title: Automated 3-dimensional morphologic analysis of sputum specimens for lung cancer detection: Performance characteristics support use in lung cancer screening.
abstract: BACKGROUND
  The LuCED Lung Test comprises an automated 3-dimensional morphologic analysis of epithelial cells in sputum. For each cell, 594 morphology-based features are measured to drive algorithmic classifiers that quantitatively assess whether neoplastic cells are present. The current interim clinical study involves sputum samples from patients with known benign and malignant outcomes to assess the feasibility of LuCED as an adjunctive test after suspicious low-dose computed tomography (LDCT) results or as an independent screening test for lung cancer.
  
  
  METHODS
  Sputum samples were fixed, enriched for epithelial cells, and analyzed with a 3-dimensional cell scanner called Cell-CT. Candidate abnormal cells were identified by the classifiers for manual review. The sensitivity, specificity, and negative and positive predictive values were calculated for the detection of neoplastic cases.
  
  
  RESULTS
  A total of 91 sputum samples from patients with confirmed lung cancer (49 patients) and patients with no known malignancy (42 patients) were evaluated. After cytology review, sensitivity in the positive group was 91.8%, and specificity was 95.2%. Specificity was not 100% because there were 2 cases in which abnormal cells were identified by the Cell-CT that were confirmed as such at the time of manual cytology review. However, at the time of last follow-up, malignancy had not been detected in these 2 cases. Modeling in a population with a 1% prevalence of lung cancer, the positive and negative predictive values would be 95.4% and 99.9%, respectively.
  
  
  CONCLUSIONS
  LuCED testing is highly sensitive and specific for the detection of lung cancer and has potential value as an adjunctive test after suspicious LDCT findings or as a primary screening test in which LuCED-positive cases would be triaged to diagnostic CT. Further prospective studies currently are underway to evaluate its full usefulness.
authors.affiliation: VisionGate Inc, Phoenix, Arizona.
authors.forename: David C
authors.initials: DC
authors.lastname: Wilbur
authors.affiliation: VisionGate Inc, Phoenix, Arizona.
authors.forename: Michael G
authors.initials: MG
authors.lastname: Meyer
authors.affiliation: VisionGate Inc, Phoenix, Arizona.
authors.forename: Chris
authors.initials: C
authors.lastname: Presley
authors.affiliation: Department of Thoracic Oncology, Swedish Hospital, Seattle, Washington.
authors.forename: Ralph W
authors.initials: RW
authors.lastname: Aye
authors.affiliation: Department of Pulmonary Medicine, Aristotle University, Thessaloniki, Greece.
authors.forename: Paul
authors.initials: P
authors.lastname: Zarogoulidis
authors.affiliation: Department of Radiation Oncology, Baptist Cancer Institute, Jacksonville, Florida.
authors.forename: Douglas W
authors.initials: DW
authors.lastname: Johnson
authors.affiliation: Thoracic Cancer Unit, Davidoff Cancer Center, Rabin Medical Center, Petach Tiqwa, Israel.
authors.forename: Nir
authors.initials: N
authors.lastname: Peled
authors.affiliation: VisionGate Inc, Phoenix, Arizona.
authors.forename: Alan C
authors.initials: AC
authors.lastname: Nelson
mesh_terms: D000368:Aged; D001331:Automation; D015331:Cohort Studies; D003581:Cytodiagnosis / Q000379:methods; D055088:Early Detection of Cancer / Q000379:methods*; D004847:Epithelial Cells / Q000000981:diagnostic imaging / Q000473:pathology; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D009361:Neoplasm Invasiveness / Q000473:pathology; D009367:Neoplasm Staging; D012680:Sensitivity and Specificity; D013183:Sputum / Q000166:cytology* / Q000000981:diagnostic imaging*; D013647:Task Performance and Analysis; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Cell-CT; LuCED; automation; cytology; lung cancer; screening