Computational Assessment of the Influence of Beam Hardening Filters on Image Quality and Patient Dose in CT Scanners

Abstract

Beam hardening filters have long been employed in X-ray Computed Tomography (CT) to preferentially absorb soft and low-energy X-rays having no or little contribution to image formation, thus allowing the reduction of patient dose and beam hardening artefacts. The aim of the study was to develop a computational program to assess the influence of additional copper (Cu) and aluminium (Al) filters on patient dose and image quality, and seek an optimum filter thickness for the CT scanner using virtual experimental phantom measurements. Computed Tomography (CT) is crucial for medical diagnosis, but concerns about high radiation doses necessitate minimizing patient exposure without compromising image quality. The effectiveness of beam hardening filters as a solution was investigated. Using the Monte Carlo N-Particle Code (MCNP) and Virtual Editor (VIS ED), a 64-slice Philips CT scanner was modeled in an experimental research design. Computational Catphan phantoms representing human tissues were utilized to assess different BHF configurations' impact on image quality and patient radiation dose. Statistical analysis was performed using SPSS. The study revealed that beam hardening filters significantly affect patient dose and image quality. The optimal beam hardening filter, that balances patient dose and image quality was the 0.48 mm thickness of the conically shaped additional copper filter, or the 1.61 mm thickness of the Rectangular shaped additional Copper beam filter. And for Aluminium the optimum filter that give best quality image was the 2.60 mm conically shaped additional Aluminium beam filter. Striking a compromise between dose reduction and image quality preservation. These findings attest to the effectiveness of the optimal filter thicknesses in providing adequate filtration. Substantial reduction in patient dose was achieved while maintaining reasonable image quality in terms of contrast and spatial resolution.