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.
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.
Authors: Christoph Karlo; Arno Lauber; Robert Paul Götti; Stephan Baumüller; Paul Stolzmann; Hans Scheffel; Lotus Desbiolles; Bernhard Schmidt; Borut Marincek; Hatem Alkadhi; Sebastian Leschka Journal: Eur Radiol Date: 2010-08-15 Impact factor: 5.315
Authors: Gorka Bastarrika; Jordi Broncano; María Arraiza; Pedro M Azcárate; Isabel Simon-Yarza; Beltrán G Levy Praschker; Jesús C Pueyo; José L Zubieta; Gregorio Rabago Journal: Eur Radiol Date: 2011-04-12 Impact factor: 5.315
Authors: W Zbijewski; G J Gang; J Xu; A S Wang; J W Stayman; K Taguchi; J A Carrino; J H Siewerdsen Journal: Med Phys Date: 2014-02 Impact factor: 4.071