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      Dual Energy CT (DECT) Monochromatic Imaging: Added Value of Adaptive Statistical Iterative Reconstructions (ASIR) in Portal Venography

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          Abstract

          Objective

          To investigate the effect of the adaptive statistical iterative reconstructions (ASIR) on image quality in portal venography by dual energy CT (DECT) imaging.

          Materials and Methods

          DECT scans of 45 cirrhotic patients obtained in the portal venous phase were analyzed. Monochromatic images at 70keV were reconstructed with the following 4 ASIR percentages: 0%, 30%, 50%, and 70%. The image noise (IN) (standard deviation, SD) of portal vein (PV), the contrast-to-noise-ratio (CNR), and the subjective score for the sharpness of PV boundaries, and the diagnostic acceptability (DA) were obtained. The IN, CNR, and the subjective scores were compared among the four ASIR groups.

          Results

          The IN (in HU) of PV (10.05±3.14, 9.23±3.05, 8.44±2.95 and 7.83±2.90) decreased and CNR values of PV (8.04±3.32, 8.95±3.63, 9.80±4.12 and 10.74±4.73) increased with the increase in ASIR percentage (0%, 30%, 50%, and 70%, respectively), and were statistically different for the 4 ASIR groups (p<0.05). The subjective scores showed that the sharpness of portal vein boundaries (3.13±0.59, 2.82±0.44, 2.73±0.54 and 2.07±0.54) decreased with higher ASIR percentages (p<0.05). The subjective diagnostic acceptability was highest at 30% ASIR (p<0.05).

          Conclusions

          30% ASIR addition in DECT portal venography could improve the 70 keV monochromatic image quality.

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          Most cited references20

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          Iterative reconstruction technique for reducing body radiation dose at CT: feasibility study.

          The purpose of this study was to evaluate the image noise, low-contrast resolution, image quality, and spatial resolution of adaptive statistical iterative reconstruction in low-dose body CT. Adaptive statistical iterative reconstruction was used to scan the American College of Radiology phantom at the American College of Radiology reference value and at one-half that value (12.5 mGy). Test objects in low- and high-contrast and uniformity modules were evaluated. Low-dose CT with adaptive statistical iterative reconstruction was then tested on 12 patients (seven men, five women; average age, 67.5 years) who had previously undergone routine-dose CT. Two radiologists blinded to scanning technique evaluated images of the same patients obtained with routine-dose CT and low-dose CT with and without adaptive statistical iterative reconstruction. Image noise, low-contrast resolution, image quality, and spatial resolution were graded on a scale of 1 (best) to 4 (worst). Quantitative noise measurements were made on clinical images. In the phantom, low- and high-contrast and uniformity assessments showed no significant difference between routine-dose imaging and low-dose CT with adaptive statistical iterative reconstruction. In patients, low-dose CT with adaptive statistical iterative reconstruction was associated with CT dose index reductions of 32-65% compared with routine imaging and had the least noise both quantitatively and qualitatively (p < 0.05). Low-dose CT with adaptive statistical iterative reconstruction and routine-dose CT had identical results for low-contrast resolution and nearly identical results for overall image quality (grade 2.1-2.2). Spatial resolution was better with routine-dose CT (p = 0.004). These preliminary results support body CT dose index reductions of 32-65% when adaptive statistical iterative reconstruction is used. Studies with larger statistical samples are needed to confirm these findings.
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            Low-tube-voltage, high-tube-current multidetector abdominal CT: improved image quality and decreased radiation dose with adaptive statistical iterative reconstruction algorithm--initial clinical experience.

