Digital 3D Models in Neurosurgical Training, Surgical Planning, and Intraoperative Guidance: Comprehensive Review of the Literature

Digital 3D Models in Neurosurgical Training, Surgical Planning, and Intraoperative Guidance: Comprehensive Review of the Literature | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 27 October 2025 V1 Latest version Share on Digital 3D Models in Neurosurgical Training, Surgical Planning, and Intraoperative Guidance: Comprehensive Review of the Literature Authors : Efecan Cekic , Gulsah Cetin , Ayse Ozer , Baylar Baylarov , Ilkan Tatar , and Sahin Hanalioglu 0000-0003-4988-4938 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.176154879.97368976/v1 345 views 144 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This review article delves into the significant role of three-dimensional (3D) digital modeling technologies in neurosurgical training, planning, and intraoperative guidance. With the increasing complexity and individuality of neurosurgical procedures, 3D modeling emerges as a transformative tool, providing neurosurgeons with immersive, patient-specific simulations to enhance anatomical understanding and procedural accuracy. The article examines the latest developments in augmented reality (AR) and virtual reality (VR). It discusses their applications in creating interactive surgical environments that bridge the gap between theoretical knowledge and practical skills. It emphasizes the impact of digital 3D models on neuroanatomical education and how they facilitate the visualization of intricate spatial relationships, significantly contributing to surgical precision and patient safety. Furthermore, the review explores the practicality, accessibility, and future prospects of these technologies, highlighting the need for continuous research and interdisciplinary collaboration to overcome current limitations and fully harness their potential for neurosurgical excellence. Introduction The advent of three-dimensional (3D) modeling technologies has marked a paradigm shift in medical education, surgical planning, training, and intraoperative navigation, particularly in the demanding field of neurosurgery[1,2]. Digital or virtual 3D models have significantly improved traditional neuroanatomical education, surgical planning methods, and procedural accuracy, safety, and efficiency[3,4]. Historically, neurosurgical education has relied heavily on two-dimensional (2D) anatomical and radiological images and cadaveric dissection for anatomical understanding. However, the complexity of cerebral structures, intricate neural pathways, and the uniqueness of individual patient anatomy present substantial challenges to novice and even experienced neurosurgeons[5]. The emergence of 3D modeling technologies has addressed these challenges by providing interactive, patient-specific, and anatomically accurate representations of the brain and associated structures[6,7]. Digital 3D models generated from medical images such as computed tomography (CT) and magnetic resonance imaging (MRI) offer an immersive comprehension of normal and pathologic neuroanatomy. They enable the visualization of complex spatial relationships and pathological variations in a virtual environment, facilitating a more profound understanding than traditional imaging alone[8–10]. Recent innovations have expanded the 3D applications into augmented reality (AR) and virtual reality (VR), introducing new dimensions to neurosurgery[11–13]. These technologies create a learning environment where trainees can engage with 3D anatomical structures in real time. Moreover, integrating AR in the operating room is a navigational aid, overlaying critical anatomical information onto the surgeon’s field of view during procedures[14–16]. Printed 3D models extend this advantage into the physical world, allowing tactile interaction and the ability to practice procedural steps on patient-specific anatomical replicas. These models have demonstrated their utility in preoperative planning and training, where surgeons can simulate surgical approaches and refine their techniques accordingly[17–19]. This review collates the current literature to assess the impact of digital 3D models and their applications on neurosurgical education and training, surgical planning, and intraoperative guidance. It also discusses these technologies’ practicality, accessibility, and potential limitations, offering insights into their future trajectory and evolving role in neurosurgical excellence. Generating 3D Digital Anatomic and Surgical Models Generating 3D models for neurosurgical purposes incorporates two primary methodologies: Radiological imaging-based models and photography/surface scanning-based applications[20–22]. Each approach leverages different data sources to create detailed representations of individual anatomy, which are crucial for preoperative planning, surgical training, and intraoperative navigation. Production of 3D Models from Radiological Images The 3D reconstruction process starts with acquiring volumetric cross-sectional (2D) MRI and CT scans in Digital Imaging and Communications in Medicine (DICOM) file format to create detailed anatomical 3D models. With its superior soft tissue contrast, MRI is invaluable for modeling neural, vascular, and other intracranial structures. Studies leveraging high-field clinical MRI systems (i.e. 3T) have showcased the ability of MRI to capture the intricacies of brain anatomy in volumetric series. CT imaging complements this by providing high-resolution data on bone and calcified structures, enabling fine detail in cranial and facial bone reconstructions[23,24]. While widely used DICOM viewers (RadiAnt, Osirix, Horos, etc.) allow for various modes of 3D reconstruction from 2D cross-sectional MRI and CT images, only basic 3D models with limited visualization options can be created. Most importantly, these viewers need more capability of detailed anatomical segmentation. The raw data acquired from these imaging techniques in DICOM format are transformed into segmented 3D models using specialized software tools and pipelines. From freely available 3D Slicer® to highly advanced but costly Mimics Innovation Suite® (Materialise), numerous software options exist to create 3D models from medical images. Mimics is recognized for its robust features, which include importing DICOM data, segmenting based on tissue densities, and merging images from different modalities. Accurate segmentation is crucial for the fidelity of 3D models[25]. Various anatomical and pathological structures can be precisely segmented using the most relevant imaging series. For instance, the T1W or T2W series can be used to segment gray and white matter and ventricles, whereas MR angiography can be used to delineate arteries and MR venography for veins. Structures like vasculature and cranial base can