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


ATTENTION: Due to the COVID-19 PANDEMIC, many events are being rescheduled for a later date, converted into virtual venues, or altogether cancelled. Please check with the event organizer or website prior to planning for any forthcoming event.

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 Supplier
Portable X-Ray System
FDR Xair
Digital Chest and Bone Room
Atlas HC2
Image Acquisition Software
ExamVue Duo
SPECT/CT Scanner
AnyScan SC

Print article
FIME - Informa
Sun Nuclear -    Mirion



view channel
Image: BiOI ruby-like crystals can improve medical imaging safety by lowering intensities of harmful X-rays (Photo courtesy of University of Cambridge)

Sustainable Solar Cell Material Could Revolutionize Medical Imaging

The use of X-rays for internal body imaging has dramatically changed non-invasive medical diagnostics. Yet, the high dose of X-rays required for these imaging techniques, due to the poor performance of... Read more


view channel
Image: A new study has shown the value of endoscopic ultrasound in NSCLC (Photo courtesy of Freepik)

Endoscopic Ultrasound Can Provide Value in NSCLC, Finds Study

The usefulness of confirmatory mediastinoscopy following tumor-negative results on endoscopic ultrasound still remains debatable among researchers. This procedure is often employed for mediastinal staging... Read more

Nuclear Medicine

view channel
Image: New imaging method offers potential for diagnosing, staging, and treating multiple types of cancer (Photo courtesy of SNMMI)

New Imaging Method Superior for Diagnosing Multiple Types of Cancer

Cancer-associated fibroblasts play a significant role in tumor development, migration, and progression. A subset of these fibroblasts expresses fibroblast activation protein (FAP), a protein prominently... 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 global AI-enabled medical imaging solutions market is expected to reach USD 18.36 billion in 2032 (Photo courtesy of Freepik)

Global AI-Enabled Medical Imaging Solutions Market Driven by Need for Early Disease Detection

The AI-enabled medical imaging solutions market is currently in its developmental stages, following the significant role of AI-based tools in combating the COVID-19 pandemic. The pandemic saw an upswing... Read more
Copyright © 2000-2023 Globetech Media. All rights reserved.