Classification of Breast Tumors Using Elastographic and B-mode Features: Comparison of Automatic Selection of Representative Slice and Physician-Selected Slice of Images
Journal
Ultrasound in Medicine and Biology
Journal Volume
39
Journal Issue
7
Pages
1147-1157
Date Issued
2013
Author(s)
Abstract
Inter-observer variability and image quality are two key factors that can affect the diagnostic performance of elastography and B-mode ultrasound for breast tumor characterization. The purpose of this study is to use an image quantification method that automatically chooses a representative slice and then segments the tumor contour to evaluate the diagnostic features for tumor characterization. First, the representative slice is selected based on either the stiffness inside the tumor (the signal-to-noise ratio on the elastogram [SNRe]) or the contrast between the tumor and the surrounding normal tissue (the contrast-to-noise ratio on the elastogram [CNRe]). Next, the level set method is used to segment the tumor contour. Finally, the B-mode and elastographic features related to the segmented tumor are extracted for tumor characterization. The performance of the representative slice selected using the proposed methods is compared to that of the physician-selected slice in 151 biopsy-proven lesions (89 benign and 62 malignant). The diagnostic accuracies using elastographic features are 82.1% (124/151) for the slice with the maximum CNRe value, 82.1% (124/151) for the slice with the maximum SNRe value and 82.8% (125/151) for the physician-selected slice, whereas the diagnostic accuracies using B-mode features are 80.8% (122/151) for the slice with the maximum CNRe value, 87.4% (132/151) for the slice with the maximum SNRe value and 84.1% (127/151) for the physician-selected slice. When using both the B-mode and elastographic features to characterize the tumor, the accuracy of diagnosis is 86.1% (130/151) for the slice with the maximum CNRe value, 90.1% (136/151) for the slice with the maximum SNRe value and 89.4% (135/151) for the physician-selected slice. Our results show that the representative slice selected by SNRe and CNRe could be used to reduce the observer variability and to increase the diagnostic performance by the B-mode and elastographic features. ? 2013 World Federation for Ultrasound in Medicine & Biology.
Subjects
B-mode ultrasound; Breast tumor; Computer-aided diagnosis; Diagnostic performance; Elastography; Level set segmentation
SDGs
Other Subjects
Characterization; Computer aided diagnosis; Medical imaging; Signal to noise ratio; Ultrasonics; Breast tumor; Contrast to noise ratio; Diagnostic performance; Elastography; Image quantification; Interobserver variability; Level set segmentation; Tumor characterization; Tumors; adult; aged; article; automation; B scan; breast tumor; computer assisted diagnosis; contrast to noise ratio; controlled study; diagnostic accuracy; diagnostic test accuracy study; elastography; false positive result; female; human; image quality; interrater reliability; major clinical study; predictive value; priority journal; radiologist; receiver operating characteristic; sensitivity and specificity; signal noise ratio; tumor classification; ultrasound scanner
Publisher
Elsevier USA
Type
journal article