be isolated and rendered using defined Hounsfield unit thresholds and anatomical landmarks obtained on CT angiography. Subsequent alignment, refinement, and detail enhancement are achieved through additional modules, such as Materialise 3-matic, which allow for intricate adjustments and ensure that the final models are precise. Even craniotomy and approach simulations can be achieved using this module, taking these 3D models to new heights for advanced training and practice in neurosurgery. Rigorous validation processes are necessary to ensure the clinical utility of these 3D reconstructions. In addition, technical validation of the models using alignment protocols and deviation analyses can confirm the anatomical accuracy. Such validation is crucial for these models to be relied upon for educational and operative planning purposes[26,27]. Figure 1 presents a comprehensive pipeline for creating 3D anatomical models, showcasing the integration of advanced imaging techniques. This pipeline demonstrates the process of transforming radiological images and photogrammetric data into detailed three-dimensional representations. The data undergoes a series of processing steps, including segmentation, reconstruction, and refinement, to produce accurate and realistic models, beginning with acquiring high-resolution radiological scans and photogrammetric captures. These models serve as essential tools for medical education, surgical planning, and simulation, bridging the gap between theoretical knowledge and practical application in a tangible and interactive format. Figure 2 demonstrates the integrative approach to constructing a full 3D model for neurosurgical planning. It incorporates various medical imaging modalities to render a detailed and accurate representation. The segmentation and synthesis of data from different imaging sources result in a comprehensive model that enhances the visualization of complex anatomical relationships. Photogrammetry-Based 3D Reconstruction in Neurosurgery Photography and photogrammetry techniques are widely used in neuroanatomy. Anaglyphic/stereoscopic photography allows for the visualization of anatomic specimens in 3D. Translating 2D photographs into 3D models harnesses the synergy between photogrammetry and computational advances. This methodology section elaborates on the cutting-edge technologies pivotal to fabricating anatomically accurate models of cadaveric specimens. Before photography, specimens are carefully arranged and sustained in a physiologically mimetic state. Tissues are hydrated periodically, while a black backdrop and strategic lighting minimize extraneous reflections, ensuring high-contrast visual capture. This meticulous setup is integral to producing images that are the foundation for 3D reconstruction [28–31]. A series of images is captured employing a high-resolution camera setup with a macro lens. A macro lens allows visualizing intricate neuroanatomical structures. The sliding plate mechanism on the tripod is pivotal for collecting stereoscopic image pairs and subsequent depth estimation via machine learning algorithms[21,31]. High Dynamic Range (HDR) photography techniques enrich the visual data by amalgamating photos with varying exposures. This trilateral capture system is synthesized to form images rich in detail and balanced in lighting. Photomatix Pro is one of the most used fusing software, while tools such as Adobe Bridge and Photoshop are employed for RAW image processing and tuning[21,32]. There are numerous tools available for photogrammetry, model editing, and visualization. Metashape offers a robust model construction from photographic data. It has been utilized to construct detailed models of the skull base anatomy via endoscopic endonasal approaches, capturing intricate details of this complex area with high fidelity[33]. SketchFab and MedReality platforms enable the viewing and sharing of 3D models, providing easy access to complex anatomical models for educational and planning purposes, with functionalities for manipulating models using different angles and magnifications. MeshLab provides mesh editing, texture mapping, and 3D rendering functionalities essential for finalizing models[34]. Recently, automated tools have come onto the stage through AI-driven 360-degree photogrammetry with the advent of computer vision techniques, artificial intelligence(AI), and high-resolution cameras of smartphones[35,36]. One of the first of its kind, Qlone® exemplifies the merging capabilities necessary for model creation[8]. Blender and Autodesk Meshmixer are noted for their capabilities in further refining and simulating the virtual models, making them functional in AR/VR formats. These applications offer comprehensive suites for 3D modeling, animation, simulation, and rendering, facilitating the creation of interactive and immersive 3D models[37,38]. These tools are critical for ensuring the 3D representations are accurate[8,31]. 3D models are further optimized through detailed annotation and augmented reality enhancement. This enables user engagement across multiple platforms, fostering an educational environment that is interactive and universally accessible[6]. To ascertain the anatomical precision of the 3D models, validation studies compared photogrammetric data to neuronavigation systems and other anatomical benchmarks[21]. Such comparative analyses are essential to confirm the models’ fidelity and testify to the methodology’s reliability[5,21,32,39]. The final step involves transitioning the validated 3D models into AR/VR platforms. Headsets and AR applications facilitate this experience, offering an innovative dimension to neurosurgical education and planning[6,11,13]. Besides AR/VR, smartphones can be used to create 3D models[40,41]. Photogrammetry’s integration with machine learning technologies provides a deep dive into neuroanatomical complexity. This methodology underscores the potential for these models to revolutionize neurosurgical education and preoperative planning. The models act as a conduit for education, allowing trainees to visualize and understand complex spatial relationships in a risk-free environment[6,7,11,12,21]. Visualization Methods Various visualization methods in 3D model reconstruction have significantly improved. Each method leverages unique technologies to create immersive experiences tailored to the needs of neurosurgical practice. Virtual and augmented reality High-resolution screen/computer displays paired with computing systems are fundamental for analyzing and manipulating 3D models. Nevertheless, recent advances in VR/AR technologies allow for a more immersive and interactive visualization experience. AR integrates virtual information with the real-world environment, enhancing the surgeon’s field of vision with 3D anatomical data. As discussed by Spiriev et al., implementations