IMIC is a Monolithic Active Pixel Sensor prototype designed for the MAPSSIC project, which aims at developing wireless intracerebral probes dedicated to image positron-emitting source activity in the brain of awake and freely moving rats. Former experiments with the PIXSIC positron probe based on a passive sensor have validated the proof of concept, but have also shown limitations with regards to the probe robustness and to its transparency to annihilation photons. The IMIC circuit features a matrix of 16 × 128 active pixels of 30 × 50 µm 2 size and targets to overcome the PIXSIC probe drawbacks by exploiting a thin sensitive layer of 18 µm, still featuring an overall thickness close to 300 µm. Additionally, by using a low power (55 nW/pixel) in-pixel front-end architecture providing binary output, IMIC solves the challenge of implanting an active sensor in tissues where overheating is forbidden. The needle-shaped sensor 610 µm × 12000 µm was fabricated and tested in laboratory. The whole sensor dissipates 160 µW and its imaging capabilities were asserted with various sources : 55 Fe, 90 Sr and 18 F. These tests also demonstrated robust count-rate measurement with IMIC in the range 10-1000 counts/matrix/s. Finally, a dedicated setup qualitatively confirmed excellent insensitivity to 511 keV γ-rays. In this paper, we present the sensor requirements and its detailed design. We also discuss the first characterisation results and the outlook for the integration of IMIC into an implantable probe.
Iodine-124 is a radionuclide well suited to the labeling of intact monoclonal antibodies. Yet, accurate quantification in preclinical imaging with I-124 is challenging due to the large positron range and a complex decay scheme including high-energy gammas. The aim of this work was to assess the quantitative performance of a fully 3D Monte Carlo (MC) reconstruction for preclinical I-124 PET. The high-resolution small animal PET Inveon (Siemens) was simulated using GATE 6.1. Three system matrices (SM) of different complexity were calculated in addition to a Siddon-based ray tracing approach for comparison purpose. Each system matrix accounted for a more or less complete description of the physics processes both in the scanned object and in the PET scanner. One homogeneous water phantom and three heterogeneous phantoms including water, lungs and bones were simulated, where hot and cold regions were used to assess activity recovery as well as the trade-off between contrast recovery and noise in different regions. The benefit of accounting for scatter, attenuation, positron range and spurious coincidences occurring in the object when calculating the system matrix used to reconstruct I-124 PET images was highlighted. We found that the use of an MC SM including a thorough modelling of the detector response and physical effects in a uniform water-equivalent phantom was efficient to get reasonable quantitative accuracy in homogeneous and heterogeneous phantoms. Modelling the phantom heterogeneities in the SM did not necessarily yield the most accurate estimate of the activity distribution, due to the high variance affecting many SM elements in the most sophisticated SM.
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