Mammography image quality optimization delivering minimal dose by means of Monte Carlo simulations

G. TIRAO; M. VALENTE

Rio de Janeiro, Brasil

Conferencia; 8º LOWRAD International Conference; 2009

Comisión Nacional de Energía Nuclear Brasilera

<!-- /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-parent:""; margin:0cm; margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman"; mso-ansi-language:IT; mso-fareast-language:IT;} @page Section1 {size:612.0pt 792.0pt; margin:70.85pt 3.0cm 70.85pt 3.0cm; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;} div.Section1 {page:Section1;} --> Objectives: The main goal of this work is to evaluate irradiation configuration, according to typical mammography facilities, in order to improve X-ray image quality. In addition, total absorbed doses are calculated with the aim of determining the optimal irradiation setup with the minimal dose delivering.   Methods: X-ray imaging process is suitably studied by means of dedicated Monte Carlo program, based on the main code PENELOPE, which allows to define the main physical and geometrical parameters affecting the absorption contrast X-ray image. Several relevant quantities, like sample properties (chemical composition, thickness and shape) and incident beam features (energy spectrum composition, source size and angular divergence) can be introduced to the program in order to evaluate their effect on image quality. Furthermore, detector resolution and inserted collimators (pin-hole grid) can be also carefully modelled. Dedicated routines are incorporated for 3D dose distribution calculation, which can be suitably visualized by means of adapted software (MatLab supported).   Results:  A commercially available mammography system is possible to model by means of the developed program. Therefore, on the base of this modellization, different setup configurations are studied in order to characterize the effect of relevant irradiation parameters on the image quality. The insertion of a dedicated parallel collimator shows a significant quality improvement. The calculation of absorbed dose for different configurations allows to establish the optimal quality-dose compromise.   Conclusions: The developed Monte Carlo program seems to be a useful tool for X-ray imaging process modelling. Actually, image quality improvement is performed according irradiation parameter configurations. Furthermore, absorbed dose calculation allows to decide optimal irradiation setup corresponding to minimal dose delivery. Finally, it should be emphasized that this model can be straightforwardly applied for other X-ray imaging techniques.