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BACKGROUND: High breast density found using mammographs (MGs) reduces positivity rates and is considered a risk factor for breast cancer. Research on the relationship between Volpara density grade (VDG) and compressed breast thickness (CBT) in the Japanese population is still lacking. Moreover, little attention has been paid to pseudo-dense breasts with CBT < 30 mm among high-density breasts. We investigated VDG, CBT, and apparent high breast density in patients with breast cancer. METHODS: Women who underwent MG and breast cancer surgery at our institution were included. VDG and CBT were measured. VDG was divided into a non-dense group (NDG) and a dense group (DG). RESULTS: This study included 419 patients. VDG was negatively correlated with CBT. The DG included younger patients with lower body mass index (BMI) and thinner CBT. In the DG, patients with CBT < 30 mm had lower BMI and higher VDG; however, no significant difference was noted in the positivity rate of the two groups. CONCLUSIONS: Younger women tend to have higher breast density, resulting in thinner CBT, which may pose challenges in detecting breast cancer on MGs. However, there was no significant difference in the breast cancer detection rate between CBT < 30 mm and CBT ≥ 30 mm.

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BACKGROUND: Higher mammographic density (MD), a radiological measure of the proportion of fibroglandular tissue in the breast, and lower terminal duct lobular unit (TDLU) involution, a histological measure of the amount of epithelial tissue in the breast, are independent breast cancer risk factors. Previous studies among predominantly white women have associated reduced TDLU involution with higher MD. METHODS: In this cohort of 611 invasive breast cancer patients (ages 23-91 years [58.4% ≥ 50 years]) from China, where breast cancer incidence rates are lower and the prevalence of dense breasts is higher compared with Western countries, we examined the associations between TDLU involution assessed in tumor-adjacent normal breast tissue and quantitative MD assessed in the contralateral breast obtained from the VolparaDensity software. Associations were estimated using generalized linear models with MD measures as the outcome variables (log-transformed), TDLU measures as explanatory variables (categorized into quartiles or tertiles), and adjusted for age, body mass index, parity, age at menarche and breast cancer subtype. RESULTS: We found that, among all women, percent dense volume (PDV) was positively associated with TDLU count (highest tertile vs. zero: Expbeta = 1.28, 95% confidence interval [CI] 1.08-1.51, ptrend = < .0001), TDLU span (highest vs. lowest tertile: Expbeta = 1.23, 95% CI 1.11-1.37, ptrend = < .0001) and acini count/TDLU (highest vs. lowest tertile: Expbeta = 1.22, 95% CI 1.09-1.37, ptrend = 0.0005), while non-dense volume (NDV) was inversely associated with these measures. Similar trend was observed for absolute dense volume (ADV) after the adjustment of total breast volume, although the associations for ADV were in general weaker than those for PDV. The MD-TDLU associations were generally more pronounced among breast cancer patients ≥ 50 years and those with luminal A tumors compared with patients < 50 years and with luminal B tumors. CONCLUSIONS: Our findings based on quantitative MD and TDLU involution measures among Chinese breast cancer patients are largely consistent with those reported in Western populations and may provide additional insights into the complexity of the relationship, which varies by age, and possibly breast cancer subtype.

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PURPOSE: Dense breast (DB) is recognized as a breast cancer (BC) risk factor. Although DB is common in Japanese women, the incidence of BC is lower than in Caucasians. We evaluated whether DB is a risk factor or whether there are other risk factors for BC in Japanese women. MATERIALS AND METHODS: We retrospectively analyzed 635 BC patients and 999 controls who received a mammography at our hospital between February 2019 and March 2021. Volumetric breast density percentage (VBD%), breast volume (BV), and fibroglandular volume (FGV) were measured using Volpara™, an automated, three-dimensional image analysis program. A VBD% of 7.5% or higher was classified as DB. The association between the VBD%, BV, and FGV, and BC risk were assessed using logistic regression. RESULTS: Of the BC group and the control group, 77% and 79% had DB. The stratified FGV was positively associated with BC risk (odds ratio: 2.84; 95% confidence interval 1.58-5.12; P < 0.001). No significant association was found between either the VBD% or BV and BC risk. CONCLUSION: The proportion of Japanese women with DB was high, suggesting that DB might not be significantly associated with BC risk. However, our results also suggested that the FGV may be related to BC risk in Japanese women.

