During particle therapy irradiation, positron emitters with half-lives ranging from 2 to 20 min are generated from nuclear processes. The half-lives are such that it is possible either to detect the positron signal in the treatment room using an in-beam positron emission tomography (PET) system, right after the irradiation, or to quickly transfer the patient to a close PET/CT scanner. Since the activity distribution is spatially correlated with the dose, it is possible to use PET imaging as an indirect method to assure the quality of the dose delivery. In this work, we present a new dedicated PET system able to operate in-beam. The PET apparatus consists in two 10 cm × 10 cm detector heads. Each detector is composed of four scintillating matrices of 23 × 23 LYSO crystals. The crystal size is 1.9 mm × 1.9 mm × 16 mm. Each scintillation matrix is read out independently with a modularized acquisition system. The distance between the two opposing detector heads was set to 20 cm. The system has very low dead time per detector area and a 3 ns coincidence window, which is capable to sustain high single count rates and to keep the random counts relatively low. This allows a new full-beam monitoring modality that includes data acquisition also while the beam is on. The PET system was tested during the irradiation at the CATANA (INFN, Catania, Italy) cyclotron-based proton therapy facility. Four acquisitions with different doses and dose rates were analysed. In all cases the random to total coincidences ratio was equal or less than 25%. For each measurement we estimated the accuracy and precision of the activity range on a set of voxel lines within an irradiated PMMA phantom. Results show that the inclusion of data acquired during the irradiation, referred to as beam-on data, improves both the precision and accuracy of the range measurement with respect to data acquired only after irradiation. Beam-on data alone are enough to give precisions better than 1 mm when at least 5 Gy are delivered.

DCE@urLAB is a software application for analysis of dynamic contrast-enhanced magnetic resonance imaging data (DCE-MRI). The tool incorporates a friendly graphical user interface (GUI) to interactively select and analyze a region of interest (ROI) within the image set, taking into account the tissue concentration of the contrast agent (CA) and its effect on pixel intensity.

This work reports on the development and performance evaluation of the VrPET/CT, a new multimodality scanner with coplanar geometry for in vivo rodent imaging. The scanner design is based on a partial-ring PET system and a small-animal CT assembled on a rotatory gantry without axial displacement between the geometric centers of both fields of view (FOV). We report on the PET system performance based on the NEMA NU-4 protocol; the performance characteristics of the CT component are not included herein. The accuracy of inter-modality alignment and the imaging capability of the whole system are also evaluated on phantom and animal studies. Tangential spatial resolution of PET images ranged between 1.56 mm at the center of the FOV and 2.46 at a radial offset of 3.5 cm. The radial resolution varies from 1.48 mm to 1.88 mm, and the axial resolution from 2.34 mm to 3.38 mm for the same positions. The energy resolution was 16.5% on average for the entire system. The absolute coincidence sensitivity is 2.2% for a 100-700 keV energy window with a 3.8 ns coincident window. The scatter fraction values for the same settings were 11.45% for a mouse-sized phantom and 23.26% for a rat-sized phantom. The peak noise equivalent count rates were also evaluated for those phantoms obtaining 70.8 kcps at 0.66 MBq/cc and 31.5 kcps at 0.11 MBq/cc, respectively. The accuracy of inter-modality alignment is below half the PET resolution, and the image quality of biological specimens agrees with measured performance parameters. The assessment presented in this study shows that the VrPET/CT system is a good performance small-animal imager, while the cost derived from a partial ring detection system is substantially reduced as compared with a full-ring PET tomograph.

A fully 3D iterative image reconstruction algorithm has been developed for high-resolution PET cameras composed of pixelated scintillator crystal arrays and rotating planar detectors, based on the ordered subsets approach. The associated system matrix is precalculated with Monte Carlo methods that incorporate physical effects not included in analytical models, such as positron range effects and interaction of the incident gammas with the scintillator material. Custom Monte Carlo methodologies have been developed and optimized for modelling of system matrices for fast iterative image reconstruction adapted to specific scanner geometries, without redundant calculations. According to the methodology proposed here, only one-eighth of the voxels within two central transaxial slices need to be modelled in detail. The rest of the system matrix elements can be obtained with the aid of axial symmetries and redundancies, as well as in-plane symmetries within transaxial slices. Sparse matrix techniques for the non-zero system matrix elements are employed, allowing for fast execution of the image reconstruction process. This 3D image reconstruction scheme has been compared in terms of image quality to a 2D fast implementation of the OSEM algorithm combined with Fourier rebinning approaches. This work confirms the superiority of fully 3D OSEM in terms of spatial resolution, contrast recovery and noise reduction as compared to conventional 2D approaches based on rebinning schemes. At the same time it demonstrates that fully 3D methodologies can be efficiently applied to the image reconstruction problem for high-resolution rotational PET cameras by applying accurate pre-calculated system models and taking advantage of the system's symmetries.

Microscopy plays a crucial role in the diagnosis of numerous diseases. However, the need for trained microscopists and pathologists, the complexity of pathology, and the accessibility and affordability of the technology can hinder the provision of rapid and high-quality diagnoses and healthcare. In this work, we present an affordable, 3D-printed, portable, robotic, mobile-based slide scanning microscope. The proposed device is composed of electronic, mechanical, and optical modules operated via smartphone with a control app. The device is connected and fully integrated with a telemedicine web platform, where digitized microscopy images can be remotely visualized and analyzed. The robotic scanner, which has approximately 1-µm resolution, has been evaluated in two clinical scenarios with histology and stool samples. The results showed sufficient image quality for performing a proper diagnosis in all cases under study.