title: Characterization of human renal stones with MDCT: advantage of dual energy and limitations due to respiratory motion.
abstract: OBJECTIVE
  Our aim was to determine, using CT attenuation values, the chemical composition of 241 human renal stones placed in a jelly phantom and to analyze the influence of respiratory motion on the classification.
  
  
  METHODS
  The stones were placed in a jelly simulating the X-ray attenuation of the kidneys. A dynamic platform was used to apply to the phantom free-breathing motion (sinusoidal motion in z-axis) and motion due to lack of maintenance of a breath-hold (5 mm x s(-1) in z-axis). Determination of the chemical composition was performed with mean CT attenuation values obtained at 80 and 120 kV and with dual-energy CT attenuation values.
  
  
  RESULTS
  Two hundred forty-one human urinary stones were classified into six groups: uric acid, cystine, struvite, weddellite (calcium oxalate dihydrate), whewellite (calcium oxalate monohydrate), and brushite. With no motion, the use of dual energy enabled differentiation of all of the types of stones with statistically significant differences. Uric acid (-20 +/- 22 H), cystine (106 +/- 19 H), struvite (271 +/- 16 H), weddellite (323 +/- 5 H), brushite (415 +/- 30 H), and whewellite (510 +/- 17 H) were identified as distinct groups. Motion-induced mean CT attenuation values were significantly different from those obtained with no motion. With motion, dual-energy CT attenuation values did not allow differentiation of all stone types.
  
  
  CONCLUSIONS
  Dual-energy CT attenuation values can be used to predict the chemical composition of stones in vitro. However, when slight motion is applied to renal stones during image acquisition, the values become significantly different from those obtained with no motion. Consequently, confusion arises in differentiating stone types. A perfect breath-hold has to be performed for in vivo use of attenuation value to discern stone type.
authors.affiliation: Interventional and Diagnostic Adaptative Imaging, INSERM ERI 13, Nancy University, Centre Hospitalier Universitaire Nancy (TD4), Rue du Morvan, 54511 Vandoeuvre-les-Nancy Cedex, France. r.grosjean@chu-nancy.fr
authors.forename: Romain
authors.initials: R
authors.lastname: Grosjean
authors.forename: Benoît
authors.initials: B
authors.lastname: Sauer
authors.forename: Rui Matias
authors.initials: RM
authors.lastname: Guerra
authors.forename: Michel
authors.initials: M
authors.lastname: Daudon
authors.forename: Alain
authors.initials: A
authors.lastname: Blum
authors.forename: Jacques
authors.initials: J
authors.lastname: Felblinger
authors.forename: Jacques
authors.initials: J
authors.lastname: Hubert
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007669:Kidney Calculi / Q000737:chemistry* / Q000000981:diagnostic imaging*; D008954:Models, Biological; D009038:Motion; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D015656:Respiratory Mechanics; D036542:Tomography, Spiral Computed / Q000379:methods*