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 hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




AI-Based MRI Tool Outperforms Current Brain Tumor Diagnosis Methods

By MedImaging International staff writers
Posted on 13 Mar 2024
Print article
Image: The deep learning tool leverages identifies behavioral patterns on imaging specific to each tumor (Photo courtesy of VHIO)
Image: The deep learning tool leverages identifies behavioral patterns on imaging specific to each tumor (Photo courtesy of VHIO)

Glioblastoma multiforme, metastases from solid tumors to the brain, and primary central nervous system lymphoma comprise up to 70% of all malignant brain cancers. Differentiating among these malignancies is crucial because each type demands a specific treatment strategy, but presents a clinical challenge. Currently, the non-invasive diagnosis of brain tumors relies on magnetic resonance imaging (MRI) analysis before and after the administration of contrast agents. However, a conclusive diagnosis often requires neurosurgical procedures, which can negatively impact the patient's quality of life. Now, a deep learning tool leverages magnetic resonance imaging (MRI) data to accurately classify brain tumors, thereby supporting clinicians in making informed decisions.

The Diagnosis in Susceptibility Contrast Enhancing Regions for Neuroncology (DISCERN) is an open access, deep learning tool developed jointly by investigators from the Vall d’Hebron Institute of Oncology (VHIO, Barcelona, Spain) and Bellvitge University Hospital (Barcelona, Spain). It is based on the training of patterns using artificial intelligence (AI) models extracted from standard MRI information. DISCERN interprets the comprehensive spatial and temporal data available from conventional MRI scans to recognize tumor-specific patterns.

By employing deep learning, the system learns to distinguish between the characteristics of various tumors based on MRI scans from previously diagnosed patients. A study led by VHIO demonstrated DISCERN's capability to facilitate the accurate diagnosis of brain tumors using perfusion MRI, surpassing the accuracy of traditional diagnostic methods. With an accuracy rate of 78% in classifying these common brain cancers, DISCERN represents a significant advancement in the field. The developers have made DISCERN accessible through an easy-to-use, open-source application to promote its widespread use in clinical research and enhance the reproducibility of findings.

“DISCERN is a computerized diagnostic support tool that facilitates the classification of brain tumors to help guide medical decision making by multidisciplinary teams regarding the need for and type of surgery required to confirm diagnosis,” said Carles Majós, clinical neuroradiologist and investigator at the Bellvitge University Hospital.

Related Links:
VHIO 
Bellvitge University Hospital

Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
Ultrasound System
Voluson Signature 18
New
NMUS & MSK Ultrasound
InVisus Pro
New
Ultrasound Table
Vascular with Fowler EA Table

Print article
Radcal

Channels

Radiography

view channel
Image: 3D cinematic renderings of the control and diseased heart in anatomic orientation (Photo courtesy of ESRF)

Innovative X-Ray Technique Captures Human Heart with Unprecedented Detail

Cardiovascular disease remains the leading cause of death globally. In 2019, ischemic heart disease, which weakens the heart due to reduced blood supply, accounted for approximately 8.9 million or 16%... Read more

Ultrasound

view channel
Image: The new FDA-cleared AI-enabled applications have been integrated into the EPIQ CVx and Affiniti CVx ultrasound systems (Photo courtesy of Royal Philips)

Next-Gen AI-Enabled Cardiovascular Ultrasound Platform Speeds Up Analysis

Heart failure is a significant global health challenge, affecting approximately 64 million individuals worldwide. It is associated with high mortality rates and poor quality of life, placing a considerable... Read more

General/Advanced Imaging

view channel
Image: HeartFlow Plaque Analysis leverages cutting-edge AI for assessment of plaque quantity and composition (Photo courtesy of HeartFlow, Inc.)

Next Gen Interactive Plaque Analysis Platform Assesses Patient Risk in Suspected Coronary Artery Disease

A first-of-its-kind plaque analysis tool to be fully integrated with FFRCT (when FFRCT is performed) provides impactful insights that enhance clinical decision-making and enable personalized patient treatment... 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 new collaborations aim to further advance AI foundation models for medical imaging (Photo courtesy of Microsoft)

Microsoft collaborates with Leading Academic Medical Systems to Advance AI in Medical Imaging

Medical imaging is a critical component of healthcare, with health systems spending roughly USD 65 billion annually on imaging alone, and about 80% of all hospital and health system visits involve at least... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.