New Studies Demonstrate How AI Can Personalize and Optimize Breast Cancer Detection

New studies have demonstrated the important role played by artificial intelligence (AI) in objective breast density assessment, cancer risk assessment, and mammography quality evaluation to personalize and optimize breast cancer detection.

The latest studies presented by Volpara Health (Wellington, New Zealand) found that combining the AI computer-aided-detection system Transpara with Volpara volumetric density assessment led to better screening efficacy for women with dense breast tissue as compared to a traditional double read by radiologists. The studies also found that using Tyrer-Cuzick with volumetric density assessment from Volpara Scorecard to identify and triage intermediate and high-risk patients for ultrasound improved the cancer detection rate as compared to traditional biennial mammography. In addition, the studies found that using Volpara Analytics software to evaluate radiographer performance improved the quality, irrespective of the experience level.

The research included personalized screening and optimization studies, such as the DENSE1, TOMMY2, and To-Be3 trials, and the PROCAS I/II4 and KARMA5 studies. A prime example, the DENSE trial, utilized Volpara's TruDensity volumetric density product to identify women with extremely dense breasts in their randomized controlled trial of supplemental MRI that helped shape the latest screening recommendations by the European Society of Breast Imaging. The recommendations suggest that density must be reported to all women receiving mammography and women aged 50 to 70 with extremely dense breasts must undertake MRI.

"Increasing our understanding of breast cancer risk, detection and prevention is essential to ensuring every patient is given the right care at the right time," said Teri Thomas, Volpara CEO.

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