title: CT imaging of congenital lung lesions: effect of iterative reconstruction on diagnostic performance and radiation dose.
abstract: BACKGROUND
  Different iterative reconstruction techniques are available for use in pediatric computed tomography (CT), but these techniques have not been systematically evaluated in infants.
  
  
  OBJECTIVE
  To determine the effect of iterative reconstruction on diagnostic performance, image quality and radiation dose in infants undergoing CT evaluation for congenital lung lesions.
  
  
  METHODS
  A retrospective review of contrast-enhanced chest CT in infants (<1 year) with congenital lung lesions was performed. CT examinations were reviewed to document the type of lung lesion, vascular anatomy, image noise measurements and image reconstruction method. CTDIvol was used to calculate size-specific dose estimates (SSDE). CT findings were correlated with intraoperative and histopathological findings. Analysis of variance and the Student's t-test were used to compare image noise measurements and radiation dose estimates between groups.
  
  
  RESULTS
  Fifteen CT examinations used filtered back projection (FBP; mean age: 84 days), 15 used adaptive statistical iterative reconstruction (ASiR; mean age: 93 days), and 11 used model-based iterative reconstruction (MBIR; mean age: 98 days). Compared to operative findings, 13/15 (87%), 14/15 (93%) and 11/11 (100%) lesions were correctly characterized using FBP, ASiR and MBIR, respectively. Arterial anatomy was correctly identified in 12/15 (80%) using FBP, 13/15 (87%) using ASiR and 11/11 (100%) using MBIR. Image noise was less for MBIR vs. ASiR (P < 0.0001). Mean SSDE was different among groups (P = 0.003; FBP = 7.35 mGy, ASiR = 1.89 mGy, MBIR = 1.49 mGy).
  
  
  CONCLUSIONS
  Congenital lung lesions can be adequately characterized in infants using iterative CT reconstruction techniques while maintaining image quality and lowering radiation dose.
authors: Section of Pediatric Radiology, Department of Radiology, C.S. Mott Children's Hospital, University of Michigan Health System, 1540 E. Hospital Drive, SPC 4252, Ann Arbor, MI, 48109-4252, USA.
authors: Jay E
authors: JE
authors: Haggerty
authors: Ethan A
authors: EA
authors: Smith
authors: Shaun M
authors: SM
authors: Kunisaki
authors: Jonathan R
authors: JR
authors: Dillman
mesh_terms: D000465:Algorithms; D003287:Contrast Media; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007223:Infant; D007231:Infant, Newborn; D008168:Lung / Q000000981:diagnostic imaging; D008297:Male; D011829:Radiation Dosage; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D015619:Respiratory System Abnormalities / Q000000981:diagnostic imaging*; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed; D014463:Ultrasonography
chemical_list: D003287:Contrast Media
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