in neurosurgery include preoperative planning, where surgeons can visualize the patient-specific anatomy in situ. AR platforms facilitate the seamless integration of digital models with live surgical views, enabling more accurate and spatially informed navigation during procedures[37,42,43]. VR offers an all-encompassing digital immersion, allowing complete engagement with 3D models within a simulated environment. This technology is critical for neurosurgeons’ training, providing a platform for rehearsing complex surgeries, as indicated by Hanalioglu et al., VR systems supported by depth processing and rendering algorithms simulate realistic surgical environments, enhancing cognitive and motor skills without patient risk[13,21,32,44,45]. AR and VR technologies, which have been utilized in most recent studies, are summarized subsequently. Microsoft HoloLens is a self-contained, holographic computer that enables high-definition holograms to blend with the real world. In neuroanatomy education, HoloLens has been employed to visualize and interact with 3D models of neurosurgical anatomy, offering a hands-free, immersive learning experience[37,46]. Medivis is a FDA approved surgical AR platform coupled with HoloLens. It facilitetes overlay of surgical 3-dimensional volumes, exoscopic and endoscopic outputs in the surgeon’s visual field. The outputs are captured, streamed to the AR computer and then transmitted to the HoloLens for manipulation and interaction for the surgeon. It is a valuable tool to enhance surgical precision, preoperative and intraoperative planning, visualization and ergonomics. It provides interactive view of the surgical field, mitigates intraoperative risks, enhances learning curve of procedures and enhances patient outcomes[47–49]. Unity is a cross-platform game engine for creating games and simulations for computers, consoles, mobile devices, and websites. Unity has been instrumental in developing AR and VR applications for neurosurgical training, facilitating the creation of interactive 3D models that can be manipulated and explored in a virtual environment[33,37]. Other than these, various systems developed by major corporations have been instrumental in advancing VR and AR technologies. These include Oculus Rift (Oculus VR and Facebook), HTC Vive (HTC and Valve Corporation), PlayStation VR (Sony Corporation), and Samsung Gear VR (Samsung Electronics). These devices provide a fully immersive VR experience and have been used to visualize complex neuroanatomical structures and surgical approaches in a controlled, virtual space. These headsets enable users to interact with the models in a way that mimics real-life manipulation and examination, enhancing the understanding of spatial relationships and surgical anatomy[46,50]. 3D printing 3D printing, also known as rapid prototyping, represents a significant technological advancement in anatomical education, surgical training, and neurosurgery, offering highly accurate and tangible reproductions of complex anatomical structures and surgical scenarios[51]. This innovative technology uses computer-aided design (CAD) data to create three-dimensional objects through an additive layering process, utilizing a wide range of materials, including polymers, ceramics, and metals, to ensure biocompatibility and realism in the final products[52,53]. Integrating DICOM data from CT and MRI scans allows for producing patient-specific models, enhancing the educational experience by providing trainees with realistic representations of standard and pathological variations[54,55]. For instance, Encarnacion Ramirez et al. (2023) harnessed the advancements in 3D printing technology to develop a cost-effective, realistic brain model with vasculature designed for neurosurgical procedure visualization and training. This model was meticulously crafted from patient-specific MRI data to replicate the color and consistency of brain tissue, providing an invaluable tool for residents and senior neurosurgeons to refine their endoscopic third ventriculostomy (ETV) skills in a risk-free environment[56]. These 3D printed models not only serve as a valuable tool in surgical planning and simulation, particularly in neurosurgery, where they facilitate the visualization of intricate neuroanatomical details and procedural steps, but also in the creation of custom patient-based implants and prosthetics, demonstrating significant advantages over traditional manufacturing methods[57–59]. Despite its limitations, including the cost of printers and materials, as well as the size constraints of the printed objects, the future of 3D printing in biomedical applications looks promising, with ongoing developments expected to enhance material range, printing speed, and cost-efficiency, thereby broadening its applications and accessibility in the medical field[17,18,60–63]. 3D Digital Models in Neurosurgical Education: Enhancing Anatomical Comprehension and Surgical Simulation Training Photogrammetry in Neuroanatomy Education Neurosurgical training is steeped in the necessity for a deep and precise understanding of intricate cerebral structures, which are often difficult to conceptualize in two dimensions. Incorporating 3D models in neurosurgical education has been transformative, addressing inherent challenges and significantly enhancing the learning experience. Traditional neurosurgical education has primarily relied on 2D imaging and cadaveric dissections, which, while foundational, present limitations in conveying the complex spatial relationships of neuroanatomy. The advent of 3D models has surmounted these limitations, offering an interactive and immersive educational platform. Gurses et al.(2022,2023) demonstrated using 3D models to accurately depict the brain, white matter, cerebellum, and brainstem anatomy, addressing the educational gap left by traditional methods. The studies 3D models allowed for a multi-angled examination, fostering a comprehensive grasp of these structures’ 3D relationships, essential for successful neurosurgical training and approaches [7,11,12]. Rubio et al. (2021) introduce an interactive and comprehensive analysis of the retrosigmoid (RS) approach utilizing volumetric models (VMs) that enable a multi-angled examination and facilitate a visuospatial understanding of critical for successful neurosurgical interventions[64]. Payman and associates (2022) have also contributed significantly by creating VMs that depict the far-lateral approach’s relevant anatomy. These VMs visualize surgical anatomy and windows in 3D and extended reality. These VMs serve as valuable anatomical education and surgical planning resources, accurately depicting critical landmarks in a complex neurosurgical approach[65]. Gonzalez-Romo and colleagues (2023) further advanced by employing cloud-based VR interfaces in a multiuser virtual anatomy