title: Interobserver and intraobserver variability in the assessment of pulmonary nodule size on CT using film and computer display methods.
abstract: OBJECTIVE
  A critical element in determining biologic behavior of pulmonary nodules is volume and temporal volume change. We evaluate variability in nodule volume among readers and measuring methods.
  
  
  METHODS
  55 small (<2 cm) lung nodules were measured in long- and short-axis dimensions independently by 4 radiologists, using 3 methods: 1) hard copy, 2) GE Advantage Windows workstation (GE Healthcare, Milwaukee, WI), 3) Siemens IMACS workstation (Siemens Medical Systems, Iselan, NJ). Nodule margin was recorded as smooth, lobulated, or spiculated. Volume was calculated from diameter measurements. Variability in nodule volume was evaluated within each reader, between readers, and across measurement tools.
  
  
  RESULTS
  Mean nodule short-axis diameter was 5.3 mm; mean long-axis diameter 7.2 mm. There was statistically significant variation among readers and measurement method for nodule volume. Volume was significantly larger using hard-copy measurements (51.9%-54.1% variation; P < .0001) than either workstation, and not different between workstations. There was greater intraobserver variability in volume using the hard-copy method, and no difference between workstation methods. Volumes based on measurements from one reader were consistently lower than those from other readers (P = < .001, .003, and .02); volume was consistently larger for another reader (P < .0001, .03, and .12). Reader agreement for nodule margin was good to excellent.
  
  
  CONCLUSIONS
  Considerable interobserver and intraobserver variability in measuring nodules exists using hard-copy and computer tools. Since a small change in diameter indicates a much larger change in volume, this may be significant when using early repeat CT to follow small pulmonary nodules. Computer-aided diagnostic tools that reproducibly measure nodule volume are strongly needed.
authors.affiliation: Department of Radiology, University of Michigan Medical School, Ann Arbor, 48109-0326, USA.
authors.forename: Naama R
authors.initials: NR
authors.lastname: Bogot
authors.forename: Ella A
authors.initials: EA
authors.lastname: Kazerooni
authors.forename: Aine M
authors.initials: AM
authors.lastname: Kelly
authors.forename: Leslie E
authors.initials: LE
authors.lastname: Quint
authors.forename: Benoit
authors.initials: B
authors.lastname: Desjardins
authors.forename: Bin
authors.initials: B
authors.lastname: Nan
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000473:pathology*; D015588:Observer Variation; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000473:pathology*; D013223:Statistics as Topic; D014057:Tomography, X-Ray Computed / Q000379:methods*