy showed relatively higher SUVR in the occipital cortex, white matter, thalamus, and brainstem. Brainstem normalization produced distinct developmental patterns, emphasizing higher white matter SUVR in infancy and broader gray matter differences in older groups. Sex-related differences were limited and regionally specific. Whole-brain atlas normalization showed lower variability than brainstem normalization and was selected for z-score mapping. In representative epilepsy cases, age-matched z-score maps identified focal or regional hypometabolism corresponding to malformations of cortical development, focal cortical dysplasia, mesial temporal sclerosis, nonlesional MRI cases, remote insult, tumor-related abnormalities, and Sturge-Weber syndrome. Discussion A large-scale normative pediatric [18F]-FDG PET database can support developmentally appropriate quantitative interpretation of pediatric brain PET. Age-matched z-score mapping may complement visual assessment by highlighting abnormal cerebral glucose metabolism in pediatric epilepsy, although findings should be interpreted with MRI, EEG, seizure semiology, and other presurgical data.

Abstract INTRODUCTION Centiloid (CL) scaling standardizes amyloid positron emission tomography (PET) quantification across tracers and platforms; however, variability across software implementations may affect diagnostic classification. This study evaluated inter‐software variability and diagnostic performance across five platforms using identical 1 8 F‐florbetapir datasets. METHODS Retrospectively, 192 patients undergoing 1 8 F‐florbetapir PET/computed tomography (CT) and magnetic resonance imaging (MRI) were analyzed. CL values were generated using four US Food and Drug Administration (FDA) ‐cleared platforms and an in‐house Centiloid standard pipeline. Agreement was assessed using intraclass correlation coefficient, with bias and limits of agreement evaluated by linear modeling and Bland–Altman analysis. Diagnostic performance was assessed using receiver operating characteristic (ROC) analysis and classification against visual interpretation. RESULTS Agreement was excellent (intraclass correlation coefficient [ICC] 0.969; 95%CI 0.961–0.975). Some platforms produced systematically higher CL values versus others slightly lower. LoA reached ± 30 CL. Diagnostic accuracy was high (area under the curve [AUC]: 0.949–0.975), with sensitivity 0.923–0.968 and specificity 0.667–0.806. DISCUSSION Despite excellent agreement, systematic differences persist and may affect classification near thresholds, supporting consistent use of a single processing pipeline.

Abstract INTRODUCTION Anti—amyloid‐β (Aβ) therapies are reshaping Alzheimer's disease (AD) management. Understanding changes in real‐world patterns of diagnostic testing and infusion chair usage is essential for optimizing access to care. METHODS Retrospective analysis of Mayo Clinic enterprise electronic health records (Jan 2019–Mar 2025) assessed trends in AD‐relevant brain imaging, fluid biomarkers, apolipoprotein E (APOE) testing, and lecanemab infusions. Rates of amyloid‐beta (Aβ) positivity by sex and age, APOE genotype frequencies, and lecanemab treatment initiation and discontinuation were evaluated. RESULTS Following national insurance coverage changes, lecanemab infusions grew by 110 infusions per quarter to 605 in Q1 2025. Aβ positron emission tomography scans increased (+22/quarter), cerebrospinal fluid biomarker orders declined (−25/quarter), and plasma p‐tau 217 orders rapidly increased (+238/quarter). Females were more likely to be Aβ positive ( p < 0.006). APOE ‐ε4 homozygotes were less likely to initiate lecanemab (HR = 0.11, p < 0.001). DISCUSSION The adoption of anti‐Aβ therapies coincided with a rapid shift in diagnostic workflows.

