Breast Imaging Reporting And Data System Mammography Research Articles

Enhancement Type at Contrast-enhanced Mammography and Association with Malignancy.

Background Despite the increasing use of contrast-enhanced mammography (CEM), there are limited data on the evaluation of findings on recombined images and the association with malignancy. Purpose To determine the rates of malignancy of enhancement findings on CEM images in the presence or absence of low-energy findings using the Breast Imaging Reporting and Data System (BI-RADS) lexicon developed for mammography and MRI. Materials and Methods All diagnostic CEM examinations performed at one academic institution between December 2015 and December 2019 had low-energy and recombined images retrospectively. Data were independently reviewed by three breast imaging radiologists with 5-25 years of experience using the BI-RADS mammography and MRI lexicon. Outcome was determined with pathologic analysis or 1-year imaging or clinical follow-up. The χ2 and Fisher exact tests were used for analysis. Results A total of 371 diagnostic CEM studies were performed in 371 women (mean age, 54 years ± 11[SD]). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value of enhancement on CEM images was 95% (104 of 109 [95% CI: 90, 98]), 67% (176 of 262 [95% CI: 61, 73]), 55% (104 of 190 [95% CI: 47, 62]), and 97% (176 of 181 [95% CI: 94, 99]), respectively. Among 190 CEM studies with enhancing findings, enhancing lesions were more likely to be malignant when associated with low-energy findings (26% vs 59%, P < .001). Among enhancement types, mass enhancement composed 71% (99 of 140) of all malignancies with PPV of 63% when associated with low-energy findings. Foci, non-mass enhancement, and mass enhancement without low-energy findings had PPV of 6%, 24%, and 38%, respectively. Neither background parenchymal enhancement nor density was associated with enhancement type (P = .19 and P = .28, respectively). Conclusion Mass enhancement on recombined images using CEM was most commonly associated with malignancy, especially when associated with low-energy findings. Enhancement types were more likely to be benign when not associated with low-energy findings; however, they should still be viewed with suspicion, given the high association with malignancy. © RSNA, 2022 Online supplemental material is available for this article.

A New Computer-Aided Diagnosis System with Modified Genetic Feature Selection for BI-RADS Classification of Breast Masses in Mammograms.

Mammography remains the most prevalent imaging tool for early breast cancer screening. The language used to describe abnormalities in mammographic reports is based on the Breast Imaging Reporting and Data System (BI-RADS). Assigning a correct BI-RADS category to each examined mammogram is a strenuous and challenging task for even experts. This paper proposes a new and effective computer-aided diagnosis (CAD) system to classify mammographic masses into four assessment categories in BI-RADS. The mass regions are first enhanced by means of histogram equalization and then semiautomatically segmented based on the region growing technique. A total of 130 handcrafted BI-RADS features are then extracted from the shape, margin, and density of each mass, together with the mass size and the patient's age, as mentioned in BI-RADS mammography. Then, a modified feature selection method based on the genetic algorithm (GA) is proposed to select the most clinically significant BI-RADS features. Finally, a back-propagation neural network (BPN) is employed for classification, and its accuracy is used as the fitness in GA. A set of 500 mammogram images from the digital database for screening mammography (DDSM) is used for evaluation. Our system achieves classification accuracy, positive predictive value, negative predictive value, and Matthews correlation coefficient of 84.5%, 84.4%, 94.8%, and 79.3%, respectively. To our best knowledge, this is the best current result for BI-RADS classification of breast masses in mammography, which makes the proposed system promising to support radiologists for deciding proper patient management based on the automatically assigned BI-RADS categories.

Incorporation of contrast-enhanced ultrasound in the differential diagnosis for breast lesions with inconsistent results on mammography and conventional ultrasound.

To identify the efficacy of contrast-enhanced ultrasound (CEUS) in re-evaluating masses with inconsistent Breast Imaging Reporting and Data System (BI-RADS) on mammography (MG) and conventional ultrasound (US). A total of 637 breast lesions were evaluated with MG, US, and CEUS within 6 months and assessed as BI-RADS MG and US. CEUS was used as an additional screening to rerate BI-RADS US according to a five-point system. Lesions were divided into consistent or inconsistent group on the basis of BI-RADS MG and US assessment. The performance of MG, US, and CEUS in the overall and inconsistent group as well as the clinicopathological differences between consistent and inconsistent group were compared using Z test, Mann-Whitney U test, and t-test. The respective AUCs of MG and US were 0.742, 0.843 for overall group and 0.412, 0.789 for inconsistent group. The corresponding values of rerated CEUS BI-RADS were 0.958 and 0.950, which were significantly prior to those of MG and US (p < 0.001). Younger age, negative lymph node status, and dense breast were significantly associated with inconsistent group. Incorporation of CEUS to re-evaluate lesions can improve the diagnostic efficacy comparing to MG or US alone especially when disagreement occurred.

Prediction of benignity or malignancy of a lesion using BI-RADS.

To determine the Positive Predictive Value (PPV) of the Breast Imaging Reporting and Data System (BI-RADS) categories as confirmed by histopathology of localized lesion. An observational study. All patients undergoing mammographic needle localizations for breast lesions from January 2001 to December 2003 were included in the study. The study was conducted at the Radiology Department of Aga Khan University Hospital, Karachi. The medical records of all patients undergoing needle localization during the study period were retrospectively reviewed. In a total of 111 patients, 114 mammographically-guided needle localizations were performed for breast lesions. In all these patients the mammographic finding and BI-RADS category were recorded. Statistical analysis was done on SPSS. Histopathological results of the localized sample were used as a gold standard to calculate the PPV. The PPV for each assessment category was calculated by dividing the number of patients positive for malignancy on histopathological examination by the total number of patients who underwent biopsy for each BI-RADS assessment category. In 114 localizations the histopathologic finding showed 25 (22%) cancers (10 [40%] were ductal carcinoma in situ (DCIS); (15 [60 %] were invasive cancers) and 89 (78 %) benign lesions. All the mammographic lesions were categorized as, 7 (6%) category 0 lesions; 3 (2%) category 1 lesions, and 30 (26%) category 2 lesions; the PPV was 0% for category 0,1,2 (0% of 7,3,30 lesions respectively). There were 18 (16 %) category 3 lesions; the PPV was 5% (1 of 18 lesions). One case of cancer in this group was DCIS. There were 50 (44%) category 4 lesions; the PPV was 34% (17 of 50 lesions). There were 6 (5%) category 5 lesions; the PPV was 83% (5 of 6 lesions). The number of biopsies performed for benign lesion can be reduced by using BI-RADS categories, as it has a good PPV.