Kemp, Bradley J.

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.

Background: Post-treatment prognosis and monitoring are critical for determining the timing of salvage treatment in glioblastoma patients but has been challenging due to difficulties differentiating progression from treatment effects in conventional images. This exploratory study aimed to establish the correlation of radiomics image features from time series of amino acid tracer 18F-DOPA PET images, with outcomes, using machine learning and dimension reduction analysis. Methods: 18F-DOPA PET images were collected for a patient cohort with wild-type IDH and unmethylated MGMT who underwent dose-escalated radiation therapy. Quantitative features were derived from the high uptake region (T/N > 2.0) in pre- and post-radiation therapy follow-up 18F-DOPA PET images. A customized workflow was utilized for pre-selecting predictive features, followed by manifold learning. Machine learning algorithms were employed to establish associations between imaging features and remaining survival (RS), defined as the time between a follow-up scan and date of death. Results: The ML models exhibited 81–83% ROC_AUC in predicting RS evaluated on an independent test dataset. A RS map is proposed for monitoring tumor alterations through serial 18F-DOPA PET scans, demonstrating superior sensitivity and better correlation with survival compared to the RANO criteria. Conclusions: Our study demonstrates that ML models utilizing FU 18F-DOPA PET images have the potential to effectively predict future survival outcomes in patients with glioblastoma treated with dose-escalated radiation therapy. The capability to assess changes in tumor over time through imaging can potentially assist in patient stratification and the selection of salvage treatments, while also aiding in distinguishing treatment effects from genuine tumor progression.

AbstractIntroductionUsing diagnostic CT for radiotherapy (RT) planning can bypass traditional CT simulation but introduces challenges in patient positioning and Hounsfield unit (HU) fidelity, affecting dose accuracy. Here a Varian Ethos adaptive‐driven CT direct‐to‐treatment (DtT) multi‐fraction stereotactic body radiation therapy (SBRT) workflow is presented.MethodsThis study employed institutional diagnostic PET‐CT images to generate an initial reference Ethos treatment plan. HU and dosimetric accuracy were validated for PET‐CT, Ethos CBCT images (with and without Hypersight (HS), and the gold‐standard helical CT simulators). Following the SBRT reference plan creation on the low dose diagnostic PET‐CT, the first fraction was delivered with a newly generated adaptive plan calculated on the HS CBCT (Ethos) images. For multi‐fraction treatments, the first day CBCT images and adaptive plan become the reference for subsequent IGRT treatments. This study includes workflow validation and initial three patient experience.ResultsThe DtT adaptive SBRT workflow was successfully implemented, with initial end‐to‐end testing demonstrating feasibility. In‐house solutions were introduced to facilitate the adaptive to IGRT plan conversion. The Ethos system, especially with HS, maintained HU fidelity and dose calculation accuracy comparable to helical CTs. On‐table adaptive sessions were within 37–51 min, aligning with single‐fraction palliative studies. Subsequent non‐adaptive IGRT fractions were efficiently completed within 7–27 min.ConclusionsThis study demonstrates the feasibility of DtT adaptive‐driven multifraction SBRT using diagnostic PET‐CT. This approach reduces the need for on‐site patient presence prior to treatment, expands planning lead times, and improves overall efficiency in radiotherapy for well selected patients.

Objective Visual assessments of amyloid-β PET, used for Alzheimer’s disease (AD) diagnosis and treatment evaluation, require a careful approach when different PET ligands are utilized. Because the gray matter (GM) and white matter (WM) ligand bindings vary with age, the objective was to investigate the agreement between visual reads of 11C- and 18F-PET scans. Methods Cognitively unimpaired (CU) younger adults (N = 30; 39.5 ± 6.0 years), CU older adults (N = 30; 68.6 ± 5.9 years), and adults with AD (N = 22; 67.0 ± 8.5 years) underwent brain MRI, 11C-Pittsburgh compound-B (PiB)-PET, and 18F-flutemetamol-PET. Amyloid-β deposition was assessed visually by two nuclear medicine specialists on 11C-PiB-PET and 18F-flutemetamol-PET, and quantitatively by PET centiloids. Results Seventy-two 11C-PiB-PET and 18F-flutemetamol-PET visual reads were concordant. However, 1 18F-flutemetamol-PET and 9 11C-PiB-PET were discordant with quantitative values. In four additional cases, while 11C-PiB-PET and 18F-flutemetamol-PET visual reads were concordant, they were discordant with quantitative values. Disagreements in CU younger adults were only with 11C-PiB-PET visual reads. The remaining disagreements were with CU older adults. Conclusion Age, GM/WM binding, amyloid-β load, and disease severity may affect visual assessments of PET ligands. Increase in WM binding with age causes a loss of contrast between GM and WM on 11C-PiB-PET, particularly in CU younger adults, leading to false positivity. In CU older adults, increased WM signal may bleed more into cortical regions, hiding subtle cortical uptake, especially with 18F-flutemetamol, whereas 11C-PiB can detect true regional positivity. Understanding these differences will improve patient care and treatment evaluation in clinic and clinical trials.

