title: Automated matching of pulmonary nodules: evaluation in serial screening chest CT.
abstract: OBJECTIVE
  The purpose of our study was to evaluate the performance of a computer-aided program that performs automated matching of pulmonary nodules imaged in three serial screening chest MDCT studies.
  
  
  METHODS
  Forty subjects with pulmonary nodules depicted in three annual (T0, T1, T2) low-dose MDCT screening studies for lung cancer were selected from the National Lung Screening Trial database at a single institution. All CT images were reevaluated by two radiologists in consensus. One hundred forty-three nodules were identified and characterized by type (solid parenchymal, juxtavascular, juxtapleural, and ground-glass opacity) and size (< or = 4 mm, 4-6 mm, 6-8 mm, and > 8 mm). Using an automated program, nodules at T0 were matched to nodules at T1, and the same nodules at T1 were matched to nodules at T2. Associations between nodule matching rate (i.e., number of nodules matched by the program divided by the number of nodules determined to match by radiologists) and nodule type or size were analyzed.
  
  
  RESULTS
  The combined matching rate of the nodules was 92.7% (T0 vs T1, 91.6%; T1 vs T2, 93.7%). By nodule type, the matching rate was 94.6% (parenchymal), 98.4% (juxtavascular), 85.8% (juxtapleural), and 100% (ground-glass opacity), with the rate significantly lower for juxtapleural nodules (p < 0.01). Matching rates were not significantly influenced by nodule size (p = 0.67).
  
  
  CONCLUSIONS
  The automated matching rate for pulmonary nodules in screening MDCT scans was high (92.7%) and was not affected by the nodule size but was slightly lower with nodules at juxtapleural locations.
authors.affiliation: Department of Radiology, University of Pittsburgh School of Medicine, 3362 Fifth Ave., Pittsburgh, PA 15213, USA.
authors.forename: Cheng
authors.initials: C
authors.lastname: Tao
authors.forename: David S
authors.initials: DS
authors.lastname: Gierada
authors.forename: Fang
authors.initials: F
authors.lastname: Zhu
authors.forename: Thomas K
authors.initials: TK
authors.lastname: Pilgram
authors.forename: Jin Hong
authors.initials: JH
authors.lastname: Wang
authors.forename: Kyongtae T
authors.initials: KT
authors.lastname: Bae
mesh_terms: D000368:Aged; D016009:Chi-Square Distribution; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*