laboratory. This approach allowed for the development of photorealistic 3D models that provide immersive and interactive experiences, augmenting the educational process by bridging the gap between theoretical learning and surgical application. These digital specimens are not merely static representations but dynamic entities that can be manipulated and explored in a virtual space, offering an unparalleled depth of interaction[30,66]. Leonel et al. (2020) emphasized the importance of HDR photodocumentation for detailed anatomical study. Integrating such advanced techniques with 3D photo documentation has provided insights into the nuanced layer-by-layer anatomy critical in the preparation and dissection phases of surgical education[67]. Similarly, Jacquesson et al. (2020) have demonstrated how stereoscopic 3D visualization offers a superior pedagogical tool compared to traditional 2D lectures, enhancing students’ comprehension of the brain and skull anatomy by engaging with the intricate 3D architecture of these structures[68]. The efforts of Krogager et al. (2022) in simplifying smartphone-based photogrammetry for 3D anatomy presentation and Spiriev et al. (2022) in creating photorealistic 3D models of the vertebral artery segments highlight the increasing accessibility and applicability of these technologies in both education and surgical simulations [69,70]. Furthermore, Nicolosi and Spena (2020) introduced a novel 3D virtual intraoperative reconstruction method that offers an interactive navigable model, enhancing the educational experience by allowing free exploration of a surgical field and extending photogrammetry applications to intraoperative neurosurgical anatomy[71]. Table 1 collates significant contributions from various authors on the advancements in photogrammetry within neurosurgery. It focuses on integrating photogrammetry with neuroimaging, 3D modeling, AR/VR, and extended reality (XR), highlighting the pivotal role these techniques play in enhancing the educational landscape of neurosurgical training. Each entry illustrates the innovative use of hardware and software to improve understanding of complex neuroanatomical structures and surgical approaches, signifying a transformative period in neurosurgical education. While 3D models, photogrammetry, and immersive technologies have advanced neurosurgical training, challenges remain. High production costs, technical expertise requirements, and variability in model fidelity limit widespread adoption. Standardized integration into curricula is also lacking. Solutions include simplified, low-cost workflows using accessible devices, open-access model repositories, and cloud-based collaborative platforms. Future work should focus on AI-driven reconstruction, incorporation of haptic and mixed reality feedback, and validated frameworks to assess educational impact. Surgical Skills Training via VR/AR/MR/XR Simulators 3D realistic virtual models of neuroanatomy provide not only valuable resources for immersive neuroanatomy teaching but also interactive tools to simulate surgical approaches and exposures as well as practice basic surgical skills. The Neurosurgical Atlas, launched in 2016, has emerged as a groundbreaking educational platform in neurosurgery, offering access to a wealth of multimedia content focused on microneurosurgery. Its core feature, ultrarealistic 3D virtual models, significantly enhances the learning and teaching of complex cranial and cerebrovascular anatomy. This digital atlas caters primarily to medical students, residents, and early-career neurosurgeons, facilitating a deeper understanding of neuroanatomical structures and surgical planning through interactive engagement. By bridging the gap between traditional learning materials and advanced surgical preparation, the Neurosurgical Atlas® exemplifies the transformative potential of digital innovations in neurosurgical education. The integration of XR in neurosurgical education, as discussed by Iop et al. (2022), is a testament to the rapid evolution within the field, leveraging immersive 3D simulations to deepen procedural understanding[5]. This interdisciplinary approach employs sophisticated software and methodologies, such as those detailed by Alaraj et al. (2015), who emphasize the utility of real-time haptic feedback in VR simulations for cerebral aneurysm clipping[72]. Similarly, Delorme et al. (2012) underscore the value of VR-based systems like NeuroTouch®, enhancing residents’ cognitive and psychomotor skills[73]. The synergy of these technologies cultivates a robust framework for training, preparing residents not just in theoretical knowledge but with hands-on, virtually augmented experience that parallels real-world scenarios. Truckenmueller et al. (2024) showcased the efficacy of augmented 360° VR videos in familiarizing medical students with complex surgical procedures, offering them a virtual hands-on experience that deepens learning[74]. Roh et al. (2021) advanced this integration further by creating photorealistic 3D models from cadaver dissections for VR platforms. This method gives residents a tangible feel for anatomical structures and surgical navigation, bridging the gap between theory and practical application[75]. The NeuroTouch® platform, a sophisticated VR simulator, has emerged as a critical tool for assessing and enhancing neurosurgical competencies. In a study by Alotaibi et al. (2015), the NeuroTouch system was employed to evaluate bimanual psychomotor skills during simulated brain tumor resections. They expanded the assessment capabilities by developing the NAJD metrics, a set of new parameters including judgment and skill extracted from NeuroTouch’s data files using standard software like Excel. This innovation allows for a more nuanced analysis of surgical techniques and decision-making processes. The platform’s metrics offered an in-depth performance analysis, including blood loss, tumor resection percentage, and the economy of instrument movements, providing valuable feedback for trainee development[76]. Gélinas-Phaneuf et al. (2013) validated the NeuroTouch simulator, demonstrating its efficacy in differentiating skill levels among medical students and residents based on metrics such as tissue removed and aspirator efficiency. This highlights the simulator’s potential in customizing training programs to match individual learning curves[77]. Bugdadi et al. (2017) integrated the Fitts and Posner model to test the automaticity of neurosurgical procedures within the NeuroVR® platform. Findings suggested that experienced neurosurgeons exhibit a higher consistency in force application, indicative of a more automatic and skilled performance than residents[78]. Joseph et al. (2023) present a study utilizing the SurgTrain® simulator for neurosurgical aneurysm clipping training. The system uses 3D-printed patient-specific