Background Mammography is currently the modality of choice for mass screening of breast cancer, although its sensitivity is low in dense breasts. Besides, higher breast density has been identified as independent risk factor so it has been conceptualized that women with dense breasts should be encouraged for supplemental screening. In this study, we aimed to estimate the distribution of volumetric breast density using fully automated Volpara software and to analyze the level of agreement between volumetric density grades and Breast Imaging Reporting and Data System (BI-RADS) density grades. We also aim to estimate the distribution of breast cancer in different VDG and to find a correlation between VDG and risk of malignancy. Results VDG-c was most common followed by VDG-b and BIRADS grade B was commonest followed by grade C. The density distribution was found inversely related to the age. Level of agreement between VDG and BIRADS grades was moderate (κ = 0.5890). Statistically significant correlation was noted between VDG-c and d for risk of malignancy (p < 0.001). Conclusion Difficulties associated with the use of BI-RADS density categories may be avoided if assessed using a fully automated volumetric method. High VDG can be considered as independent risk factor for malignancy. Thus, awareness of a woman’s breast density might be useful in determining the frequency and imaging modality for screening.

Introduction: Microcalcification (MC) is an effective and sometimes the only indicator of breast cancer. Early detection and characterisation of malignant MC can facilitate early diagnosis and timely treatment of breast cancer. However, due to the small size and low contrast as compared to the background parenchyma, it is difficult and time-consuming for radiologists to accurately evaluate MC. Aim: To compare the diagnostic abilities of Full Field Digital Mammography (FFDM) and Digital Breast Tomosynthesis (DBT) in the detection and characterisation of breast calcifications. Materials and Methods: This retrospective descriptive study was conducted in the year 2022 at the breast imaging unit of Dr. Ram Manohar Lohia Institute of Medical Sciences, Lucknow, Uttar Pradesh, India and data of patients who had undergone FFDM and DBT between March 2019- September 2020 was collected. Mammograms of 702 women with 1217 breasts were evaluated and MC was detected in 622 breasts. Based on the morphology and distribution pattern, Breast Imaging Reporting and Data System (BI-RADS) assessment Category was assigned from 2 to 5. Cases with BI-RADS 2 and 3 were followed-up by repeat Mammograms at 6-month to 1-year intervals. Cases with BI-RADS 4 and 5 were biopsied under stereotactic or ultrasound guidance. Histopathology findings and the stability of the calcifications on sequential mammograms were considered the gold standard for final BI-RADS categorisation. The Chi-square test was applied for the comparison of FFDM and DBT. Results: Typically benign morphology MC was noted in 508 (81.67%) of breasts on FFDM and 505 (80.67%) on DBT. Suspicious morphology MC was noted in 114 (18.33%) of breasts on FFDM and 121 (19.33%) on DBT. Vascular calcification was the most common benign MC seen in 233 cases (37.45%) on FFDM and 244 cases (38.9%) on DBT. Similarly, fine pleomorphic was the most common suspicious morphology MC on FFDM and DBT both seen in 47 cases (7.5%) and 44 cases (7.02%), respectively. The most common distribution pattern was diffuse seen in 582 cases (93.56%) on FFDM and 583 cases (93.13%) on DBT, respectively. No significant difference was observed (p=0.283) in the rate of detection or characterisation of MC by FFDM or DBT. The sensitivity of both modalities were almost similar (97.7% and 97.9%) without any significant difference (p=0.278). Similarly, there was no difference in the specificity (94.9% and 94.4%, respectively, p=0.289). Conclusion: The performance of FFDM and DBT for the detection and characterisation of MC is not significantly different.

Background Mammography is the primary imaging modality for diagnosing breast cancer in women more than 40 years of age. Digital breast tomosynthesis (DBT), when supplemented with digital mammography (DM), is useful for increasing the sensitivity and improving BIRADS characterization by removing the overlapping effect. Ultrasonography (US), when combined with the above combination, further increases the sensitivity and diagnostic confidence. Since most of the research regarding tomosynthesis has been in screening settings, we wanted to quantify its role in diagnostic mammography. The purpose of this study was to assess the performance of DM alone vs. DM combined with DBT vs. DM plus DBT and ultrasound in diagnosing malignant breast neoplasms with the gold standard being histopathology or cytology. Results A prospective study of 1228 breasts undergoing diagnostic or screening mammograms was undertaken at our institute. Patients underwent 2 views DM, single view DBT and US. BIRADS category was updated after each step. Final categorization was made with all three modalities combined and pathological correlation was done for those cases in which suspicious findings were detected, i.e. 256 cases. Diagnosis based on pathology was done for 256 cases out of which 193 (75.4%) were malignant and the rest 63 (24.6%) were benign. The diagnostic accuracy of DM alone was 81.1%. Sensitivity, Specificity, PPV and NPV were 87.8%, 60%, 81.3% and 61.1%, respectively. With DM + DBT the diagnostic accuracy was 84.8%. Sensitivity, Specificity, PPV and NPV were 92%, 56.5%, 89% and 65%, respectively. The diagnostic accuracy of DM + DBT + US was found to be 85.1% and Sensitivity, Specificity, PPV and NPV were 96.3%, 50.7%, 85.7% and 82%, respectively. Conclusion The combination of DBT to DM led to higher diagnostic accuracy, sensitivity and PPV. The addition of US to DM and DBT further increased the sensitivity and diagnostic accuracy and significantly increased the NPV even in diagnostic mammograms and should be introduced in routine practice for characterizing breast neoplasms.

Background Mammographic breast density is acknowledged as an independent risk factor for breast cancer. Its association with different pathological types and tumors markers is still under evaluation. This study aims to assess the associations of volumetric density grades (VDG) with breast cancer risk in premenopausal and postmenopausal age groups separately. We also aim to assess the association of VDG with hormone receptor status and breast cancer subtypes defined by histology and tumor markers (ER, PR, Her 2-neu and Ki 67). Results This retrospective study was done with inclusion of two comparable groups of 185 breast cancer cases and 244 healthy controls. These groups were further divided into pre‑ and postmenopausal subgroups. Mammograms of the cases and controls were evaluated by fully automated volumetric breast density software-VOLPARA and classified into four VDG. The hormone receptor status and breast cancer subtypes defined by histological features and tumor markers in the various VDG were also evaluated. The risk of developing carcinoma was significantly higher in women with high-density breasts (VDG-c + VDG-d) as compared with low-density breasts (VDG-a + VDG-b) in both premenopausal and postmenopausal subgroups. No significant difference was seen in the histopathological characteristics of breast cancer among various VDG. Conclusions Our study suggests positive association between high VDG and risk of cancer in both premenopausal and postmenopausal group of Indian women. The hormone receptor status and breast cancer subtypes defined by histology and tumor markers did not reveal any relation to the grades of breast density.

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