Solid Breast Masses: Classification with Computer-aided Analysis of Continuous US Images Obtained with Probe Compression
- 1 August 2005
- journal article
- Published by Radiological Society of North America (RSNA) in Radiology
- Vol. 236 (2) , 458-464
- https://doi.org/10.1148/radiol.2362041095
Abstract
To prospectively evaluate the accuracy of continuous ultrasonographic (US) images obtained during probe compression and computer-aided analysis for classification of biopsy-proved (reference standard) benign and malignant breast tumors. This study was approved by the local ethics committee, and informed consent was obtained from all included patients. Serial US images of 100 solid breast masses (60 benign and 40 malignant tumors) were obtained with US probe compression in 86 patients (mean age, 45 years; range, 20-67 years). After segmentation of tumor contours with the level-set method, three features of strain on tissue from probe compression--contour difference, shift distance, area difference--and one feature of shape--solidity-were computed. A maximum margin classifier was used to classify the tumors by using these four features. The Student t test and receiver operating characteristic curve analysis were used for statistical analysis. The mean values of contour difference, shift distance, area difference, and solidity were 3.52% +/- 2.12 (standard deviation), 2.62 +/- 1.31, 1.08% +/- 0.85, and 1.70 +/- 1.85 in malignant tumors and 9.72% +/- 4.54, 5.04 +/- 2.79, 3.17% +/- 2.86, and 0.53 +/- 0.63 in benign tumors, respectively. Differences with P < .001 were statistically significant for all four features. Area under the receiver operating characteristic curve (A(Z)) values for contour difference, shift distance, area difference, and solidity were 0.88, 0.85, 0.86, and 0.79, respectively. The A(Z) value of three features of strain was significantly higher than that of the feature of shape (P < .01). The accuracy, sensitivity, specificity, and positive and negative predictive values of US classifications that were based on values for these four features were 87.0% (87 of 100), 85% (34 of 40), 88% (53 of 60), 83% (34 of 41), and 90% (53 of 59), respectively, with an A(Z) value of 0.91. Continuous US images obtained with probe compression and computer-aided analysis can aid in classification of benign and malignant breast tumors.Keywords
This publication has 20 references indexed in Scilit:
- Performance of computer-aided diagnosis in the interpretation of lesions on breast sonographyAcademic Radiology, 2004
- In vivo real-time freehand palpation imagingUltrasound in Medicine & Biology, 2003
- Nonlinear stress-strain relationships in tissue and their effect on the contrast-to-noise ratio in elastogramsUltrasound in Medicine & Biology, 2000
- Elastography: Ultrasonic estimation and imaging of the elastic properties of tissuesProceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 1999
- A new elastographic method for estimation and imaging of lateral displacements, lateral strains, corrected axial strains and poisson’s ratios in tissuesUltrasound in Medicine & Biology, 1998
- Disparity mapping applied to sonography of the breast: technical note.Radiology, 1998
- Elastography of breast lesions: initial clinical results.Radiology, 1997
- Solid breast nodules: use of sonography to distinguish between benign and malignant lesions.Radiology, 1995
- Elastography: Elasticity Imaging Using Ultrasound with Application to Muscle and Breast in VivoUltrasonic Imaging, 1993
- Elastography: A Quantitative Method for Imaging the Elasticity of Biological TissuesUltrasonic Imaging, 1991