SUPPORTING THE FUTURE OF BREAST CANCER RESEARCH

By Christy Marx Barber, Staff Writer

In 2014, Dr. Regina Barzilay, a distinguished professor at the Massachusetts Institute of Technology Computer Science and Artificial Intelligence (AI) Lab, was immersed in researching natural language processing—a form of AI that gives computers the ability to understand spoken and written human language.

Then, Dr. Barzilay was diagnosed with breast cancer, at age 43, and her research focus shifted.

After her successful treatment regimen for breast cancer, she asked, as good scientists do, an important question. Could she use her knowledge of AI to find breast cancer earlier? Based on a preliminary retrospective research study completed in 2021, that answer is trending toward “yes.” Now, with a $500,000 two-year grant from the Zeta Tau Alpha Foundation to the Breast Cancer Research Foundation (BCRF), Dr. Barzilay’s research is moving forward in a clinical setting.

Retrospective Study

Following treatment for breast cancer, Dr. Barzilay returned to work in 2016. “Doing early detection and risk assessment was the first thing on my mind, even though I had never done any work on medical data before,” she said. “I was obsessed by it, but it was not an easy route.”

Because she had never previously worked with medical data, scientific funding sources rejected her grant proposals for the first time in her career. “Even though I wrote that I had just gone through breast cancer treatment,” she said, “they would say ‘well, this technology is lacking.’” So, she and her team took a new approach. “Doing more of the same doesn’t change much,” she said. “We need to try to go in other directions with scientifically grounded alternative actions to change the status quo.” BCRF and five other funders agreed and supported a retrospective study of mammography using AI.

Dr. Barzilay draws a parallel between AI and teaching a child to write letters. “You want to explain to a child how to write the letter ‘a.’ So, you explain that it has to be round, and it has this (curved) end, and they practice it over and over,” she explained. “Artificial intelligence refers to different methodologies for machines to learn tasks from provided data. You give the machine lots of examples over and over and then create an algorithm that enables it to discriminate between things.”

In a retrospective study, the machine doesn’t know the outcome, but the researchers do. Dr. Barzilay’s plan was to obtain mammograms from patients diagnosed with breast cancer—from their first scan to the one that showed the cancerous mass. The goal was to determine if an algorithm created from those scans would “teach” a computer to identify the cancer earlier than is possible for the human eye.

Adam Yala, then an undergraduate at MIT, did the legwork to obtain the data. “When I met him, I didn’t have normal hair and I was obsessed,” Dr. Barzilay said. “Breast cancer is not something an MIT undergraduate really thinks about. He could have done so many interesting projects in computer science. He had to go and beg and beg for data from people who were extremely skeptical. I am very grateful he had the strength of character to push through it.” Adam is now Dr. Yala, a professor at University of California Berkely and University of California San Francisco.

The MIT team was able to create an algorithm that would make a prediction from the mammogram. Of those who were later diagnosed with breast cancer, this algorithm correctly predicted 40% of the cases compared to the current widely used statistical model, Tyrer-Cuzick, that correctly predicts 23%. They named the algorithm “MIRAI,” the Japanese word for future. And that’s where the research continues.

Clinical Study

“It’s not enough to make this technique with retrospective data. The bigger question now is what happens prospectively. We need to create a clinical pipeline,” Dr. Barzilay said. That clinical study using MIRAI is what the ZTA Foundation is funding through its grant to BCRF.

The study is being conducted at Massachusetts General Hospital in Worcester, which has a diverse patient population of races and ethnicities. The team is currently recruiting and identifying the cohort for the clinical study. Consumers use AI every day to book travel, turn on their smart phones or select movies, but the general population still has misconceptions about its use. AI is not as prevalent in the medical field, so the team has prepared educational materials to encourage patients to join the study.

Radiologists will run MIRAI on the mammograms of patients who agree to participate in hopes of validating its efficacy, affordability and accessibility.

Dr. Barzilay explains that MIRAI is more effective than traditional screening technology that roughly determines the propensity for cancer based on family history, ethnicity and breast density.

MIRAI is also affordable. Radiologists already use automation to assess mammograms. MIRAI is an extra processing layer on top of the existing workflow. Clinics will not need any additional equipment.

MIRAI could make additional treatment more accessible. Most insurance companies will not pay for follow-up procedures, like an MRI, if a patient is not high risk. A patient may want additional screening but not be able to afford it. MIRAI can increase accessibility of that screening by identifying high-risk patients earlier.

MIRAI could also produce a more personalized breast health care plan by identifying women who are not at risk and may only need a mammogram every two years and those who are at risk and need to be screened more often.

Dr. Barzilay is grateful for the ZTA Foundation funding that could dramatically change the clinical system and patient outcomes. “We didn’t want to wait 10 years until I was an expert in this field,” she said. “We shouldn’t kill new ideas because this disease has not been cured for many decades. We need to have all the different perspectives, however wild they may seem, to be able to change the state of the art.”

The ZTA Foundation’s role in this progress is encouraging to President Carolyn Hof Carpenter. “For 30 years, Zetas have educated millions about the importance of regular mammograms,” she said. “Funding the clinical study of MIRAI allows us to continue to raise awareness and be at the forefront of possible advancements in early detection.