News | Women's Health | July 21, 2015

University of Virginia Researchers Demonstrate High Precision of Automated Volumetric Breast Density

Scientific study confirms reduced variation between exam results with automated density measurements

July 21, 2015 - Researchers at the University of Virginia (UVA) Health System have demonstrated that automated volumetric fibroglandular breast density measurement tools are more precise than area-based methods.  Results of the study, "Reliability of Automated Breast Density Measurements," recently featured in Radiology, suggest that with lower variability, volumetric breast density is well suited for inclusion in breast cancer risk models. The announcement was made at The Association for Medical Imaging Management (AHRA)'s 43rd annual meeting and exposition, July 19-22 in Las Vegas. 

"Breast density is increasingly being considered with other known risk factors to improve risk prediction in order to give women personalized knowledge to make decisions about screening. However, variability in assigned density category may result in changes in recommendations for adjuvant screening. Thus, for consistency, objectivity, and ease of use, breast density measurement ideally should be automated and accurate," said Jennifer Harvey, M.D., professor of radiology at the UVA School of Medicine. "The purpose of this study was to estimate the reliability of area-based methods and automated volumetric breast density measurements using repeated measures."

Thirty women undergoing screening mammography consented to undergo a repeated left craniocaudal examination performed by a second technologist in this prospective study. Breast density was measured by using both area-based and volumetric methods (Volpara software). Discrepancy between the first and second breast density measurements was obtained for each algorithm by subtracting the second measurement from the first and then analyzed with a random-effects model to derive limits of measurement agreement. 

Results of the study demonstrate that variability in a repeated measurement of breast density is highest for area-based measurement tools, standard deviation 3.32 percent (2.65-4.44). In contrast, precision was highest for automated volumetric breast density tools, such as VolparaDensity, standard deviation 0.99 percent (0.79-1.33).  

"The excellent reproducibility of automated breast density measurements indicates that they would be well suited for inclusion in a breast cancer risk model.  This is consistent with results we presented at the San Antonio Breast Cancer Symposium in December that showed that the addition of volumetric breast density improved breast cancer risk discrimination," Harvey added.

For more information: www.uvahealth.com

Related Content

Novel Technique May Significantly Reduce Breast Biopsies
News | Breast Biopsy Systems | January 17, 2019
A novel technique that uses mammography to determine the biological tissue composition of a tumor could help reduce...
Digital Mammography Increases Breast Cancer Detection
News | Mammography | January 16, 2019
The shift from film to digital mammography increased the detection of breast cancer by 14 percent overall in the United...
Artificial Intelligence Used in Clinical Practice to Measure Breast Density
News | Artificial Intelligence | January 15, 2019
An artificial intelligence (AI) algorithm measures breast density at the level of an experienced mammographer,...
Machine Learning Uncovers New Insights Into Human Brain Through fMRI
News | Neuro Imaging | January 11, 2019
An interdisciplinary research team led by scientists from the National University of Singapore (NUS) has successfully...
Sponsored Content | Videos | Breast Imaging | January 11, 2019
Supplemental screening with ABUS helps personalize breast care for women with dense breasts and offers advanced...
Mobile App Data Collection Shows Promise for Population Health Surveys
News | Population Health | January 10, 2019
Mobile app data collection can bring access to more potential clinical study participants, reduce clinical study...
Hypertension With Progressive Cerebral Small Vessel Disease Increases Cognitive Impairment Risk
News | Magnetic Resonance Imaging (MRI) | January 08, 2019
Patients with high blood pressure and progression of periventricular white matter hyperintensities showed signs of...
Artificial Intelligence Pinpoints Nine Different Abnormalities in Head Scans

A brain scan (left) showing an intraparenchymal hemorrhage in left frontal region and a scan (right) of a subarachnoid hemorrhage in the left parietal region. Both conditions were accurately detected by the Qure.ai tool. Image courtesy of Nature Medicine.

News | Artificial Intelligence | January 07, 2019
The rise in the use of computed tomography (CT) scans in U.S. emergency rooms has been a well-documented trend1 in...
Electronic Brachytherapy Effective in Long-Term Study of 1,000 Early-Stage Breast Cancers
News | Brachytherapy Systems, Women's Healthcare | January 07, 2019
Breast cancer recurrence rates of patients treated with intraoperative radiation therapy (IORT) using the Xoft Axxent...
Brachytherapy Alone Superior Treatment for Intermediate-Risk Prostate Cancer
News | Brachytherapy Systems | January 04, 2019
Patient-reported outcomes (PROs) indicated a significantly different clinician and patient-reported late toxicity...