Methods for clinical evaluation of noise reduction techniques in abdominopelvic CT.

Most noise reduction methods involve nonlinear processes, and objective evaluation of image quality can be challenging, since image noise cannot be fully characterized on the sole basis of the noise level at computed tomography (CT). Noise spatial correlation (or noise texture) is closely related to the detection and characterization of low-contrast objects and may be quantified by analyzing the noise power spectrum. High-contrast spatial resolution can be measured using the modulation transfer function and section sensitivity profile and is generally unaffected by noise reduction. Detectability of low-contrast lesions can be evaluated subjectively at varying dose levels using phantoms containing low-contrast objects. Clinical applications with inherent high-contrast abnormalities (eg, CT for renal calculi, CT enterography) permit larger dose reductions with denoising techniques. In low-contrast tasks such as detection of metastases in solid organs, dose reduction is substantially more limited by loss of lesion conspicuity due to loss of low-contrast spatial resolution and coarsening of noise texture. Existing noise reduction strategies for dose reduction have a substantial impact on lowering the radiation dose at CT. To preserve the diagnostic benefit of CT examination, thoughtful utilization of these strategies must be based on the inherent lesion-to-background contrast and the anatomy of interest. The authors provide an overview of existing noise reduction strategies for low-dose abdominopelvic CT, including analytic reconstruction, image and projection space denoising, and iterative reconstruction; review qualitative and quantitative tools for evaluating these strategies; and discuss the strengths and limitations of individual noise reduction methods.

Development and validation of a practical lower-dose-simulation tool for optimizing computed tomography scan protocols.

OBJECTIVE: The objective of this study was to develop and validate a novel noise insertion method that can accurately simulate lower-dose images from existing standard-dose computed tomography (CT) data. METHODS: The noise insertion method incorporates the effects of the bowtie filter, automatic exposure control, and electronic noise. We validated this tool using both phantom and patient studies. The phantom study compared simulated lower-dose images with the actually acquired lower-dose images. The patient studies included 105 pediatric and 24 adult CT body examinations. RESULTS: The noise level in the simulated images was within 3.2% of the actual lower-dose images in phantom experiments. Noise power spectrum also demonstrated excellent agreement. For the patient examinations, a mean difference of noise level between 2.0% and 9.7% was observed for simulated dose levels between 75% and 30% of the original dose. CONCLUSIONS: An accurate technique for simulating lower-dose CT images was developed and validated, which can be used to retrospectively optimize CT protocols.