A Multi-Element Detector System for Intelligent Imaging: I-ImaS

I-ImaS is a European project aiming to produce new, intelligent x-ray imaging systems using novel APS sensors to create optimal diagnostic images. Initial systems concentrate on mammography and encephalography. Later development will yield systems for other types of radiography such as industrial QA and homeland security. The I-ImaS system intelligence, due to APS technology and FPGAs, allows real-time analysis of data during image acquisition, giving the capability to build a truly adaptive imaging system with the potential to create images with maximum diagnostic information within given dose constraints. A companion paper deals with the DAQ system and preliminary characterization. This paper considers the laboratory x-ray characterization of the detector elements of the I-ImaS system. The characterization of the sensors when tiled to form a strip detector will be discussed, along with the appropriate correction techniques formulated to take into account the misalignments between individual sensors within the array. Preliminary results show that the detectors have sufficient performance to be used successfully in the initial mammographic and encephalographic I-ImaS systems under construction and this paper will further discuss the testing of these systems and the iterative processes used for intelligence upgrade in order to obtain the optimal algorithms and setting

A Multi-Element Detector System for Intelligent Imaging: I-ImaS

I-ImaS is a European project aiming to produce new, intelligent x-ray imaging systems using novel APS sensors to create optimal diagnostic images. Initial systems concentrate on mammography and encephalography. Later development will yield systems for other types of radiography such as industrial QA and homeland security. The I-ImaS system intelligence, due to APS technology and FPGAs, allows real-time analysis of data during image acquisition, giving the capability to build a truly adaptive imaging system with the potential to create images with maximum diagnostic information within given dose constraints. A companion paper deals with the DAQ system and preliminary characterization. This paper considers the laboratory x-ray characterization of the detector elements of the I-ImaS system. The characterization of the sensors when tiled to form a strip detector will be discussed, along with the appropriate correction techniques formulated to take into account the misalignments between individual sensors within the array. Preliminary results show that the detectors have sufficient performance to be used successfully in the initial mammographic and encephalographic I-ImaS systems under construction and this paper will further discuss the testing of these systems and the iterative processes used for intelligence upgrade in order to obtain the optimal algorithms and settings

Signalling of DNA damage and cytokines across cell barriers exposed to nanoparticles depends on barrier thickness

The use of nanoparticles in medicine is ever increasing, and it is important to understand their targeted and non-targeted effects. We have previously shown that nanoparticles can cause DNA damage to cells cultured below a cellular barrier without crossing this barrier. Here, we show that this indirect DNA damage depends on the thickness of the cellular barrier, and it is mediated by signalling through gap junction proteins following the generation of mitochondrial free radicals. Indirect damage was seen across both trophoblast and corneal barriers. Signalling, including cytokine release, occurred only across bilayer and multilayer barriers, but not across monolayer barriers. Indirect toxicity was also observed in mice and using ex vivo explants of the human placenta. If the importance of barrier thickness in signalling is a general feature for all types of barriers, our results may offer a principle with which to limit the adverse effects of nanoparticle exposure and offer new therapeutic approaches