Korean J Radiol.  2013 Aug;14(4):683-691. 10.3348/kjr.2013.14.4.683.

A Comparison of Two Commercial Volumetry Software Programs in the Analysis of Pulmonary Ground-Glass Nodules: Segmentation Capability and Measurement Accuracy

• Kim H
• Park CM
• Lee SM
• Lee HJ
• Goo JM

• KMID: 1715775
• DOI: http://doi.org/10.3348/kjr.2013.14.4.683

Abstract

OBJECTIVE
To compare the segmentation capability of the 2 currently available commercial volumetry software programs with specific segmentation algorithms for pulmonary ground-glass nodules (GGNs) and to assess their measurement accuracy.
MATERIALS AND METHODS
In this study, 55 patients with 66 GGNs underwent unenhanced low-dose CT. GGN segmentation was performed by using 2 volumetry software programs (LungCARE, Siemens Healthcare; LungVCAR, GE Healthcare). Successful nodule segmentation was assessed visually and morphologic features of GGNs were evaluated to determine factors affecting segmentation by both types of software. In addition, the measurement accuracy of the software programs was investigated by using an anthropomorphic chest phantom containing simulated GGNs.
RESULTS
The successful nodule segmentation rate was significantly higher in LungCARE (90.9%) than in LungVCAR (72.7%) (p = 0.012). Vascular attachment was a negatively influencing morphologic feature of nodule segmentation for both software programs. As for measurement accuracy, mean relative volume measurement errors in nodules > or = 10 mm were 14.89% with LungCARE and 19.96% with LungVCAR. The mean relative attenuation measurement errors in nodules > or = 10 mm were 3.03% with LungCARE and 5.12% with LungVCAR.
CONCLUSION
LungCARE shows significantly higher segmentation success rates than LungVCAR. Measurement accuracy of volume and attenuation of GGNs is acceptable in GGNs > or = 10 mm by both software programs.

Keyword

Lung neoplasms; Solitary pulmonary nodule; Multidetector computed tomography; Phantoms, imaging; Technology, radiologic

MeSH Terms

Adult
Aged
*Algorithms
Female
Humans
Lung Neoplasms/diagnosis
Male
Middle Aged
Multidetector Computed Tomography/*methods
*Phantoms, Imaging
Reproducibility of Results
Retrospective Studies
*Software
Solitary Pulmonary Nodule/*radiography

Figure

• 

  Fig. 1 29-year-old woman with ground-glass nodule (GGN). A. LungCARE provides volume-rendered image of nodule and surrounding structures in volume of interest. B, C. LungVCAR provides segmented boundary of GGN overlaid on transverse thin-section image (B) as well as volume-rendered image of segmented nodule (C).

• 

  Fig. 2 Comparison of ground-glass nodule segmentation profile between 2 volumetry software programs (LungCARE and LungVCAR). Note that poor and failure portions of LungVCAR segmentation are 16.7% and 10.6%, respectively, while poor segmentation in LungCARE is 9.1% with no cases of failed segmentation.

• 

  Fig. 3 43-year-old woman with vessel-attached ground-glass nodule (GGN). A. Transverse thin-section chest CT shows 7.3 mm pure GGN (arrow) in right lower lobe. B. Volume-rendered image of LungCARE shows poor segmentation of GGN with vascular segmentation leakage. C, D. LungVCAR provides segmentation boundary of GGN overlaid on transverse thin-section image (C) and volume-rendered image also shows poor segmentation of GGN due to attached vessels (D).

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