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Diagnostic Efficiency of Split-Bolus Dual-Energy Computed Tomography for Patients With Suspected Urinary Stones

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Author(s)
Yu Jin YeoSee Hyung KimMi Jeong KimYoung Hwan KimSeung Hyun ChoEun Joo Lee
Keimyung Author(s)
Kim, See HyungKim, Mi JeongKim, Young Hwan
Department
Dept. of Radiology (영상의학)
Journal Title
Journal Of Computer Assisted Tomography
Issued Date
2015
Volume
39
Issue
1
Keyword
dual-energy CTsplit-bolus CT urographyurinary stone
Abstract
Objective: The objective of this study was to evaluate the efficiency of virtual noncontrast image (VNCI) generated from dual-energy split-bolus computed tomographic urography (DE-SBCTU) for urinary stones detection.



Methods: Three hundred fifty-six patients underwent true noncontrast image (TNCI) and DE-SBCTU. Two radiologists evaluated opacification scores of DE-SBCTU as well as iodine subtractions and image noise on VNCI. Diagnostic performance of the VNCI was evaluated using TNCI as a reference standard, according to diameter and image quality. The results were compared between patient groups with body mass index of less than 25 and 25 kg/m2 or greater.



Results: Agreements for opacification, iodine subtraction, and image noise between the radiologists were excellent, and there were no significant difference in the 2 patients groups. A total of 499 stones were detected on VNCI, with a sensitivity and diagnostic accuracy of 95.1% (468/492) and 92.9% (499/537). Mean (SD) diameter was significantly smaller on VNCI (3.6 [2.3] mm) than on TNCI (4.4 [2.0] mm) (P = 0.01). The stone diameter with false interpretation was less than 4 mm in 48 of 51 patients. The diameter and image quality on VNCI had no significant difference between the 2 patients groups.



Conclusions: Virtual noncontrast image displays high accuracy for detecting urinary stones, regardless of body mass index.
Keimyung Author(s)(Kor)
김시형
김미정
김영환
Publisher
School of Medicine
Citation
Yu Jin Yeo et al. (2015). Diagnostic Efficiency of Split-Bolus Dual-Energy Computed Tomography for Patients With Suspected Urinary Stones. Journal Of Computer Assisted Tomography, 39(1), 25–31. doi: 10.1097/RCT.0000000000000151
Type
Article
ISSN
0363-8715
Source
http://lps3.insights.ovid.com.proxy.dsmc.or.kr/pubmed?pmid=25247691
DOI
10.1097/RCT.0000000000000151
URI
https://kumel.medlib.dsmc.or.kr/handle/2015.oak/34008
Appears in Collections:
1. School of Medicine (의과대학) > Dept. of Radiology (영상의학)
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