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Optimized FDG-PET/MRI protocol reveals metabolic predictors of long-term survival in pancreatic cancer patients.
Front Oncol
November 2024
Department of Nuclear Medicine, University Hospital Basel, Basel, Switzerland.
Purpose: To optimize and assess an abbreviated dual time-point 18-Fluor-Deoxyglucose (FDG)-Positron Emission Tomography (PET)/Magnetic Resonance Imaging (MRI) protocol for predicting patient outcomes in pancreatic cancer.
Methods: 70 patients (47 pancreatic cancer, 23 chronic pancreatitis) underwent hybrid PET/MRI with dual time-point PET/CT at 60 and 84 minutes post-injection. Metabolic indices (MI) were calculated from Standardized Uptake Value (SUV) changes (SUVmin, SUVmean and SUVmax).
Synthesis, preclinical assessment, and first-in-human study of [F]d-FET for brain tumor imaging.
Eur J Nucl Med Mol Imaging
November 2024
Center of Cyclotron and PET Radiopharmaceuticals, Department of Nuclear Medicine, & Key Laboratory of Basic and Translational Research On Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China.
Purpose: Tumor-to-background ratio (TBR) is a critical metric in oncologic PET imaging. This study aims to enhance the TBR of [F]FET in brain tumor imaging by substituting deuterium ("D") for hydrogen ("H"), thereby improving the diagnostic sensitivity and accuracy.
Methods: [F]d-FET was synthesised by two automated radiochemistry modules.
An assessment of PET and CMR radiomic features for the detection of cardiac sarcoidosis.
Front Nucl Med
January 2024
Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom.
Article Synopsis
- The study investigates the effectiveness of [F]FDG PET and LGE-CMR imaging methods for distinguishing cardiac sarcoidosis (CS) from myocardial inflammation resulting from COVID-19.
- It involved analyzing image data from 35 post-COVID-19 patients and 40 CS patients, focusing on extracting and testing radiomic features to improve diagnostic accuracy for these conditions.
- The results indicated that the combined signature of features from [F]FDG PET performed exceptionally well with an AUC of 0.98 and accuracy of 0.91, while LGE-CMR achieved an accuracy of 0.75 and AUC of 0.87, highlighting the potential of machine learning classifiers in enhancing diagnostic outcomes.
Case report: Anti-ARHGAP26 autoantibodies in atypical dementia with Lewy bodies.
Front Dement
August 2023
Department of Nuclear Medicine, University Medical Center Göttingen, Göttingen, Germany.
Background: Dementia with Lewy bodies (DLB) is the second most common type of neurodegenerative dementia. Here, we report a case of dementia associated with anti-Rho-GTPase-activating protein 26 (ARHGAP26) autoantibodies, which have never been previously linked to DLB.
Methods: We describe the case of a 78-year-old man who underwent cerebrospinal fluid (CSF) analysis, magnetic resonance imaging (MRI), F-fluorodesoxyglucose positron emission tomography (FDG-PET), and a detailed neuropsychological evaluation.
Advancements in Neuroendocrine Neoplasms: Imaging and Future Frontiers.
J Clin Med
June 2024
Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA.
Neuroendocrine neoplasms (NENs) are a diverse group of tumors with varying clinical behaviors. Their incidence has risen due to increased awareness, improved diagnostics, and aging populations. The 2019 World Health Organization classification emphasizes integrating radiology and histopathology to characterize NENs and create personalized treatment plans.
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