title: Simulation of liver lesions for pediatric CT.
abstract: OBJECTIVE
  To develop and validate a technique based on characteristics of real lesions for simulating realistic small liver lesions on pediatric computed tomographic (CT) images.
  
  
  METHODS
  The institutional review board provided exempt status for this study, determined that it was not subject to HIPAA compliance, and did not require informed consent. Patient identification information was removed from clinical images from contrast material-enhanced multi-detector row CT examinations performed in 10 children. Patients were infants or children up to 18 years old. Information about sex was not available. Children had one or more liver lesions of 2-6 mm in maximum transverse diameter. Images with more than one lesion were rendered multiple times, and each time, all but one of the lesions were digitally removed in sequence. This process provided images (n = 19) with a single real lesion. For consistency, the same image backgrounds (images with all real lesions removed) were used to create an identical number of images (n = 19), each with a single simulated lesion. Subsequently, three radiologists independently assessed images of real and simulated lesions that were presented in random order with a score on a continuous scale of 0 (definitely simulated) to 100 (definitely real). Mixed-model analysis of variance was used to test the null hypothesis that the difference in population mean scores between the two lesion types was zero.
  
  
  RESULTS
  The observer study did not reveal a significant difference in the ability of any radiologist to discriminate between real and simulated lesions (P > .31). The differences in mean scores for discrimination between real and simulated lesions for the three observers were -6, 9, and -7, respectively. The estimated overall difference was -1.
  
  
  CONCLUSIONS
  Mathematic simulation of liver lesions is a feasible technique for creating realistic lesions for image quality or dose reduction studies in pediatric CT.
authors.affiliation: Duke Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Box 3302, Durham, NC 27710, USA.
authors.forename: Chee L
authors.initials: CL
authors.lastname: Hoe
authors.forename: Ehsan
authors.initials: E
authors.lastname: Samei
authors.forename: Donald P
authors.initials: DP
authors.lastname: Frush
authors.forename: David M
authors.initials: DM
authors.lastname: Delong
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D006801:Humans; D007223:Infant; D008107:Liver Diseases / Q000000981:diagnostic imaging*; D019047:Phantoms, Imaging; D014057:Tomography, X-Ray Computed