Multidetector CT features of pulmonary focal ground-glass opacity: differences between benign and malignant

• Published in: British journal of radiology Vol. 85; no. 1015; pp. 897 - 904
• Main Authors: FAN, L, LIU, S.-Y, LI, Q.-C, YU, H, XIAO, X.-S
• Format: Journal Article
• Language: English
• Published: London British Institute of Radiology 01.07.2012; The British Institute of Radiology
• Subjects: Aged; Biological and medical sciences; Cohort Studies; Diagnosis, Differential; Female; Focal Infection - diagnostic imaging; Focal Infection - pathology; Humans; Immunohistochemistry; Investigative techniques, diagnostic techniques (general aspects); Likelihood Functions; Logistic Models; Lung - diagnostic imaging; Lung - pathology; Lung Diseases - diagnostic imaging; Lung Diseases - pathology; Lung Neoplasms - diagnostic imaging; Lung Neoplasms - pathology; Male; Medical sciences; Middle Aged; Multidetector Computed Tomography - methods; Multivariate Analysis; Retrospective Studies; Sensitivity and Specificity; Solitary Pulmonary Nodule - diagnostic imaging; Solitary Pulmonary Nodule - pathology; Statistics, Nonparametric; Nuclear medicine; Multidetector scanner; Radiodiagnosis; Radiologic sign; Lung; Radiology; Medical imagery; Computerized axial tomography; Malignant tumor; Respiratory system; Cancer
• ISSN: 0007-1285; 1748-880X
• DOI: 10.1259/bjr/33150223

To evaluate different features between benign and malignant pulmonary focal ground-glass opacity (fGGO) on multidetector CT (MDCT). 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. 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. An fGGO with lobulation, a well-defined but coarse interface and pleural indentation gives a greater than average likelihood of being malignant.