Author Interviews, Breast Cancer, JAMA, UCLA / 12.08.2019
AI Better At Reading Some Forms of Early Breast Cancer Pathology Slides
MedicalResearch.com Interview with:
Joann G. Elmore, MD, MPH
Professor of Medicine,
Director of the UCLA National Clinician Scholars Program
David Geffen School of Medicine at UCLA
MedicalResearch.com: What is the background for this study? What are the main findings?
- A pathologist makes the diagnosis of breast cancer versus non-cancer after reviewing the biopsy specimen. Breast biopsies are performed on millions of women each year and It is critical to get a correct diagnosis so that we can guide patients to the most effective treatments.
- Our prior work (Elmore et al. 2015 JAMA) found significant levels of disagreement among pathologists when they interpreted the same breast biopsy specimen. We also found that pathologists would disagree with their own interpretations of breast biopsies when they where shown the same biopsy specimen a year later.
- In this study, 240 breast biopsy images were fed into a computer, training it to recognize patterns associated with several types of breast lesions, ranging from benign (noncancerous) to invasive breast cancer. We compared the computer readings to independent diagnoses made by 87 practicing U.S. pathologists and found that while our artificial intelligence program came close to performing as well as human doctors in differentiating cancer from non-cancer, the AI program outperformed doctors when differentiating ductal carcinoma in situ (DCIS) from atypia, which is considered the greatest diagnostic challenge.