Bilgin, Cem

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.

Purpose Radioligand therapy (RLT) with [ 177 Lu] Lu-PSMA-617 has shown significant benefits in metastatic castration-resistant prostate cancer (mCRPC), including prolonged overall survival (OS) and progression-free survival (PFS), as well as improved quality of life. For patients previously treated with [ 177 Lu]Lu-PSMA-617 who subsequently experience disease progression, retreatment with [ 177 Lu] Lu-PSMA-617 has emerged as a potential approach, yet data on the outcomes of RLT retreatment remains limited. This study aimed to assess the efficacy and safety of retreatment RLT in mCRPC. Methods Clinical and imaging data of patients who underwent at least two cycles of [ 177 Lu] Lu-PSMA-617, followed by a second course of treatment with [ 177 Lu] Lu-PSMA-617 between March 2018 and December 2024, were retrospectively reviewed. Endpoints included biochemical response, imaging response, toxicity, PSA-PFS, rPFS, and OS. Radiologic and biochemical responses were evaluated using RECIST 1.1 criteria and PSA levels, respectively. Results A total of 589 patients underwent [ 177 Lu] Lu-PSMA-617 RLT, of whom 20 (3.4%, 20/589) received RLT retreatment. The median age was 71.3 years (range: 63.7–95.2), and the median follow-up was 73.3 months (95% CI, 35.7–77.2 months) after the initial treatment and 21.7 months (95% CI, 16.9–26.0 months) after retreatment. The initial treatment involved a median of 4.5 cycles (range: 2–6). Following the first course of RLT, 15 patients (75%, 15/20) had exhibited a >50% decline in PSA levels, including 9 who achieved a >90% decrease. Additionally, 12 patients (60%, 12/20) had demonstrated a complete or partial imaging response, while 3 (15%, 3/20) patients had stable disease, and 5 (25%, 5/20) patients had progressive radiologic disease. Patients received a median of 4 retreatment cycles (range, 1–6), and the median interval between initial RLT and retreatment RLT was 33.1 months (IQR, 16.2–48.9 months; range, 10.7–58.8 months). A PSA decline of ≥50% was observed in 9 out of 20 patients (45%, 9/20). An imaging response was observed in 10 patients (50%, 10/20), with 4 achieving a complete response and 6 achieving a partial response, whereas 10 patients (50%, 10/20) showed progression. The median PSA-PFS was 9.8 months (95% CI, 4.1–17.9 months), and the median rPFS was 8.2 months (95% CI, 3.3–17.9 months). Eight deaths occurred during follow-up. The estimated Kaplan Meier OS rates were 83.6% at 12 months (95% CI, 57.3%–94.4%) and 53.7% at 24 months (95% CI, 28.3%–73.7%). Grade 2 renal toxicity was observed in one patient (5%, 1/20). Three patients (15%, 3/20) developed Grade 2 anemia. Notably, no grade 3 or grade 4 adverse events were observed during either treatment period. Conclusion In our cohort, retreatment with [¹ 77 Lu]Lu-PSMA-617 RLT was associated with biochemical and imaging responses in some patients, with observed survival outcomes that support further investigation. However, given the retrospective single-arm design and small sample size, large prospective studies are needed to more rigorously evaluate the safety, efficacy, and optimal patient selection for retreatment RLT.

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 Ischemic stroke is an important cause of morbidity and mortality in children, yet no clinical trials have evaluated mechanical thrombectomy (MT) in this population. Consequently, in contrast to adults, pediatric MT remains an off-label intervention. This meta-analysis aimed to assess its safety and efficacy and compare outcomes with medical management (MM). Methods MEDLINE, Scopus, and Web of Science were searched to identify original studies reporting outcomes of MT, with or without intravenous thrombolysis (IVT) in pediatric ischemic stroke. In studies that concurrently reported MT±IVT and MM±IVT within the same study, outcomes from the MM arms were also extracted for comparative analysis. Results Eighteen studies encompassing 612 pediatric patients were included. The pooled successful recanalization rate (thrombolysis in cerebral infarction (TICI) 2b–3) after mechanical thrombectomy was 88.9% (95% confidence interval (CI) 85.65 to 92.06), and 43.9% (95% CI, 38.67 to 49.09) achieved complete recanalization (TICI 3). Favorable functional outcomes (modified Rankin Scale (mRS) 0–2) occurred in 78.6% (95% CI, 69.58 to 87.61) of patients, with mortality and symptomatic intracranial hemorrhage (sICH) rates of 3.9% (95% CI, 1.88 to 5.92) and 1.3% (95% CI, 1.07 to 2.58), respectively. Shift analysis demonstrated a significant overall improvement in functional outcomes with MT±IVT compared with MM±IVT (common (OR), 0.43; 95% CI, 0.30 to 0.63; P<0.001). Conclusion Our findings suggest that MT has a favorable safety and efficacy profile, resulting in a more favorable mRS shift compared with MM in pediatric ischemic stroke. Further research is needed to identify the pediatric stroke patients who are likely to benefit from MT.

