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|Title:||Characterization of renal stone composition by using fast kilovoltage switching dual-energy computed tomography compared to laboratory stone analysis: a pilot study|
Faculty of Medicine, Siriraj Hospital, Mahidol University
|Citation:||Abdominal Radiology. Vol.44, No.3 (2019), 1027-1032|
|Abstract:||© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Purpose: To prospectively examine the diagnostic performance of fast kilovoltage switching dual-energy computed tomography (DECT) in characterization of in vivo renal stone composition compared with postoperative stone analysis. Methods: Consecutive consenting patients scheduled for endoscopic kidney stone surgery in a tertiary referral hospital from June 2015 to January 2016 were enrolled. Patients were preoperatively scanned with single-source, fast kilovoltage switching DECT. Stone compositions were determined regarding the effective atomic number measurements. Results of the stone compositions from DECT were compared to postoperative infrared spectroscopy stone analysis as the standard reference. Results: For the 39 patients enrolled in the study, DECT was able to detect uric acid stone with sensitivity of 88.9% and specificity of 100%. There was 100% positive predictive value, 96.8% negative predictive value, and 97.4% accuracy. For non-contrast CT scan, sensitivity was 88.9%, specificity was 96.7%, positive predictive value was 88.9%, negative predictive value was 96.7%, and accuracy was 94.8%. Of the 39 samples examined, 21 (54%) were single composition, whereas 18 (46%) were combined. Single composition stones were correctly characterized by DECT in 100% (8/8) for uric acid. Whereas the result of uric acid stone containing stone discrimination in mixed composition was not so good with Z eff alone, iodine imaging can compensated this fault. Conclusions: DECT provides excellent accuracy in characterizing uric acid stone compositions. With the addition of iodine image, all of uric acid-containing stones can be determined by the DECT.|
|Appears in Collections:||Scopus 2019|
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