Emerging Technologies in Neuro-Oncology: AI, Intraoperative Imaging, Augmented Reality, and Robotics

Technological innovation is rapidly transforming neuro-oncologic surgery, yet a major unmet need remains: translating promising tools into reliable, workflow-integrated intraoperative systems that demonstrably improve oncological and functional outcomes. This Research Topic will focus on the intraoperative layer of emerging technologies, where imaging, visualization, and surgeon–machine interaction converge to enable safer and more precise brain and spinal tumor surgery.Recent advances in AI and computer vision have enabled automated tumor segmentation, real-time structure identification, outcome/extent-of-resection estimation, and decision-support methods that can operate on intraoperative data streams. In parallel, intraoperative imaging modalities, including intraoperative MRI (iMRI), CT (iCT), ultrasound, fluorescence-guided surgery, and hybrid imaging, allow continuous updating of anatomy and tumor boundaries to support adaptive surgical strategies. Intraoperative radiation therapy and image-guided radiation delivery approaches are also within scope when they are integrated into the intraoperative workflow for neuro-oncologic surgery. Augmented and mixed reality (AR/MR) systems are increasingly integrated into neuronavigation, microscopes, exoscopes, and head-mounted displays, enhancing spatial understanding, communication, and surgeon–machine interaction. Robotic platforms are also evolving, and are within scope for this Research Topic when they are coupled to imaging, navigation, AR/MR visualization, or AI-enabled intraoperative guidance in cranial or spinal tumor surgery.A central aim of this collection is to advance the field from innovation to evidence-based implementation. Despite rapid progress, many intraoperative technologies remain heterogeneous in implementation, incompletely validated, and variably adopted. Their clinical value, limitations, safety and ethical implications, cost-effectiveness, and integration into neuro-oncologic workflows remain active areas of investigation. We therefore encourage contributions that emphasize clinical translation and validation, including prospective evaluation, comparative effectiveness, reproducibility, robustness to real-world variability, and clinically meaningful endpoints (e.g., extent of resection, functional preservation, complications, quality of life, and survival where applicable).This Research Topic welcomes contributions from neurosurgeons, neuroradiologists, neuro-oncologists, radiation oncologists, medical physicists, engineers, imaging scientists, and computer scientists, and invites Original Research, Technical Notes, Clinical Trials/Study Protocols, Systematic Reviews, Narrative Reviews, and Perspectives. Submissions should ideally connect technical innovation to practical intraoperative deployment and measurable clinical impact.This Research Topic also welcomes contributions addressing, but not limited to:- Intraoperative imaging for neuro-oncology (iMRI, iCT, ultrasound, fluorescence and hybrid imaging; image fusion; real-time updating; extent-of-resection assessment)- AR/MR and advanced visualization (navigation overlays; microscope/exoscope integration; head-mounted displays; spatial cognition; ergonomics; communication and team situation awareness)- AI and computer vision for intraoperative guidance (real-time segmentation; registration; tracking; uncertainty estimation; robustness/domain shift; decision support at the point of care)- Imaging–AI–AR/MR integration (multimodal data fusion; closed-loop or adaptive guidance; interoperability with neuronavigation)- Robotics in neuro-oncology surgery when integrated with image guidance/AR/MR or AI-enabled intraoperative decision-making (planning, execution support, safety/verification)- Intraoperative radiation therapy and image-guided radiation delivery integrated into surgical workflows- Workflow, human factors, and implementation (usability, training, human–machine interaction, surgeon workload, standardization, data governance)- Validation and clinical impact (phantom and cadaver studies with clear translational relevance, prospective clinical studies, real-world implementations, safety and ethics, regulatory considerations)Manuscripts consisting solely of bioinformatics or computational analyses of public databases, or purely retrospective computational predictions without independent clinical/patient cohort validation or biological validation, are not suitable for this Research Topic. Additionally, manuscripts focused primarily on general clinical informatics/registries or perioperative protocols without a direct intraoperative imaging/visualization/guidance component are outside the main focus of this collection. Topic editors: Mirza Pojskic, Malik Galijasevic, Francesco Costa Source: https://www.frontiersin.org/research-topics/77392/emerging-technologies-in-neuro-oncology-ai-intraoperative-imaging-augmented-reality-and-robotics