Publications by authors named "Marco Galelli"
COVID-19 clinical presentation and prognosis are highly variable, ranging from asymptomatic and paucisymptomatic cases to acute respiratory distress syndrome and multi-organ involvement. We developed a hybrid machine learning/deep learning model to classify patients in two outcome categories, non-ICU and ICU (intensive care admission or death), using 558 patients admitted in a northern Italy hospital in February/May of 2020. A fully 3D patient-level CNN classifier on baseline CT images is used as feature extractor.
View Article and Find Full Text PDFUnlabelled: We recently demonstrated in a clinical trial the ability of a new protocol, IQ SPECT, to acquire myocardial perfusion imaging (MPI) studies in a quarter of the time (12 s/view) of the standard protocol, with preserved diagnostic accuracy. We now aim to establish the lower limit of radioactivity that can be administered to patients and the minimum acquisition time in SPECT MPI using an IQ SPECT protocol, while preserving diagnostic accuracy.
Methods: An anthropomorphic cardiac phantom was used to acquire clinical rest scans with a simulated in vivo distribution of (99m)Tc-tetrofosmin at full dose (740 MBq) and at doses equal to 50%, 25%, and 18%.
Background: We have recently validated a quarter-time protocol in Myocardial Perfusion Imaging named IQ-SPECT, whose basic principle is to implement a multifocal collimator; However, in clinical practice, it may sometimes be difficult to center the heart in the region of highest magnification of the multifocal collimators (the so-called sweet spot). We therefore aimed to evaluate whether a heart mispositioning may affect results in MPI.
Methods: We simulated a rest study with an anthropomorphic phantom with an in vivo distribution of 400 MBq [(99m)Tc]tetrofosmin, with and without a transmural defect (TD).