Yanxin Su1, Hong Wang, Ying Wang, Yanhui Guo, Hengda Cheng, Yingtao Zhang, Jiawei Tian. 1. Ultrasound Department, The Second Affiliated Hospital, Key Laboratory of Education Ministry for Myocardial Ischemia Mechanism and Treatment, Harbin Medical University, 148 Baojian Road, Harbin 150086, Heilongjiang, China.
Abstract
OBJECTIVES: To retrospectively evaluate the effects of a speckle reduction algorithm on radiologists' diagnosis of malignant and benign breast lesions on ultrasound (US) images. METHODS: Using a database of 603 breast (US) images of 211 cases (109 benign lesions and 102 malignant ones), the original and speckle-reduced images were assessed by five radiologists and final assessment categories were assigned to indicate the probability of malignancy according to BI-RADS-US. The diagnostic sensitivity and specificity were investigated by the areas (Az) under the receiver operating characteristic (ROC) curves. RESULTS: The sensitivity and specificity of breast lesions on Ultrasound images improved from 88.7% to 94.3%, from 68.6% to 75.2%, respectively, and the area (Az) under ROC curve of diagnosis also increased from 0.843 to 0.939, Z=4.969, there were significant differences in the Az between the original breast lesions and speckle-reduced ones on Ultrasound images (P<0.001). The diagnostic accuracy of breast lesions had been highly improved from 78.67% to 92.73% after employing this algorithm. CONCLUSIONS: The results demonstrate the promising performance of the proposed speckle reduction algorithm in distinguishing malignant from benign breast lesions which will be useful for breast cancer diagnosis. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.
OBJECTIVES: To retrospectively evaluate the effects of a speckle reduction algorithm on radiologists' diagnosis of malignant and benign breast lesions on ultrasound (US) images. METHODS: Using a database of 603 breast (US) images of 211 cases (109 benign lesions and 102 malignant ones), the original and speckle-reduced images were assessed by five radiologists and final assessment categories were assigned to indicate the probability of malignancy according to BI-RADS-US. The diagnostic sensitivity and specificity were investigated by the areas (Az) under the receiver operating characteristic (ROC) curves. RESULTS: The sensitivity and specificity of breast lesions on Ultrasound images improved from 88.7% to 94.3%, from 68.6% to 75.2%, respectively, and the area (Az) under ROC curve of diagnosis also increased from 0.843 to 0.939, Z=4.969, there were significant differences in the Az between the original breast lesions and speckle-reduced ones on Ultrasound images (P<0.001). The diagnostic accuracy of breast lesions had been highly improved from 78.67% to 92.73% after employing this algorithm. CONCLUSIONS: The results demonstrate the promising performance of the proposed speckle reduction algorithm in distinguishing malignant from benign breast lesions which will be useful for breast cancer diagnosis. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.