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Dense breasts are a risk factor for breast cancer. Assessment of breast density is important and radiologist-dependent. We objectively measured mammographic density using the three-dimensional automatic mammographic density measurement device Volpara™ and examined the criteria for combined use of ultrasonography (US). Of 1227 patients who underwent primary breast cancer surgery between January 2019 and April 2021 at our hospital, 441 were included. A case series study was conducted based on patient age, diagnostic accuracy, effects of mammography (MMG) combined with US, size of invasion, and calcifications. The mean density of both breasts according to the Volpara Density Grade (VDG) was 0-3.4% in 2 patients, 3.5-7.4% in 55 patients, 7.5-15.4% in 173 patients, and ≥15.5% in 211 patients. Breast density tended to be higher in younger patients. Diagnostic accuracy of MMG tended to decrease with increasing breast density. US detection rates were not associated with VDG on MMG and were favorable at all densities. The risk of a non-detected result was high in patients without malignant suspicious calcifications. Supplementary use of US for patients without suspicious calcifications on MMG and high breast density, particularly ≥25.5%, could improve the breast cancer detection rate.

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In order to find a consistent, simple and time-efficient method of assessing mammographic breast density (MBD), different methods of assessing density comparing subjective, quantitative, semi-subjective and semi-quantitative methods were investigated. Subjective MBD of anonymized mammographic cases (n = 250) from a national breast-screening programme was rated by 49 radiologists from two countries (UK and USA) who were voluntarily recruited. Quantitatively, three measurement methods, namely VOLPARA, Hand Delineation (HD) and ImageJ (IJ) were used to calculate breast density using the same set of cases, however, for VOLPARA only mammographic cases (n = 122) with full raw digital data were included. The agreement level between methods was analysed using weighted kappa test. Agreement between UK and USA radiologists and VOLPARA varied from moderate (κw = 0.589) to substantial (κw = 0.639), respectively. The levels of agreement between USA, UK radiologists, VOLPARA with IJ were substantial (κw = 0.752, 0.768, 0.603), and with HD the levels of agreement varied from moderate to substantial (κw = 0.632, 0.680, 0.597), respectively. This study found that there is variability between subjective and objective MBD assessment methods, internationally. These results will add to the evidence base, emphasising the need for consistent, simple and time-efficient MBD assessment methods. Additionally, the quickest method to assess density is the subjective assessment, followed by VOLPARA, which is compatible with a busy clinical setting. Moreover, the use of a more limited two-scale system improves agreement levels and could help minimise any potential country bias.

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OBJECTIVE: We aimed to compare visual and quantitative measurements of breast density and to reveal the density profile with compression characteristics. MATERIALS AND METHODS: Screening mammograms of 1399 women between May 2014 and May 2015 were evaluated by using Volpara 4th and 5th version. First 379 mammograms were assessed according to ACR BI-RADS 4th edition and compared to Volpara. We categorized the breast density in two subgroups as dens or non-dens. Two radiologists reviewed the images in consensus. Agreement level between visual and volumetric methods and volumetric methods between themselves assessed using weighted kappa statistics. Volpara data such as fibroglandular volume (FGV), breast volume (BV), compression thickness (CT), compression force (CF), compression pressure (CP) were also analyzed with relation to the age. RESULTS: 1399 mammograms were distributed as follows: 12.7% VDG1, 39.3% VDG2, 34.1% VDG3, 13.9% VDG4 according to the 4th edition of Volpara; 1.2% VDG1, 46% VDG2, 36.8% VDG3, 15.9% VDG4 according to the 5th edition of Volpara. The difference between two editions was 4.7% increase in dense category. 379 mammograms, according to ACR BI-RADS 4th edition, were distributed as follows: 25.9% category A, 50.9% category B, 19.8% category C, 3.4% category D. The strength of agreement between the Volpara 4th and 5th editions was found substantial (k=0.726). The agreements between visual assessment and both Volpara editions were poor (k=-0.413, k=-0.399 respectively). There was a 142% increase in dense group with the VDG 4th edition and 162% with the VDG 5th edition when compared to visual assessment. Compression force decreased while compression pressure increased with increasing Volpara Density Grade (VDG) (p for trend <0.001 for both). Compression thickness and breast volume decreased with increasing VDG (p for trend <0.001 for both). The FGV decreases with age and the breast volume increases with increasing age (p<0.001). CONCLUSION: Visual assessment of breast density doesn't correlate well with volumetric assessments. Obtaining additional information about physical parameters and breast profile by the results of quantified methods is important for breast cancer risk assessments and prevention strategies.

