Artificial intelligence and machine learning are emerging as disruptive technologies that have the potential to significantly improve clinical decision-making in spine surgery.
While AI is still in its infancy in healthcare, its potential to transform spine surgery is vast. As the technology develops and becomes more widely adopted, surgeons will have the ability to plan surgical strategies with advanced platforms; safely, reliably and expeditiously place implants; and predict the correction and define goals of spine surgeries.
"We will truly have a more comprehensive approach to the patients in terms of planning, execution and patient-reported outcomes," Ronald Lehman Jr., MD, of New York City-based Columbia Orthopedic Surgery, told Becker's. "Using data and predictive analytics will allow us to tell each patient what their expected results will be before they consider a spine surgery, and also, perhaps, who best to perform the surgery, as all of our metrics, as surgeons, will be available as well."
In spinal deformity, algorithms have been developed to accurately inform the surgeon in real time of the risk and benefit of a particular procedure for a specific patient. Other algorithms are being built to suggest the ideal alignment parameters for a specific patient based on their unique anatomy, and devices such as patient-specific rods have been designed to help surgeons achieve these goals.
"As outcomes from these surgeries are collected and added to the datasets, machine learning allows the algorithm to become even more accurate," according to David Kaye, MD, of Philadelphia-based Rothman Orthopaedic Institute. "In a drive to improve patient outcomes, AI allows for assimilation of big data and interpretation in a meaningful and trainable way. These tools will become an increasingly important part of the preoperative, intraoperative and postoperative management of our patients, and may allow safer, more effective and more cost-efficient surgery moving forward."
Spinal deformity procedures are typically larger and more complex cases that are performed for patients who are experiencing significant pain and contribute to a difficult quality of life.
"We don't want to undertake these larger surgeries without really being granular in guiding our patients about what to expect and how to achieve those corrections intraoperatively," said Saad Chaudhary, MD, of New York City-based Mount Sinai Health System. "When we place all these parameters about patients, such as their disease status, their bone quality, their specifics and spine needs, into an algorithm which uses AI technology, we hope we can better predict and better effectuate a good, effective treatment option for them."