Speaker
Description
Summary
Among the tumors, pancreatic carcinoma is one of the most aggressive and resistant to current therapies, and most often is detected only on an advanced state of development. On the other hand, prostate cancer is the most diffuse cancer among males. The fusion of the high resolution metabolic image from PET and the anatomical image from ultrasound will improve the diagnosis and the therapeutic oncology of the mentioned tumors, especially at the early stages of development.
EndoTOFPET-US aims to push forward the limits of the current PET scanners: the endoscopic approach together with the Time Of Flight (TOF) information with an unprecedented CTR of 200 ps (3 cm along the line of response) allow to define a specific Region Of Interest (ROI), and drastically suppress the background coming from the neighboring organs.
The EndoTOFPET-US detector consists of a PET head extension mounted on a commercial US endoscope placed close to the ROI and an external PET plate facing the patient’s abdomen, in coincidence with the PET head. The internal probe is an highly miniaturized system: the
cooling system, electronics and the LYSO:Ce scintillating crystals coupled to digital SIPMs are housed in a very small volume (15 mm diameter for Pancreas case). The external plate is a square
of 20x20 cm2 and it is made of 256 detector unit modules, each consisting of a 4x4 LYSO:Ce crystal matrix glued to a discrete array of 4x4 analog SiPM from Hamamatsu. SiPM readout is performed
by a fast and low-noise Application-Specific Integrated Circuit (ASIC) developed by the collaboration. FPGAs concentrate event data sent by ASICs and transmit this information to an external Data Acquisition System (DAQ) where the data from the probe are met.
Different options for the tracking system are under study: optical, electromagnetic and mechanical. However, it has to provide at least 1 mm precision, in order to guarantee the requested spatial resolution.
Simulations of the whole detector are performed with the GAMOS framework. They provide a test on sensitivity, time and spatial resolution and therefore guide the detector design. Finally, the image reconstruction has to cope to low sensitivity, high noise and limited angle. GPU computation is used to provide on-line imaging for intraoperative application.