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
GLOBETECH PUBLISHING LLC

Download Mobile App




Machine Learning Analyzes MRI Data to Predict Brain Tumor Progression

By MedImaging International staff writers
Posted on 17 Jan 2023
Print article
Researchers have used MRI data to further personalize cancer medicine (Photo courtesy of Pexels)
Researchers have used MRI data to further personalize cancer medicine (Photo courtesy of Pexels)

Glioblastoma multiforme (GBM), a brain cancer that has an average survival rate of just one year, can be difficult to treat because of its highly dense core, rapid growth, and location. Clinicians find it difficult to quickly and accurately estimate the diffusivity and proliferation rate for these tumors in an individual patient. Now, researchers have created a computational model that uses MRI data to predict the growth of these deadly brain tumors more accurately.

Researchers at the University of Waterloo (Waterloo, ON, Canada) analyzed MRI data from several sufferers of GBM using machine learning in order to better predict the progression of cancer. The team analyzed two sets of MRIs from each of five GBM patients who underwent extensive MRIs, waited for months, and then received another set of MRIs. Since these patients opted not to receive any treatment or intervention during this time, the researchers were provided a unique opportunity to examine how GBM grows when left unchecked by analyzing their MRIs.

Using a deep learning model, the researchers turned the MRI data into patient-specific parameter estimates that inform a predictive model for GBM growth. They applied this technique to the patients’ and synthetic tumors, for which the true characteristics were known, allowing them to validate the model. The scientists now have a good model of how GBM grows untreated and will now expand the model to include the impact of treatment on the tumors. The data set would then grow from a handful of MRIs to thousands. According to the researchers, access to MRI data – and partnership between mathematicians and clinicians – can significantly impact patients in the future.

“The integration of quantitative analysis into healthcare is the future,” said Cameron Meaney, a PhD candidate in Applied Mathematics and the study’s lead researcher.

Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
New
Brachytherapy Planning System
Oncentra Brachy
New
Thyroid Shield
Standard Thyroid Shield
Imaging Table
Stille imagiQ2

Print article

Channels

Ultrasound

view channel
Image: Structure of the proposed transparent ultrasound transducer and its optical transmittance (Photo courtesy of POSTECH)

Ultrasensitive Broadband Transparent Ultrasound Transducer Enhances Medical Diagnosis

The ultrasound-photoacoustic dual-modal imaging system combines molecular imaging contrast with ultrasound imaging. It can display molecular and structural details inside the body in real time without... Read more

Nuclear Medicine

view channel
Image: PET/CT of a 60-year-old male patient with clinical suspicion of lung cancer (Photo courtesy of EJNMMI Physics)

Early 30-Minute Dynamic FDG-PET Acquisition Could Halve Lung Scan Times

F-18 FDG-PET scans are a way to look inside the body using a special dye, and these scans can be either static or dynamic. Static scans happen 60 minutes after the dye is administered into the body, showing... 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: The acquisition will expand IBA’s medical imaging quality assurance offering (Photo courtesy of Radcal)

IBA Acquires Radcal to Expand Medical Imaging Quality Assurance Offering

Ion Beam Applications S.A. (IBA, Louvain-La-Neuve, Belgium), the global leader in particle accelerator technology and a world-leading provider of dosimetry and quality assurance (QA) solutions, has entered... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.