A.I. VERSUS M.D.
What happens when diagnosis is automated?
By Siddhartha Mukherjee
Apr 3 2017 Issue
One evening last November, a fifty-four-year-old woman from the Bronx arrived at the emergency room at Columbia University’s medical center with a grinding headache. Her vision had become blurry, she told the E.R. doctors, and her left hand felt numb and weak. The doctors examined her and ordered a CT scan of her head.
A few months later, on a morning this January, a team of four radiologists-in-training huddled in front of a computer in a third-floor room of the hospital. The room was windowless and dark, aside from the light from the screen, which looked as if it had been filtered through seawater. The residents filled a cubicle, and Angela Lignelli-Dipple, the chief of neuroradiology at Columbia, stood behind them with a pencil and pad. She was training them to read CT scans.
“It’s easy to diagnose a stroke once the brain is dead and gray,” she said. “The trick is to diagnose the stroke before too many nerve cells begin to die.” Strokes are usually caused by blockages or bleeds, and a neuroradiologist has about a forty-five-minute window to make a diagnosis, so that doctors might be able to intervene—to dissolve a growing clot, say. “Imagine you are in the E.R.,” Lignelli-Dipple continued, raising the ante. “Every minute that passes, some part of the brain is dying. Time lost is brain lost.”
She glanced at a clock on the wall, as the seconds ticked by. “So where’s the problem?” she asked.
Strokes are typically asymmetrical. The blood supply to the brain branches left and right and then breaks into rivulets and tributaries on each side. A clot or a bleed usually affects only one of these branches, leading to a one-sided deficit in a part of the brain. As the nerve cells lose their blood supply and die, the tissue swells subtly. On a scan, the crisp borders between the anatomical structures can turn hazy. Eventually, the tissue shrinks, trailing a parched shadow. But that shadow usually appears on the scan several hours, or even days, after the stroke, when the window of intervention has long closed. “Before that,” Lignelli-Dipple told me, “there’s just a hint of something on a scan”—the premonition of a stroke.
The images on the Bronx woman’s scan cut through the skull from its base to the apex in horizontal planes, like a melon sliced from bottom to top. The residents raced through the layers of images, as if thumbing through a flipbook, calling out the names of the anatomical structures: cerebellum, hippocampus, insular cortex, striatum, corpus callosum, ventricles. Then one of the residents, a man in his late twenties, stopped at a picture and motioned with the tip of a pencil at an area on the right edge of the brain. “There’s something patchy here,” he said. “The borders look hazy.” To me, the whole image looked patchy and hazy—a blur of pixels—but he had obviously seen something unusual.
“Hazy?” Lignelli-Dipple prodded. “Can you describe it a little more?”
The resident fumbled for words. He paused, as if going through the anatomical structures in his mind, weighing the possibilities. “It’s just not uniform.” He shrugged. “I don’t know. Just looks funny.”
Lignelli-Dipple pulled up a second CT scan, taken twenty hours later. The area pinpointed by the resident, about the diameter of a grape, was dull and swollen. A series of further scans, taken days apart, told the rest of the story. A distinct wedge-shaped field of gray appeared. Soon after the woman got to the E.R., neurologists had tried to open the clogged artery with clot-busting drugs, but she had arrived too late. A few hours after the initial scan, she lost consciousness, and was taken to the I.C.U. Two months later, the woman was still in a ward upstairs. The left side of her body—from the upper arms to the leg—was paralyzed.
I walked with Lignelli-Dipple to her office. I was there to learn about learning: How do doctors learn to diagnose? And could machines learn to do it, too?