Our rationale was to investigate whether F-FDG PET/MRI in addition to (guideline-recommended) conventional staging leads to changes in therapeutic management in patients with newly diagnosed breast cancer and compare the diagnostic accuracy of F-FDG PET/MRI with that of conventional staging for determining the Union for International Cancer Control (UICC) stage. In this prospective, double-center study, 208 women with newly diagnosed, therapy-naïve invasive breast cancer were enrolled in accordance with the inclusion criteria. All patients underwent guideline-recommended conventional staging and whole-body F-FDG PET/MRI with a dedicated breast examination.
View Article and Find Full Text PDFPurpose: The aim of this study was to investigate the potential of multiparametric F-FDG PET/MR imaging as a platform for radiomics analysis and machine learning algorithms based on primary cervical cancers to predict N- and M-stage in patients.
Materials And Methods: A total of 30 patients with histopathological confirmation of primary and untreated cervical cancer were prospectively enrolled for a multiparametric F-FDG PET/MR examination, comprising a dedicated protocol for imaging of the female pelvis. The primary tumor in the uterine cervix was manually segmented on post-contrast T1-weighted images.
Meningiomas are known to express somatostatin receptor (SSTR) type 2 to a high degree. Therefore, radiolabeled somatostatin analogs, such as DOTATOC, have been introduced for PET imaging of meningiomas. However, the benefit of hybrid SSTR PET/MRI is still debated.
View Article and Find Full Text PDFBr J Radiol
June 2023
Objective: Body tissue composition plays a crucial role in the multisystemic processes of advanced liver disease and has been shown to be influenced by transjugular intrahepatic portosystemic shunt (TIPS). A differentiated analysis of the various tissue compartments has not been performed until now. The purpose of this study was to evaluate the value of imaging biomarkers derived from automated body composition analysis (BCA) to predict clinical and functional outcome.
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