models from radiological data, facilitating the rehearsal of multiple clipping strategies through a mixed-reality environment. It features a cardiophysiological pump that simulates pulsatile blood flow and allows intraoperative ICG-FA to be applied. This approach enables neurosurgeons to practice complex procedures, offering a high-fidelity platform to anticipate surgical outcomes, albeit with noted ICG-FA sensitivity limitations[19,79]. The cumulative research utilizing VR simulations reflects a significant shift toward objective, data-driven assessments in neurosurgical education. These studies underscore the potential of VR technology to revolutionize surgical training, offering a controlled, risk-free environment where surgeons can hone their skills, refine techniques, and improve patient outcomes. By incorporating VR tools into neurosurgical curricula, educators can provide targeted training that adapts to the field’s evolving demands and the individual learning needs of residents[80–82]. Complementing these approaches, Hanalioglu et al. (2022) combined neuroimaging and photogrammetry to produce immersive simulations that facilitate the exploration of intricate neuroanatomy and the practice of surgical techniques. Their work exemplifies the potential of 3D models to improve spatial understanding and enhance the overall quality of neurosurgical training[21]. Table 2 summarizes the key findings from various articles that review and assess the use of 3D modeling techniques and VR simulations in neurosurgical education. It highlights various hardware and software tools used to facilitate the learning and training of neurosurgical procedures, offering insights into the effectiveness of these technologies and critical findings of the articles in enhancing the acquisition of neurosurgical skills, knowledge, and procedural understanding. In conclusion, these studies illuminate the collection of 3D models and AR/VR simulations, reinforcing these technologies’ transformative impact on neurosurgical education and surgical simulations. They highlight the necessity of a hybrid anatomical and neurosurgical curriculum that incorporates these advances, thereby ensuring a higher standard of training for neurosurgeons. While immersive simulators have transformed neurosurgical skills training, challenges remain, including high implementation costs, limited accessibility, and inconsistent integration into curricula. Solutions lie in developing low-cost, validated platforms with standardized assessment metrics and leveraging AI, haptic feedback, and cloud-based collaboration to enhance realism. Future efforts should focus on large-scale validation and equitable global access to ensure these technologies advance surgical proficiency across diverse training environments. Integration of Patient-Specific 3D Digital Models to the Surgical Workflow AR/VR technologies have shown significant potential in neurosurgery operations. AR/VR has been particularly beneficial in enhancing preoperative planning and efficiency in the operating room, with applications in spinal, cranial, neurovascular, and peripheral nerve surgery. By converting high-resolution MRI and CT images into interactive 3D digital models, surgeons can delve into the patient’s unique anatomy with an unparalleled depth of detail, facilitating meticulous surgical approaches. Similarly, AR has improved preoperative planning and intraoperative navigation. Despite these advancements, cost, legal, and ethical challenges could enhance the widespread adoption of AR/VR in neurosurgery.Further research is needed to compare the outcomes of standard and AR/VR-supplemented procedures and address the barriers to the clinical use of these technologies[83,84]. Integrating AR/VR into spinal surgery offers significant potential for enhancing surgical precision, patient outcomes, and the education of trainees. Most recent studies underscore the contributory role of AR/VR in improving spinal surgical efficacy and pedicle screw placement accuracy and yielding favorable clinical [85–88]. Moreover, AR/VR facilitates the adoption of minimally invasive spinal surgery (MISS) approaches, reducing operative durations and enhancing patient recovery trajectories. In a pioneering studies, the authors demonstrate the feasibility, safety, and high accuracy rate of screw placement facilitated by AR, emphasizing its significant potential to refine surgical precision and outcomes. It is an instrumental tool for educating and training medical students and residents, thus fostering a more profound comprehension and proficiency in complex MISS procedures. This review illuminates the pivotal role of AR in revolutionizing surgical training and operative outcomes, showcasing the technological advancements and educational potential of AR systems like XVision, HoloLens, and ImmersiveTouch in pedicle screw placement models [89–91]. Cohort studies underscore the safety, efficacy, and high accuracy rate of AR-guided screw placements, which contribute to the integration of AR technology in spine surgery, paving the way for enhancing surgical precision and patient care[85,87,90–93]. These studies collectively underscore the transformative potential of AR and VR technologies in spine surgery, highlighting their significant contributions to surgical precision, patient outcomes, and the pedagogical landscape of surgical education. The application of AR neuronavigation in spinal tumor surgery showcases the precision and safety of ARNV in minimizing incision length and enhancing the visualization of adjacent critical anatomy during en-bloc tumor resections. This is a significant advancement, demonstrating AR’s expanding utility beyond cranial neurosurgery to spinal column lesions, offering new insights into surgical navigation and planning[94–96]. The advent of AR/VR technologies in neurosurgery, particularly in managing intracranial pathologies, heralds a transformative era in surgical precision, planning, and education. These cutting-edge technologies facilitate an enhanced surgical field visualization, offering surgeons a more intuitive understanding of complex anatomical relationships and the spatial orientation of critical brain structures. Walter C. Jean, MD, and his colleagues leverage the Surgical Theater® platform. They utilize patient-specific VR models for surgical planning, rehearsal, and AR overlays during surgery, facilitated by navigation-tracked microscopes like the StealthStation S8® and Leica M530®[97–100]. The integration of AR in anterior petrosectomy, as demonstrated by Jean et al., showcases how AR facilitates the visualization of critical neurovascular structures, such as the cochlea and carotid artery, to avoid iatrogenic injuries during intricate skull base surgeries[97]. This application mitigates traditional risks, like seizures and temporal lobe