ABSTRACT Background Gastric emptying (GE) scintigraphy with 4‐h imaging and a radiolabeled chicken egg‐based meal (320 kcal, 30% fat) is the standard test for gastroparesis at Mayo Clinic, with an intraindividual coefficient of variation (COV intra ) of 23.8% for GE half emptying time (T 1/2 ). Alternative meals for patients with dietary restrictions, including egg allergies or vegan diets, are lacking, limiting test accessibility. The study aimed to establish a vegan, lactose‐, nut‐, and gluten‐free meal with similar caloric and fat content to the egg meal and to assess its performance in GE studies. Methods In Vitro: 99m Tc binding to egg meal over 4 h was compared to a calorically and nutritionally similar vegan alternative, JUST Egg, using a validated in vitro model simulating gastric conditions of pH, pepsin, and stirring. In Vivo: 10 healthy participants underwent randomized crossover GE scintigraphy with standard and vegan meals, spaced ≥ 3 days apart to measure GE% at 2 h, 4 h, and GE T 1/2 . Group comparisons and variance analysis included Rank Sum tests and Bland–Altman plots. Key Results In Vitro: A strong correlation ( R = 0.975, p ‐value < 0.01) between 99m Tc binding in the egg and vegan egg models was observed. Minimal variance (< 10%) was recorded at all time points. In Vivo: GE at 4 h and GE T 1/2 showed non‐statistically significant mean differences, < 2% and < 10 min respectively, between both meals. The intra‐individual variability was 18.8%. Conclusions and Inferences The vegan meal demonstrated in vitro stability, in vivo performance comparable to the egg meal, and a COV intra of 18.8%, which was lower than the 23.8% reported in repeat egg meal GE studies. Trial Registration ClinicalTrials.gov number NCT06991036 ( https://clinicaltrials.gov/study/NCT06991036?term=NCT06991036&rank=1 )

Abstract Background PET visual reads for multi‐center studies are conducted centrally by one or a few experts. In CLARiTI, a broader network of raters will perform the reads, necessitating methods to ensure their accuracy and reliability. Method All ADRC sites ( N = 37) will prospectively acquire amyloid PET scans for 800 cognitively unimpaired and 1200 cognitively impaired participants. Each site can use one of four amyloid PET tracers ([ 18 F]florbetaben, [ 18 F]florbetapir, [ 11 C]PIB, [ 18 F]NAV4694). PET scans will be visually interpreted by ten PET neuroimaging experts located across eight ADRCs, using their preferred hardware, software, and file format (DICOM, NIFTI). Calibration requires readers to perform blinded, independent visual interpretation of 180 amyloid PET scans (30 unique and 15 duplicate scans per tracer), previously read and selected by an expert (Table 1). An even mix of visually non‐elevated and elevated scans were selected, with quantitation spanning ‐26‐123 Centiloids (Figure 1), and 15% were visually borderline (similar proportion to ADNI4), with quantitation spanning 4‐48 Centiloids (mean 21). Kruskal‐Wallis H test showed no significant difference in the distribution of Centiloid values for scans in each tracer group, Χ 2 (3)=2.133, p = 0.545. Result Calibration scans were read by a second expert not serving in CLARiTI. There was 97% concordance and almost perfect agreement between readers (κ=0.932, p <0.001; Figure 2). Discordantly read scans were visually borderline elevated ( N = 2), borderline non‐elevated ( N = 1), and negative ( N = 1), with quantitation of 8‐21 Centiloids (mean 14). Intra‐rater reads were 98% concordant and had almost perfect agreement (κ=0.966, p <0.001). These findings hold promise for scaling‐up visual reads in CLARiTI, and we expect ≥80% concordance and substantial to almost perfect agreement (κ≥0.7) for inter/intra‐rater reliability. Conclusion Calibration is essential for accurate/reliable amyloid PET visual reads in large multi‐center studies with multiple raters. Through the calibration process, we will develop methods to improve the adjudication of borderline/challenging scans and formalize methods for visual reads of amyloid PET tracers that are investigational (i.e., [ 11 C]PIB, [ 18 F]NAV4694). Involving multiple raters across different sites, who use diverse hardware/software/file format combinations, will mirror the natural heterogeneity present in real‐world clinical practice. This calibration set can also serve as a standardized training tool for other studies incorporating amyloid PET visual reads.