Literature DB >> 29076347

Assessment of noise reduction potential and image quality improvement of a new generation adaptive statistical iterative reconstruction (ASIR-V) in chest CT.

Hui Tang1, Nan Yu2, Yongjun Jia2, Yong Yu2, Haifeng Duan2, Dong Han2, Guangming Ma2, Chenglong Ren2, Taiping He1,2.   

Abstract

OBJECTIVE: To evaluate the image quality improvement and noise reduction in routine dose, non-enhanced chest CT imaging by using a new generation adaptive statistical iterative reconstruction (ASIR-V) in comparison with ASIR algorithm.
METHODS: 30 patients who underwent routine dose, non-enhanced chest CT using GE Discovery CT750HU (GE Healthcare, Waukesha, WI) were included. The scan parameters included tube voltage of 120 kVp, automatic tube current modulation to obtain a noise index of 14HU, rotation speed of 0.6 s, pitch of 1.375:1 and slice thickness of 5 mm. After scanning, all scans were reconstructed with the recommended level of 40%ASIR for comparison purpose and different percentages of ASIR-V from 10% to 100% in a 10% increment. The CT attenuation values and SD of the subcutaneous fat, back muscle and descending aorta were measured at the level of tracheal carina of all reconstructed images. The signal-to-noise ratio (SNR) was calculated with SD representing image noise. The subjective image quality was independently evaluated by two experienced radiologists.
RESULTS: For all ASIR-V images, the objective image noise (SD) of fat, muscle and aorta decreased and SNR increased along with increasing ASIR-V percentage. The SD of 30% ASIR-V to 100% ASIR-V was significantly lower than that of 40% ASIR (p < 0.05). In terms of subjective image evaluation, all ASIR-V reconstructions had good diagnostic acceptability. However, the 50% ASIR-V to 70% ASIR-V series showed significantly superior visibility of small structures when compared with the 40% ASIR and ASIR-V of other percentages (p < 0.05), and 60% ASIR-V was the best series of all ASIR-V images, with a highest subjective image quality. The image sharpness was significantly decreased in images reconstructed by 80% ASIR-V and higher.
CONCLUSION: In routine dose, non-enhanced chest CT, ASIR-V shows greater potential in reducing image noise and artefacts and maintaining image sharpness when compared to the recommended level of 40%ASIR algorithm. Combining both the objective and subjective evaluation of images, non-enhanced chest CT images reconstructed with 60% ASIR-V have the highest image quality. Advances in knowledge: This is the first clinical study to evaluate the clinical value of ASIR-V in the same patients using the same CT scanner in the non-enhanced chest CT scans. It suggests that ASIR-V provides the better image quality and higher diagnostic confidence in comparison with ASIR algorithm.

Entities:  

Keywords:  Adaptive statistical iterative reconstruction; Computed tomography; Image noise; Image quality

Mesh:

Year:  2017        PMID: 29076347      PMCID: PMC5966217          DOI: 10.1259/bjr.20170521

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  21 in total

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2.  Initial phantom study comparing image quality in computed tomography using adaptive statistical iterative reconstruction and new adaptive statistical iterative reconstruction v.

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3.  Reducing radiation dose in the diagnosis of pulmonary embolism using adaptive statistical iterative reconstruction and lower tube potential in computed tomography.

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4.  The Detection of Focal Liver Lesions Using Abdominal CT: A Comparison of Image Quality Between Adaptive Statistical Iterative Reconstruction V and Adaptive Statistical Iterative Reconstruction.

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5.  Cranial CT with adaptive statistical iterative reconstruction: improved image quality with concomitant radiation dose reduction.

Authors:  O Rapalino; Shervin Kamalian; Shahmir Kamalian; S Payabvash; L C S Souza; D Zhang; J Mukta; D V Sahani; M H Lev; S R Pomerantz
Journal:  AJNR Am J Neuroradiol       Date:  2011-12-29       Impact factor: 3.825

6.  Reducing abdominal CT radiation dose with the adaptive statistical iterative reconstruction technique in children: a feasibility study.

