We present a computer-aided diagnosis (CAD) method for breast lesions on ultrasound that is based on the automatic segmentation of lesions and the automatic extraction of four features related to the lesion shape, margin, texture, and posterior acoustic behavior. Using a database of 400 cases (94 malignant lesions, 124 complex cysts, and 182 benign solid lesions), we investigate the marginal benefit of each feature in our CAD method and the performance of our CAD method in distinguishing malignant lesions from various classes of benign lesions. Finally, independent validation is performed on our CAD method. Eleven independent trials yielded an average Az value of 0.87 in the task of distinguishing malignant from benign lesions.

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In this paper we present a computationally efficient segmentation algorithm for breast masses on sonography that is based on maximizing a utility function over partition margins defined through gray-value thresholding of a preprocessed image. The performance of the segmentation algorithm is evaluated on a database of 400 cases in two ways. Of the 400 cases, 124 were complex cysts, 182 were benign solid lesions, and 94 were malignant lesions. In the first evaluation, the computer-delineated margins were compared to manually delineated margins. At an overlap threshold of 0.40, the segmentation algorithm correctly delineated 94% of the lesions. In the second evaluation, the performance of our computer-aided diagnosis method on the computer-delineated margins was compared to the performance of our method on the manually delineated margins. Round robin evaluation yielded Az values of 0.90 and 0.87 on the manually delineated margins and the computer-delineated margins, respectively, in the task of distinguishing between malignant and nonmalignant lesions.

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This study was undertaken to evaluate the various strategies currently in use to manage complex cysts and specifically address the need for intervention. MATERIALS AND METHODS. A review of 4562 breast sonograms obtained during an 18-month period revealed 308 complex cysts in 252 women. Data collected from review of patient records included the patient's age and risk factors for breast cancer, aspiration or biopsy results (or both), follow-up imaging studies, and management recommendations. RESULTS. Management recommendations for complex cysts were 1-year follow-up in 13 patients, 6-month follow-up in 148, sonographically guided aspiration in 82, aspiration with possible core biopsy in 62, and excisional biopsy in three. No malignancies were diagnosed in the group treated with follow-up imaging, sonographically guided aspiration, or excisional biopsy. One malignancy, a papilloma with a 3-mm focus of ductal carcinoma in situ. was diagnosed in one of the patients who underwent core biopsy. CONCLUSION. Of the lesions classified as complex cysts, the malignancy rate was 0.3% (1/308). This malignancy rate is lower than that for lesions classified as probably benign using mammographic criteria (i.e., for lesions classified as category 3 lesions using the Breast Imaging Reporting and Data System). Because the accepted standard practice for management of probably benign lesions is follow-up studies, the low yield of malignancy in this series suggests that complex cysts can be managed with follow-up imaging studies instead of intervention.