title: Three-dimensional analysis of pulmonary nodules: variability of semiautomated volume measurements between different versions of the same software.
abstract: OBJECTIVE
  This study was done to evaluate the variability of semiautomated volume measurements of solid pulmonary nodules between two different versions of the same volumetric software.
  
  
  METHODS
  The volumes of 100 solid intraparenchymal nodules (mean volume 88.10 mm(3); range 7.36-595.25 mm(3)) studied with the same multidetector computed tomography (MDCT) protocol were determined using two different versions of the same volumetric software (LungCARE 2006G and LungCARE 2007S). The 2006G version is based on a single-segmentation algorithm, whereas the newer version features two algorithms: SmallSizeNodule and AllSizeNodule. The results obtained with the 2006G version were compared with those of the 2007S version with the SmallSizeNodule algorithm, as recommended by the user manual. In addition, we compared the volumetric measurements obtained by the two different algorithms of the 2007S version.
  
  
  RESULTS
  The 2006G version and the 2007S version with the SmallSizeNodule algorithm agreed in only two of 100 cases and showed a mean variability of 1.66% (range 0%-8.78%). A more significant volumetric discrepancy was observed between the two different algorithms of the 2007S version, with the AllSizeNodule algorithm providing on average larger volumes (mean variability 71.08%; range 6.02%-218.80%) than SmallSizeNodule. Volume discrepancies were more pronounced in the subgroups of smaller nodules in all comparisons.
  
  
  CONCLUSIONS
  There is variability also in the results provided by different versions of the same volumetric software, and this may affect the calculation of the nodule-doubling time. Computer-aided assessment of the growth of lung nodules should always be performed using the same version of volumetric software and the same segmentation algorithm.
authors.affiliation: Radiologia III, Policlinico S. Orsola-Malpighi, Bologna, Italy.
authors.forename: M F
authors.initials: MF
authors.lastname: Rinaldi
authors.forename: T
authors.initials: T
authors.lastname: Bartalena
authors.forename: L
authors.initials: L
authors.lastname: Braccaioli
authors.forename: N
authors.initials: N
authors.lastname: Sverzellati
authors.forename: S
authors.initials: S
authors.lastname: Mattioli
authors.forename: E
authors.initials: E
authors.lastname: Rimondi
authors.forename: G
authors.initials: G
authors.lastname: Rossi
authors.forename: M
authors.initials: M
authors.lastname: Zompatori
authors.forename: G
authors.initials: G
authors.lastname: Battista
authors.forename: R
authors.initials: R
authors.lastname: Canini
mesh_terms: D000465:Algorithms; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D010363:Pattern Recognition, Automated / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012984:Software; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging* / Q000473:pathology; D014057:Tomography, X-Ray Computed / Q000379:methods*