            To investigate whether an adaptive statistical iterative reconstruction (ASIR) algorithm improves the image quality at low-tube-voltage (80-kVp), high-tube-current (675-mA) multidetector abdominal computed tomography (CT) during the late hepatic arterial phase. This prospective, single-center HIPAA-compliant study was institutional review board approved. Informed patient consent was obtained. Ten patients (six men, four women; mean age, 63 years; age range, 51-77 years) known or suspected to have hypervascular liver tumors underwent dual-energy 64-section multidetector CT. High- and low-tube-voltage CT images were acquired sequentially during the late hepatic arterial phase of contrast enhancement. Standard convolution FBP was used to reconstruct 140-kVp (protocol A) and 80-kVp (protocol B) image sets, and ASIR (protocol C) was used to reconstruct 80-kVp image sets. The mean image noise; contrast-to-noise ratio (CNR) relative to muscle for the aorta, liver, and pancreas; and effective dose with each protocol were assessed. A figure of merit (FOM) was computed to normalize the image noise and CNR for each protocol to effective dose. Repeated-measures analysis of variance with Bonferroni adjustment for multiple comparisons was used to compare differences in mean CNR, image noise, and corresponding FOM among the three protocols. The noise power spectra generated from a custom phantom with each protocol were also compared. When image noise was normalized to effective dose, protocol C, as compared with protocols A (P = .0002) and B (P = .0001), yielded an approximately twofold reduction in noise. When the CNR was normalized to effective dose, protocol C yielded significantly higher CNRs for the aorta, liver, and pancreas than did protocol A (P = .0001 for all comparisons) and a significantly higher CNR for the liver than did protocol B (P = .003). Mean effective doses were 17.5 mSv +/- 0.6 (standard error) with protocol A and 5.1 mSv +/- 0.3 with protocols B and C. Compared with protocols A and B, protocol C yielded a small but quantifiable noise reduction across the entire spectrum of spatial frequencies. Compared with standard FBP reconstruction, an ASIR algorithm improves image quality and has the potential to decrease radiation dose at low-tube-voltage, high-tube-current multidetector abdominal CT during the late hepatic arterial phase.
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              Innovations in CT dose reduction strategy: application of the adaptive statistical iterative reconstruction algorithm.

              The purpose of this article is to discuss the application of a new CT reconstruction algorithm, adaptive statistical iterative reconstruction (ASIR), to reduce radiation dose at body CT and to provide imaging examples in comparison with low-dose and standard-dose filtered back projection CT. The ASIR reconstruction algorithm is a promising technique for providing diagnostic quality CT images at significantly reduced radiation doses.
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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, CA USA )
                1932-6203
                17 June 2016
                2016
                : 11
                : 6
                : e0156830
                Affiliations
                [1 ]Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
                [2 ]Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
                Chongqing University, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: LZ WH. Performed the experiments: LZ SW RJ XW WH. Analyzed the data: LZ SW RJ XW WH. Contributed reagents/materials/analysis tools: LZ SW RJ XW WH. Wrote the paper: LZ SW RJ XW WH. Edited the manuscript: LZ SW RJ XW WH. Reviewed the manuscript: LZ SW RJ XW WH.

                Author information
                http://orcid.org/0000-0002-1274-5179
                Article
                PONE-D-15-43623
                10.1371/journal.pone.0156830
                4912087
                27315158
                7ec15016-fb95-4f30-a371-aa6996e89820
                © 2016 Zhao et al

                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.

                History
                : 13 October 2015
                : 22 May 2016
                Page count
                Figures: 4, Tables: 3, Pages: 10
                Funding
                Funded by: the National Natural Science Foundation of China
                Award ID: No.81201092
                Award Recipient :
                Funded by: the Beijing Health System High Level Health Technical Personnel Training Plan
                Award ID: No. 2013-3-068
                Award Recipient :
                This article is supported by a grant from the National Natural Science Foundation of China (No.81201092) ( http://isisn.nsfc.gov.cn/egrantindex/funcindex/prjsearch-list) and the Beijing Health System High Level Health Technical Personnel Training Plan (No. 2013-3-068) ( http://www.bjwsrc.org/hhrnew/index.php?a=show&c=index&catid=30&id=1094&m=content). Both of the roles of the two funders were in data collection and analysis.
                Categories
                Research Article
                Research and Analysis Methods
                Imaging Techniques
                Neuroimaging
                Computed Axial Tomography
                Biology and Life Sciences
                Neuroscience
                Neuroimaging
                Computed Axial Tomography
                Medicine and Health Sciences
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