title: Comparison of CT-based methodologies for detection of growth of solid renal masses on active surveillance.
abstract: OBJECTIVE
  The purpose of this study is to retrospectively compare 1D, 2D, and 3D measurements on CT for detection of growth of solid renal masses on active surveillance.
  
  
  METHODS
  Forty solid renal masses measuring at least 1 cm in patients who underwent two CT studies at least 3 months apart were included. Two radiologists independently assessed the studies for interval growth using gestalt visual assessment and 1D, 2D, and 3D measurements. Prospective reports were also evaluated for indications of growth. The summation-of-areas technique was used to calculate volumes of lesions, which served as reference standard in determination of growth. Logistic regression analysis for correlated data was used to compare accuracy of methodologies for detection of lesion growth. Interreader agreement was assessed using kappa coefficients and intraclass correlation coefficients.
  
  
  RESULTS
  The accuracy of gestalt visual, 1D, 2D, and 3D assessments for detection of interval growth was 72.5%, 70.0%, 82.5%, and 85% for reader 1 and 77.5%, 70.0%, 90.0%, and 95.0% for reader 2. These differences were significant or nearly significant (p = 0.003-0.054) for the greater accuracy of 2D or 3D measurements than for 1D measurements for reader 1 as well as the greater accuracy of 2D measurements than 1D measurements and 3D measurements than gestalt visual assessment or 1D measurements for reader 2. The accuracy of prospective reports for detection of growth was 65.0%. Reader agreement was fair for gestalt visual assessment (κ = 0.31) and nearly perfect for 1D, 2D, and 3D measurements (intraclass correlation coefficient = 0.97-0.99).
  
  
  CONCLUSIONS
  Our results show that 2D or 3D measurements may be preferable to 1D measurements on CT in assessment for growth of solid renal masses on active surveillance.
authors: Department of Radiology, New York University Langone Medical Center, 560 First Ave, TCH-HW202, New York, NY 10016, USA. andrew.rosenkrantz@nyumc.org
authors: Andrew B
authors: AB
authors: Rosenkrantz
authors: Thais C
authors: TC
authors: Mussi
authors: Molly B
authors: MB
authors: Somberg
authors: Samir S
authors: SS
authors: Taneja
authors: James S
authors: JS
authors: Babb
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D007680:Kidney Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*