Literature DB >> 10479003

Prediction of stone composition from plain radiographs: a prospective study.

S Ramakumar1, D E Patterson, A J LeRoy, C E Bender, S B Erickson, D M Wilson, J W Segura.   

Abstract

BACKGROUND AND OBJECTIVES: Stone composition, as reflected in radiographic appearance, is important to help choose between SWL and percutaneous/endoscopic procedures. Predicting a stone's composition accurately from a plain radiograph would be a useful tool in clinical decision-making. However, the ability of physicians to predict composition has not been adequately assessed. A prospective study was designed to quantify the accuracy of a panel of physicians who routinely deal with stones in classifying stone composition solely from radiographs.
MATERIALS AND METHODS: A panel of six members was created to review 100 plain-film radiographs from patients with renal stones of known composition. The panel consisted of two urologists, two radiologists, and two nephrologists, all of whom have expertise in stone disease. If the composition guessed was at least 40% of the total stone composition, the response was deemed correct.
RESULTS: Overall, there was an average 39% correct response score among the six panelists. When the stones were divided by size, 35% were <1 cm, and 65% were larger. The accuracy of chemical composition determination did not improve with greater stone size, nor was there a difference in accuracy for pure and mixed stones. The most frequently misclassified stone was calcium phosphate, with only 14% being correctly diagnosed.
CONCLUSIONS: With a random sampling of plain radiographs, a panel of physicians specializing in stone disease correctly diagnosed the composition of renal calculi less than half of the time without being given clinical information.

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Year:  1999        PMID: 10479003     DOI: 10.1089/end.1999.13.397

Source DB:  PubMed          Journal:  J Endourol        ISSN: 0892-7790            Impact factor:   2.942


  6 in total

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Authors:  Adnan Gücük; Uğur Uyetürk
Journal:  World J Nephrol       Date:  2014-11-06

2.  Prediction of fragmentation of kidney stones: A statistical approach from NCCT images.

Authors:  Krishna Moorthy; Meenakshy Krishnan
Journal:  Can Urol Assoc J       Date:  2016-07-12       Impact factor: 1.862

3.  Determination of the chemical composition of urinary calculi by noncontrast spiral computerized tomography.

Authors:  Khaled Z Sheir; Osama Mansour; Khaled Madbouly; Emad Elsobky; Mohamed Abdel-Khalek
Journal:  Urol Res       Date:  2005-01-06

4.  Are Hounsfield densities of ureteral stones a predictive factor for effectiveness of extracorporeal shock wave lithotripsy?

Authors:  Basri Cakiroglu; S Erkan Eyyupoglu; Tuncay Tas; Mb Can Balci; Ismet Hazar; S Hilmi Aksoy; Orhun Sinanoglu
Journal:  Int J Clin Exp Med       Date:  2014-05-15

Review 5.  Advances in CT imaging for urolithiasis.

Authors:  Yasir Andrabi; Manuel Patino; Chandan J Das; Brian Eisner; Dushyant V Sahani; Avinash Kambadakone
Journal:  Indian J Urol       Date:  2015 Jul-Sep

6.  The success of extracorporeal shock-wave lithotripsy based on the stone-attenuation value from non-contrast computed tomography.

Authors:  Amr M Massoud; Ahmed M Abdelbary; Ahmad A Al-Dessoukey; Ayman S Moussa; Ahmed S Zayed; Osama Mahmmoud
Journal:  Arab J Urol       Date:  2014-02-16
  6 in total

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