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Background: One of the challenges in the management of patients with follicular lymphoma (FL) is the identification of individuals with histological transformation, most commonly into diffuse large B-cell lymphoma (DLBCL). [18F]FDG-PET/CT is used for staging of patients with lymphoma, but visual interpretation cannot reliably discern FL from DLBCL. This study evaluated whether radiomic features extracted from clinical baseline [18F]FDG PET/CT and analyzed by machine learning algorithms may help discriminate FL from DLBCL. Materials and methods: Patients were selected based on confirmed histopathological diagnosis of primary FL (n=44) or DLBCL (n=76) and available [18F]FDG PET/CT with EARL reconstruction parameters within 6 months of diagnosis. Radiomic features were extracted from the volume of interest on co-registered [18F]FDG PET and CT images. Analysis of selected radiomic features was performed with machine learning classifiers based on logistic regression and tree-based ensemble classifiers (AdaBoosting, Gradient Boosting, and XG Boosting). The performance of radiomic features was compared with a SUVmax-based logistic regression model. Results: From the segmented lesions, 121 FL and 227 DLBCL lesions were included for radiomic feature extraction. In total, 79 radiomic features were extracted from the SUVmap, 51 from CT, and 6 shape features. Machine learning classifier Gradient Boosting achieved the best discrimination performance using 136 radiomic features (AUC of 0.86 and accuracy of 80%). SUVmax-based logistic regression model achieved an AUC of 0.79 and an accuracy of 70%. Gradient Boosting classifier had a significantly greater AUC and accuracy compared to the SUVmax-based logistic regression (p≤0.01). Conclusion: Machine learning analysis of radiomic features may be of diagnostic value for discriminating FL from DLBCL tumor lesions, beyond that of the SUVmax alone. [ABSTRACT FROM AUTHOR]

Background: Post-transplant lymphoproliferative disorders (PTLDs) are a spectrum of hematological malignancies occurring after solid organ and hematopoietic stem cell transplantation. [18F]FDG PET/CT is routinely performed at PTLD diagnosis, allowing for both staging of the disease and quantification of volumetric parameters, such as whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG). In this retrospective study, we aimed to determine the prognostic value of MTV and TLG in PTLD patients, together with other variables of interest, such as the International Prognostic Index (IPI), organ transplant type, EBV tumor status, time after transplant, albumin levels and PTLD morphology. Results: A total of 88 patients were included. The 1-, 3-, 5- year overall survival rates were 67%, 58% and 43% respectively. Multivariable analysis indicated that a high IPI (HR: 1.56, 95% CI: 1.13–2.16) and an EBV-negative tumor (HR: 2.71, 95% CI: 1.38–5.32) were associated with poor overall survival. Patients with a kidney transplant had a longer overall survival than any other organ recipients (HR: 0.38 95% CI: 0.16–0.89). IPI was found to be the best predicting parameter of overall survival in our cohort. Whole-body MTV, TLG, time after transplant, hypoalbuminemia and PTLD morphology were not associated with overall survival. Conclusion: [18F]FDG PET/CT whole-body volumetric quantitative parameters were not predictive of overall survival in PTLD. In our cohort, high IPI and an EBV-negative tumor were found to predictors of worse overall survival while kidney transplant patients had a longer overall survival compared to other organ transplant recipients [ABSTRACT FROM AUTHOR]

Purpose: Post-transplant lymphoproliferative disorder (PTLD) is a serious complication after solid organ and hematopoietic stem cell transplantation, requiring a timely and accurate diagnosis. In this study, we evaluated the diagnostic performance of FDG-PET/CT in patients with suspected PTLD and examined if lactate dehydrogenase (LDH) levels, Epstein-Barr virus (EBV) load, or timing of FDG-PET/CT relate to detection performance of FDG-PET/CT. Methods: This retrospective study included 91 consecutive patients with clinical suspicion of PTLD and a total of 97 FDG-PET/CT scans within an 8-year period. Pathology reports and a 2-year follow-up were used as the reference standard. Diagnostic performance of FDG-PET/CT for detection of PTLD as well as logistic regression analysis for factors expected to affect diagnostic yield were assessed. Results: The diagnosis of PTLD was established in 34 patients (35%). Fifty-seven FDG-PET/CT scans (59%) were true negative, 29 (30%) were true positive, 6 (6%) false positive, and 5 (5%) false negative. Sensitivity of FDG-PET/CT for the detection of PTLD was 85%, specificity 90%, positive predictive value 83%, and negative predictive value 92%, with good inter-observer variability (k = 0.78). Of the parameters hypothesized to be associated with a true positive FDG-PET/CT result for the diagnosis of PTLD, only LDH was statistically significant (OR 1.03, p = 0.04). Conclusion: FDG-PET/CT has a good diagnostic performance in patients suspected of PTLD, with a good inter-observer agreement. Only LDH levels seemed to influence the detection performance of FDG-PET/CT. EBV-DNA load and timing of FDG-PET/CT after transplantation did not affect FDG-PET/CT diagnostic yield. [ABSTRACT FROM AUTHOR]

The article discusses about a 10-week-old newborn presented with Staphylococcus aureus sepsis of unknown origin. It informs that the total body 18F-FDG PET/CT imaging was performed without sedation on the Biograph Vision Quadra system. It also informs that the scan showed normal physiological uptake in the kidneys, bladder, myocardium, and developing brain, including physiological hypometabolism in the frontal cortex (A).

