AI software IDs common cause of stroke, dementia
Researchers from the at Imperial College London and the University of Edinburgh have developed artificial intelligence (AI) software capable of detecting a common cause of dementia and stroke. Findings were published May 15 in Radiology.
Currently, clinicians diagnose small vessel disease (SVD)—where a reduction in blood flow to deep white matter leads to cell death—by identifying changes in white matter with MRI or CT scan. In this study, researchers evaluated the feasibility of a new software in identifying and measuring the severity of SVD.
"This is the first time that machine learning methods have been able to accurately measure a marker of small vessel disease in patients presenting with stroke or memory impairment who undergo CT scanning,” said Paul Bentley, PhD, lead author and Clinical Lecturer at Imperial College London. “Our technique is consistent and achieves high accuracy relative to an MRI scan—the current gold standard technique for diagnosis. This could lead to better treatments and care for patients in everyday practice."
The study used data from 1,082 CT scans of stroke patients from 70 hospitals in the United Kingdom from 2000 to 2014 to evaluate the software. The program was able to both identify and pinpoint a severity score of SVD from mild to severe. Additionally, researchers noted the software agreed with experts at 85 percent accuracy.
"Current methods to diagnose the disease through CT or MRI scans can be effective, but it can be difficult for doctors to diagnose the severity of the disease by the human eye,” concluded Bentley and colleagues. “The importance of our new method is that it allows for precise and automated measurement of the disease. This also has applications for widespread diagnosis and monitoring of dementia, as well as for emergency decision-making in stroke."
Cara joined TriMed Media in 2016 and is currently a Senior Writer for Clinical Innovation & Technology. Originating from Detroit, Michigan, she holds a Bachelors in Health Communications from Grand Valley State University.