An end-to-end deep learning pipeline to derive blood input with partial volume corrections for automated parametric brain PET mapping.

Dynamic 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (dFDG-PET) for human brain imaging has considerable clinical potential, yet its utilization remains limited. A key challenge in the quantitative analysis of dFDG-PET is characterizing a patient-specific blood input function, traditionally reliant on invasive arterial blood sampling. This research introduces a novel approach employing non-invasive deep learning model-based computations from the internal carotid arteries (ICA) with partial volume (PV) corrections, thereby eliminating the need for invasive arterial sampling.

Experimental validation of a rodent PET scanner prototype based on a single LYSO crystal tube.

Improving sensitivity and spatial resolution in small animal Positron Emission Tomography imaging instrumentation constitutes one of the main goals of nuclear imaging research. These parameters are degraded by the presence of gaps between the detectors. The present manuscript experimentally validates our prototype of an edge-less pre-clinical PET system based on a single LYSO:Ce annulus with an inner diameter of 62 mm and 10 outer facets of 26 × 52 mm.

Dynamic FDG-PET in localization of focal epilepsy: A pilot study.

Epilepsy surgery remains underutilized, in part because non-invasive methods of potential seizure foci localization are inadequate. We used high-resolution, parametric quantification from dynamic 2-[18F] fluoro-2-deoxy-d-glucose positron emission tomography (dFDG-PET) imaging to locate hypometabolic foci in patients whose standard clinical static PET images were normal. We obtained dFDG-PET brain images with simultaneous EEG in a one-hour acquisition on seven patients with no MRI evidence of focal epilepsy to record uptake and focal radiation decay.