Artificial Intelligence Applications in Stereotactic Radiosurgery and Neurosurgical Oncology
A special issue of Current Oncology (ISSN 1718-7729). This special issue belongs to the section "Neuro-Oncology".
Deadline for manuscript submissions: 30 November 2026 | Viewed by 230
Special Issue Editors
Interests: stereotactic radiosurgery; neurosurgical oncology; artificial intelligence; machine learning; precision medicine; radiobiology; neuroinformatics; translational neurosurgery
2. Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA
Interests: stereotactic radiosurgery; brain and spine tumor imaging; surgery and therapeutics; medical device development
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) is reshaping cranial neurosurgical oncology and stereotactic radiosurgery, moving from experimental algorithms to tools that directly support precision medicine. In stereotactic radiosurgery, AI‑driven methods improve radiobiology modeling, volumetric analysis, treatment planning, and outcome prediction, leading to better dose distribution, more efficient workflows, and improved normal‑tissue protection. In cranial neurosurgical oncology, machine learning, radiomics, and radiogenomics support quantitative tumor characterization, guide image‑based surgical navigation, and inform adaptive treatment strategies for gliomas, meningiomas, skull base lesions, and brain metastases.
This Current Oncology Special Issue, “Artificial Intelligence Applications in Stereotactic Radiosurgery and Neurosurgical Oncology,” will bring together multidisciplinary perspectives to define practical standards for AI integration in cranial cancer care. Submissions are invited from medical physics, radiation oncology, neurosurgery, neuro‑oncology, and AI research groups or start‑ups working on validation methods, predictive modeling and outcome prediction, treatment planning and workflow optimization, workflow automation and quality assurance, regulatory oversight, and transparent deployment of AI in neurosurgical and radiosurgical practice. The goal is to move beyond technical novelty toward consistent, reproducible patient benefit grounded in safety, precision, and collaborative, cross‑industry implementation.
This Special Issue welcomes original research and reviews on the clinical integration of artificial intelligence, machine learning, radiomics, and radiogenomics in stereotactic radiosurgery and cranial neurosurgical oncology. Submissions focusing on translational neurosurgery, clinical integration and implementation science, predictive modeling and outcome prediction, treatment planning and workflow optimization, and transparent AI deployment are particularly encouraged to advance precision, safety, and reproducibility in cranial oncologic care.
Dr. Maleeha Ahmad
Dr. Susan C. Pannullo
Guest Editors
Manuscript Submission Information
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Keywords
- stereotactic radiosurgery
- cranial neurosurgical oncology
- artificial intelligence
- machine learning
- radiomics and radiogenomics
- precision medicine
- predictive modeling and outcome prediction
- treatment planning and workflow optimization
- translational neurosurgery
- clinical integration and implementation science
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