Breast density measured volumetrically in a clinical environment: cross-sectional study with photon counting technology.

OBJECTIVE: Mammographic breast density (BDen), the ratio of glandular volume (GVol) to breast volume (BVol), is the second most prevalent risk factor for breast cancer (BC). Newly developed photon counting technology allows precise and systematic measurements in clinical practice. Our objective is to see how these parameters change with age in women with and without cancer. MATERIALS AND METHODS: This retrospective study analyzed results of BDen, GVol, and BVol in 64,182 mammograms performed with photon counting technology on 32,448 consecutive women from April 2014 to December 2015. Only their first study was included. We excluded women with incomplete data or with breast implants. RESULTS: Mean age of women without BC diagnosed during the study period was 52.1 ± 9.9. BC and was found in 263 women (0.81%). Mean age was 53.0 ± 10.4. BDen, GVol, and BVol were 14%, 24%, and 2% greater in women with BC (P < 0.001 for BDen and GVol and P = 0.02 for BVol). BDen and GVol diminished following similar patterns across age in both groups, with soft slopes before and after a steep drop from 50 to 60, probably due to menopause. CONCLUSION: BDen diminishes with age in women with or without BC, but it is generally higher in women with BC. GVol could be a more robust indicator associated with BC risk than BDen. This technology can ease the way to studies of interventions to diminish BDen (or GVol) in the hope of diminishing BC incidence or predict if longitudinal changes are indicative of impending cancer.

"Are changes in breast density during the menstrual cycle relevant? To what?"

PURPOSE: Cancers can be hidden by high breast density (BDen)- the masking effect (ME). BDen is also a modifiable and highly prevalent breast cancer risk (BCR) factor. The purposes of this study were to determine how much glandular volume (GVol), breast volume (BVol) and their ratio: BDen change during the menstrual cycle, and if these changes could affect ME or be relevant to results of interventional studies aiming to diminish BCR using these parameters as surrogates. METHODS: We retrieved GVol, BVol and BDen data values obtained from 39,997 right mammograms performed with photon counting technique of 19,904 premenopausal women who reported their first day of last menses (FDLM). Many women had more than one study included over the years (with a different FDLM) but were not studied longitudinally. We segregated women by age (yearly), divided the menstrual cycle in 4 weeks, and assigned results with respect to the FDLM. RESULTS: All parameters vary cyclically, with higher values in week 4 (GVol and BDen) or week 1 (BVol). Mean inter-week differences were very small for the three parameters, and diminished with age. However, especially in the youngest women, inter-week differences could be more than 10% for BDen, 15% for GVol, and 50% for BVol. CONCLUSION: Small inter-week mean differences almost certainly rule out relevant changes to ME directly attributable to BDen. However, the possibility of large differences during the menstrual cycle in younger women, who are the ideal targets of interventional studies to diminish BCR, might distort results and should be accounted for.

Changes in breast density during hormone treatment with transdermal estrogens alone or in combination with progesterone.

A retrospective observational study to assess whether hormonal treatment (HT) with transdermal estrogens alone or in combination with micronized progesterone increases breast density and to compare these changes to those of a control group of 4120 patients were not given HT. We included 150 patients whose baseline breast density was assessed with photon-counting spectral mammography and 1 year after hormone treatment. The reduction in breast density was compared using an analysis of covariance. The difference in breast density between mammographies in the HT group was -0.40 ± 5.5 and -0.85 ± 4.2 in the control group. The changes in density according to the type of HT, we found that women on treatment with estrogen alone presented a difference of 0.44 ± 5.8, and -1.35 ± 5 (p = 0.13) in women on combined treatment. After adjusting changes in density for age and average number of days between mammographies, we observed a difference of -0.36 95% confidence intervals (CI) [-1.04 to -0.31] in the women on HT and -0.71 95% CI [-1.65 to -0.21] in the control group. No increased breast density was observed in women on HT treatment, nor did we observe an increase according to HT type. The difference in breast density loss was smaller in the HT group versus the control group.

AI: Can It Make a Difference to the Predictive Value of Ultrasound Breast Biopsy?

(1) Background: This study aims to compare the ground truth (pathology results) against the BI-RADS classification of images acquired while performing breast ultrasound diagnostic examinations that led to a biopsy and against the result of processing the same images through the AI algorithm KOIOS DS TM (KOIOS). (2) Methods: All results of biopsies performed with ultrasound guidance during 2019 were recovered from the pathology department. Readers selected the image which better represented the BI-RADS classification, confirmed correlation to the biopsied image, and submitted it to the KOIOS AI software. The results of the BI-RADS classification of the diagnostic study performed at our institution were set against the KOIOS classification and both were compared to the pathology reports. (3) Results: 403 cases were included in this study. Pathology rendered 197 malignant and 206 benign reports. Four biopsies on BI-RADS 0 and two images are included. Of fifty BI-RADS 3 cases biopsied, only seven rendered cancers. All but one had a positive or suspicious cytology; all were classified as suspicious by KOIOS. Using KOIOS, 17 B3 biopsies could have been avoided. Of 347 BI-RADS 4, 5, and 6 cases, 190 were malignant (54.7%). Because only KOIOS suspicious and probably malignant categories should be biopsied, 312 biopsies would have resulted in 187 malignant lesions (60%), but 10 cancers would have been missed. (4) Conclusions: KOIOS had a higher ratio of positive biopsies in this selected case study vis-à-vis the BI-RADS 4, 5 and 6 categories. A large number of biopsies in the BI-RADS 3 category could have been avoided.

Role of elastography in the assessment of breast lesions: preliminary results.

OBJECTIVES: The purposes of this study were to evaluate the diagnostic utility of elastography in differentiating benign from malignant breast lesions and compare it with conventional sonography. METHODS: A total of 124 breast lesions (59 malignant and 65 benign) were examined with B-mode sonography and subsequently with elastography. Conventional sonographic findings were classified according to the American College of Radiology Breast Imaging Reporting and Data System for sonography, and elastographic images were assigned an elasticity score of 1 to 5 (1-3, benign; 4 and 5, malignant) according to the Ueno classification. Cytologic diagnoses obtained from fine-needle aspiration and histopathologic results from a core-needle biopsy or surgical biopsy were used as reference standards. Statistical analysis included sensitivity, specificity, and positive and negative predictive values for both elastography and conventional sonography. RESULTS: B-mode sonography had sensitivity of 96.6% (95% confidence interval, 93.3%-99.9%), specificity of 76.9% (69.2%-84.6%), a positive predictive value of 79.2% (72.1%-86.2%), and a negative predictive value of 96.2% (92.4%-99.9%), compared with sensitivity of 69.5% (60.5%-78.5%), specificity of 83.1% (76.3%-89.8%), a positive predictive value of 78.9% (70.6%-87.1%), and a negative predictive value of 75.0% (67.4%-82.6%) for elastography. Elastography showed less sensitivity but higher specificity than conventional sonography. CONCLUSIONS: Our results show that elastography may be useful as a complementary technique in addition to conventional sonography in the characterization of breast lesions because it increases the diagnostic specificity, thus reducing the false-positive rate.