Neuro-Oncology | Neuroimaging for Brain Tumors*
Date: October 20, 2026
Time: 11:00 am to 12:30 pm
Room: Coral 5
Track: Traditional Special Interest Group (SIG)
Session Description
The theme of this year’s Neuro-oncology Special Interest Group session is Neuroimaging for Brain Tumors. Advances over the past decade have expanded neuroimaging beyond structural techniques to include physiologic and molecular approaches that provide insight into tumor biology. Modalities such as perfusion imaging and amino acid PET are enhancing diagnostic accuracy and enabling earlier, more targeted interventions.
In the context of emerging immunotherapies and targeted treatments, improved imaging may significantly impact clinical decision-making and patient outcomes. This session will highlight current and emerging imaging techniques, their correlation with tumor pathology, and the growing role of artificial intelligence in advancing neuro-oncologic imaging.
Learning Objectives
At the conclusion of this session, attendees will be able to:
- Describe key neuroimaging modalities used in the evaluation of brain tumors.
- Explain the relationship between imaging findings and tumor pathology.
- Discuss the role of artificial intelligence in enhancing neuroimaging interpretation.
Speakers
- (Chair) Eric Wong, MD, MA, FAAN, FANA
- (Co-Chair) Adilia Hormigo, MD, PhD, FANA
- (Speaker) Peter LaViolette, PhD
- (Speaker) Kambiz Nael, MD
- (Speaker) Zhicheng Jiao, PhD
- (Speaker) Hans Shuhaiber, MD (2026 SIG Oral Presenter)
- (Speaker) Milan Chheda, MD (2026 SIG Oral Presenter)
Radio-pathomic Mapping of Glioblastoma: Detecting Invisible Infiltrative Tumor
Description
Glioblastoma is characterized by diffuse tumor infiltration that often extends beyond the boundaries visible on conventional imaging, making complete tumor characterization and treatment planning particularly challenging. Advances in artificial intelligence and radiologic-pathologic integration are creating new opportunities to identify these otherwise undetectable regions of disease.
This presentation will explore the use of radio-pathomic mapping to detect invisible infiltrative tumor in glioblastoma by integrating artificial intelligence with radiologic-pathologic (rad-path) correlation. Participants will examine how AI-driven imaging analyses can identify patterns associated with microscopic tumor infiltration, review the underlying principles of radio-pathomic mapping, and discuss the potential applications of these techniques for surgical planning, radiation targeting, and treatment monitoring. Topics will also include the role of multimodal data integration in advancing precision neuro-oncology and improving patient outcomes.
Attendees will leave with a greater understanding of how AI-enabled radio-pathomic mapping is transforming the detection of infiltrative glioblastoma and practical insights into the future role of advanced imaging technologies in precision diagnosis and treatment planning.
Advanced MRI for Brain Tumor Characterization: A Case-based Practical Approach
Description
Advanced magnetic resonance imaging (MRI) techniques have become indispensable tools for the evaluation of brain tumors, providing critical physiological and microstructural information beyond conventional imaging. Techniques such as perfusion and diffusion MRI can improve diagnostic accuracy, guide treatment planning, and enhance the assessment of treatment response.
This presentation will provide a case-based overview of advanced MRI applications in brain tumor characterization, with a focus on perfusion and diffusion imaging. Participants will review representative clinical cases that demonstrate the practical use of these advanced imaging techniques, learn how to interpret key imaging findings, and discuss strategies for distinguishing tumor types, assessing tumor grade, and differentiating treatment-related changes from disease progression. Topics will also include practical tips and common pitfalls to improve diagnostic confidence and optimize the clinical use of advanced MRI.
Attendees will leave with a greater understanding of the role of perfusion and diffusion MRI in brain tumor evaluation and practical insights into applying advanced imaging techniques to improve diagnostic accuracy and patient management in neuro-oncology.
Evolving Brain Tumor MRI AI: From Conventional Deep Imaging Models to Multimodal Foundation-Model Fusion
Description
Artificial intelligence is rapidly transforming brain tumor imaging, moving beyond conventional image-based deep learning models toward multimodal foundation models that integrate imaging with clinical, molecular, and genomic data. These next-generation approaches have the potential to enhance diagnostic accuracy, improve prognostic assessment, and support more personalized treatment strategies in neuro-oncology.
This presentation will provide an overview of the evolution of artificial intelligence in brain tumor MRI, highlighting the transition from conventional deep imaging models to multimodal foundation-model fusion. Participants will examine how these advanced AI frameworks integrate diverse sources of patient data to improve tumor characterization, diagnosis, prognosis, and treatment planning. Topics will also include current applications, emerging research, implementation challenges, and the future role of multimodal AI in advancing precision neuro-oncology.
Attendees will leave with a greater understanding of the rapidly evolving landscape of AI-driven brain tumor imaging and practical insights into how multimodal foundation models may transform clinical decision-making and personalized care for patients with brain tumors.
Pain Outcomes in Patients With/Without Volumetric Tumor Response: Post Hoc From the ReNeu Trial of Mirdametinib in Adults & Children With Neurofibromatosis Type 1-Associated Plexiform Neurofibroma
Description
Neurofibromatosis type 1 (NF1) is a rare autosomal-dominant genetic condition caused by loss-of-function variants in the NF1 gene. Patients with NF1 often develop plexiform neurofibromas (PNs), which are nonmalignant nerve sheath tumors that can cause pain and significantly impact quality of life. Mirdametinib is the first FDA-approved MEK1/2 inhibitor for both adults and children with NF1 and symptomatic inoperable PNs, and has been previously shown to alleviate pain in patients with NF1-PN. The exact mechanism of pain improvement is unknown, though tumor volume reduction and/or changes in nerve pain signaling may play a role.
This presentation will evaluate changes in pain with mirdametinib in both adults and children with NF1-PN from the phase 2 ReNeu clinical trial. Participants will learn how pain severity and its impact on daily activities change over time with mirdametinib treatment. Additionally, participants will explore whether pain improvements with mirdametinib treatment are associated with reductions in tumor volume. Attendees will leave with a greater understanding of how mirdametinib alleviates pain burden in patients with NF1-PN and the contribution of tumor size on pain.
Attendees will also appreciate the multifactorial nature of pain associated with NF1-PN, which cannot be solely attributed to one cause.
Siglec-15 and PD-1 Checkpoint Blockade in Combination with Oncolytic Zika Virus Infection Confers Protection Against Immune-resistant Gliomas
Description
Immune checkpoint blockade has led to significant advances in survival for many cancers, however, in multiple phase 3 trials for glioblastoma, they have failed.
This presentation will review new data using patient samples and genetic and antibody-based therapies in animal models, suggesting the potential importance of Siglec-15 as a clinically tractable immune checkpoint in GBM. We also discuss our work developing a new oncolytic therapy for GBM.
Attendees will leave with a greater understanding of the current challenges in brain tumors and the immunosuppressive tumor microenvironment, and emerging treatments.