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INTRODUCTION: The aim of this study was to investigate mammographic density in a sample of Victorian women and explore a possible association between mammographic density and ethnicity. METHODS: Categories of mammographic density, using Volpara Density Grade, were reported using two editions of Volpara automated software in a data set of women attending two Victorian sites for mammographic screening. The variables available for analysis were age, self-reported exposure to menopausal hormone therapy (MHT) and ethnicity based on country of birth. RESULTS: Data from 16,943 women were available for analysis. Using the VDG 4th edition, 40% of women were classified in the higher two categories (42% for the 5th edition) and 76.9% of women were in the same VDG category using both systems. In the sample, 87.7% of women were in the age range currently invited for screening in Victoria (50-74 years). Of the total group, 82.5% could be classified on the basis of country of birth. In multivariable logistic regression analyses examining factors associated with higher VDG, age (protective), use of MHT (risk factor) and being born in a country with predominantly Asian ancestry (risk factor) were all statistically significant at P < 0.001 for both editions irrespective of whether the reference category was the lowest two or three VDG categories. CONCLUSIONS: Mammographic density as assessed by VDG was positively associated with ever exposure to MHT and inversely associated with age. Being born in a country with predominantly Asian ancestry was associated with higher VDG when controlled for age and MHT exposure.

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BACKGROUND: Mammographic density has been shown to be a strong independent predictor of breast cancer and a causative factor in reducing the sensitivity of mammography. There remain questions as to the use of mammographic density information in the context of screening and risk management, and of the association with cancer in populations known to be at increased risk of breast cancer. AIM: To assess the association of breast density with presence of cancer by measuring mammographic density visually as a percentage, and with two automated volumetric methods, Quantra™ and VolparaDensity™. METHODS: The TOMosynthesis with digital MammographY (TOMMY) study of digital breast tomosynthesis in the Breast Screening Programme of the National Health Service (NHS) of the United Kingdom (UK) included 6020 breast screening assessment cases (of whom 1158 had breast cancer) and 1040 screened women with a family history of breast cancer (of whom two had breast cancer). We assessed the association of each measure with breast cancer risk in these populations at enhanced risk, using logistic regression adjusted for age and total breast volume as a surrogate for body mass index (BMI). RESULTS: All density measures showed a positive association with presence of cancer and all declined with age. The strongest effect was seen with Volpara absolute density, with a significant 3% (95% CI 1-5%) increase in risk per 10 cm3 of dense tissue. The effect of Volpara volumetric density on risk was stronger for large and grade 3 tumours. CONCLUSIONS: Automated absolute breast density is a predictor of breast cancer risk in populations at enhanced risk due to either positive mammographic findings or family history. In the screening context, density could be a trigger for more intensive imaging.

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PURPOSE: Subjective methods of mammographic breast density (MBD) assessment are prone to inter-reader variability. This work aims to assess the impact of a short self-directed, experiential learning intervention on radiographers' reproducibility of MBD assessment. METHOD: The study used two sets of images (test and learning intervention) containing left craniocaudal and left mediolateral oblique views. The test set had MBD ratings from Volpara™ and radiologists using the fourth edition Breast Imaging and Data Systems (BI-RADS®). Seven radiographers rated the MBD of the test set before and after a self-directed learning intervention using the percentage descriptors in the fourth edition BI-RADS® Atlas. The inter-reader agreement, the agreement between radiographers and Volpara™ as well as radiologists, was assessed using a Weighted Kappa (кw). RESULTS: Overall, radiographers' inter-reader agreement (кw) was substantial (0.79; 95% CI: 0.70-0.87) before the intervention and almost perfect (0.84; 95% CI: 0.77-0.90) after the intervention. Before the intervention, radiographers demonstrated fair agreement with radiologists (0.24; 95% CI: -0.46-0.61) and Volpara™ (0.24; 95% CI: -0.41-0.59). A fair but slightly improved agreement was also observed between radiographers and radiologists (0.31; 95% CI: -0.33-0.64) as well as Volpara™ (0.28; 95% CI: -0.34-0.61) after the intervention. CONCLUSION: Findings demonstrate that a short duration self-directed, experiential learning intervention reduces inter-reader differences in MBD classification, but has a negligible impact on improving the agreement between inexperienced and expert readers.

