title: Differentiation of malignant and benign pulmonary nodules with first-pass dual-input perfusion CT.
abstract: OBJECTIVE
  To assess diagnostic performance of dual-input CT perfusion for distinguishing malignant from benign solitary pulmonary nodules (SPNs).
  
  
  METHODS
  Fifty-six consecutive subjects with SPNs underwent contrast-enhanced 320-row multidetector dynamic volume CT. The dual-input maximum slope CT perfusion analysis was employed to calculate the pulmonary flow (PF), bronchial flow (BF), and perfusion index [Formula: see text]. Differences in perfusion parameters between malignant and benign tumours were assessed with histopathological diagnosis as the gold standard. Diagnostic value of the perfusion parameters was calculated using the receiver-operating characteristic (ROC) curve analysis.
  
  
  RESULTS
  Amongst 56 SPNs, statistically significant differences in all three perfusion parameters were revealed between malignant and benign tumours. The PI demonstrated the biggest difference between malignancy and benignancy: 0.30 ± 0.07 vs. 0.51 ± 0.13 , P < 0.001. The area under the PI ROC curve was 0.92, the largest of the three perfusion parameters, producing a sensitivity of 0.95, specificity of 0.83, positive likelihood ratio (+LR) of 5.59, and negative likelihood ratio (-LR) of 0.06 in identifying malignancy.
  
  
  CONCLUSIONS
  The PI derived from the dual-input maximum slope CT perfusion analysis is a valuable biomarker for identifying malignancy in SPNs. PI may be potentially useful for lung cancer treatment planning and forecasting the therapeutic effect of radiotherapy treatment.
  
  
  CONCLUSIONS
  • Modern CT equipment offers assessment of vascular parameters of solitary pulmonary nodules (SPNs) • Dual vascular supply was investigated to differentiate malignant from benign SPNs. • Different dual vascular supply patterns were found in malignant and benign SPNs. • The perfusion index is a useful biomarker for differentiate malignancy from benignancy.
authors.affiliation: Department of Radiology, the 309th Hospital of Chinese People's Liberation Army, 17 Heishanhu Road, Haidian District, Beijing, 100091, People's Republic of China.
authors.forename: Xiaodong
authors.initials: X
authors.lastname: Yuan
authors.forename: Jing
authors.initials: J
authors.lastname: Zhang
authors.forename: Changbin
authors.initials: C
authors.lastname: Quan
authors.forename: Jianxia
authors.initials: J
authors.lastname: Cao
authors.forename: Guokun
authors.initials: G
authors.lastname: Ao
authors.forename: Yuan
authors.initials: Y
authors.lastname: Tian
authors.forename: Hong
authors.initials: H
authors.lastname: Li
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D015415:Biomarkers / Q000378:metabolism; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D061705:Image-Guided Biopsy / Q000379:methods; D008175:Lung Neoplasms / Q000175:diagnosis; D008297:Male; D008875:Middle Aged; D010477:Perfusion; D011446:Prospective Studies; D012372:ROC Curve; D011878:Radiotherapy / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D036542:Tomography, Spiral Computed / Q000379:methods; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D015415:Biomarkers