Diagnosis of solid breast tumors using vessel analysis in three-dimensional power Doppler ultrasound images
Journal
Journal of Digital Imaging
Journal Volume
26
Journal Issue
4
Pages
731-739
Date Issued
2013
Author(s)
Abstract
This study aims to evaluate whether the distribution of vessels inside and adjacent to tumor region at three-dimensional (3-D) power Doppler ultrasonography (US) can be used for the differentiation of benign and malignant breast tumors. 3-D power Doppler US images of 113 solid breast masses (60 benign and 53 malignant) were used in this study. Blood vessels within and adjacent to tumor were estimated individually in 3-D power Doppler US images for differential diagnosis. Six features including volume of vessels, vascularity index, volume of tumor, vascularity index in tumor, vascularity index in normal tissue, and vascularity index in surrounding region of tumor within 2 cm were evaluated. Neural network was then used to classify tumors by using these vascular features. The receiver operating characteristic (ROC) curve analysis and Student's t test were used to estimate the performance. All the six proposed vascular features are statistically significant (p < 0.001) for classifying the breast tumors as benign or malignant. The A Z (area under ROC curve) values for the classification result were 0.9138. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the diagnosis performance based on all six proposed features were 82.30 (93/113), 86.79 (46/53), 78.33 (47/60), 77.97 (46/59), and 87.04 % (47/54), respectively. The p value of A Z values between the proposed method and conventional vascularity index method using z test was 0.04. ? 2013 Society for Imaging Informatics in Medicine.
SDGs
Other Subjects
3-D ultrasound; Area under roc curve (AUC); Breast tumor; Positive predictive values; Power Doppler; Power doppler ultrasonographies; Receiver operating characteristic curve analysis; Vascularity; Blood vessels; Medical imaging; Non Newtonian flow; Three dimensional; Tumors; Diagnosis; breast tumor; computer assisted diagnosis; differential diagnosis; Doppler flowmetry; echography; echomammography; female; human; image processing; pathology; predictive value; procedures; receiver operating characteristic; reproducibility; sensitivity and specificity; three dimensional imaging; tumor volume; vascularization; article; breast tumor; Doppler flowmetry; echography; echomammography; methodology; three dimensional imaging; vascularization; Breast Neoplasms; Diagnosis, Differential; Female; Humans; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted; Imaging, Three-Dimensional; Predictive Value of Tests; Reproducibility of Results; ROC Curve; Sensitivity and Specificity; Tumor Burden; Ultrasonography, Doppler; Ultrasonography, Mammary; Breast Neoplasms; Diagnosis, Differential; Female; Humans; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted; Imaging, Three-Dimensional; Predictive Value of Tests; Reproducibility of Results; ROC Curve; Sensitivity and Specificity; Tumor Burden; Ultrasonography, Doppler; Ultrasonography, Mammary
Type
journal article