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PURPOSE: The aim of this paper is to evaluate the spatial glandular volumetric tissue distribution as well as the density measures provided by Volpara™ using a dataset composed of repeated pairs of mammograms, where each pair was acquired in a short time frame and in a slightly changed position of the breast. MATERIALS AND METHODS: We conducted a retrospective analysis of 99 pairs of repeatedly acquired full-field digital mammograms from 99 different patients. The commercial software Volpara™ Density Maps (Volpara Solutions, Wellington, New Zealand) is used to estimate both the global and the local glandular tissue distribution in each image. The global measures provided by Volpara™, such as breast volume, volume of glandular tissue, and volumetric breast density are compared between the two acquisitions. The evaluation of the local glandular information is performed using histogram similarity metrics, such as intersection and correlation, and local measures, such as statistics from the difference image and local gradient correlation measures. RESULTS: Global measures showed a high correlation (breast volume R=0.99, volume of glandular tissue R=0.94, and volumetric breast density R=0.96) regardless the anode/filter material. Similarly, histogram intersection and correlation metric showed that, for each pair, the images share a high degree of information. Regarding the local distribution of glandular tissue, small changes in the angle of view do not yield significant differences in the glandular pattern, whilst changes in the breast thickness between both acquisition affect the spatial parenchymal distribution. CONCLUSIONS: This study indicates that Volpara™ Density Maps is reliable in estimating the local glandular tissue distribution and can be used for its assessment and follow-up. Volpara™ Density Maps is robust to small variations of the acquisition angle and to the beam energy, although divergences arise due to different breast compression conditions.

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BACKGROUND: Breast density often affects cancer detection via mammography (MMG). Because of this, additional tests are recommended for women with dense breasts. This study aimed to reveal trends in breast density among Japanese women and determine whether differences in breast density differentially affected the detection of abnormalities via MMG. METHODS: We retrospectively analyzed 397 control women who underwent MMG screening as well as 269 patients who underwent surgery for breast cancer for whom preoperative MMG data were available. VolparaDensity™ (Volpara), a three-dimensional image analysis software with high reproducibility, was used to calculate breast density. Breasts were categorized according to the volumetric density grade (VDG), a measure of the percentage of dense tissue. The associations between age, VDG, and MMG density categories were analyzed. RESULTS: In the control group, 78% of women had dense breasts, while in the breast cancer group, 87% of patients had dense breasts. One of 36 patients with non-dense breasts (2.7%) was classified as category 1 or 2 (C-1 or C-2), indicating that abnormal findings could not be detected by MMG. The proportion of patients with breast cancer who had dense breasts and were classified as C-1 or C-2 was as high as 22.3%. CONCLUSIONS: The proportions of Japanese women with dense breasts were high. In addition, the false-negative rate for women with dense breasts was also high. Owing to this, Japanese women with dense breasts may need to commonly undergo additional tests to ensure detection of breast cancer in the screening MMG.

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Personalised breast screening requires assessment of individual risk of breast cancer, of which one contributory factor is weight. Self-reported weight has been used for this purpose, but may be unreliable. We explore the use of volume of fat in the breast, measured from digital mammograms. Volumetric breast density measurements were used to determine the volume of fat in the breasts of 40,431 women taking part in the Predicting Risk Of Cancer At Screening (PROCAS) study. Tyrer-Cuzick risk using self-reported weight was calculated for each woman. Weight was also estimated from the relationship between self-reported weight and breast fat volume in the cohort, and used to re-calculate Tyrer-Cuzick risk. Women were assigned to risk categories according to 10 year risk (below average <2%, average 2-3.49%, above average 3.5-4.99%, moderate 5-7.99%, high ≥8%) and the original and re-calculated Tyrer-Cuzick risks were compared. Of the 716 women diagnosed with breast cancer during the study, 15 (2.1%) moved into a lower risk category, and 37 (5.2%) moved into a higher category when using weight estimated from breast fat volume. Of the 39,715 women without a cancer diagnosis, 1009 (2.5%) moved into a lower risk category, and 1721 (4.3%) into a higher risk category. The majority of changes were between below average and average risk categories (38.5% of those with a cancer diagnosis, and 34.6% of those without). No individual moved more than one risk group. Automated breast fat measures may provide a suitable alternative to self-reported weight for risk assessment in personalized screening.

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OBJECTIVE: To determine the association between serum 25 hydroxyvitamin D levels and percent breast density among asymptomatic premenopausal women. METHODS: Hundred asymptomatic, pre-menopausal women who visited the General Surgery Breast Clinic, Patel Hospital, Karachi, Pakistan between 3rd March and 10th November, 2015 were included in this study. The serum 25 (OH)D and calcium levels were measured and mammographic density (MD) was assessed using automated volumetric breast density software, Volpara Research (algorithm version 1.5.1, Volpara solutions Ltd, Wellington, NZ) on the same day. The volumetric breast density (VBD) was categorized as; VG1: 0% - 4.5 %; VG2: 4.6% - 7.5%; VG3: 7.6% - 15.5% and VG4 >15.5%. Mean serum 25(OH)D and calcium levels were compared across the four volumetric breast density categories. The percent volumetric density was also correlated with anthropometric measurements and other related variables. RESULTS: No significant difference was found in mean serum 25 (OH)D level across the four groups (15.87 Vs. 12.40 Vs. 8.99 Vs. 9.68; p-value = 0.106). The percent VBD were found significantly negatively correlated with age (r = - 0.365; p-value = 0.001), weight (r = - 0.575; p-value = 0.001), height (r = - 0.197; p-value = 0.049), and BMI (r = - 0.519; p-value = 0.001). The serum Vitamin D, and calcium levels were not found significantly correlated with percent VBD (p-value > 0.05). CONCLUSION: No significant association exists between serum 25(OH)D level and breast density.

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INTRODUCTION: The aim of this study was to evaluate observer variability in mammographic density assessment as measured using the Royal Australian and New Zealand College of Radiologists (RANZCR) synoptic scales. Visual assessment of mammographic density by radiologists is commonly used in clinical practice; however, these assessments have been shown to be more subjective than quantitative methods. METHODS: The study included 40 cases of left cranial-caudal (CC) and mediolateral oblique (MLO) radiographs from 20 women. RANZCR-registered radiologists (n = 26) estimated mammographic breast density of the same images according to RANZCR synoptic scales 1-4. All images had their volumetric density classified using Volpara Density Grade (VDG) and Average Volumetric Breast Density percentage (AvBD%). RESULTS: The results showed that the radiologists sampled had specialized for 17.18 years (sd 12.03) and read 2072 (sd 2441) mammograms per year on average. Inter-observer agreement using RANZCR synoptic scales had an average Kappa of 0.360; (95% CI = 0.308-0.412) and a range of 0.078-0.499. Radiologists estimated percentage density was lower by 0.37 than VDG, with their mean being 2.18 and the mean VDG was 2.55 (Z = -3.873; P < 0.001). VDG and RANZCR showed a positive strong correlation (ρ = 0.898; P < 0.001). AvBD% and RANZCR also showed a positive strong correlation (ρ = 0.904; P < 0.001). CONCLUSION: The inter-observer agreement with RANZCR synoptic scales was fair. Wide inter-observer variability was observed. Continued research on appropriate assessment methods for mammographic density assessment is required to avoid unnecessary variations.

