Literature DB >> 28258740

Uric acid versus non-uric acid renal stones: in vivo differentiation with spectral CT.

F Lombardo1, M Bonatti2, G A Zamboni3, G Avesani2, N Oberhofer4, M Bonelli4, A Pycha5, R Pozzi Mucelli3, G Bonatti2.   

Abstract

AIM: To differentiate uric acid from non-uric acid renal stones based on their spectral attenuation values.
MATERIALS AND METHODS: The present study was approved by the institutional review board and the need for informed consent was waived. Thirty-three consecutive patients (21 men, 12 women; mean age 55 years) with symptomatic urolithiasis underwent dual-energy computed tomography (DECT) using a second-generation dual-source CT system. Stone composition was assessed by means of chemical analysis after extraction or spontaneous expulsion. The composition of one stone was considered to represent all remaining stones in patients presenting with more than one stone. Image-domain virtual monoenergetic images were generated from the dual-energy datasets. One radiologist evaluated stone attenuation values from 40 to 190 keV; attenuation curves were created and 40/190 keV attenuation ratios calculated. Qualitative evaluation of the spectral attenuation curves was also performed. Imaging findings were compared with laboratory results.
RESULTS: Sixty-two stones were considered in 33 patients (mean diameter 6.5 mm). Fifteen of the 62 stones were mainly composed of uric acid and 47/62 of cysteine or calcium oxalates/phosphates. Forty to 190 keV attenuation ratios were significantly lower for uric acid stones (mean 0.87±0.3) than for non-uric acid stones (mean 3.80±0.6; p<0.0001). Accuracy was 100% with a cut-off value of 1.76. Qualitative analysis of spectral attenuation curves showed unique shapes for uric acid and non-uric acid stones.
CONCLUSIONS: Spectral CT quantitatively and qualitatively differentiates uric acid from non-uric acid stones.
Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

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Year:  2017        PMID: 28258740     DOI: 10.1016/j.crad.2017.01.018

Source DB:  PubMed          Journal:  Clin Radiol        ISSN: 0009-9260            Impact factor:   2.350


  5 in total

1.  Prediction of the Uric Acid Component in Nephrolithiasis Using Simple Clinical Information about Metabolic Disorder and Obesity: A Machine Learning-Based Model.

Authors:  Hao-Wei Chen; Yu-Chen Chen; Jung-Ting Lee; Frances M Yang; Chung-Yao Kao; Yii-Her Chou; Ting-Yin Chu; Yung-Shun Juan; Wen-Jeng Wu
Journal:  Nutrients       Date:  2022-04-27       Impact factor: 6.706

2.  Diagnostic accuracy of third-generation dual-source dual-energy CT: a prospective trial and protocol for clinical implementation.

Authors:  Tim Nestler; Kai Nestler; Andreas Neisius; Hendrik Isbarn; Christopher Netsch; Stephan Waldeck; Hans U Schmelz; Christian Ruf
Journal:  World J Urol       Date:  2018-08-03       Impact factor: 4.226

Review 3.  [Update of the 2Sk guidelines on the diagnostics, treatment and metaphylaxis of urolithiasis (AWMF register number 043-025) : What is new?]

Authors:  C Seitz; T Bach; M Bader; W Berg; T Knoll; A Neisius; C Netsch; M Nothacker; S Schmidt; M Schönthaler; R Siener; R Stein; M Straub; W Strohmaier; C Türk; B Volkmer
Journal:  Urologe A       Date:  2019-11       Impact factor: 0.639

4.  Evaluation of split-filter dual-energy CT for characterization of urinary stones.

Authors:  Elisabeth Appel; Christoph Thomas; Andrea Steuwe; Benedikt M Schaarschmidt; Olga R Brook; Joel Aissa; Jörg Hennenlotter; Gerald Antoch; Johannes Boos
Journal:  Br J Radiol       Date:  2021-10-07       Impact factor: 3.039

5.  Disk injury in patients with vertebral fractures-a prospective diagnostic accuracy study using dual-energy computed tomography.

Authors:  Matthias Pumberger; Michael Fuchs; Nils Engelhard; Kay Geert Hermann; Michael Putzier; Marcus R Makowski; Bernd Hamm; Torsten Diekhoff
Journal:  Eur Radiol       Date:  2019-01-16       Impact factor: 5.315

  5 in total

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