Contrast-enhanced tomosynthesis: The best of both worlds or more of the same?

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Purpose To investigate the combination of mammography radiomics and quantitative three-compartment breast (3CB) image analysis of dual-energy mammography to limit unnecessary benign breast biopsies. Materials and Methods For this prospective study, dual-energy craniocaudal and mediolateral oblique mammograms were obtained immediately before biopsy in 109 women (mean age, 51 years; range, 31-85 years) with Breast Imaging Reporting and Data System category 4 or 5 breast masses (35 invasive cancers, 74 benign) from 2013 through 2017. The three quantitative compartments of water, lipid, and protein thickness at each pixel were calculated from the attenuation at high and low energy by using a within-image phantom. Masses were automatically segmented and features were extracted from the low-energy mammograms and the quantitative compartment images. Tenfold cross-validations using a linear discriminant classifier with predefined feature signatures helped differentiate between malignant and benign masses by means of (a) water-lipid-protein composition images alone, (b) mammography radiomics alone, and (c) a combined image analysis of both. Positive predictive value of biopsy performed (PPV3) at maximum sensitivity was the primary performance metric, and results were compared with those for conventional diagnostic digital mammography. Results The PPV3 for conventional diagnostic digital mammography in our data set was 32.1% (35 of 109; 95% confidence interval [CI]: 23.9%, 41.3%), with a sensitivity of 100%. In comparison, combined mammography radiomics plus quantitative 3CB image analysis had PPV3 of 49% (34 of 70; 95% CI: 36.5%, 58.9%; P < .001), with a sensitivity of 97% (34 of 35; 95% CI: 90.3%, 100%; P < .001) and 35.8% (39 of 109) fewer total biopsies (P < .001). Conclusion Quantitative three-compartment breast image analysis of breast masses combined with mammography radiomics has the potential to reduce unnecessary breast biopsies. © RSNA, 2018 Online supplemental material is available for this article.
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Purpose: To compare the diagnostic performance of digital breast tomosynthesis (DBT) and digital mammography (DM) for breast cancers. Materials and methods: Fifty-seven female patients with pathologically proved breast cancer were enrolled. Three readers gave a subjective assessment superiority of the index lesions (mass, focal asymmetry, architectural distortion, or calcifications) and a forced BIRADS score, based on DM reading alone and with additional DBT information. The relevance between BIRADS category and index lesions of breast cancer was compared by chi-square test. Result: A total of 59 breast cancers were reviewed, including 17 (28.8%) mass lesions, 12 (20.3%) focal asymmetry/density, 6 (10.2%) architecture distortion, 23 (39.0%) calcifications, and 1 (1.7%) intracystic tumor. Combo DBT was perceived to be more informative in 58.8% mass lesions, 83.3% density, 94.4% architecture distortion, and only 11.6% calcifications. As to the forced BIRADS score, 84.4% BIRADS 0 on DM was upgraded to BIRADS 4 or 5 on DBT, whereas only 27.3% BIRADS 4A on DM was upgraded on DBT, as BIRADS 4A lesions were mostly calcifications. A significant P value (<0.001) between the BIRADS category and index lesions was noted. Conclusion: Adjunctive DBT gives exquisite information for mass lesion, focal asymmetry, and/or architecture distortion to improve the diagnostic performance in mammography.
Purpose: To compare the diagnostic accuracy of contrast-enhanced digital mammography (CEDM) and contrast-enhanced tomosynthesis (CET) to dynamic contrast enhanced breast MRI (DCE-MRI) using a multireader-multicase study. Methods: Institutional review board approval and informed consents were obtained. Total 185 patients (mean age 51.3) with BI-RADS 4 or 5 lesions were evaluated before biopsy with mammography, tomosynthesis, CEDM, CET and DCE-MRI. Mediolateral-oblique and cranio-caudal views of the target breast CEDM and CET were acquired at 2 and 4min after contrast agent injection. A mediolateral-oblique view of the non-target breast was taken at 6min. Each lesion was scored with forced BI-RADS categories by three readers. Each reader interpreted lesions in the following order: mammography, tomosynthesis, CEDM, CET, and DCE-MRI during a single reading session. Results: Histology showed 81 cancers and 144 benign lesions in the study. Of the 81 malignant lesions, 44% (36/81) were invasive and 56% (45/81) were non-invasive. Areas under the ROC curve, averaged for the 3 readers, were as follows: 0.897 for DCE-MRI, 0.892 for CET, 0.878 for CEDM, 0.784 for tomosynthesis and 0.740 for mammography. Significant differences in AUC were found between the group of contrast enhanced modalities (CEDM, CET, DCE-MRI) and the unenhanced modalities (all p<0.05). No significant differences were found in AUC between DCE-MRI, CET and CEDM (all p>0.05). Conclusion: CET and CEDM may be considered as an alternative modality to MRI for following up women with abnormal mammography. All three contrast modalities were superior in accuracy to conventional digital mammography with or without tomosynthesis.