Abstract
The purpose of this study was to investigate whether maximum nodule perimeter to the
approximate oval could discriminate benign nodules from malignancy.
Measurement of maximum nodule perimeter difference to the approximate oval was performed
using volume-rendering images of three directions of each pulmonary nodule. The margin
was then traced manually and our custom software delineated the approximate oval automatically.
The maximum nodule perimeter difference was 26.5±23.3 mm for malignant and 16.6±16.9
mm for benign nodules, showing an almost statistically significant difference (P=.07).
This study suggests that the maximum nodule perimeter difference to the approximate
oval of the malignant nodules has a tendency to be longer than benign nodules.
Keywords
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Clinical ImagingAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- New classification of small pulmonary nodules by margin characteristics on high-resolution CT.Acta Radiol. 1999; 40: 496-504
- Malignant versus benign nodules at CT screening for lung cancer: comparison of thin-section CT findings.Radiology. 2004; 233: 793-798
- Solitary pulmonary nodule: high-resolution CT and radiologic–pathologic correlation.Radiology. 1991; 179: 469-476
- Solitary pulmonary nodules: part I. Morphologic evaluation for differentiation of benign and malignant lesions.Radiographics. 2000; 20: 43-58
- Computer-aided diagnosis: a shape classification of pulmonary nodules imaged by high-resolution CT.Comput Med Imaging Graph. 2005; 29: 565-570
- Computer-aided differentiation of malignant from benign solitary pulmonary nodules imaged by high-resolution CT.Comput Med Imaging Graph. 2008; 32: 416-422
- Usefulness of circumference difference for estimating the likelihood of malignancy in small solitary pulmonary nodules on CT.Lung Cancer. 2007; 58: 348-354
- Small solitary pulmonary nodules (< or =1 cm) detected at population-based CT screening for lung cancer: reliable high-resolution CT features of benign lesions.AJR Am J Roentgenol. 2003; 180: 955-964
- Computer-aided diagnosis for pulmonary nodules based on helical CT images.Comput Med Imaging Graph. 1998; 22: 157-167
- Fractal analysis of small peripheral pulmonary nodules in thin-section CT: evaluation of the lung-nodule interfaces.J Comput Assist Tomogr. 2002; 26: 573-578
- Usefulness of an artificial neural network for differentiating benign from malignant pulmonary nodules on high-resolution CT: evaluation with receiver operating characteristic analysis.AJR Am J Roentgenol. 2002; 178: 657-663
- A pattern classification approach to characterizing solitary pulmonary nodules imaged on high resolution CT: preliminary results.Med Phys. 1999; 26: 880-888
Article info
Publication history
Published online: May 26, 2010
Accepted:
March 8,
2010
Received:
February 24,
2010
Identification
Copyright
© 2011 Elsevier Inc. Published by Elsevier Inc. All rights reserved.
