Purpose: To evaluate the feasibility of spatio-temporal encoding (SPEN) readout for pseudo-continuous ASL (pCASL) in brain, and its robustness to susceptibility artifacts as introduced by aneurysm clips.
Methods: A 2D self-refocused T *-compensated hybrid SPEN scheme, with super-resolution reconstruction was implemented on a 1.5T Philips system.
Pancreatic ductal adenocarcinoma (PDAC), estimated to become the second leading cause of cancer deaths in western societies by 2030, was flagged as a neglected cancer by the European Commission and the United States Congress. Due to lack of investment in research and development, combined with a complex and aggressive tumour biology, PDAC overall survival has not significantly improved the past decades. Cross-sectional imaging and histopathology play a crucial role throughout the patient pathway.
View Article and Find Full Text PDFEarly detection improves prognosis in pancreatic ductal adenocarcinoma (PDAC), but is challenging as lesions are often small and poorly defined on contrast-enhanced computed tomography scans (CE-CT). Deep learning can facilitate PDAC diagnosis; however, current models still fail to identify small (<2 cm) lesions. In this study, state-of-the-art deep learning models were used to develop an automatic framework for PDAC detection, focusing on small lesions.
View Article and Find Full Text PDFProton beam therapy (PBT) for uveal melanoma (UM) is performed in sitting position, while the acquisition of the Magnetic resonance (MR)-images for treatment planning is performed in supine position. We assessed the effect of this difference in position on the eye- and tumour- shape. Seven subjects and six UM-patients were scanned in supine and a seating mimicking position.
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