Abstract
The purpose of this study was to reduce the radiation dosage associated with computed tomography (CT) lung cancer screening while maintaining overall diagnostic image quality and definition of ground‐glass opacities (GGOs). A lung screening phantom and a multipurpose chest phantom were used to quantitatively assess the performance of two iterative image reconstruction algorithms (adaptive statistical iterative reconstruction (ASIR) and model‐based iterative reconstruction (MBIR)) used in conjunction with reduced tube currents relative to a standard clinical lung cancer screening protocol (51 effective mAs (3.9 mGy) and filtered back‐projection (FBP) reconstruction). To further assess the algorithms' performances, qualitative image analysis was conducted (in the form of a reader study) using the multipurpose chest phantom, which was implanted with GGOs of two densities. Our quantitative image analysis indicated that tube current, and thus radiation dose, could be reduced by 40% or 80% from ASIR or MBIR, respectively, compared with conventional FBP, while maintaining similar image noise magnitude and contrast‐to‐noise ratio. The qualitative portion of our study, which assessed reader preference, yielded similar results, indicating that dose could be reduced by 60% (to 20 effective mAs (1.6 mGy)) with either ASIR or MBIR, while maintaining GGO definition. Additionally, the readers' preferences (as indicated by their ratings) regarding overall image quality were equal or better (for a given dose) when using ASIR or MBIR, compared with FBP. In conclusion, combining ASIR or MBIR with reduced tube current may allow for lower doses while maintaining overall diagnostic image quality, as well as GGO definition, during CT lung cancer screening.PACS numbers: 87.57.Q‐, 87.57.nf
Highlights
272 Mathieu et al.: Dose reduction for computed tomography (CT) lung screening that diagnostic image quality is not sacrificed in favor of dose reduction
When comparing the mean contrast-to-noise ratio (CNR) and image noise across reconstructions, our results indicated that dose could be reduced by 40% when using adaptive statistical iterative reconstruction (ASIR) or 80% when using model-based iterative reconstruction (MBIR), compared with the clinical protocol (51 effective mAs, filtered back-projection (FBP)), while maintaining a similar level of mean noise and CNR; Table 1 details these result alongside the corresponding CT images
When considering the mean CNRs, we found that, in images acquired at 30 effective mAs (40% dose reduction) when using ASIR or 10 effective mAs (80% dose reduction) when using MBIR, the average CNR was equal or greater than in images acquired at 51 effective mAs and reconstructed using FBP
Summary
272 Mathieu et al.: Dose reduction for CT lung screening that diagnostic image quality is not sacrificed in favor of dose reduction. It is extremely important that reductions in dose during CT lung screening examinations do not limit the detectability of ground-glass opacities (GGO), which are often indicative of premalignant lesions or early adenocarcinomas.[3]. Our hypothesis was that advanced iterative image reconstruction techniques would improve nodule definition and overall image quality (for a given dose), which in turn would allow for reduction of the radiation dose typically associated with CT lung cancer screening. The purpose of this study was to investigate the feasibility of using the image reconstruction techniques of adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) in conjunction with lowering tube current to minimize radiation doses, while maintaining GGO definition and overall image quality
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