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Marc Gil

Publications and source records attributed to Marc Gil.

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Initial Performance of a Long Axial FOV PET with TOF and DOI capabilities: IMAS system

This work summarizes the design, construction, initial performance evaluation and pilot clinical results of the IMAS system, a long axial field of view (FOV), also known as total-body (TB-), positron emission tomography (PET) prototype scanner. This PET enables for the first time in TB-PET imaging, simultaneously time-of-flight (TOF) and depth-of-interaction (DOI) capabilities. The IMAS detector block is based on LYSO semi monolithic scintillators, with individual slab sizes of 3 mm x 25 mm x 20 mm each. Arrays of 1x8 slabs are coupled to 8x8 Silicon Photomultiplier arrays. A proprietary readout reduces the 64 signals to only 16 outputs, preserving both 3D photon impact positioning and timing accuracy. IMAS has a total of 30,720 channels. PETsys electronics is used for data acquisition. The IMAS geometry is based on 5 rings of 10 cm each, with a 5 cm gap between them. It defines an axial FOV of 71 cm with a bore aperture of 82 cm. We report in this work the pilot tests of the system performance and the first clinical results. We found that the system spatial resolution remained below 4 mm across the entire FOV, even at the off-radial position of 30 cm. A coincidence time resolution with a small size 22Na source of 560 ps FWHM was measured. A sensitivity of 56.54 cps/kBq is in good agreement with previous simulation studies; however, the noise equivalent count rates performance (79 kcps at 3.26 kBq/mL) was significantly lower than expected, likely due to a data transfer bottleneck between the system and the acquisition workstation. Finally, a comparison of one of the imaged patients with a commercial TOF PET/CT scanner is also provided, pinpointing an improved tumor identification for IMAS, and the advantages of TOF and especially DOI capabilities.

physics.med-ph

Model-driven Engineering IDE for Quality Assessment of Data-intensive Applications

This article introduces a model-driven engineering (MDE) integrated development environment (IDE) for Data-Intensive Cloud Applications (DIA) with iterative quality enhancements. As part of the H2020 DICE project (ICT-9-2014, id 644869), a framework is being constructed and it is composed of a set of tools developed to support a new MDE methodology. One of these tools is the IDE which acts as the front-end of the methodology and plays a pivotal role in integrating the other tools of the framework. The IDE enables designers to produce from the architectural structure of the general application along with their properties and QoS/QoD annotations up to the deployment model. Administrators, quality assurance engineers or software architects may also run and examine the output of the design and analysis tools in addition to the designer in order to assess the DIA quality in an iterative process.

cs.SE