Purpose
To evaluate the possibility of lowering radiation dose from a localizer radiograph (LR) using a tin spectral shaping filter and to investigate the effect of this adaptation on the radiation dose and image quality of subsequent computed tomography (CT) examination.
Methods
The study utilized a set of semianthropomorphic abdomen phantoms, representing small, medium, and large patients. The LR scans were performed with and without a tin spectral shaping filter using various kVp/mA settings. The tube current values of spiral CT examinations following the LR were assessed to evaluate the effect of LR settings on automatic exposure control (AEC). The image quality of CT examinations with various LRs was evaluated by measuring image noise in several regions‐of‐interest. Organ dose values from LR scans were derived from Monte Carlo simulations performed on a set of virtual anthropomorphic phantoms and the effective dose (ED) values were calculated.
Results
The radiation dose from the LR can be strongly reduced by using a tin spectral shaping filter (P < 0.001). The optimal settings of the LR scan depend on the size of the scanned subject: for small and medium size subjects, the combination of a tin spectral shaping filter with 100 kVp and 20 mA resulted in the lowest possible radiation dose (ED = 0.007 mGy) without compromising the AEC and image quality of subsequent CT. In contrast, the LR settings of 100 kVp with a tin spectral shaping filter and the tube current values of 20 and 35 mA in large subject (47.4 cm in diameter) resulted in significant variation of the TCM values (11.1% and 8.4%, respectively) and the corresponding increase of noise by >5% in subsequent CT examination. For all investigated phantom sizes, the combination of 100 Sn kV with a tin spectral shaping filter and tube current values of 75 mA results in the lowest possible radiation dose, while still keeping the AEC function unchanged.
Conclusion
The study indicated that tin spectral shaping filtration can be applied to LRs for radiation dose reduction, but such adaptation needs to take patient size into account.