| Resumo: | Cancer is the second leading cause of death in the world, and therefore, there is an undeniable need to ensure early screening and detection systems worldwide. The aim of this project is to study the feasibility of a Cone Beam Computed Tomography (CBCT) scanner for simultaneous breast and lung imaging. Additionally, the development of reconstruction algorithms and the study of their impact to the image quality was considered. Monte Carlo (MC) simulations were performed using the PENELOPE code system. A MC geometry model of a CBCT scanner was implemented for energies of 30 keV and 80 keV for hypothetical scanning protocols. Microcalcifications were inserted into the breast and lung of the computational phantom (ICRP Adult Female Reference), used in the simulations for dose assessment and projection acquisition. Reconstructed images were analyzed in terms of the Contrast-to-Noise Ratio (CNR) and dose calculations were performed for two protocols, one with a normalization factor of 2 mGy in the breast and another with 5 mGy in the lungs. Both, MC geometry model and reconstruction algorithm were validated by means of on-field measurements and data acquisition in a clinical center. Dosimetric and imaging performances were evaluated through Quality Assurance phantoms (Computed Tomography Dose Index and Catphan, respectively). Results indicate that the best implementation of the reconstruction algorithm was achieved with 80 keV, using the Hanning filter and linear interpolation. More specifically, for a spherical lung lesion with a radius of 7 mm a 30% CNR gain was found when the number of projections varied from 12 to 36 (corresponding to a dose increase of a factor of 3). This research suggests the possibility of developing a CBCT modulated beam scanner for simultaneous breast and lung imaging while ensuring dose reduction. However further investigation regarding the number of projections needed for image reconstruction is required.
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