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A.I. Comes to the Operating Room

Brain surgeons are bringing artificial intelligence and new imaging techniques into the operating room, to diagnose tumors as accurately as pathologists, and much faster, according to a report in the journal Nature Medicine.

The new approach streamlines the standard practice of analyzing tissue samples while the patient is still on the operating table, to help guide brain surgery and later treatment.

The traditional method, which requires sending the tissue to a lab, freezing and staining it, then peering at it through a microscope, takes 20 to 30 minutes or longer. The new technique takes two and a half minutes. Like the old method, it requires that tissue be removed from the brain, but uses lasers to create images and a computer to read them in the operating room.

“Although we often have clues based on preoperative M.R.I., establishing diagnosis is a primary goal of almost all brain tumor operations, whether we’re removing a tumor or just taking a biopsy,” said Dr. Daniel A. Orringer, a neurosurgeon at N.Y.U. Langone Health and the senior author of the report.

In addition to speeding up the process, the new technique can also detect some details that traditional methods may miss, like the spread of a tumor along nerve fibers, he said. And unlike the usual method, the new one does not destroy the sample, so the tissue can be used again for further testing.

The new process may also help in other procedures where doctors need to analyze tissue while they are still operating, such as head and neck, breast, skin and gynecologic surgery, the report said. It also noted that there is a shortage of neuropathologists, and suggested that the new technology might help fill the gap in medical centers that lack the specialty.


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Doctors demonstrated acquiring a tissue sample and putting it through the AI pipeline to test for brain cancer. Video by Michigan MedicineCreditCredit…Michigan Medicine

Algorithms are also being developed to help detect lung cancers on CT scans, diagnose eye disease in people with diabetes and find cancer on microscope slides. The new report brings artificial intelligence — so-called deep neural networks — a step closer to patients and their treatment.

The study involved brain tissue from 278 patients, analyzed while the surgery was still going on. Each sample was split, with half going to A.I. and half to a neuropathologist. The diagnoses were later judged right or wrong based on whether they agreed with the findings of lengthier and more extensive tests performed after the surgery.

The result was a draw: humans, 93.9 percent correct; A.I., 94.6 percent.

The study was paid for by the National Cancer Institute, the University of Michigan and private foundations. Dr. Orringer owns stock in the company that made the imaging system, as do several co-authors, who are company employees. He conducted the research at the University of Michigan, before moving to New York.

“Having an accurate intra-operative diagnosis is going to be very useful,” said Dr. Joshua Bederson, the chairman of neurosurgery for the Mount Sinai Health System, who was not involved in the study. He added, “I think they understated the significance of this.”

He said the traditional method of examining tissue during brain surgery, called a frozen section, often took much longer than 30 minutes, and was often far less accurate than it was in the study. At some centers, he said, brain surgeons do not even order frozen sections because they do not trust them and prefer to wait for tissue processing after the surgery, which may take weeks to complete.

“The neuropathologists I work with are outstanding,” Dr. Bederson said. “They hate frozen sections. They don’t want us to make life-altering decisions based on something that’s not so reliable.”

Dr. Bederson said that the study authors had set a very high bar for their new technique by pitting it against experts at three medical centers renowned for excellence in neurosurgery and neuropathology: Columbia University in New York, the University of Miami and the University of Michigan, Ann Arbor.

“I think that what happened with this study is that because they wanted to do a good comparison, they had the best of the best of the traditional method, which I think far exceeds what’s available in most cases,” Dr. Bederson said.

The key to the study was the use of lasers to scan tissue samples with certain wavelengths of light, a technique called stimulated Raman histology. Different types of tissue scatter the light in distinctive ways. The light hits a detector, which emits a signal that a computer can process to reconstruct the image and identify the tissue.

The system also generates virtual images similar to traditional slides that humans can examine.

The researchers used images from tissue from 415 brain surgery patients to train an artificial intelligence system to identify the 10 most common types of brain tumor.

Some types of brain tumor are so rare that there is not enough data on them to train an A.I. system, so the system in the study was designed to essentially toss out samples it could not identify.

Over all, the system did make mistakes: It misdiagnosed 14 cases that the humans got right. And the doctors missed 17 cases that the computer got right.

