PURPOSE: This study aimed to characterize the urinary tract stones in phantom and patients using single-source dual-energy computed tomography.
MATERIALS AND METHODS: Twenty stones of pure crystalline composition (uric acid [UA], struvite, cystine, and calcium oxalate monohydrate) were assessed in a phantom and 11 patients (age 39-67 years) with urinary tract stones were evaluated. An initial low-dose unenhanced CT (tube potential, 120 kilovolts [peak]; milliampere range, 150-450; noise index, 26; section thickness, 5 mm) followed by a targeted dual-energy computed tomography acquisition on a single-source dual-energy computed tomography (Discovery CT 750 HDCT, GE) was performed. Uric acid and non-UA stones were defined using a 2-material decomposition (material density-iodine/water) algorithm. The stone effective atomic number (Zeff) was used to subclassify non-UA stones. The stone attenuation (Hounsfield unit) was also studied to determine its performance in predicting the composition. Ex vivo chemical analysis of the stone served as a criterion standard.
RESULTS: Of the 59 verified stones (phantom, 20; patients, 39; mean size, 6 mm), there were 16 UA and 43 non-UA type. The material density images were 100% sensitive and accurate in detecting UA and non-UA stones. The Zeff accurately stratified struvite, cystine, and calcium (calcium oxalate monohydrate) stones in the phantom. In patients, Zeff identified 83% of calcium stones (n = 24), and in stones of mixed type, it resembled dominant composition. The Hounsfield unit measurements alone were 71% sensitive and 69% accurate in detecting the UA stones.
CONCLUSIONS: Single-source dual-energy computed tomography can accurately predict UA and non-UA stone composition in vitro and in vivo. Substratification of non-UA stones of pure composition can be made in vitro and in vivo. In stones of mixed composition, the Zeff values reflect the dominant composition.
Written by:
Kulkarni NM, Eisner BH, Pinho DF, Joshi MC, Kambadakone AR, Sahani DV. Are you the author?
Abdominal Imaging and Intervention, Harvard Medical School, Massachusetts General Hospital, Boston, MA 02114, USA.
Reference: J Comput Assist Tomogr. 2013 Jan;37(1):37-45.
doi: 10.1097/RCT.0b013e3182720f66
PubMed Abstract
PMID: 23321831
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