title: Multidetector CT features of pulmonary focal ground-glass opacity: differences between benign and malignant.
abstract: OBJECTIVE
  To evaluate different features between benign and malignant pulmonary focal ground-glass opacity (fGGO) on multidetector CT (MDCT).
  
  
  METHODS
  82 pathologically or clinically confirmed fGGOs were retrospectively analysed with regard to demographic data, lesion size and location, attenuation value and MDCT features including shape, margin, interface, internal characteristics and adjacent structure. Differences between benign and malignant fGGOs were analysed using a χ(2) test, Fisher's exact test or Mann-Whitney U-test. Morphological characteristics were analysed by binary logistic regression analysis to estimate the likelihood of malignancy.
  
  
  RESULTS
  There were 21 benign and 61 malignant lesions. No statistical differences were found between benign and malignant fGGOs in terms of demographic data, size, location and attenuation value. The frequency of lobulation (p=0.000), spiculation (p=0.008), spine-like process (p=0.004), well-defined but coarse interface (p=0.000), bronchus cut-off (p=0.003), other air-containing space (p=0.000), pleural indentation (p=0.000) and vascular convergence (p=0.006) was significantly higher in malignant fGGOs than that in benign fGGOs. Binary logistic regression analysis showed that lobulation, interface and pleural indentation were important indicators for malignant diagnosis of fGGO, with the corresponding odds ratios of 8.122, 3.139 and 9.076, respectively. In addition, a well-defined but coarse interface was the most important indicator of malignancy among all interface types. With all three important indicators considered, the diagnostic sensitivity, specificity and accuracy were 93.4%, 66.7% and 86.6%, respectively.
  
  
  CONCLUSIONS
  An fGGO with lobulation, a well-defined but coarse interface and pleural indentation gives a greater than average likelihood of being malignant.
authors: Department of Radiology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
authors: L
authors: L
authors: Fan
authors: S-Y
authors: SY
authors: Liu
authors: Q-C
authors: QC
authors: Li
authors: H
authors: H
authors: Yu
authors: X-S
authors: XS
authors: Xiao
mesh_terms: D000368:Aged; D015331:Cohort Studies; D003937:Diagnosis, Differential; D005260:Female; D005490:Focal Infection / Q000000981:diagnostic imaging / Q000473:pathology; D006801:Humans; D007150:Immunohistochemistry; D016013:Likelihood Functions; D016015:Logistic Models; D008168:Lung / Q000000981:diagnostic imaging* / Q000473:pathology*; D008171:Lung Diseases / Q000000981:diagnostic imaging / Q000473:pathology; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D061330:Multidetector Computed Tomography / Q000379:methods*; D015999:Multivariate Analysis; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging* / Q000473:pathology; D018709:Statistics, Nonparametric