“I couldn’t have hoped for a better result,” Dr. Orringer said. “It’s exciting. It says the combination of an algorithm plus human intuition improves our ability to predict diagnosis.”

In his own practice, Dr. Orringer said that he often used the system to determine quickly whether he had removed as much of a brain tumor as possible, or should keep cutting.

“If I have six questions during an operation, I can get them answered without having six times 30 or 40 minutes,” he said. “I didn’t do this before. It’s a lot of burden to the patient to be under anesthesia for that long.”

Dr. Bederson said that he had participated in a pilot study of a system similar to the one in the study and wanted to use it, and that his hospital was considering acquiring the technology.

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To Prevent Deadly Infections, F.D.A. Approves the First Disposable ‘Scope’

Following a series of deadly outbreaks in hospitals around the country, the Food and Drug Administration on Friday approved the first fully disposable version of the medical device implicated in the infections.

Reusable versions of the device — a long, snakelike tube with a fiber-optic camera at one end, called a duodenoscope — are inserted in one patient after another to diagnose and treat diseases of the pancreas and bile duct, like tumors and gallstones.

Duodenoscopes are used in 700,000 medical procedures each year. Yet tests showed that the devices could not be properly decontaminated between procedures because they cannot be sterilized by the usual methods.

After the outbreaks caused by duodenoscopes came to light, the F.D.A. had urged hospitals to use models with disposable parts and had called on manufacturers to produce fully disposable models.

The new device, called Exalt and made by Boston Scientific, is designed to be used only once before being discarded or recycled. The device should eliminate “the risk of potential infection due to ineffective reprocessing,” the arduous cleaning process, said Dr. Jeff Shuren, head of the F.D.A.’s Center for Devices and Radiological Health.

The disposable duodenoscope was designated a “breakthrough” device, indicating it provides for more effective treatment or diagnosis of life-threatening conditions. Its review at the F.D.A. was expedited in order to get it to market as soon as possible.

Since 2012, contaminated duodenoscopes have been implicated in dozens of infectious outbreaks affecting hundreds of hospital patients in the United States and Europe. Many were infected with bacteria resistant to powerful antibiotics.

More than 30 patients in Seattle with infected with resistant bacteria following duodenoscope procedures between 2012 and 2014. Eleven of them died. In 2015, two patients in Los Angeles died and five were sickened by contaminated duodenoscopes.

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The devices are used to perform a procedure, called endoscopic retrograde cholangiopancreatography, needed to diagnose and treat diseases of the pancreas, bile duct and gallbladder, such as life threatening jaundice, tumors, blocked bile ducts and stones.

The long tube, with a camera at the tip, is inserted through the patient’s mouth and stomach, and then into the first part of the small intestine, called the duodenum.

Many different reusable scopes are used in medicine, but duodenoscopes — which have a movable mechanism at the tip — are particularly difficult to clean. Though they are disinfected with chemicals, they have tiny nooks where bodily fluids and bacteria can lodge.

Cleaning, also called reprocessing, between patients involves nearly 100 steps, including both hand-scrubbing the device and inspecting it visually to check for biological debris clinging to the scopes.

Recent tests performed by manufacturers at the F.D.A.’s request found that even after the proper cleaning procedures were followed, one in 20 duodenoscopes retained disease-causing microbes like E. coli.

Whether the new disposable duodenoscope will be widely adopted remains to be seen. The Exalt is expected to carry a price tag of approximately $3,000, and insurance coverage is still uncertain.

Health care systems already have a full inventory of durable, reusable duodenoscopes, which cost between $35,000 and $45,000. Some of the durable devices already have disposable parts.

The disposable models will also have an environmental impact, creating a new stream of medical waste if they cannot be recycled. A spokesman for Boston Scientific said the company planned to offer a recycling program and was “currently finalizing plans with a medical waste recycle company to facilitate this process.”

Art Butcher, senior vice president of Boston Scientific Corp., said the new device would represent a “unique solution to a complex problem.”

Six experts who used the disposable scope in a clinical trial of 60 patients gave it satisfactory scores. Ninety percent said the disposable scope was as good as the reusable scope, and 2 percent said it was preferable. Eight percent said it was inferior to the reusable scope.