The study is the first to use multiphase CTA to look at occlusions in both the arteries of the front, or anterior, part of the head and neck and those in the back, or posterior.
"Posterior circulation occlusions have not been discussed much in machine learning literature," Dr. Stib said. "They're less common but have pretty profound clinical consequences if missed. It's important to have an algorithm that detects all categories of occlusion, both anterior and posterior."
The next step in the research is to validate the results using the algorithm in real time and see if it can improve outcomes for patients. If the results hold up, then the deep learning model could be a useful asset in medical centers or hospitals that don't have the expertise for reading large vessel occlusion CTA images.
"This algorithm is not replacing the ability of radiologists to do their job; rather, it's trying to speed up the time to diagnosis," Dr. Stib said. "So if the radiologist isn't around or there is a large workflow that is preventing someone from looking at the exam results quickly, there will be an alert that says an occlusion may be present and someone should look at this. That's where the value is in this kind of a model."
The team worked under the direction of the study's senior author Ryan A. McTaggart, M.D., a neuroradiologist specializing in interventional neuroradiology at Rhode Island Hospital in Providence, Rhode Island, and proponent of decreasing the time to treatment for large vessel occlusions.
"Detecting Large Vessel Occlusion at Multiphase CT Angiography by Using a Deep Convolutional Neural Network." Collaborating with Drs. Stib and McTaggart were Justin Vasquez, M.S., Mary P. Dong, Yun Ho Kim, Sumera S. Subzwari, Harold J. Triedman, Amy Wang, Hsin-Lei Charlene Wang, B.A., Anthony D. Yao, B.S., Mahesh Jayaraman, M.D., Jerrold L. Boxerman, M.D., Ph.D., Carsten Eickhoff, Ph.D., Ugur Cetintemel, Ph.D., and Grayson L. Baird, Ph.D.
Radiology is edited by David A. Bluemke, M.D., Ph.D., University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, and owned and published by the Radiological Society of North America, Inc.
About RSNA
RSNA is an association of radiologists, radiation oncologists, medical physicists and related scientists promoting excellence in patient care and health care delivery through education, research and technologic innovation. The Society is based in Oak Brook, Illinois.
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