The new Breast Cancer Risk Calculator (BRISK), designed at Houston Methodist by a team led by Jenny Chang, MD, Emily Herrmann Chair in Cancer Research and director of the Cancer Center, and Stephen T.C. Wong, PhD, John S. Dunn, Sr. Presidential Distinguished Chair in Biomedical Engineering, provides a novel, precise risk-assessment model to reduce overdiagnosis and unnecessary biopsies after an abnormal mammogram.

BRISK helps physicians more precisely characterize breast tissue for patients in subgroup BI-RADS 4. Using BRISK oncologists and radiologists now can more accurately determine whether to biopsy breast tissue of this subgroup that currently contains more than 70 percent false-positive biopsy results after mammography.

A study published in JCO: Clinical Cancer Informatics shows that the deep learning algorithm-based BRISK can properly identify subtle patterns and generate a more optimized risk score to support the decision to biopsy after abnormal breast imaging. It has also shown to improve accuracy of diagnosis for patients with findings suggestive of breast cancer.

See JCO: Clinical Cancer Informatics for more information on the study results and methodology.