Value of Computerized 3D Shape Analysis in Differentiating Encapsulated from Invasive Thymomas

OBJECTIVES: To retrospectively investigate the added value of quantitative 3D shape analysis in differentiating encapsulated from invasive thymomas. MATERIALS AND METHODS: From February 2002 to October 2013, 53 patients (25 men and 28 women; mean age, 53.94 ± 13.13 years) with 53 pathologically-confirmed thymomas underwent preoperative chest CT scans (slice thicknesses ≤ 2.5 mm). Twenty-three tumors were encapsulated thymomas and 30 were invasive thymomas. Their clinical and CT characteristics were evaluated. In addition, each thymoma was manually-segmented from surrounding structures, and their 3D shape features were assessed using an in-house developed software program. To evaluate the added value of 3D shape features in differentiating encapsulated from invasive thymomas, logistic regression analysis and receiver-operating characteristics curve (ROC) analysis were performed. RESULTS: Significant differences were observed between encapsulated and invasive thymomas, in terms of cystic changes (p=0.004), sphericity (p=0.016), and discrete compactness (p=0.001). Subsequent binary logistic regression analysis revealed that absence of cystic change (adjusted odds ratio (OR) = 6.636; p=0.015) and higher discrete compactness (OR = 77.775; p=0.012) were significant differentiators of encapsulated from invasive thymomas. ROC analyses revealed that the addition of 3D shape analysis to clinical and CT features (AUC, 0.955; 95% CI, 0.935–0.975) provided significantly higher performance in differentiating encapsulated from invasive thymomas than clinical and CT features (AUC, 0.666; 95% CI, 0.626–0.707) (p<0.001). CONCLUSION: Addition of 3D shape analysis, particularly discrete compactness, can improve differentiation of encapsulated thymomas from invasive thymomas.