AbstractBackgroundBoth 11C‐Pittsburgh compound‐B (PiB) and 18F‐Flutemetamol (FMT) have off‐target white matter (WM) signal that increases with age, but WM uptake is stronger with FMT than PiB. Although their WM patterns are comparably associated with age, the difference between them may impact visual and quantitative assessments of cortical amyloid‐β uptake. Our objective was to determine whether PiB PET and FMT PET visual assessments agree with quantitative cortical amyloid‐β evaluations.MethodA cohort of cognitively unimpaired (CU) younger adults with median (range) of 39 (30, 48) years (N = 30), CU older adults with age of 67 (61, 83) years (N = 30) and older adults with AD dementia with age of 67 (54‐84) years (N = 23) underwent MRI, PiB PET and FMT PET. PiB‐PET and FMT PET scans were evaluated visually by two nuclear medicine specialists blinded to participant information. Disagreements were reconciled with a second, joint round of visual reads. Readers applied standard visual assessment criteria using the absence of regional gray matter (GM) and WM contrast as an indication of a positive scan. The global cortical PiB standard uptake value ratio (SUVr) was obtained referencing to cerebellar crus uptake and converted to centiloid values. Participants were classified as PiB positive/negative using a centiloid cut‐off of 22.ResultPiB and FMT visual positivity agreed with quantitative positivity on PiB‐based centiloid values in 69/83 for PiB and 78/83 for FMT. There were 10 disagreements with PiB, 1 disagreement with FMT and 4 disagreements with both. Few disagreements occurred near the centiloid threshold. Interestingly, all disagreements between visual reads (amyloid‐β positive) and centiloid (amyloid‐β negative) in the CU younger were with PiB. FMT disagreements were always in the CU older and AD groups.ConclusionDisagreements between amyloid‐β positivity on visual reads and quantitative measurements (centiloid) may depend on age and tracer. PiB WM uptake is lower than FMT WM uptake, which may lead to reduced contrast between GM and WM (part of the standard criteria for visual reads), especially in younger ages. In contrast, WM uptake increases at older ages, and increased WM signal may bleed more into cortical regions, hiding subtle, near‐threshold cortical uptake, especially with FMT.

Evaluate the quantitative, subjective (Deauville score [DS]) and reader agreement differences between standard ordered subset expectation maximization (OSEM) and Bayesian penalized likelihood (BPL) positron emission tomography (PET) reconstruction methods. A retrospective review of 104 F-18 fluorodeoxyglucose PET/computed tomography (CT) exams among 52 patients with diffuse large B-cell lymphoma. An unblinded radiologist moderator reviewed both BPL and OSEM PET/CT exams. Four blinded radiologists then reviewed the annotated cases to provide a visual DS for each annotated lesion. Significant (P < .001) differences in BPL and OSEM PET methods were identified with greater standard uptake value (SUV) maximum and SUV mean for BPL. The DS was altered in 25% of cases when BPL and OSEM were reviewed by the same radiologist. Interobserver DS agreement was higher for OSEM (>1 cm lesion = 0.89 and ≤1 cm lesion = 0.84) compared to BPL (>1 cm lesion = 0.85 and ≤1 cm lesion = 0.81). Among the 4 readers, average intraobserver visual DS agreement between OSEM and BPL was 0.67 for lesions >1cm and 0.4 for lesions ≤1 cm. F-18 Fluorodeoxyglucose PET/CT of diffuse large B-cell lymphoma reconstructed with BPL has higher SUV values, altered DSs and reader agreement when compared to OSEM. This report finds volumetric PET measurements such as metabolic tumor volume to be similar between BPL and OSEM PET reconstructions. Efforts such as adoption of European Association Research Ltd accreditation should be made to harmonize PET data with an aim at balancing the need for harmonization and sensitivity for lesion detection.