hematomas, and significantly improves the surgeon’s spatial awareness, enhancing the procedure’s safety and efficacy. Building upon this technological prowess, their work extends to AR and VR in the paramedian supracerebellar infratentorial approach for accessing pineal region tumors and the mini-pterional craniotomy for clinoid meningiomas[98,101,102]. The team achieved optimized surgical exposure and trajectory planning through surgical VR rehearsal and patient-specific AR templates. This meticulous preoperative strategy, facilitated by AR, ensures maximal preservation of critical anatomical features while affording precise and tailored surgical interventions for each patient. These advancements underscore a significant shift towards minimally invasive and surgeon-centered neurosurgical practices. Another example of this innovative approach is the expanded endoscopic endonasal trans tuberculum surgery for tuberculum sellae meningiomas, where the preoperative planning and surgical rehearsal in VR were instrumental. The Surgical Theater SRP7.4.0 software rendered a detailed 3D visualization of the patient’s anatomy, allowing the surgical team to meticulously plan the approach to avoid critical structures and ensure optimal tumor resection[103]. Other studies by the team showcased transorbital approaches for intradural tumors and aneurysms with high efficacy and accuracy and mitigating the adverse complications[99,100]. Van Gestel et al. present an AR-based workflow for intracranial tumor resection planning using the Microsoft HoloLens II. This workflow significantly improves surgical planning efficiency and accuracy by displaying critical structures directly on the patient. This AR application in surgery delineation reduced planning time by 39%, with accuracy independent of user experience. This demonstrates AR’s potential to streamline preoperative preparations and enhance intraoperative navigation[104]. Figure 3 synthesizes complex neuroimaging into a cohesive 3D model, highlighting a temporoinsular tumor’s interaction with surrounding neural pathways and structures. This visual amalgamation provides a comprehensive and precise view essential for surgical planning and precise surgical execution. Recent studies employ AR for cortical and subcortical motor mapping during awake craniotomy, integrating image guidance to optimize tumor resection while preserving essential motor functions[105,106]. Mofatteh et al. systematically reviews the application of AR/VR in awake craniotomies, highlighting the technologies’ contributions to safer and more effective resections of lesions in eloquent brain areas[107]. Despite current technological limitations, AR Head-Mounted Displays (HMDs) are promising tools for augmenting the surgeon’s capabilities, particularly in tasks requiring high manual precision. However, it highlights the necessity for future devices to overcome perceptual conflicts and calibration issues to achieve robust virtual-to-real alignment[108,109]. In glioma surgery, innovative techniques combine AR with or without diffusion tensor imaging-based fiber tractography (AR-iFT) to guide the resection of motor area tumors. This technique demonstrates AR’s potential in maximizing tumor resection and underscores its value in improving postoperative motor outcomes and progression-free survival, confirming AR’s significant impact on neuro-oncological surgery[110–112]. Neurovascular surgery has witnessed transformative advances with the adoption of 3D technologies and VR, significantly enhancing the precision and outcomes of complex surgical procedures[113]. AR/VR has been used during extracranial-to-intracranial bypass surgeries, arteriovenous malformations (AVMs), and aneurysm clippings. These innovative approaches enable the overlay of virtual images into the surgical field. AR has facilitated the precise localization of donor and recipient vessels in neurovascular procedures, tailoring craniotomies to individual patient anatomy and optimizing the surgical workflow[114–116]. Figure 4 encapsulates the multifaceted imaging of a left middle cerebral artery(MCA) aneurysm, merging diverse modalities into a singular 3D representation crucial for surgical precision. Each step enriches the final model from MRI to angiographic sequences, culminating in a real-time surgical comparison that underscores the model’s accuracy and utility. Similarly, VR and 3D printing technologies have been employed to create patient-specific preoperative planning and rehearsal models, which have profoundly impacted procedural efficiency, particularly in clipping cerebral aneurysms[117–119]. These patient-specific models allow surgeons to anticipate potential challenges and meticulously plan the surgical approach, reducing procedure times and improving safety and efficacy[120,121]. Furthermore, integrating haptic feedback in VR simulators has revolutionized neurosurgical education. This approach enables trainees to gain hands-on experience with the tactile sensations of surgery before stepping into the operating room[122]. This approach improves anatomical understanding and refines the surgical skills necessary for successful interventions[123]. Table 3 comprehensively overviews the interdisciplinary efforts to harness AR/VR, MR, and XR within neurosurgical planning and intraoperative guidance. It underscores how these advanced technologies have been adopted across a spectrum of neurosurgical procedures, contributing to precision, safety, and educational depth in the operating room. The table summarizes key findings from recent studies demonstrating improved surgical outcomes and the potential for these technologies to refine the surgeon’s approach, enhance patient-specific treatment strategies, and contribute to the evolving landscape of precise operation execution. Integrating patient-specific 3D digital models into the surgical workflow has enhanced preoperative planning, intraoperative navigation, and surgical precision across neurosurgical subspecialties. However, adoption remains limited by high production costs, reliance on advanced imaging and processing infrastructure, and technical issues such as overlay calibration errors. Solutions include AI-assisted automated model generation, streamlined workflows compatible with standard hospital systems, and cloud-based platforms for collaborative planning. Future efforts should emphasize multicenter validation of clinical benefits, integration with haptic and augmented feedback systems, and development of cost-effective approaches to ensure equitable access in diverse healthcare settings. Ultimately, the seamless incorporation of these models into routine surgical practice holds the potential to redefine precision surgery, shorten learning curves, and significantly improve patient outcomes. Limitations and Future Directions While incorporating 3D modeling and