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

Lee JH, Park CM, Park SJ, Bae JS, Lee SM, Goo JM - PLoS ONE (2015)

Bottom Line: Their clinical and CT characteristics were evaluated.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).

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus

CT images of encapsulated and invasive thymomas.(a) A 61 year old female who underwent surgical resection of an encapsulated thymoma (arrow) (discrete compactness, 0.925; sphericity, 0.703). (b) A 40 year old female who underwent surgical resection of an invasive thymoma (arrow) (discrete compactness, 0.722; sphericity, 0.646). Note that although these two kinds of thymomas cannot be easily differentiated grossly owing to similar CT features, there is a distinct difference in 3D shape features, particularly in discrete compactness, between the encapsulated thymoma and invasive thymoma.
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pone.0126175.g002: CT images of encapsulated and invasive thymomas.(a) A 61 year old female who underwent surgical resection of an encapsulated thymoma (arrow) (discrete compactness, 0.925; sphericity, 0.703). (b) A 40 year old female who underwent surgical resection of an invasive thymoma (arrow) (discrete compactness, 0.722; sphericity, 0.646). Note that although these two kinds of thymomas cannot be easily differentiated grossly owing to similar CT features, there is a distinct difference in 3D shape features, particularly in discrete compactness, between the encapsulated thymoma and invasive thymoma.

Mentions: On univariate analysis, significant differences were observed in cystic change (encapsulated thymomas, 3/23; invasive thymomas, 16/30; p = 0.004), sphericity (0.677 vs. 0.604; p = 0.016), and discrete compactness (0.825 vs. 0.691; p = 0.001). The results of univariate analysis discriminating encapsulated from invasive thymomas are summarized in Tables 1 and 2 (Fig 2).


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

Lee JH, Park CM, Park SJ, Bae JS, Lee SM, Goo JM - PLoS ONE (2015)

CT images of encapsulated and invasive thymomas.(a) A 61 year old female who underwent surgical resection of an encapsulated thymoma (arrow) (discrete compactness, 0.925; sphericity, 0.703). (b) A 40 year old female who underwent surgical resection of an invasive thymoma (arrow) (discrete compactness, 0.722; sphericity, 0.646). Note that although these two kinds of thymomas cannot be easily differentiated grossly owing to similar CT features, there is a distinct difference in 3D shape features, particularly in discrete compactness, between the encapsulated thymoma and invasive thymoma.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4418613&req=5

pone.0126175.g002: CT images of encapsulated and invasive thymomas.(a) A 61 year old female who underwent surgical resection of an encapsulated thymoma (arrow) (discrete compactness, 0.925; sphericity, 0.703). (b) A 40 year old female who underwent surgical resection of an invasive thymoma (arrow) (discrete compactness, 0.722; sphericity, 0.646). Note that although these two kinds of thymomas cannot be easily differentiated grossly owing to similar CT features, there is a distinct difference in 3D shape features, particularly in discrete compactness, between the encapsulated thymoma and invasive thymoma.
Mentions: On univariate analysis, significant differences were observed in cystic change (encapsulated thymomas, 3/23; invasive thymomas, 16/30; p = 0.004), sphericity (0.677 vs. 0.604; p = 0.016), and discrete compactness (0.825 vs. 0.691; p = 0.001). The results of univariate analysis discriminating encapsulated from invasive thymomas are summarized in Tables 1 and 2 (Fig 2).

Bottom Line: Their clinical and CT characteristics were evaluated.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).

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus