Jennifer A. Harvey

Robust breast composition measurement - Volpara™

Volumetric breast composition measurements generally require accurate imaging physics data In this paper we describe a new method (VolparaTM) that uses relative (as opposed to absolute) physics modeling together with additional information derived from the image to substantially reduce the dependence on imaging physics data Results on 2,217 GE digital images, from a diversity of sites, show encouraging agreement with MRI data, as well as robustness to noise and errors in the imaging physics data.

Effects of Bazedoxifene/Conjugated Estrogens on the Endometrium and Bone: A Randomized Trial

OBJECTIVEnThis phase 3 study evaluated the endometrial safety of bazedoxifene (BZA)/conjugated estrogens (CE) and bone mineral density (BMD) effects vs BZA alone, hormone therapy, and placebo (PBO).nnnMETHODSnThe Selective estrogens, Menopause, And Response to Therapy (SMART)-5 trial was a multicenter, randomized, double-blind, PBO- and active-controlled study in postmenopausal women with an intact uterus (N = 1843; aged 40-65 years) seeking treatment for menopausal symptoms. Subjects received daily oral BZA 20 mg/CE 0.45 or 0.625 mg, BZA 20 mg, CE 0.45 mg/medroxyprogesterone acetate (MPA) 1.5 mg, or PBO. Primary endpoints were incidence of endometrial hyperplasia and percent change in lumbar spine BMD at 12 months. Secondary endpoints included additional osteoporosis parameters and assessments of tolerability and safety.nnnRESULTSnAt 12 months, endometrial hyperplasia incidence was low (<1%) and similar among groups. The BZA/CE group showed significantly greater increases in lumbar spine and total hip BMD vs decreases with PBO (P < .001); the CE/MPA group had increased lumbar spine BMD compared with that in the BZA/CE group. The BZA 20 mg/CE 0.45 and 0.625 mg groups had cumulative amenorrhea rates similar to those with PBO and BZA and significantly higher than those with CE 0.45 mg/MPA 1.5 mg (P < .001). The incidence of breast tenderness with BZA/CE was similar to that with PBO and BZA and significantly lower than with that with CE/MPA (P < .01). Although adverse event (AE) rates were similar among the groups, the incidence of serious AEs overall and AE-related discontinuation rates were higher with CE/MPA than with BZA/CE, BZA, or PBO.nnnCONCLUSIONSnBZA/CE showed low rates of endometrial hyperplasia and improved lumbar spine and total hip BMD and was generally safe and well tolerated.

Comparing a new volumetric breast density method (Volpara TM ) to cumulus

Computer-aided thresholding programs, such as Cumulus, are seen as the gold standard for breast density measurement In this paper we compare a new volumetric breast density software package, VolparaTM to an experts BI-RADS visual assessment and Cumulus and show that all are closely related, whilst there is a less close relationship between Cumulus percent breast density and absolute volume of dense tissue These results support the further validation of this new method against breast cancer outcomes.

MRI-guided needle localization : Technique

Magnetic resonance imaging (MRI) is being used increasingly in breast cancer diagnosis. Such indications include the search for a breast primary in women with metastatic carcinoma in the axillary lymph nodes, improving surgical planning in women with a biopsy-proven breast cancer, and in screening very high-risk women. If a suspicious lesion is found by MRI, localization with either directed additional mammographic or sonographic views or with MRI-guided needle localization or biopsy is necessary. We describe the use of a biopsy device with embedded internal fiducial markers. The coordinates for needle placement are calculated by distances between the fiducial markers and the lesion. The technique is simple to master and is aided by the use of a practice phantom.

Do women with dense breasts have higher radiation dose during screening mammography

Radiation dose during screening mammography is a concern among women. The purpose of this study was to evaluate the relative contribution of breast density to the radiation dose from screening mammography. This IRB approved retrospective study involved collecting patient age, weight, height, compressed breast thickness, and average glandular dose for each exposure for 434 sequential patients undergoing screening mammography at our institution. Automated volumetric density software was used to quantify breast density. The relationship of predictors was evaluated by univariate and multivariate analysis. Median patient age was 58 years and median body mass index (BMI) was 26.8. Median volumetric breast density was 5.8% (range 1.7‐30.5%). Median compressed breast thickness was 63.4 mm (range 24.5‐111.5 mm). Univariate analysis showed positive associations between radiation dose and both breast thickness and BMI, an inverse association with age, and no association with density. Multivariate regression analysis demonstrated a significant association between dose and age (P=.021), laterality (P<.001), BMI (P=.038), density (P<.001), and breast thickness (P<.001). Decomposition of the multivariate regression model coefficient of determination showed that breast thickness was the primary determinant of dose, accounting for 76% of the 58% of the dose variability, followed by density (8%), laterality (4%), age (<1%), and BMI (<1%). Compressed breast thickness had the greatest effect on average glandular dose. Breast density has a minor impact, while BMI and age have minimal impact on dose.

Outcome of Architectural Distortion Detected Only at Breast Tomosynthesis versus 2D Mammography

Purpose To compare the outcome of architectural distortion (AD) without associated mass only on digital breast tomosynthesis (DBT) with AD seen at two-dimensional (2D) mammography and to evaluate if the incidence of malignancy is influenced by the presence of a correlate at ultrasonography (US). Materials and Methods This retrospective study had institutional review board approval and was HIPAA compliant. All consecutive cases in which patients with AD were ultimately assigned Breast Imaging Reporting and Data System (BI-RADS) 4 or 5 categories from 2009 to 2016 were reviewed by three readers for visibility (2D vs DBT). The level of suspicion was assigned using a Likert scale. Pathologic results were compared between 2D-detected and DBT-detected AD. Frequencies were compared by using the McNemar and Pearson χ2 exact tests. Results One hundred eighty-one AD lesions were included; 122 (67.4%) were 2D visible while 59 (32.6%) were DBT detected. Forty-two women (with 43 lesions) underwent 2D mammography prior to initiation of DBT. In 117 women with 121 AD lesions who underwent 2D mammography plus DBT, 59 lesions (48.8%) were detected only with DBT. The malignancy rate based on final pathology was significantly higher for 2D-detected AD (53 [43.4%] of 122) compared with DBT (six [10.2%] of 59) (P < .001). A US correlate was more frequent with 2D-detected AD (103 [84.4%] of 122) than DBT (33 [55.9%] of 59) (P < .001). Malignancy rate was not different for DBT-detected AD with (four [12.1%] of 33; 95% confidence interval [CI]: 3.4%, 28.2%]) or without (two [7.7%] of 26; 95% CI: 0.9%, 25.1%]) a US correlate. NPV based on radiologists level of suspicion was high (91.8%-98.0%) but not sufficient enough to forgo biopsy. Conclusion DBT-detected suspicious AD has a lower malignancy outcome compared with 2D mammography-detected suspicious AD, although still high enough to warrant biopsy.

Linkage of the ACR National Mammography Database to the Network of State Cancer Registries: Proof of Concept Evaluation by the ACR National Mammography Database Committee

PURPOSEnThe National Mammography Database (NMD) contains nearly 20 million examinations from 693 facilities; it is the largest information source for use and effectiveness of breast imaging in the United States. NMD collects demographic, imaging, interpretation, biopsy, and basic pathology results, enabling facility and physician comparison for quality improvement. However, NMD lacks treatment and clinical outcomes data. The network of state cancer registries (CRs) contains detailed pathologic, treatment, and clinical outcomes data. This pilot study assessed electronic linkage of NMD and CR data at a multicenter institution as proof of concept.nnnMATERIALS AND METHODSnWe obtained Quality Oversight Committee approval for this retrospective study. Data of patients diagnosed with breast cancer in 2014 and 2015 were retrieved from our NMD-approved radiology information system (RIS) and matched with reportable patients in our CR using social security number (SSN), first name (fname), last name (lname), and date of birth (DOB). Matching was repeated without SSN. Percentage and reasons for mismatch were evaluated.nnnRESULTSnThe RIS query identified 1,316 patients. CR linkage was 99.2% successful (nxa0= 1,305 of 1,316) using SSN, fname, lname, and DOB. Eleven mismatches included four CR case-finding failures, one NMD fname error, five nonreportable in the CR, and one with correct identifiers in both databases. Without SSN, linkage was 97.3% successful (nxa0= 1,281 of 1,316); name errors accounted for 19 and DOB accounted for 5 additional mismatches.nnnCONCLUSIONnUsing common data elements, linkage between the NMD and state CRs may be feasible and could provide critical outcomes information to advance accurate assessment of breast imaging in the United States.

Do women with dense breasts have higher radiation dose during screening mammography? Reply to-Letter to the Editor

Thanks for allowing us to respond to Niall Phelan’s thoughtful letter regarding our article “Do women with dense breasts have higher radiation dose during screening mammography?” Mr. Phelan raised two concerns about our research design in his letter. One was that average glandular dose (AGD) estimates are affected by the assumed breast glandularity and that the glandularity assumed in the AGD estimate reported by the imaging system may not be the same as that determined by image-based density analysis. We fully agree that all models of breast radiation dose include fibroglandular fraction, and Tromans et al have shown that there can be small discrepancies between system-reported AGD and the AGD calculated using Volpara software to measure glandularity. The same group of investigators have also demonstrated that the discrepancies trend are different for different imaging systems. These manufacturer-specific differences are in part due to differences in the way that glandularity is estimated. However, not all mammographic systems assume a universal 50/50 glandular/adipose ratio; for example, some estimate glandular fraction based on the relationship between compressed thickness and glandularity as is used in the dose model of Dance et al. In general, the details of the AGD calculation whose results are reported in the DICOM header are not available to end users, and without these, it is impossible to “correct” the system-reported AGD using an image-derived glandularity estimate. Even if it were possible, the changes in estimated AGD would be too small to affect the primary conclusion of this study, which is that compared to compressed thickness glandularity has a small effect on radiation dose. The other concern was possible errors in the system-reported AGD due to improper or incomplete setup and calibration on the part of the imaging system’s service engineers. In our experience at the University of Virginia, there was very little difference between the engineer and site physicist measurements of AGD-relevant quantities (mAs–kerma relationship, HVL, kVp, or AGD itself), and certainly nothing approaching 50%.

Masking risk predictors in screening mammography.

High mammographic density reduces the diagnostic accuracy of mammography by masking tumors, leading to interval cancers and late stage diagnosis. In this study, various models to predict masking risk are computed on a cohort of 90 interval or undiagnosed (“masked”) invasive cancers and 186 screen-detected invasive cancers, based on biometric (age and BMI) and image-based parameters (BI-RADS density, volumetric breast density (VBD) and detectability). Univariate logistic regressions were computed to predict masked cancers, and the accuracy of the regressions was evaluated using the area under receiver operator characteristic curve (AUC). The univariate AUC for BMI, age, BIRADS density, VBD and mean detectability were 0.61 [0.54-0.68], 0.65 [0.58-0.73], 0.67 [0.61–0.73], 0.72 [0.65-0.78] and 0.75 [0.68-0.81] respectively (95% confidence intervals are noted in the brackets). The models were applied to a set of 248 mammography exams from cancer-free women of the same population. A stratified screening model was tested by computing the fraction of disease-free women identified as masked (the recruitment rate) as a function of the fraction of masked cancers that were correctly identified. For BI-RADS densities 3 or 4 (4th edition), up to 60% of masked cancers could potentially be detected by supplemental tests, requiring 43% of women to be recruited for extra screening. Selecting by mean detectability would require a 29% recruitment rate for the same potential capture. Future work to develop multivariate masking risk predictors could yield more efficient stratified screening approaches for breast cancer detection.

Automated Volumetric Mammographic Breast Density Measurements May Underestimate Percent Breast Density for High-density Breasts

RATIONALE AND OBJECTIVESnThe purpose of this study was to evaluate discrepancy in breast composition measurements obtained from mammograms using two commercially available software methods for systematic trends in overestimation or underestimation compared to magnetic resonance-derived measurements.nnnMATERIALS AND METHODSnAn institutional review board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study was performed to calculate percent breast density (PBD) by quantifying fibroglandular volume and total breast volume derived from magnetic resonance imaging (MRI) segmentation and mammograms using two commercially available software programs (Volpara and Quantra). Consecutive screening MRI exams from a 6-month period with negative or benign findings were used. The most recent mammogram within 9 months was used to derive mean density values from for processing images at the per breast level. Bland-Altman statistical analyses were performed to determine the mean discrepancy and the limits of agreement.nnnRESULTSnA total of 110 women with 220 breasts met the study criteria. Overall, PBD was not different between MRI (mean 10%, range 1%-41%) and Volpara (mean 10%, range 3%-29%); a small but significant difference was present in the discrepancy between MRI and Quantra (4.0%, 95% CI: 2.9 to 5.0, Pu2009<u20090.001). Discrepancy was highest at higher breast densities, with Volpara slightly underestimating and Quantra slightly overestimating PBD compared to MRI. The mean discrepancy for both Volpara and Quantra for total breast volume was not significantly different from MRI (pu2009=u20090.89, 0.35, respectively). Volpara tended to underestimate, whereas Quantra tended to overestimate fibroglandular volume, with the highest discrepancy at higher breast volumes.nnnCONCLUSIONSnBoth Volpara and Quantra tend to underestimate PBD, which is most pronounced at higher densities. PBD can be accurately measured using automated volumetric software programs, but values should not be used interchangeably between vendors.