How MSK Doctors Are Improving Radiation Treatments With AI

She has helped robots learn to get around indoors and pick up balls from the ground. And she has developed computer programs to monitor traffic at intersections.

But these days, Harini Veeraraghavan, PhD, applies her expertise to fighting cancer. Her lab at Memorial Sloan Kettering Cancer Center (MSK) leads the development of new artificial intelligence (AI) models to improve the targeting of radiation therapy — teaching computers to better isolate tumors and spare more of the surrounding healthy tissue.

In radiation therapy, where high-energy beams are fired at cancer cells, precision is imperative. Every millimeter matters. Yet much of the human body is squishy inside. Organs, especially in the abdomen, naturally move around and change shape from day to day and treatment to treatment.

It’s actually a very challenging and interesting problem,” says Dr. Veeraraghavan, an associate attending computer scientist in MSK’s Department of Medical Physics. “These organs move quite a bit. Breathing, the contractions that move food through the digestive system, and even water flowing through can alter their shape.”

Overcoming this, she says, requires developing computer models with a built-in understanding of how organs can change shape and position.

“Currently, we’re developing a virtual digital twin that would model how a patient’s abdominal organs move so we can better plan their treatment and ensure that the right doses of radiation are being delivered to precisely the right places,” she says.

‘Like Having Your Best Resident on the Case’

And the abdomen isn’t the only area where Dr. Veeraraghavan’s innovations are being used. Her research is already being applied by MSK radiation oncologists across more than 40 tissue types — including in head and neck, lung, pancreatic, liver, and prostate cancers, says Joseph Deasy, PhD, Chair of the Department of Medical Physics.

Dr. Veeraraghavan leads a multi-disciplinary effort, which includes radiation oncologists and other physicists, to safely implement novel AI technology in the clinic. The technology is used to guide hundreds of radiotherapy treatments given at MSK each day, making it a great example of the positive impact AI is already starting to have in medicine, Dr. Deasy adds.

Nancy Lee, MD, MSK’s Chief of Head and Neck Radiation Oncology, says the algorithms have been a great help in treating patients with head and neck cancer.

In the past, doctors had to identify a patient’s organs in imaging scans by hand — a task often given to residents. Starting with the blank canvas of a CT or MRI scan, they would trace the outlines of a patient’s eyes, nose, teeth, salivary glands, and so forth. This “contouring” process takes hours.

Today, a physician like Dr. Lee can start with computer-generated contours and apply her expertise to tweaking and refining some of the lines and boundaries — making sure tumors are precisely targeted and healthy tissues avoided.

“It’s like having your best resident on the case,” Dr. Lee says. “If you asked 10 human radiation oncologists to contour the same image, there are going to be slight variations among them, even though we’re all experts. The algorithm can help us be even more precise, consistent, systematic, and efficient.”

Deep learning models developed at MSK have been shown to overcome the type of day-to-day variability that can cause not enough or too much radiation to reach a given spot. MSK researchers are also developing AI methods to better track precisely how much radiation a tumor or organ has received to date.

The MSK Difference

While AI assistance is quickly becoming the industry standard in radiology, MSK stands apart both for the sophistication and innovation of its AI models as well as for the human expertise it’s paired with, Dr. Veeraraghavan notes.

She was recently awarded two R01 research grants — the gold standard for federally funded research — totaling more than $4 million. The first grant, from the National Cancer Institute, aims to develop new AI tools against lung cancer, offering less toxicity for patients while better targeting tumors in difficult-to-treat locations. The second, from the National Institute of Biomedical Imaging and Bioengineering and co-led by MSK associate attending physicist Neelam Tyagi, PhD, is to develop the virtual twin approach to modeling abdominal organs.

And more work is underway to provide radiation oncologists with “rough drafts” of regions to target in addition to outlining normal tissue, as well as to estimate how much mass tumors lose following radiation therapy.

“Together these tools will offer unprecedented insights into each person’s cancer to help guide treatment decisions,” Dr. Veeraraghavan says.

Artificial Intelligence 101