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In Vivo Analysis of Urinary Stones With Dual-Energy Computed Tomography.

Abstract：

OBJECTIVE:Formation mechanisms and treatment of the urinary stones are different, depending on their chemical structure. Therefore, determining the stone type plays a key role in planning treatment and preventive measures. Computed tomography (CT), with the use of dual-energy technology in recent years, has made it possible to do in vivo analysis of urinary stones. In this study, we aimed to evaluate the diagnostic efficacy of dual-energy CT (DECT) and compare its results with in vitro analysis, which is accepted as a gold standard for analysis of urinary stones. MATERIALS AND METHODS:The DECT examinations were performed on 373 patients using 128-slice dual-source CT scanner. Analysis of attenuation ratios in the high and low kilovoltage peak values of the stone was performed at workstation, and stones were classified as hydroxyapatite, calcium oxalate, cystine, and uric acid. On follow-up, the stone was obtained in 35 patients as a result of surgery or passed spontaneously. The DECT analysis and in vitro analysis results were compared and statistically evaluated. RESULTS:In all patients, 136 hydroxyapatite, 160 calcium oxalate, 57 uric acid, and 20 cystine stones were detected with DECT. In vitro analyses of the stones were performed in 35 patients, and 8 hydroxyapatite, 18 calcium oxalate, 6 uric acid, and 3 cystine stones were revealed. When DECT analysis results were compared with in vitro analysis results, stone types were detected correctly in 32 (91.4%) patients and incorrectly in 3 (8.6%) patients. Especially all uric acid and cystine stones were correctly detected with DECT. CONCLUSIONS:With advanced postprocess analysis methods, DECT is able to analyze urinary stones. The DECT is found superior especially in detecting uric acid and cystine stones. Its success in detecting hydroxyapatite and calcium oxalate stones is also high. When in vivo analyses of the stones are performed with DECT, it will be possible to make a contribution to the personalization and optimization of the treatment.

journal_name

J Comput Assist Tomogr

journal_title

Journal of computer assisted tomography

authors

Erdogan H,Temizoz O,Koplay M,Ozturk B

doi

10.1097/RCT.0000000000000831

subject

Has Abstract

pub_date

2019-03-01 00:00:00

pages

214-219

issue

eissn

0363-8715

issn

1532-3145

journal_volume

pub_type

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In Vivo Analysis of Urinary Stones With Dual-Energy Computed Tomography.