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RATIONALE AND OBJECTIVES: To investigate agreement on mammographic breast density (MD) assessment between automated volumetric software and Breast Imaging Reporting and Data System (BIRADS) categorization by expert radiologists. MATERIALS AND METHODS: Forty cases of left craniocaudal and mediolateral oblique mammograms from 20 women were used. All images had their volumetric density classified using Volpara density grade (VDG) and average volumetric breast density percentage. The same images were then classified into BIRADS categories (I-IV) by 20 American Board of Radiology examiners. RESULTS: The results demonstrated a moderate agreement (κ = 0.537; 95% CI = 0.234-0.699) between VDG classification and radiologists' BIRADS density assessment. Interreader agreement using BIRADS also demonstrated moderate agreement (κ = 0.565; 95% CI = 0.519-0.610) ranging from 0.328 to 0.669. Radiologists' average BIRADS was lower than average VDG scores by 0.33, with their mean being 2.13, whereas the mean VDG was 2.48 (U = -3.742; P < 0.001). VDG and BIRADS showed a very strong positive correlation (ρ = 0.91; P < 0.001) as did BIRADS and average volumetric breast density percentage (ρ = 0.94; P < 0.001). CONCLUSIONS: Automated volumetric breast density assessment shows moderate agreement and very strong correlation with BIRADS; interreader variations still exist within BIRADS. Because of the increasing importance of MD measurement in clinical management of patients, widely accepted, reproducible, and accurate measures of MD are required.

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Mammographic density (MD) is a significant risk factor for breast cancer and has been shown to reduce the sensitivity of mammography screening. Knowledge of a woman's density can be used to predict her risk of developing breast cancer and personalize her imaging pathway. However, measurement of breast density has proven to be troublesome with wide variations in density recorded using radiologists' visual Breast Imaging Reporting and Data System (BIRADS). Several automated methods for assessing breast density have been proposed, each with their own source of measurement error. The use of differing mammographic imaging systems further complicates MD measurement, especially for the same women imaged over time. The purpose of this study was to investigate whether having a mammogram on differing manufacturer's equipment affects a woman's MD measurement. Raw mammographic images were acquired on two mammography imaging systems (General Electric and Hologic) one year apart and processed using VolparaDensity™ to obtain the Volpara Density Grade (VDG) and average volumetric breast density percentage (AvBD%). Visual BIRADS scores were also obtained from 20 expert readers. BIRADS scores for both systems showed strong positive correlation ([Formula: see text]; [Formula: see text]), while the VDG ([Formula: see text]; [Formula: see text]) and AvBD% ([Formula: see text]; [Formula: see text]) showed stronger positive correlations. Substantial agreement was shown between the systems for BIRADS ([Formula: see text]; [Formula: see text]), however, the systems demonstrated an almost perfect agreement for VDG ([Formula: see text]; [Formula: see text]).

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BACKGROUND: Volumetric breast density analysis is useful for quantitative mammographic assessment. However, there are few studies about clinical-radiologic factors contributing to discrepancies in the visual assessment by radiologists. PURPOSE: To compare automated volumetric breast density measurement with BI-RADS breast density category by radiologists' visual assessments and to evaluate the clinical-radiologic factors affecting disagreement between two estimations. MATERIAL AND METHODS: From February 2011 to September 2012, 860 patients (mean age, 54.7 ± 10.2 years) who had undergone digital mammography including fully automated volumetric breast density analysis, were enrolled. The agreement in breast density assessments between two radiologists, and between an experienced radiologist and the automated software were evaluated using a weighted kappa (k) value. Clinical-radiologic factors contributing to disagreement between the results obtained by a radiologist and the automated software were evaluated using univariate and multivariate analysis. RESULTS: Breast density assessments obtained by two different radiologists were in good agreement (weighted k statistics 0.835%; 95% confidence interval [CI], 0.8098-0.8608); breast density assessments obtained by an experienced radiologist versus automated software were in moderate agreement (weighted k statistics 0.799%; 95% CI, 0.7708-0.8263). Univariate analysis identified a difference in bilateral breast density and patient age as two factors that significantly contributed to disagreement between the two approaches (P = 0.0002, P = 0.019). Multivariate analysis only identified a difference in bilateral breast density as a contributing factor. CONCLUSION: The automated volumetric breast density measurement showed good agreement with radiologists' assessment. The difference in bilateral breast density affected the disagreement between results from visual assessment and automated software.

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