A Proposal to Define Three New Breast Calcification Shapes: Square, Sandwich, and Teardrop, Pill & Capsule

Objective To define and illustrate three new descriptors for microcalcification morphology on mammography, and provide a preliminary assessment of their potential clinical value. Methods The institutional review board approved this retrospective study and waived the requirement for informed consent. One thousand consecutive biopsy-proven cases of microcalcifications were retrospectively reviewed by the index study observer, a fellowship-trained breast radiologist blinded to histologic outcome. Each case was evaluated for traditional Breast Imaging Reporting and Data System (BI-RADS) morphology descriptors, as well as for the presence of one of three proposed new calcification morphology descriptors: (1) square, (2) sandwich, and (3) teardrop, pill & capsule. Positive predictive value (PPV) for each proposed shape was calculated. Interobserver variability was calculated on a subset of 200 cases, which were evaluated by two additional breast radiologists blinded to the interpretation of the index observer. Results Of 1000 cases, 702 (70.2%) were benign, and 298 (29.8%) were malignant. There were 51 (5.1%) square and 60 (6.0%) sandwich calcification cases, which were all benign at biopsy (PPV, 0%). Of the 106 (10.6%) cases that included teardrop, pill & capsule calcifications, 90 were malignant (PPV, 84.9%). Interobserver variability for the traditional BI-RADS morphology descriptors (κ = 0.40) was comparable to observer variability of the proposed new morphologies: square (κ = 0.39), sandwich (κ = 0.47), and teardrop, pill & capsule (κ = 0.49). Conclusion The proposed calcification descriptors square and sandwich-shaped had a PPV of 0%, and they may represent new typically benign morphologies. In contrast, teardrop, pill & capsule–shaped calcifications indicate a higher likelihood of malignancy than that of previously established descriptors.

Identification of Micro-calcification in Mammogram for Breast Cancer Analysis using SVM Classifier

Breast cancer is most common disease in women of all ages. To identify & confirm the state of tumor in breast cancer diagnosis, patients are undergo biopsy number of times to identify malignancy. Early detection of cancer can save the patient. In this paper a novel approach for automatic segmentation & classification of breast calcification is proposed. The diagnostic test technique for detection of breast condition is very costly & requires human expertise whereas proposed method can help in automatically identifying the disease by comparing the data with the standard database. In proposed method a database has been created to define various stage of breast calcification & testing images are pre-processed to resize, enhance & filtered to remove background noise. Clustering is performed by using k-means clustering algorithm. GLCM is used to extract out statistical feature like area, mean, variance, standard deviation, homogeneity, skewness etc. to classify the state of tumor. SVM classifier is used for the classification using extracted feature.

Ultrasound-guided mammotome for diagnosis and minimally invasive excision of mammary clustered calcifications.

e13034 Background: To validate the ultrasound-guided vacuum-assisted breast biopsy system (Mammotome) for diagnosis and minimally invasive excision of calcification in breast. Methods: In 20 patients, breast calcification lesions diagnosed by mammography were excised by ultrasound-guided Mammotome system with 8-gauge probe. The samples were taken mammography and followed by pathological examination. Results: All lesions were removed accurately and thoroughly with satisfactory cosmetic outcomes. No clinically significant hematoma developed. Each mass was resected through 9.15±2.70 cores on average over a mean of 11.65±3.88 minutes. Two cases of them were histologically diagnosed as ductal carcinoma in situ and 8 cases were fibroadenoma and 10 cases were adenosis. Conclusions: Ultrasound-guided Mammotome system can profit to diagnose and treat breast calcification lesions which is ultrasound positive. Ultrasound detection rate of microcalcifications is up to the instrument resolution and the operator's experience and patience.