AR/VR technologies in neurosurgery marks a significant advance, several limitations and directions for future development must be considered. The high cost of AR/VR equipment and 3D modeling software can hinder widespread adoption. These expenses extend to the maintenance and updates of hardware and software. Ensuring cost-effectiveness and accessibility for a broader range of medical institutions remains a challenge that must be addressed through economic strategies and possibly industry partnerships. A learning curve is associated with these technologies, requiring surgeons and support staff training. Additionally, integrating AR/VR into existing surgical workflows can be complex, necessitating technical support and user adaptability. It should be kept in mind that the installation of 3D modeling and AR/VR equipment will take extra time and will prolong the preoperative and intraoperative period. Ensuring the accuracy and quality of 3D models is crucial for their effective use in surgical planning and education. Standardized protocols for creating and validating models are needed to guarantee their reliability and safety. Ongoing advancements in 3D printing materials and resolution, VR haptic feedback, and AR visualization tools are expected to enhance the utility and realism of these models. Developing portable and user-friendly systems can also broaden their application in diverse clinical settings. AI and machine learning algorithms promise to automate and improve the precision of 3D model construction. These technologies could reduce manual segmentation time, leading to real-time model generation and adjustments during surgeries. The future direction in 3D modeling and AR/VR in neurosurgery lies in the convergence of these technologies with machine learning, increased computational power, and the Internet of Things (IoT), which can deliver more refined, personalized, and interactive models. Collaboration across disciplines, combining the expertise of engineers, computer scientists, and clinicians, will be paramount to overcoming current limitations and fully realizing the potential of these technologies in clinical practice. Discussion 3D digital modeling, AR, and VR are steadily reshaping the landscape of neurosurgical training, preoperative planning, and intraoperative navigation. Yet, despite significant progress, their translation into routine practice has been slower than anticipated, revealing persistent gaps between technological potential and clinical adoption. The most fundamental challenge lies in the preparation and integration of patient-specific models. High-fidelity reconstructions often require extensive manual or semi-automated segmentation, multi-modal data registration, and hardware-dependent rendering, all of which can disrupt already complex surgical workflows. Automated segmentation powered by deep learning and real-time Graphics Processing Units (GPU)-accelerated pipelines holds promise, but robust, reproducible, and clinically validated solutions remain scarce. Equally pressing are economic and accessibility barriers. Current AR/VR systems and advanced navigation platforms demand substantial investment in hardware, software, and technical support, which restricts their adoption to well-funded academic centers. Without cost-effectiveness analyses, standardized reimbursement models, or modular integration with existing surgical infrastructure, widespread clinical use will remain elusive. In parallel, ergonomic and sterility considerations limit intraoperative feasibility; headset-based or secondary-screen visualizations can be cumbersome, whereas embedding AR directly into microscopes or neuronavigation displays represents a more practical pathway toward seamless integration. Another critical limitation in the literature is the lack of rigorous validation and standardization. Most studies report improvements in anatomical understanding, confidence, or efficiency but seldom provide quantitative metrics such as segmentation accuracy [e.g., Dice coefficient, Intersection over Union (IoU)], surgical performance indicators (e.g., task time, error rates), or learning curve analyses. Furthermore, evaluation protocols are heterogeneous, with little consensus on how to measure efficacy across training, surgical planning, and intraoperative guidance. Establishing multicenter, standardized validation frameworks will be essential for regulatory approval, evidence-based adoption, and meaningful comparison between technologies. Moving forward, a paradigm shift is required to bridge innovation and clinical utility. Automated, AI-driven model generation must be coupled with real-time updates from intraoperative imaging to create dynamic, patient-specific AR guidance. Integration of radiological, functional, and molecular data into unified 3D models will enable precision approaches to tumor resection and functional preservation. Cloud-based platforms and multi-user VR environments could democratize access, allowing surgeons to rehearse cases, share patient-specific models, and conduct collaborative training across geographic boundaries. Finally, the field must embrace structured cost-benefit studies, regulatory pathways, and user-centered design to transition from experimental demonstration to indispensable clinical tool. In essence, while 3D digital modeling and immersive technologies have already demonstrated transformative potential in neurosurgery, their future impact will be determined by our ability to streamline workflows, validate outcomes, lower barriers to adoption, and integrate multimodal data into actionable clinical solutions. Only through such a deliberate, multidisciplinary effort can these innovations fulfill their promise to fundamentally reshape the practice in neurosurgery. Conclusion In conclusion, integrating 3D digital models, AR, and VR applications into neurosurgery represents a remarkable field advancement. These tools have revolutionized neurosurgical education, providing immersive and highly detailed anatomical understanding and significantly enhanced surgical planning and intraoperative navigation. 