Reducing False Positives in Breast Cancer Detection

The following article was written by Vignesh Arasu, M.D., former UCSF Medical student and future UCSF diagnostic radiology resident (incoming July 2012).

I was recently featured on the UCSF Clinical & Translational Science Institute (CTSI) blog about my breast cancer imaging research through the Pathways to Career in Clinical and Translational Research Program (PACCTR).

The study investigated how to reduce the large number of false positives generated when using breast MRI to detect breast cancer. Although MRI is the best tool for detecting breast cancer, false positives lead to invasive biopsies that turn out to be benign. The study used a computer algorithm called Signal Enhancement Ratio (developed at UCSF by the Hylton lab) to more precisely measure how blood flows through breast lesions.

The study found that when retrospectively applying the tool, benign biopsies could be reduced by up to 60 percent- effectively reducing the number of unnecessary biopsy surgeries in women.

This video helps explain my research and its impact on patients:

To learn more about my educational research experience with my mentor and blog contributor, Dr. Bonnie M. Joe, please click here.

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