Literature DB >> 25833747

CT for evaluation of urolithiasis: image quality of ultralow-dose (Sub mSv) CT with knowledge-based iterative reconstruction and diagnostic performance of low-dose CT with statistical iterative reconstruction.

Joonho Hur1, Sung Bin Park2, Jong Beum Lee1, Hyun Jeong Park1, In Ho Chang3, Jong Kyou Kwon3,4, Yang Soo Kim1.   

Abstract

PURPOSE: To compare radiation dose and image quality in regular, low, and ultralow-dose CT protocols, and to evaluate diagnostic performance of low-dose CT for urolithiasis.
MATERIALS AND METHODS: Sixty-five patients with suspected urolithiasis underwent three different scans under the regular, low, and ultralow-dose protocols. The regular dose scans were reconstructed using filtered back projection and the low-dose scans were reconstructed using a statistical iterative reconstruction. The ultralow-dose scans were reconstructed using both techniques in addition to a knowledge-based IR. Effective radiation doses were compared. Objective image noise was assessed by measuring standard deviation of HU and subjective image assessment was performed with a 3- or 5-point scale. Diagnostic performance of the low-dose image was evaluated, using the regular dose image as a standard reference and the interobserver agreement between two reviewers with different levels of experience was calculated.
RESULTS: The effective radiation dose was significantly different in each protocol (p < 0.001) and estimated dose reduction of the low-dose and ultralow-dose protocols was 76.4% and 89.8%, respectively. The knowledge-based iterative reconstruction algorithm showed poorer subjective image quality than the regular and low-dose protocols, but it also had the least objective image noise. Overall, the low-dose image set showed a greater than 84% concordance rate and 100% in ureter stones larger than 3 mm. Interobserver agreement was substantial (kappa value = 0.61).
CONCLUSIONS: The knowledge-based IR can provide a better quality image while reducing radiation exposure under the same protocol. Furthermore, the diagnostic performance of the low-dose CT protocol is comparable to the regular dose scan.

Entities:  

Keywords:  Filtered back projection; Knowledge-based iterative reconstruction; Low-dose computed tomography; Model-based iterative reconstruction; Radiation dosage; Statistical iterative reconstruction; Urolithiasis

Mesh:

Year:  2015        PMID: 25833747     DOI: 10.1007/s00261-015-0411-2

Source DB:  PubMed          Journal:  Abdom Imaging        ISSN: 0942-8925


  4 in total

1.  Using a three-dimensional computer assisted stone volume estimates to evaluate extracorporeal shockwave lithotripsy treatment of kidney stones.

Authors:  Lene Hyldgaard Bigum; Peter Sommer Ulriksen; Omar Salah Omar
Journal:  Urolithiasis       Date:  2016-02-25       Impact factor: 3.436

2.  Determination of optimal imaging settings for urolithiasis CT using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR): a physical human phantom study.

Authors:  Se Y Choi; Seung H Ahn; Jae D Choi; Jung H Kim; Byoung-Il Lee; Jeong-In Kim; Sung B Park
Journal:  Br J Radiol       Date:  2015-11-18       Impact factor: 3.039

3.  Low-dose CT urography using deep learning image reconstruction: a prospective study for comparison with conventional CT urography.

Authors:  Yannan Cheng; Yangyang Han; Jianying Li; Ganglian Fan; Le Cao; Junjun Li; Xiaoqian Jia; Jian Yang; Jianxin Guo
Journal:  Br J Radiol       Date:  2021-02-24       Impact factor: 3.039

4.  A prospective study on the use of ultralow-dose computed tomography with iterative reconstruction for the follow-up of patients liver and renal abscess.

Authors:  Nieun Seo; Mi-Suk Park; Jun Yong Choi; Joon-Sup Yeom; Myeong-Jin Kim; Yong Eun Chung; Nam Su Ku
Journal:  PLoS One       Date:  2021-02-12       Impact factor: 3.240

  4 in total

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