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




AI Predicts Brain Cancer Survivors within Eight-Months of Radiotherapy Using MRI Scan

By MedImaging International staff writers
Posted on 01 Feb 2024
Print article
Image: AI can predict if brain cancer patients will survive more than 8 months after receiving radiotherapy treatment (Photo courtesy of KCL)
Image: AI can predict if brain cancer patients will survive more than 8 months after receiving radiotherapy treatment (Photo courtesy of KCL)

Glioblastoma, a particularly challenging adult primary brain cancer to treat, has a low survival rate, with only one in four patients living beyond a year after diagnosis. Typically, patients undergo an eight-month course of chemotherapy following radiotherapy. Currently, regular and routine scanning is performed on patients with adult primary brain cancer to evaluate the effectiveness of chemotherapy. However, this process can result in some patients undergoing ineffective chemotherapy that not only fails to prolong life but also subjects them to detrimental side effects. Now, researchers have demonstrated that artificial intelligence (AI) can predict whether adult brain cancer patients will survive for more than eight months following radiotherapy. This groundbreaking use of AI in predicting patient outcomes could significantly guide clinicians in planning subsequent treatment stages and expedite referrals to potentially life-saving therapies. This marks the first instance of AI being used to distinguish between short-term and long-term survivors within eight months post-radiotherapy.

After radiotherapy, follow-up brain scan findings are often non-specific and oncologists cannot be certain whether a treatment is working or failing. A team from King’s College London developed a deep learning model to enhance the reliability and accuracy of predicting outcomes for patients with adult primary brain cancer. The AI was trained on tens of thousands of scans from a diverse range of brain cancer patients. Instead of trying to grapple with interpreting every non-specific follow-up brain scan, the AI can make an immediate and accurate prediction of which patients will not survive the next 8 months by simply looking at one routine scan after radiotherapy. This can empower clinicians and patients to make choices about their treatment. By providing an instant and accurate prediction from one routine MRI scan, the AI enables physicians to identify those patients unlikely to benefit from chemotherapy, allowing them to consider alternative treatments or enroll patients in clinical trials for experimental therapies.

“This is exciting and fundamental research for people living with a glioblastoma, for two reasons,” said Dr. Helen Bulbeck, Director of Services and Policy at brainstrust. “At its simplest level it demonstrates how AI can be used for patient benefit. More importantly however, it empowers patients and their caregivers to make choices about the clinical pathway and gives control back at a time when so much control has been lost. Patients will be able to make informed decisions about treatment choices and will be able to plan how they want to spend the time they have left so that they can live their best possible day, every day.”

Related Links:
King’s College London

Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
New
Color Doppler Ultrasound System
KC20
New
X-Ray QA Meter
Piranha CT
New
X-Ray Detector
FDR-D-EVO III

Print article

Channels

Ultrasound

view channel
Image: The powerful machine learning algorithm can “interpret” echocardiogram images and assess key findings (Photo courtesy of 123RF)

Largest Model Trained On Echocardiography Images Assesses Heart Structure and Function

Foundation models represent an exciting frontier in generative artificial intelligence (AI), yet many lack the specialized medical data needed to make them applicable in healthcare settings.... Read more

Nuclear Medicine

view channel
Image: The multi-spectral optoacoustic tomography (MSOT) machine generates images of biological tissues (Photo courtesy of University of Missouri)

New Imaging Technique Monitors Inflammation Disorders without Radiation Exposure

Imaging inflammation using traditional radiological techniques presents significant challenges, including radiation exposure, poor image quality, high costs, and invasive procedures. Now, new contrast... 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
Copyright © 2000-2024 Globetech Media. All rights reserved.