We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App

AI-Powered Algorithm Catches Unruptured Brain Aneurysms Missed in Routine CT Scans

By MedImaging International staff writers
Posted on 18 Sep 2023
Print article
Image: An AI-powered algorithm can help detect unruptured brain aneurysms missed in routine clinical care (Photo courtesy of 123RF)
Image: An AI-powered algorithm can help detect unruptured brain aneurysms missed in routine clinical care (Photo courtesy of 123RF)

Each year, a significant number of people worldwide suffer from ruptured aneurysms in the brain. Often, these aneurysms are discovered by chance during brain scans conducted for unrelated issues. Now, a machine learning algorithm has been found to better identify these unruptured aneurysms that need medical attention but may be overlooked during routine brain scans.

Researchers from UTHealth Houston (Houston, TX, USA) studied a prospectively maintained registry that involved eight approved stroke centers. They focused on patients who had undergone CT angiography scans to evaluate potential stroke risks. A machine learning algorithm called Viz Aneurysm from Viz.ai (San Francisco, CA, USA), analyzed these scans to identify unruptured cerebral aneurysms that were at least four millimeters large. Out of 1,191 scans reviewed during the study, the algorithm flagged 50 as possibly showing an unruptured aneurysm. From those, 36 genuine aneurysms were detected from 31 CT angiograms, including four cases of multiple aneurysms.

Of these 36 confirmed aneurysms, 67% had not been previously marked for further evaluation, and they had a median size of 4.4 millimeters. Five of these untracked aneurysms were larger than seven millimeters and carried an average 2.4% risk of rupture over the next five years. To put it simply, only a third of the unruptured aneurysms that likely needed further investigation had been initially flagged for follow-up during routine clinical care. The most common location for these aneurysms was the internal carotid artery, accounting for 46% of cases. Researchers believe that such machine learning algorithms can enhance the detection rate of unruptured cerebral aneurysms by flagging CT angiograms suspected of aneurysm. Such algorithms can also help streamline follow-up and communication among healthcare providers through the same platform.

“We have already seen the tremendous benefit that machine learning can bring to patients suffering from acute stroke,” said senior author Sunil A. Sheth, MD, associate professor at UTHealth Houston. “In this study, we see a similar possibility for substantially improving the way in which we identify, counsel, and help patients with brain aneurysms.”

Related Links:
UTHealth Houston 

Gold Supplier
Ultrasound System
Gold Supplier
Conductive Gel
Interventional Robot
Ferromagnetic Hand-Held Detector
FerrAlert Target Scanner

Print article



view channel
Image: Intelligent NR provides high-quality diagnostic images containing significantly less grainy noise (Photo courtesy of Canon)

AI-Driven DR System Produces Higher Quality Images While Limiting Radiation Doses in Pediatric Patients

Ionizing radiation is a fundamental element in producing diagnostic X-rays, yet it's widely acknowledged for its cancer risk potential. Digital projection radiography, a vital imaging modality, accounts... Read more


view channel
Image: The researchers are using MRI-guided radiation therapy that pairs daily MRIs with radiation treatment (Photo courtesy of Sylvester)

AI Technique Automatically Traces Tumors in Large MRI Datasets to Guide Real-time Glioblastoma Treatment

Treating glioblastoma, a prevalent and aggressive brain cancer, involves the use of radiation therapy guided by CT imaging. While this method is effective in targeting radiation, it doesn't provide real-time... Read more


view channel
Image: The new ultrasound patch can measure how full the bladder is (Photo courtesy of MIT)

Ultrasound Patch Designed to Monitor Bladder and Kidney Health Could Enable Earlier Cancer Diagnosis

Bladder dysfunction and related health issues affect millions worldwide. Monitoring bladder volume is crucial for assessing kidney health. Traditionally, this requires a visit to a medical facility and... Read more

Nuclear Medicine

view channel
Image: A novel PET radiotracer facilitates early, noninvasive detection of IBD (Photo courtesy of Karmanos)

New PET Radiotracer Aids Early, Noninvasive Detection of Inflammatory Bowel Disease

Inflammatory bowel disease (IBD), which includes Crohn’s disease and ulcerative colitis, is an inflammatory condition of the gastrointestinal tract affecting roughly seven million individuals globally.... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more

Industry News

view channel
Image: Attendees can discover innovative products and technology in the RSNA 2023 Technical Exhibits (Photo courtesy of RSNA)

RSNA 2023 Technical Exhibits to Offer Innovations in AI, 3D Printing and More

The 109th Scientific Assembly and Annual Meeting of the Radiological Society of North America (RSNA, Oak Brook, IL, USA) to be held in Chicago, Nov. 26 to 30 is all set to offer a vast array of medical... Read more
Copyright © 2000-2023 Globetech Media. All rights reserved.