Back to all news
AI Model Improves Differentiation of Brain Tumor Progression from Radiation Necrosis on MRI
A York University-led study shows a novel AI using advanced MRI can distinguish between progressive brain tumors and radiation necrosis more accurately than human assessment.
Key Details
- 1AI model uses attention-guided deep learning with chemical exchange saturation transfer (CEST) MRI.
- 2Study included over 90 patients with brain metastases treated by stereotactic radiosurgery (SRS).
- 3AI achieved over 85% accuracy in distinguishing tumor progression from necrosis, compared to ~60% for standard MRI and ~70% for advanced MRI alone.
- 4Published December 2025 in International Journal of Radiation Oncology, Biology, Physics.
- 5A crucial clinical challenge as treatment decisions for tumor progression vs necrosis are substantially different.
Why It Matters
Differentiating tumor progression from radiation necrosis on MRI post-therapy is a major clinical challenge, as each requires different treatments. AI that improves diagnosis accuracy could substantially impact patient management and outcomes in neuro-oncology.
Source
EurekAlert
Related News
•EurekAlert
AI Model Accurately Predicts Blood Loss Risk in Liposuction
A machine learning model predicts blood loss during high-volume liposuction with 94% accuracy.
•EurekAlert
AI-Driven CT Tool Predicts Cancer Spread in Oropharyngeal Tumors
Researchers have created an AI tool that uses CT imaging to predict the spread risk of oropharyngeal cancer, offering improved treatment stratification.
•EurekAlert
AI Model PRTS Predicts Spatial Transcriptomics From H&E Histology Images
Researchers developed PRTS, a deep learning model that infers single-cell spatial transcriptomics from standard H&E-stained tissue images.