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      Validation of a Low Dose Simulation Technique for Computed Tomography Images

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Purpose

          Evaluation of a new software tool for generation of simulated low-dose computed tomography (CT) images from an original higher dose scan.

          Materials and Methods

          Original CT scan data (100 mAs, 80 mAs, 60 mAs, 40 mAs, 20 mAs, 10 mAs; 100 kV) of a swine were acquired (approved by the regional governmental commission for animal protection). Simulations of CT acquisition with a lower dose (simulated 10–80 mAs) were calculated using a low-dose simulation algorithm. The simulations were compared to the originals of the same dose level with regard to density values and image noise. Four radiologists assessed the realistic visual appearance of the simulated images.

          Results

          Image characteristics of simulated low dose scans were similar to the originals. Mean overall discrepancy of image noise and CT values was −1.2% (range −9% to 3.2%) and −0.2% (range −8.2% to 3.2%), respectively, p>0.05. Confidence intervals of discrepancies ranged between 0.9–10.2 HU (noise) and 1.9–13.4 HU (CT values), without significant differences (p>0.05). Subjective observer evaluation of image appearance showed no visually detectable difference.

          Conclusion

          Simulated low dose images showed excellent agreement with the originals concerning image noise, CT density values, and subjective assessment of the visual appearance of the simulated images. An authentic low-dose simulation opens up opportunity with regard to staff education, protocol optimization and introduction of new techniques.

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          Most cited references 26

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          Cancer risks attributable to low doses of ionizing radiation: assessing what we really know.

          High doses of ionizing radiation clearly produce deleterious consequences in humans, including, but not exclusively, cancer induction. At very low radiation doses the situation is much less clear, but the risks of low-dose radiation are of societal importance in relation to issues as varied as screening tests for cancer, the future of nuclear power, occupational radiation exposure, frequent-flyer risks, manned space exploration, and radiological terrorism. We review the difficulties involved in quantifying the risks of low-dose radiation and address two specific questions. First, what is the lowest dose of x- or gamma-radiation for which good evidence exists of increased cancer risks in humans? The epidemiological data suggest that it is approximately 10-50 mSv for an acute exposure and approximately 50-100 mSv for a protracted exposure. Second, what is the most appropriate way to extrapolate such cancer risk estimates to still lower doses? Given that it is supported by experimentally grounded, quantifiable, biophysical arguments, a linear extrapolation of cancer risks from intermediate to very low doses currently appears to be the most appropriate methodology. This linearity assumption is not necessarily the most conservative approach, and it is likely that it will result in an underestimate of some radiation-induced cancer risks and an overestimate of others.
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            A three-dimensional statistical approach to improved image quality for multislice helical CT.

            Multislice helical computed tomography scanning offers the advantages of faster acquisition and wide organ coverage for routine clinical diagnostic purposes. However, image reconstruction is faced with the challenges of three-dimensional cone-beam geometry, data completeness issues, and low dosage. Of all available reconstruction methods, statistical iterative reconstruction (IR) techniques appear particularly promising since they provide the flexibility of accurate physical noise modeling and geometric system description. In this paper, we present the application of Bayesian iterative algorithms to real 3D multislice helical data to demonstrate significant image quality improvement over conventional techniques. We also introduce a novel prior distribution designed to provide flexibility in its parameters to fine-tune image quality. Specifically, enhanced image resolution and lower noise have been achieved, concurrently with the reduction of helical cone-beam artifacts, as demonstrated by phantom studies. Clinical results also illustrate the capabilities of the algorithm on real patient data. Although computational load remains a significant challenge for practical development, superior image quality combined with advancements in computing technology make IR techniques a legitimate candidate for future clinical applications.
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              American College of Radiology white paper on radiation dose in medicine.

              The benefits of diagnostic imaging are immense and have revolutionized the practice of medicine. The increased sophistication and clinical efficacy of imaging have resulted in its dramatic growth over the past quarter century. Although data derived from the atomic bomb survivors in Japan and other events suggest that the expanding use of imaging modalities using ionizing radiation may eventually result in an increased incidence of cancer in the exposed population, this problem can likely be minimized by preventing the inappropriate use of such imaging and by optimizing studies that are performed to obtain the best image quality with the lowest radiation dose. The ACR, which has been an advocate for radiation safety since its inception in 1924, convened the ACR Blue Ribbon Panel on Radiation Dose in Medicine to address these issues. This white paper details a proposed action plan for the college derived from the deliberations of that panel.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                23 September 2014
                : 9
                : 9
                Affiliations
                [1 ]Department of Radiology, Technische Universitaet Muenchen, Munich, Germany
                [2 ]Philips Technologie GmbH, Innovative Technologies, Hamburg, Germany
                [3 ]Philips Healthcare, Cleveland, Ohio, United States of America
                [4 ]MITI - Minimal-invasive Interdisciplinary therapeutic intervention research group, Technische Universitaet Muenchen, Munich, Germany
                University of Groningen, University Medical Center Groningen, Netherlands
                Author notes

                Competing Interests: TK is an employee of Philips Technologie GmbH; KB and SZ are employees of Philips Healthcare. The remaining authors have no financial disclosures and had complete, unrestricted access to the study data at all stages of the study. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: DM TK KB SZ EJR PBN. Performed the experiments: DM AS PBN MD. Analyzed the data: DM TK AAF SW EB TZ. Contributed reagents/materials/analysis tools: DM AS TK KB SZ PBN EJR. Wrote the paper: DM TK KB SZ PBN.

                Article
                PONE-D-14-05336
                10.1371/journal.pone.0107843
                4172631
                25247422

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Pages: 8
                Funding
                This work is supported by Philips Healthcare. The funder provided support in the form of salaries for authors (TK, KB, SZ), but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Neuroscience
                Neuroimaging
                Computed Axial Tomography
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Medical Physics
                Radiology and Imaging

                Uncategorized

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