Multimodal Neuroimaging in Image-Guided Neurosurgery: Current Applications, Clinical Challenges and Future Directions -A Narrative Review

Abstract

Background Modern neurosurgery increasingly relies on individualized neuroimaging to maximize lesion resection while preserving neurological function. Conventional magnetic resonance imaging (MRI) provides detailed anatomical information but does not fully characterize cortical function, white-matter connectivity, or anatomical changes occurring during surgery. Multimodal neuroimaging integrates complementary structural, functional, and connectivity information and can therefore support more individualized image-guided surgical planning.  Objective This narrative review examines the current applications of multimodal neuroimaging in image-guided neurosurgery, focusing on structural MRI, functional MRI (fMRI), diffusion tensor imaging (DTI) and tractography, neuronavigation, intraoperative MRI, intraoperative ultrasound, and approaches for addressing intraoperative brain shift. Emerging computational and artificial intelligence (AI)-assisted approaches are also discussed.  Methods A narrative literature search was conducted using PubMed/MEDLINE. Additional relevant publications were identified through reference-list screening of selected reviews and primary studies. Search concepts included multimodal neuroimaging, image-guided neurosurgery, functional MRI, diffusion tensor imaging, tractography, neuronavigation, intraoperative MRI, intraoperative ultrasound, brain shift, functional brain mapping, and brain tumor surgery. Clinical studies, systematic reviews, meta-analyses, and methodological literature relevant to these topics were considered. Because this was a narrative review, no formal meta-analysis or quantitative risk-of-bias assessment was performed.  Results Structural MRI remains the anatomical foundation of image-guided neurosurgery. Functional MRI can provide noninvasive information regarding cortical networks, while diffusion imaging and tractography can characterize major whitematter pathways. Integration of these datasets into neuronavigation can assist individualized surgical planning, particularly for lesions involving eloquent cortex or critical subcortical tracts. Intraoperative MRI can update navigation and identify residual tumor after anatomical deformation, whereas intraoperative ultrasound provides real-time imaging with lower infrastructure requirements. Important limitations include neurovascular uncoupling, functional reorganization, tractography uncertainty, registration errors, brain shift, cost, workflow complexity, and limited prospective validation.  Conclusion Multimodal neuroimaging provides a clinically valuable framework for precision image-guided neurosurgery by integrating anatomical, functional, and connectivity information across the surgical pathway. Future advances should prioritize reliable multimodal integration, real-time intraoperative updating, standardized imaging protocols, interpretable computational tools, and prospective evaluation of patient-centered outcomes.