Evaluation of breast amorphous calcifications by a computer-aided detection system in full-field digital mammography

Abstract

Objectives: The purpose of this study was to evaluate the performance of a direct computer-aided detection (d-CAD) system integrated with full-field digital mammography (FFDM) in assessment of amorphous calcifications. Methods: From 1438 consecutive stereotactic-guided biopsies, FFDM images with amorphous calcifications were selected for retrospective evaluation by d-CAD in 122 females (mean age, 56 years; range, 35-84 years). The sensitivity, specificity, accuracy and false-positive rate of the d-CAD system were calculated in the total group of 124 lesions and in the subgroups based on breast density, mammographic lesion distribution and extension. Logistic regression analysis was used to stratify the risk of malignancy by patient risk factors and age. Results: The d-CAD marked all (36/36) breast cancers, 85% (11/13) of the high-risk lesions and 80% (60/75) of benign amorphous calcifications (p,0.01) correctly. The sensitivity, specificity and diagnostic accuracy for the combined malignant and ''highrisk'' lesions was 96, 80 and 86%, respectively. The likelihood of malignancy was 29%. There was no significant difference between the marking of fatty or dense breasts (p.0.05); however, d-CAD marks showed differences for small (,7 mm) lesions (p50.02) and clustered calcifications (p50.03). The false-positive rate of d-CAD was 1.76 marks per full examination. Conclusion: The d-CAD system correctly marked all biopsy-proven breast cancers and a large number of biopsy-proven high-risk lesions that presented as amorphous calcifications. Given our 29% likelihood of malignancy, imaging-guided biopsy appears to be a reasonable recommendation in cases of amorphous calcifications marked by d-CAD.

Computer-aided detection system for clustered microcalcifications in digital breast tomosynthesis using joint information from volumetric and planar projection images

“…Nevertheless, all cases in the test set had BI-RADS assessments of 4 or 5 that are the targets of interest for a CAD system for breast cancer screening. Furthermore, we believe that the test performance would not be optimistic because malignant clusters, on average, were detected with higher sensitivity than benign clusters as observed in previous studies (Scaranelo et al , 2014; Ge et al , 2007; Sahiner et al , 2012; Bria et al , 2014). …”

Detection rate of breast malignancy of needle localization biopsy of breast microcalcification

“…Mammography is an extremely sensitive tool for the detection of microcalcifications. Distinguishing benign calcifications from malignant may sometimes be challenging; therefore, the specificity of mammography for lesions remains low [ 14 ]. Only 20%–30% of cases suspected to be malignant are eventually determined to have breast cancer based on mammography-guided needle localization and surgical excision [ 15 16 ].…”

Diagnostic Performance of Artificial Intelligence-Based Computer-Aided Diagnosis for Breast Microcalcification on Mammography

“…Detection of microcalcification on mammography results in a diagnosis of malignancy in up to 0.3% of women screened. Previous computeraided detection systems were able to detect microcalcifications on mammography [11,12] with improved sensitivity for calcification ranging from 80 to 100% [9,10,12]; however, they also increased false-positive rates [13]. The reported positive predictive value for malignancy of suspicious microcalcifications ranged between 15.9 and 90.6% [14,15]; thus, many benign microcalcifications were biopsied.…”