In Vivo Discrimination of Nonuric Acid Kidney Stone Types (original) (raw)

Abstract

PURPOSE To evaluate the use of an advanced dual energy processing algorithm to improve the ability of dual energy CT (DECT) protocol to differentiate non-uric acid (NUA) renal stone types in a patient cohort. METHOD AND MATERIALS We evaluated data from 81 patients that received a non-enhanced DECT scan prior to surgical removal of kidney stones and subsequent stone composition analysis by infrared spectroscopy (IR). DECT scans were performed using a dual-source CT scanner (Somatom Definition Flash, Siemens Healthcare), 100 kV and 140 kV with tin filtration, and 240 and 185 mAs quality reference mAs values for the low and high energy tubes, respectively. Images were reconstructed with medium smooth kernel (D30) and 1 mm thickness. Only relatively pure kidney stones (≥90% of a single composition, as determined by IR) were included in this analysis (n=44 stones). A Matlab-based processing algorithm was developed to semiautomatically segment kidney stones and predict stone composition u...

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