ABSTRACT
Objective
To evaluate the detection and quantification of urinary stones using virtual unenhanced
images (VUE) at different phases and slice thickness in contrast-enhanced dual-energy
CT Urography (DECTU) in comparison with true unenhanced images (TUE).
Methods
One hundred and twelve urinary stone patients who required triphasic DECTU were analyzed.
Data were reconstructed as the followings: TUE images with 1.25 mm thickness (TUE
portal venous phase VUE images with 1.25 and 5-mm thickness (VUE(VP)_1.25 mm and VUE(VP)_5
mm) and excretory phase VUE images with 1.25 and 5-mm thickness (VUE(EP)_1.25mm and
VUE(EP)_5mm). The. The stones were divided into large (≥5 mm) and small stones. The
detection rate, size and CT value of stones were assessed by 2 radiologists and statistically
compared among the above groups.
Results
Two hundred and thirty urinary stones (163 large and 67 small stones) were detected
on TUE_1.25 mm images. For large stones, the detection rate on VUE(VP)_1.25 mm, VUE(VP)_5
mm, VUE(EP)_1.25 mm and VUE(EP)_5 mm was 100%, 96.9%, 85.9%, and 80.4%; while for
small stones, the rate was 77.6%, 37.3%, 46.3%, and 23.9%, respectively. VUE(VP) images
significantly improved the stone detection rate compared with VUE(EP) images at both
slice thicknesses. In general, VUE images identified stones with smaller sizes and
lower Hounsfield units, but thinner slice thickness images reduced the inaccuracy.
Inter-reader agreement of the stone detection revealed a k value range from 0.85 to
0.94 for TUE and VUE images.
Conclusion
Large stones (≥5 mm) can reliably be detected on thin section VUE(VP) images with
33% radiation dose reduction. However, for small stones TUE remains superior. Stone
size is underestimated on VUE images.
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Article info
Publication history
Published online: April 21, 2022
Accepted:
February 17,
2022
Received:
November 6,
2021
Footnotes
Conflict of Interest: None.
Funding Support: This work was supported by the Key R&D Program of Shaanxi Province Universities and Colleges [NO. 2020GXLH-Y-026]. 3D Printing Medical Research Funding Project of the First Affiliated Hospital of Xi'an Jiaotong University [NO. XJTU1AF-3D-2018-003] and Science Development Foundation of the First Affiliated Hospital of Xi'an Jiaotong University (2018MS-27). The funding sources had no role in the whole study.
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