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. 2014 Aug;28(8):1016-21.
doi: 10.1089/end.2014.0151. Epub 2014 Jun 3.

The evolution of CT diagnosed papillae tip microcalcifications: can we predict the development of stones?

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Free article

The evolution of CT diagnosed papillae tip microcalcifications: can we predict the development of stones?

Alexandru Ciudin et al. J Endourol. 2014 Aug.
Free article

Abstract

Objectives: To determine the incidence of computed tomography (CT) identifiable Randall plaques in a CT explored population; to determine the clinical relevance of this radiological finding by a 7-year follow-up; to determine a cut point to identify a population with high risk of developing calcium stone disease (SD).

Materials and methods: Retrospective study of all patients explored by abdominal CT in our center between January and March 2005.

Inclusion criteria: age 30-60 years and no SD. Papillae attenuation was measured on nonenhanced CT in Hounsfield units (HU) and the mean of all papillae was calculated. Patients were re-evaluated after 7 years to identify calcium stone formers. Anamnesis and already available CT, ultrasound, kidney, ureter, and bladder radiograph (KUB) or intravenous urography (IVU) images performed as part of their follow-up were used. In patients with no follow-up, ultrasound and KUB were to be performed. Pearson correlation, Student t-test, and the receiver operator curve were used for statistical analysis.

Results: A total of 362 patients fulfilled the inclusion criteria and were analyzed; 12 developed calcium SD after 7 years. A significant difference was encountered between the papillae attenuation of stone formers (SF) versus non-SF (47.2HU vs. 35.5HU, p=0.001). There was good correlation between papillae attenuation and the possibility of developing SD (R=0.87). An optimal cut point of 43HU with a sensitivity of 81% and specificity of 97%, area under the curve 0.91, separated SF and non-SF.

Conclusion: Patients with high papillae density have a higher risk of developing SD. A cut point of 43HU could accurately be used to identify a high-risk population.

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