Authors:  Gregory A Vorona; Rafael C Ceschin; Barbara L Clayton; Tom Sutcavage; Sameh S Tadros; Ashok Panigrahy
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7.  Adaptive Statistical Iterative Reconstruction-V: Impact on Image Quality in Ultralow-Dose Coronary Computed Tomography Angiography.

Authors:  Dominik C Benz; Christoph Gräni; Fran Mikulicic; Jan Vontobel; Tobias A Fuchs; Mathias Possner; Olivier F Clerc; Julia Stehli; Oliver Gaemperli; Aju P Pazhenkottil; Ronny R Buechel; Philipp A Kaufmann
Journal:  J Comput Assist Tomogr       Date:  2016 Nov/Dec       Impact factor: 1.826

8.  Quantitative analysis of the effect of iterative reconstruction using a phantom: determining the appropriate blending percentage.

Authors:  Hyun Gi Kim; Yong Eun Chung; Young Han Lee; Jin Young Choi; Mi Suk Park; Myeong Jin Kim; Ki Whang Kim
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9.  Adaptive statistical iterative reconstruction improves image quality without affecting perfusion CT quantitation in primary colorectal cancer.

Authors:  D Prezzi; V Goh; S Virdi; S Mallett; C Grierson; D J Breen
Journal:  Eur J Radiol Open       Date:  2017-06-01

10.  Patient radiation biological risk in computed tomography angiography procedure.

Authors:  M Alkhorayef; E Babikir; A Alrushoud; H Al-Mohammed; A Sulieman
Journal:  Saudi J Biol Sci       Date:  2016-01-12       Impact factor: 4.219

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  11 in total

1.  Full model-based iterative reconstruction (MBIR) in abdominal CT increases objective image quality, but decreases subjective acceptance.

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Journal:  Eur Radiol       Date:  2019-01-30       Impact factor: 5.315

2.  Low-dose CT angiography using ASiR-V for potential living renal donors: a prospective analysis of image quality and diagnostic accuracy.

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3.  The influence of a deep learning image reconstruction algorithm on the image quality and auto-analysis of pulmonary nodules at ultra-low dose chest CT: a phantom study.

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4.  Clinical value of a new generation adaptive statistical iterative reconstruction (ASIR-V) in the diagnosis of pulmonary nodule in low-dose chest CT.

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Journal:  Br J Radiol       Date:  2019-09-06       Impact factor: 3.039

5.  Impact of preset and postset adaptive statistical iterative reconstruction-V on image quality in nonenhanced abdominal-pelvic CT on wide-detector revolution CT.

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Journal:  Quant Imaging Med Surg       Date:  2021-01

6.  Effect of adaptive statistical iterative reconstruction-V (ASiR-V) levels on ultra-low-dose CT radiomics quantification in pulmonary nodules.

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7.  Task-Based Model Observer Assessment of A Partial Model-Based Iterative Reconstruction Algorithm in Thoracic Oncologic Multidetector CT.

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Journal:  Sci Rep       Date:  2018-12-07       Impact factor: 4.379

8.  Detection of pulmonary nodules: a clinical study protocol to compare ultra-low dose chest CT and standard low-dose CT using ASIR-V.

Authors:  Marie Ludwig; Emilie Chipon; Julien Cohen; Emilie Reymond; Maud Medici; Anthony Cole; Alexandre Moreau Gaudry; Gilbert Ferretti
Journal:  BMJ Open       Date:  2019-08-15       Impact factor: 2.692

9.  Image Quality and Radiation Dose in CT Venography Using Model-Based Iterative Reconstruction at 80 kVp versus Adaptive Statistical Iterative Reconstruction-V at 70 kVp.

Authors:  Chankue Park; Ki Seok Choo; Jin Hyeok Kim; Kyung Jin Nam; Ji Won Lee; Jin You Kim
Journal:  Korean J Radiol       Date:  2019-07       Impact factor: 3.500

10.  Image quality and clinical usefulness of automatic tube current modulation technology in female chest computed tomography screening.

Authors:  Cheng Li; Lin Qi; Yusheng Zhang; Feng Gao; Xiu Jin; Lukai Zhang; Huan Tang; Ming Li
Journal:  Medicine (Baltimore)       Date:  2020-08-14       Impact factor: 1.817

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