The company will spotlight the breast cancer risk stratification software Volpara Risk Pathways and a new mammography training collaboration with Mammography Educators.
Recognizing the shift from age-based breast cancer screening to screening programs that are more focused on risk stratification, Volpara will be spotlighting its Volpara Risk Pathways™ software at the annual Society of Breast Imaging (SBI)/American College of Radiology (ACR) conference in Savannah, Ga. this week.
Drawing upon patient data from mammography reporting systems or electronic health records, Volpara Risk Pathways reportedly facilitates the identification and management of patients who are at high risk for breast cancer, according to Volpara. The company said the software’s assessment of an individual’s risk for breast cancer enables enhanced triage decisions for supplemental imaging and/or genetic testing.
Volpara will also spotlight the Analytics in Action program, which offers on-site training from Mammography Educators.
“The Analytics in Action program is designed to help deliver high-quality, personalized breast cancer screening by improving image quality, reducing errors, and increasing proficiency and efficiency. We are excited for our partnership with Volpara to deliver hands-on, personalized training sessions designed not only to help address common positioning performance issues but also to create a culture of quality and continuous improvement that ultimately will result in better screening and better patient care,” noted Louise Miller, R.T. (R)(M)(ARRT), CRT, FSBI, FNCBC, the director of education and co-founder of Mammography Educators.
Could a Deep Learning Model for Mammography Improve Prediction of DCIS and Invasive Breast Cancer?
April 15th 2024Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.
Mammography-Based AI Abnormality Scoring May Improve Prediction of Invasive Upgrade of DCIS
April 9th 2024Emerging research suggests that an artificial intelligence (AI) score of 75 or greater for mammography abnormalities more than doubles the likelihood of invasive upgrade of ductal carcinoma in situ (DCIS) diagnosed with percutaneous biopsy.
Mammography Study: AI Improves Breast Cancer Detection and Reduces Reading Time with DBT
April 3rd 2024An emerging artificial intelligence (AI) model demonstrated more than 12 percent higher specificity and reduced image reading time by nearly six seconds in comparison to unassisted radiologist interpretation of digital breast tomosynthesis (DBT) images.