Radioiodine ablation therapy is commonly used for patients with well-differentiated thyroid cancer. False-positive radioiodine uptake in benign cystic lesions on post-therapy SPECT/CT presents a recognized diagnostic challenge. Here, we present the case of a 33-year-old woman who underwent total thyroidectomy, followed by I-131 radioiodine therapy. Her post–I-131 therapy SPECT/CT revealed incidental radioiodine uptake in a diaphragmatic mesothelial cyst, prompting further investigation. She subsequently underwent a dedicated liver MRI and excision biopsy, both of which were negative for thyroid cancer metastasis. This case highlights the importance of identifying benign sources of radioiodine uptake to avoid unnecessary interventions.

Background Carotid artery tortuosity (CAT) may complicate mechanical thrombectomy (MT), potentially causing delays or preventing recanalization. However, the relationship between CAT and MT outcomes remains largely unexplored. This systematic review aims to evaluate the existing evidence regarding the impact of CAT on MT outcomes. Methods Following PRISMA guidelines, a systematic literature search was conducted using MEDLINE, EMBASE, Web of Science, Cochrane, and Scopus databases. Studies providing data for MT outcomes based on CAT status were included. Outcomes of interest included successful recanalization, first-pass efficacy (FPE), procedure time, functional independence, and procedure-related complications. Results Our search identified nine studies with 2737 patients. Three studies employed DSA to assess tortuosity, whereas the remaining six studies preferred CTA. In seven studies, CAT was associated with prolonged procedure times. In five studies, successful recanalization rates were significantly lower in CAT patients as compared to patients with non-tortuous arteries. Two studies showed that CAT could alter FPE or successful recanalization rates of first-line MT techniques. No study found statistically significant relationships between CAT and functional independence. Three studies examined the association between CAT and safety outcomes, and only one study found increased intracranial hemorrhage rates in patients with CAT. All nine studies employed different CAT criteria. Conclusions Despite the vast MT literature, the number of studies reporting CAT status remains low. CAT may affect procedure time and technical outcomes of MT. Therefore, employing a uniform CAT definition and reporting CAT more frequently can provide insights into management of patients with acute large vessel occlusions.

Background As the use of flow diverters has expanded in recent years, predicting successful outcomes has become more challenging for certain aneurysms. Objective To provide neurointerventionalists with an understanding of the available machine learning algorithms for predicting the success of flow diverters in occluding aneurysms. Methods This study followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and the four major medical databases (PubMed, Embase, Scopus, Web of Science) were screened. The study included original research articles that evaluated the predictive abilities of various machine learning algorithms for determining the success of flow diverters in achieving aneurysm occlusion. Results Five studies out of 217 were included based on our criteria. The included studies used various variables (patient demographics, aneurysm and parent artery characteristics, flow diverter and hemodynamic-related features, and angiographic parametric imaging) to predict flow diverter treatment outcomes. The machine learning algorithms used, along with their respective accuracy rates, were as follows: logistic regression (61% and 85%), support vector machine (88%), Gaussian support vector machine (90%), linear support vector machine (85%), decision tree (80%), random forest (87%), k-nearest neighbors (83% and 85%), XGBoost (87%), CatBoost (86%), deep neural networks (77.9%), and recurrent neural networks (74%).Two studies trained the machine learning models with both all features and the most significant features. Both studies observed that the accuracy of machine learning models decreased by removing the insignificant features. Conclusion The current literature indicates that machine learning algorithms can be trained to predict the success of flow diverters with an accuracy of up to 90%.