Use of Artificial Intelligence to Support Same-Day Breast Cancer Diagnostic Testing


Optimizing Care Delivery for Clinicians


Using Real-Time Digital Healthcare Data to Improve Timely Treatment or Diagnosis

Use of an artificial intelligence algorithm that would allow for screening mammography interpretation and same-day diagnostic imaging has the potential to vastly shorten the time from an abnormal screening mammogram to diagnostic workup, resolving false positives in a timelier fashion, and reducing the anxiety incurred in patients by long wait times for diagnostic evaluation.

While breast cancer screening can save lives, false positives are common

Mammography screening in the United States has been an incredibly successful tool for identifying breast cancer and has led to a 25-40 percent reduction in breast cancer-related deaths. While most screenings reveal normal results, approximately 10 percent of all screenings require a followup diagnostic exam to confirm a cancer diagnosis. Of women recalled for additional diagnostic exams, roughly 95 percent do not receive a diagnosis of breast cancer.

While this is good news, breast cancer is scary. And the need to return for a diagnostic exam can induce substantial anxiety and distress in women as they wait for their diagnostic appointment and results.

Artificial intelligence will improve time to diagnostic exam

Dr. William Hsu, an informaticist, and Dr. Anne Hoyt, a breast radiologist, both from the University of California Los Angeles, wanted to find a way to speed up the process to reduce patient stress and anxiety. Breast radiologists typically review screening mammograms in batches. This can occur anywhere from the day of the mammogram to more than a week later, depending on workload and staff availability. Identifying abnormal screenings immediately and conducting diagnostic exams on the same day would alleviate patient stress and enable a transformative “one-stop-shop” paradigm for breast cancer screening and diagnosis.

To do this, the team is using artificial intelligence (AI) algorithms at several steps throughout their workflow to immediately interpret screening mammograms and set up same-day diagnostic imaging, if required. This would allow women to undergo their regularly scheduled mammogram and any necessary diagnostic exam on the same day.

“AI is a tool that can help us to be better radiologists, more efficient radiologists, and ultimately to benefit the patients by finding cancers more quickly and initiate treatment sooner.”- Dr. Anne Hoyt

Same-day diagnostic exams supported by AI expected to improve care for women

The team will validate various AI algorithms for assessing breast cancer risk and detecting breast cancers on screening mammograms. Using the information on the performance of the AI algorithms, they will investigate how the implementation of an AI-enabled same-day diagnostic exam workflow would impact the number of patients who can be seen at the clinic, the workload of the breast imaging clinic staff, and the number of same-day diagnostic exams that would need to be accommodated. These insights will inform how to integrate the algorithms into clinical workflow to increase efficiency, maximize patient throughput, and promptly communicate results and appropriate next steps to patients while performing at the same level as current radiologist standards. The team expects that imaging centers using AI to provide immediate interpretation of screening exams and same-day diagnostic exams, as needed, will have lower callback rates of women with abnormal screening, increased patient satisfaction from same-day interpretation, and shorter times between screening and diagnostic workup when compared to centers that use the current state of mammography review.