Radiation Dose Reduction in Computed Tomography-Guided Lung Interventions using an Iterative Reconstruction Technique.

Purpose: To compare the radiation doses and image qualities of computed tomography (CT)-guided interventions using a standard-dose CT (SDCT) protocol with filtered back projection and a low-dose CT (LDCT) protocol with both filtered back projection and iterative reconstruction. Materials and Methods: Image quality and radiation doses (dose-length product and CT dose index) were retrospectively reviewed for 130 patients who underwent CT-guided lung interventions. SDCT at 120 kVp and automatic mA modulation and LDCT at 100 kVp and a fixed exposure were each performed for 65 patients. Image quality was objectively evaluated as the contrast-to-noise ratio and subjectively by two radiologists for noise impression, sharpness, artifacts and diagnostic acceptability on a four-point scale. Results: The groups did not significantly differ in terms of diagnostic acceptability and complication rate. LDCT yielded a median 68.6 % reduction in the radiation dose relative to SDCT. In the LDCT group, iterative reconstruction was superior to filtered back projection in terms of noise reduction and subjective image quality. The groups did not differ in terms of beam hardening artifacts. Conclusion: LDCT was feasible for all procedures and yielded a more than two-thirds reduction in radiation exposure while maintaining overall diagnostic acceptability, safety and precision. The iterative reconstruction algorithm is preferable according to the objective and subjective image quality analyses. Key Points: • Implementation of a low-dose computed tomography (LDCT) protocol for lung interventions is feasible and safe. • LDCT protocols yield a significant reduction (more than 2/3) in radiation exposure. • Iterative reconstruction algorithms considerably improve the image quality in LDCT protocols. Citation Format: • Chang DH, Hiss S, Mueller D et al. Radiation Dose Reduction in Computed Tomography-Guided Lung Interventions using an Iterative Reconstruction Technique. Fortschr Rontgenstr 2015; 187: 906 – 914