Computer-aided tumor diagnosis using shear wave breast elastography.
The shear wave elastography (SWE) uses the acoustic radiation force to measure the stiffness of tissues and is less operator dependent in data acquisition compared to strain elastography. However, the reproducibility of the result is still interpreter dependent. The purpose of this study is to develop a computer-aided diagnosis (CAD) method to differentiate benign from malignant breast tumors using SWE images. After applying the level set method to automatically segment the tumor contour and hue-saturation-value color transformation, SWE features including average tissue elasticity, sectional stiffness ratio, and normalized minimum distance for grouped stiffer pixels are calculated. Finally, the performance of CAD based on SWE features are compared with those based on B-mode ultrasound (morphologic and textural) features, and a combination of both feature sets to differentiate benign from malignant tumors. In this study, we use 109 biopsy-proved breast tumors composed of 57 benign and 52 malignant cases. The experimental results show that the sensitivity, specificity, accuracy and the area under the receiver operating characteristic ROC curve (Az value) of CAD are 86.5%, 93.0%, 89.9%, and 0.905 for SWE features whereas they are 86.5%, 80.7%, 83.5% and 0.893 for B-mode features and 90.4%, 94.7%, 92.3% and 0.961 for the combined features. The Az value of combined feature set is significantly higher compared to the B-mode and SWE feature sets (p=0.0296 and p=0.0204, respectively). Our results suggest that the CAD based on SWE features has the potential to improve the performance of classifying breast tumors with US.
Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, Republic of Korea.
Woo Kyung
WK
Moon
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
Yao-Sian
YS
Huang
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
Yan-Wei
YW
Lee
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
Shao-Chien
SC
Chang
Graduate Institute of Biomedical Informatics Taipei Medical University, Taipei, Taiwan.
Chung-Ming
CM
Lo
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
Min-Chun
MC
Yang
Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, Republic of Korea.
Min Sun
MS
Bae
Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, Republic of Korea.
Su Hyun
SH
Lee
Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, Republic of Korea.
Jung Min
JM
Chang
Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan.
Chiun-Sheng
CS
Huang
Graduate Institute of Network and Multimedia, National Taiwan University, Taipei, Taiwan.
Yi-Ting
YT
Lin
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan; Graduate Institute of Network and Multimedia, National Taiwan University, Taipei, Taiwan; Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan. Electronic address: rfchang@csie.ntu.edu.tw.
Ruey-Feng
RF
Chang
D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003937:Diagnosis, Differential; D054459:Elasticity Imaging Techniques; D005260:Female; D006801:Humans; D008875:Middle Aged; D015203:Reproducibility of Results; D012189:Retrospective Studies; D016217:Ultrasonography, Mammary / Q000379:methods*
Breast; Computer-aided diagnosis; Elastography; Shear wave; Tumor segmentation