Abstract BACKGROUND Interpretation of serial magnetic resonance imaging (MRI) for glioblastoma following radiation therapy (RT) is complicated by difficulty differentiating tumor from treatment-related changes, even using updated RANO criteria. The incorporation of novel imaging such as 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (18F-DOPA) PET/CT to post-treatment serial imaging may improve prognostication and better facilitate future treatment decisions. METHODS The secondary analysis of a recent phase II prospective clinical trial of 18F-DOPA PET/CT-directed dose-escalated RT included patients with IDH-wildtype, MGMT-unmethylated glioblastoma who underwent post-treatment serial 18F-DOPA PET/CT surveillance. Quantitative features were extracted from pre-RT and post-RT serial PET/CT images, and robust prognostic features were selected using an in-house workflow. Both an automated machine learning (ML) algorithm and an interpretable ML algorithm were utilized to correlate surveillance PET image features with subsequent survival of greater than 12 months versus less than 12 months from the surveillance timepoint. Changes from pre-RT to post-RT PET/CT (delta model) were also assessed for association with post-RT survival and validated with a separate cohort. RESULTS Thirty-five patients with IDH-wildtype, MGMT-unmethylated glioblastoma who had at least one available (range: 1-14) post-treatment 18F-DOPA PET/CT were included. Twenty-four were used for model training, while 11 were used for validation. Ultimately, a five-feature post-RT model utilizing two shape, two texture, and one first-order radiomic feature was selected. For the delta model, five texture, two shape, and one first order radiomic feature were selected. The models show 90% accuracy in predicting survival &lt; 12 months post-surveillance on the training set, and 68%-73% accuracy (AUC 0.64-0.73) for the validation cohort. Delta features were significantly associated with overall survival (p &lt; 0.05). CONCLUSIONS Post-RT serial 18F-DOPA PET/CT imaging can help distinguish true tumor progression in patients with glioblastoma using a radiomics model. Tumor response evaluated for changes from pre-RT to post-RT 18F-DOPA PET/CT also predicted subsequent overall survival.

AbstractBackgroundWhite matter (WM) 11C‐Pittsburgh compound‐B (PiB) and 18F‐Flutemetamol (FMT) uptake is increasingly being used as a reference region to calculate the standard uptake value ratios (SUVr) in longitudinal amyloid‐β PET studies. PiB uptake is lower in WM hyperintensities (WMH) in older adults. Furthermore, WM PiB uptake increases with aging. Our objective was to determine whether a similar variation in WM uptake exists with an 18F‐ligand FMT.MethodA cohort of cognitively unimpaired (CU) older adults with median (range) age of 67 (61, 83) years (N=31), and younger adults with median (range) age of 38 (30, 48) years (N=30) from the community responding to a study advertisement underwent MRI, PiB and FMT PET. MRI‐FLAIR images were segmented into WMH and normal appearing white matter (NAWM) and registered to the T1‐weighted image. PiB and FMT PET images were registered to the T1‐weighted image. PiB and FMT SUVrs from the WMH and NAWM compartments were calculated using cerebellar crus uptake as a reference.ResultWMH PiB SUVr and NAWM PiB SUVr were lower in the younger compared to the older adults (p<0.001). WMH FMT SUVr and NAWM FMT SUVr were lower in younger compared to older adults (p<0.001). PiB SUVr was lower than FMT SUVr both in younger and older adults in both WMH and NAWM compartments (p<0.001). In both age groups, PiB SUVr and FMT SUVr in WMH was lower than NAWM (p<0.001). AUROC analysis demonstrated no difference between PiB versus FMT SUVr in differentiating WMH from NAWM in younger and older adults.ConclusionWMH and NAWM SUVRs are higher with FMT than PiB, however both PiB and FMT show a similar topographic pattern of uptake in the WM with higher uptake in NAWM compared to WMH. Aging is associated with a decrease in myelin integrity and increase of WMH volume. Higher WMH and NAWM PiB and FMT uptake in the older compared to younger adults suggests that additional aging‐related mechanisms are influencing WM PET tracer uptake. Age and WMH volume should be considered when WM uptake is used as a reference region for the evaluation of cortical uptake of both PiB and FMT.