title: Radiological diagnosis of small pulmonary nodules detected on low-dose screening computed tomography.
abstract: OBJECTIVE
  Early detection and treatment of small malignant pulmonary lesions can improve survival; however, screening by CT detects many false positives. This study retrospectively evaluated a protocol for the diagnostic work-up of nodules detected by low-dose CT (LDCT) that are < or = 10 mm in diameter.
  
  
  METHODS
  A health screening programme included LDCT. Lesions detected were allocated to one of four categories: negative, semi-negative, positive and semi-positive. Positive and semi-positive categories included non-calcified nodules without a polygonal shape, and these patients had an initial diagnostic HRCT and were then followed up using high-resolution CT (HRCT) at intervals determined by the characteristics of the lesion on screening LDCT and the initial diagnostic HRCT.
  
  
  RESULTS
  There were 275 nodules detected on screening LDCT; 84 patients had lesions classified as positive and 99 as semi-positive. Thirteen nodules detected on screening LDCT were only determined to be polygonal and benign following the diagnostic HRCT. The sensitivity and specificity of the screening CT, when compared with diagnostic HRCT, for determining if nodules should be classified as positive were 100% and 97%. The sensitivity and specificity of the initial diagnostic HRCT for being able to predict lung cancer were 87.5% and 91.7% respectively.
  
  
  CONCLUSIONS
  Following the detection of a pulmonary lesion on screening LDCT, a diagnostic HRCT is necessary to determine the timing of follow-up HRCT. Diagnostic HRCT is needed to rationalize the screening for lung cancer to reduce the frequency of unnecessary follow-up scans.
authors.affiliation: Azumi General Hospital, Kita-Azumi-gun, Japan.
authors.forename: Kenji
authors.initials: K
authors.lastname: Tsushima
authors.forename: Shusuke
authors.initials: S
authors.lastname: Sone
authors.forename: Takaomi
authors.initials: T
authors.lastname: Hanaoka
authors.forename: Keishi
authors.initials: K
authors.lastname: Kubo
mesh_terms: D000465:Algorithms; D002985:Clinical Protocols; D005471:Fluoroscopy; D006801:Humans; D055613:Multiple Pulmonary Nodules / Q000000981:diagnostic imaging*; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed / Q000379:methods*