Literature DB >> 27745816

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.

Sangyun Lee1, Heejin Kwon2, Jihan Cho1.   

Abstract

RATIONALE AND
OBJECTIVES: To investigate image quality characteristics of abdominal computed tomography (CT) scans reconstructed with adaptive statistical iterative reconstruction V (ASIR-V) vs currently using applied adaptive statistical iterative reconstruction (ASIR). MATERIALS AND
METHOD: This institutional review board-approved study included 35 consecutive patients who underwent CT of the abdomen. Among these 35 patients, 27 with focal liver lesions underwent abdomen CT with a 128-slice multidetector unit using the following parameters: fixed noise index of 30, 1.25 mm slice thickness, 120 kVp, and a gantry rotation time of 0.5 seconds. CT images were analyzed depending on the method of reconstruction: ASIR (30%, 50%, and 70%) vs ASIR-V (30%, 50%, and 70%). Three radiologists independently assessed randomized images in a blinded manner. Imaging sets were compared to focal lesion detection numbers, overall image quality, and objective noise with a paired sample t test. Interobserver agreement was assessed with the intraclass correlation coefficient.
RESULTS: The detection of small focal liver lesions (<10 mm) was significantly higher when ASIR-V was used when compared to ASIR (P <0.001). Subjective image noise, artifact, and objective image noise in liver were generally significantly better for ASIR-V compared to ASIR, especially in 50% ASIR-V. Image sharpness and diagnostic acceptability were significantly worse in 70% ASIR-V compared to various levels of ASIR.
CONCLUSION: Images analyzed using 50% ASIR-V were significantly better than three different series of ASIR or other ASIR-V conditions at providing diagnostically acceptable CT scans without compromising image quality and in the detection of focal liver lesions.
Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Computed tomography; diagnosis; image quality; iterative reconstruction

Mesh:

Year:  2016        PMID: 27745816     DOI: 10.1016/j.acra.2016.08.013

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  6 in total

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

Authors:  Hui Tang; Nan Yu; Yongjun Jia; Yong Yu; Haifeng Duan; Dong Han; Guangming Ma; Chenglong Ren; Taiping He
Journal:  Br J Radiol       Date:  2017-11-16       Impact factor: 3.039

2.  Detection of Colorectal Hepatic Metastases Is Superior at Standard Radiation Dose CT versus Reduced Dose CT.

Authors:  Corey T Jensen; Nicolaus A Wagner-Bartak; Lan N Vu; Xinming Liu; Bharat Raval; David Martinez; Wei Wei; Yuan Cheng; Ehsan Samei; Shiva Gupta
Journal:  Radiology       Date:  2018-11-27       Impact factor: 11.105

3.  A study of using a deep learning image reconstruction to improve the image quality of extremely low-dose contrast-enhanced abdominal CT for patients with hepatic lesions.

Authors:  Le Cao; Xiang Liu; Jianying Li; Tingting Qu; Lihong Chen; Yannan Cheng; Jieliang Hu; Jingtao Sun; Jianxin Guo
Journal:  Br J Radiol       Date:  2020-12-11       Impact factor: 3.039

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

Authors:  Zheng Zhu; Yanfeng Zhao; Xinming Zhao; Xiaoyi Wang; Weijun Yu; Mancang Hu; Xuan Zhang; Chunwu Zhou
Journal:  Quant Imaging Med Surg       Date:  2021-01

5.  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

6.  Measurement accuracy of lung nodule volumetry in a phantom study: Effect of axial-volume scan and iterative reconstruction algorithm.

Authors:  Han Na Lee; Jung Im Kim; So Youn Shin
Journal:  Medicine (Baltimore)       Date:  2020-06-05       Impact factor: 1.817

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.