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In vivo identification of uric acid stones with dual-energy CT: diagnostic performance evaluation in patients


Stolzmann, P; Kozomara, M; Chuck, N; Müntener, M; Leschka, S; Scheffel, H; Alkadhi, H (2010). In vivo identification of uric acid stones with dual-energy CT: diagnostic performance evaluation in patients. Abdominal Imaging, 35(5):629-635.

Abstract

BACKGROUND: To prospectively investigate the in vivo diagnostic performance of dual-energy (DE) computed tomography (CT) for the differentiation between uric acid (UA)-containing and non-UA-containing urinary stones. METHODS: DE CT scans were performed in 180 patients with suspected urinary stone disease using a dual-source CT scanner in the DE mode (tube voltages 80 and 140 kV). Urinary stones were classified as UA-containing or non-UA-containing based on CT number measurements and DE software results. Sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV) for the detection of UA-containing urinary stones were calculated using the crystallographic stone analysis as the reference standard. RESULTS: DE CT detected 110/180 patients (61%) with urinary stone disease. In 53 patients, stones were sampled. Forty-four out of 53 stones (83%) were non-UA-containing; and nine stones (17%) were UA-containing. The software automatically mapped 52/53 (98%) stones. One non-UA-containing stone (UA, 2 mm) was missed; one UA-containing stone (3 mm) was misclassified by software analysis. The sensitivity, specificity, PPV, and NPV for the detection of UA-containing stones was 89% (8/9, 95% CI: 52-100%), 98% (43/44, 95% CI: 88-100%), 89% (8/9, 95% CI: 52-100%), and 98% (43/44, 95% CI: 88-100%). CONCLUSION: Our results indicate that DE dual-source CT permits for the accurate in vivo differentiation between UA-containing and non-UA-containing urinary stones.

Abstract

BACKGROUND: To prospectively investigate the in vivo diagnostic performance of dual-energy (DE) computed tomography (CT) for the differentiation between uric acid (UA)-containing and non-UA-containing urinary stones. METHODS: DE CT scans were performed in 180 patients with suspected urinary stone disease using a dual-source CT scanner in the DE mode (tube voltages 80 and 140 kV). Urinary stones were classified as UA-containing or non-UA-containing based on CT number measurements and DE software results. Sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV) for the detection of UA-containing urinary stones were calculated using the crystallographic stone analysis as the reference standard. RESULTS: DE CT detected 110/180 patients (61%) with urinary stone disease. In 53 patients, stones were sampled. Forty-four out of 53 stones (83%) were non-UA-containing; and nine stones (17%) were UA-containing. The software automatically mapped 52/53 (98%) stones. One non-UA-containing stone (UA, 2 mm) was missed; one UA-containing stone (3 mm) was misclassified by software analysis. The sensitivity, specificity, PPV, and NPV for the detection of UA-containing stones was 89% (8/9, 95% CI: 52-100%), 98% (43/44, 95% CI: 88-100%), 89% (8/9, 95% CI: 52-100%), and 98% (43/44, 95% CI: 88-100%). CONCLUSION: Our results indicate that DE dual-source CT permits for the accurate in vivo differentiation between UA-containing and non-UA-containing urinary stones.

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Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Urological Clinic
04 Faculty of Medicine > University Hospital Zurich > Clinic for Diagnostic and Interventional Radiology
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Health Sciences > Radiological and Ultrasound Technology
Health Sciences > Radiology, Nuclear Medicine and Imaging
Health Sciences > Gastroenterology
Health Sciences > Urology
Language:English
Date:2010
Deposited On:25 Sep 2009 10:19
Last Modified:03 Nov 2023 03:00
Publisher:Springer
ISSN:0942-8925
OA Status:Green
Publisher DOI:https://doi.org/10.1007/s00261-009-9569-9
Related URLs:https://www.zora.uzh.ch/25536/
PubMed ID:19727931