Introduction: In patients with potentially resectable esophageal cancer (EC), the value of endoscopic ultrasonography (EUS) after fluorine-18 labeled fluorodeoxyglucose positron emission tomography with computed tomography (F-FDG-PET/CT) is questionable. Retrospectively, we assessed the impact of EUS after PET/CT on the given treatment in EC patients. Methods: During the period 2009-2015, 318 EC patients were staged as T1-4aN0-3M0 with hybrid F-FDG-PET/CT or F-FDG-PET with CT and EUS if applicable in a nonspecific order. We determined the impact of EUS on the given treatment in 279 patients who also were staged with EUS. EUS had clinical consequences if it changed curability, extent of radiation fields or lymph node resection (AJCC stations 2-5), and when the performed fine-needle aspiration (FNA) provided conclusive information of suspicious lymph node. Results: EUS had an impact in 80 (28.7%) patients; it changed the radiation field in 63 (22.6%), curability in 5 (1.8%), lymphadenectomy in 48 (17.2%), and FNA was additional in 21 (7.5%). In patients treated with nCRT ( n = 194), EUS influenced treatment in 53 (27.3%) patients; in 38 (19.6%) the radiation field changed, in 3 (1.5%) the curability, in 35 (18.0%) the lymphadenectomy, and in 17 (8.8%) FNA was additional. EUS influenced both the extent of radiation field and nodal resection in 31 (16.0%) nCRT patients. Conclusions: EUS had an impact on the given treatment in approximately 29%. In most patients, the magnitude of EUS found expression in the extent of radiotherapy target volume delineation to upper/high mediastinal lymph nodes. [ABSTRACT FROM AUTHOR]

Semiquantitative 18F-fluoro-2-deoxy-D-glucose positron emission tomography (18F-FDG PET) parameters have been proposed as prognostic markers in classical Hodgkin lymphoma (cHL). In non-Hodgkin lymphoma necrosis as assessed by 18F-FDG PET or computed tomography (CT) (necrosisvisual) correlates with an adverse prognosis. We investigated whether semiquantitative 18F-FDG PET metrics correlate with necrosisvisual, determined the incidence of necrosisvisual and explored the prognostic impact of these factors in cHL. From 87 cHL cases treated with ABVD, (escalated) BEACOPP or CHOP chemotherapy between 2010 and 2017, 71 had both a NEDPAS/EARL accredited 18F-FDG PET and a contrast enhanced CT scan. Semiquantitative 18F-FDG PET parameters were determined using Hermes Hybrid 3D software. Necrosisvisual, defined by photopenic tumor areas on 18F-FDG PET and attenuation values between 10 and 30 Hounsfield units (HUs) on CT, was assessed blinded to outcome. Univariate Cox regression survival analyses of progression free survival (PFS) were performed. Necrosisvisual was observed in 18.3% of cHL patients. Bulky disease (tumor mass >10 cm in any direction) (P = 0.002) and TLG (P = 0.041) but no other semiquantitative parameters were significantly associated with necrosisvisual. In exploratory univariate survival analysis for PFS the covariates IPS, bulky disease, MTV and TLG were prognostic, while necrosisvisual was not. [ABSTRACT FROM AUTHOR]

The article presents a case study of a 37-year-old man who was presented for an F-fluorodeoxyglycuse (F-FDG) positron emission tomography (PET) scan of the brain. He has a history of a large arteriovenous malformation (AVM) associated with a slowly progressive angiopathy. A moderate to severe hypometabolism of the entire right hemisphere was shown by the F-FDG PET scan. The advantage of FDG PET in assessing the degree and extend of cerebral metabolic involvement in AVM patients is discussed.

This review describes the main benefits of using long axial field of view (LAFOV) PET in clinical applications. As LAFOV PET is the latest development in PET instrumentation, many studies are ongoing that explore the potentials of these systems, which are characterized by ultra-high sensitivity. This review not only provides an overview of the published clinical applications using LAFOV PET so far, but also provides insight in clinical applications that are currently under investigation. Apart from the straightforward reduction in acquisition times or administered amount of radiotracer, LAFOV PET also allows for other clinical applications that to date were mostly limited to research, e.g., dual tracer imaging, whole body dynamic PET imaging, omission of CT in serial PET acquisition for repeat imaging, and studying molecular interactions between organ systems. It is expected that this generation of PET systems will significantly advance the field of nuclear medicine and molecular imaging., (© 2022. The Author(s).)