3D digital models offer unparalleled preoperative planning capabilities, allowing surgeons to approach each case with a bespoke strategy that accounts for the patient’s unique anatomy. During surgery, it provides real-time, overlayed guidance that enhances the surgeon’s perception, allowing for more precise and less invasive procedures. VR has opened doors to rehearse complex operations in a controlled environment, enabling surgeons to refine their skills and anticipate challenges before entering the operating theater. As these technologies advance, their integration into routine clinical practice will likely become standard. This will improve outcomes by reducing surgical risks and enhancing the precision of neurosurgical interventions. Despite the challenges, such as high costs and the need for specialized training, the trajectory of 3D modeling and AR/VR technologies in neurosurgery is clear. They are set to become integral components of surgical planning and execution. The future holds the promise of even more integrated systems where AI and machine learning will provide real-time insights during surgeries, further enhancing the accuracy and safety of neurosurgical procedures. As we stand on the cusp of a new era in neurosurgery, it is essential to continue research and development in this field to fully realize the potential of these innovative tools in improving patient care. The commitment to this endeavor will ensure that neurosurgery remains at the forefront of medical technology, continuing to improve patient outcomes through precision, innovation, and advanced training methodologies. Author Contributions: Conception or design of the work: Efecan Cekic, Ilkan Tatar, Sahin Hanalioglu; Data collection: Efecan Cekic, Gulsah Cetin, Ayse Gul Ozer, Baylar Baylarov, Ilkan Tatar, Sahin Hanalioglu; Data analysis and interpretation: Efecan Cekic, Ilkan Tatar, Sahin Hanalioglu; Manuscript Composition: Efecan Cekic, Gulsah Cetin, Ayse Gul Ozer, Baylar Baylarov, Ilkan Tatar, Sahin Hanalioglu; Critical revision of the article: Efecan Cekic, Gulsah Cetin, Sahin Hanalioglu; Study supervision: Sahin Hanalioglu. Funding: This research received no external funding Institutional Review Board Statement: Institutional Review Board Statement: Not applicable. This article does not contain any studies with human participants or animals performed by any of the authors. Informed Consent Statement: Not applicable. This review article does not involve any new studies of human or animal subjects conducted by any of the authors. Data Availability Statement: The data supporting the findings of this study, including all images and datasets, are available from the corresponding author, Sahin Hanalioglu, M.D., Ph.D., upon reasonable request. No additional external data repositories were used, and the data are not publicly archived due to the nature of this study. All relevant data are contained within the article. Acknowledgments: The authors thank to Osman Tunc for his technical assistance, and BTech Innovation for their generous support in 3D modeling and printing Conflicts of Interest: The authors declare no conflict of interest. Abbreviations The following abbreviations are used in this manuscript: AR Augmented Reality VR Virtual Reality CT Computed Tomography MRI Magnetic Resonance Imaging DICOM Digital Imaging and Communications in Medicine AI Artificial Intelligence CAD Computer Aided Design ETV Endoscopic Third Ventriculostomy RS Retrosigmoid VM Volumetric Models XR Extended Reality HMD Head Mounted Displays AVM Arteriovenous Malformation References [1] Randazzo M, Pisapia J, Singh N, Thawani J. 3D printing in neurosurgery: A systematic review. Surg Neurol Int 2016;7:801. doi: 10.4103/2152-7806.194059. [2] Hanalioglu S, Romo NG, Mignucci-Jiménez G, Tunc O, Gurses ME, Abramov I, et al. Development and Validation of a Novel Methodological Pipeline to Integrate Neuroimaging and Photogrammetry for Immersive 3D Cadaveric Neurosurgical Simulation. Front Surg 2022;9. doi: 10.3389/fsurg.2022.878378. [3] Baskaran V, Štrkalj G, Štrkalj M, Di Ieva A. 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[123] Gmeiner M, Dirnberger J, Fenz W, Gollwitzer M, Wurm G, Trenkler J, et al. Virtual Cerebral Aneurysm Clipping with Real-Time Haptic Force Feedback in Neurosurgical Education. World Neurosurg 2018;112:e313–23. doi: 10.1016/j.wneu.2018.01.042. [124] Caglar YS, Zaimoglu M, Ozgural O, Erdin E, Alpergin BC, Mete EB, Dogan I. Mixed Reality Assisted Navigation Guided Microsurgical Removal of Cranial Lesions. Turk Neurosurg. 2024;34(5):926-938. Doi: 10.5137/1019-5149.JTN.44974-23.2. Tables Table 1: Advancements in Photogrammetry for Neurosurgical Education: A Review of Technique Integration and Applications Sahin Hanalioglu et al. (2022) Proof-of-Concept Study Neuroimaging & Photogrammetry integration MRI, CT, cameras, neuronavigation Mimics, Intel ISL MiDaS, Open3D, MeshLab, Sketchfab Pterional craniotomy 4 cadaver heads used. Neuroimaging and photogrammetry models were merged, 63% of surface maps were perfectly matched. Enhanced neurosurgical simulation and education. Muhammet Enes Gurses et al.(2024) Perspective Analysis Interactive microsurgical anatomy education using 3D models and AR cube AR foam cube with QR codes Advanced photogrammetry Neurosurgical anatomy Seven photogrammetry 3D models were created and imported to the AR cube. 35 neurosurgery trainees from international programes tested the cube and agreed that AR cube enhances neurosurgical anatomy education by combining tactile and visual experiences with realistic 3D models. Muhammet Enes Gurses et al.(2023) Detailed Study 3D Modeling and Extended Reality Simulations of Cross-Sectional Anatomy Photogrammetry 360° photogrammetry Cerebrum, cerebellum, and brainstem cross-sections 3 cadaveric specimens disected and 11 axial, 9 sagittal, 7 coronal 3 D models were created. This study is the first to combine photogrammetry, AR, and VR for detailed 3D visualization of the brain’s cross-sectional anatomy. Muhammet Enes Gurses et al.(2021) Technical Note Photogrammetry-Based 3D Modeling of Cadaveric Specimens Standard mobile devices (smartphone and tablet) Qlone® (EyeCue Vision Technologies) Cadaveric specimens A simple, accessible method for creating 3D cadaveric models enhancing neuroanatomy training worldwide. Muhammet Enes Gurses et al.(2022) Detailed Study 3D Modeling and AR/VR Simulations of the White Matter Anatomy of the Cerebrum Photogrammetry Klingler method, photogrammetry White matter anatomy 20 cadeveric brain specimens were disected from lateral to medial and medial to lateral for 3D modelling, AR and VR. This is the first study integrates various technologies for 3D visualization of dissected white matter fibers of the human cerebrum. Muhammet Enes Gurses et al.(2022) Detailed Study 3D Modeling and AR/VR Simulation of Fiber Dissection of the Cerebellum and Brainstem Photogrammetry Klingler’s method, Qlone (EyeCue Vision Technologies, Ltd.) Cerebellum and brainstem Ten cadaveric cerebellum and brainstem specimens were dissected under the operating microscope, and 2-dimensional and 3D images were captured at every stage. With a photogrammetry tool, AR and VR simulations and 3D models were created by combining several 2-dimensional pictures This is the first creation of high-resolution, accessible 3D models and AR/VR cerebellum and brainstem dissection simulations. Nicolas I Gonzalez-Romo et al.(2023) Experimental Study Virtual Neurosurgery Anatomy Lab in the Metaverse Cloud-based VR interface Multiple photogrammetry softwares Microsurgery Anatomy 5 multinational neurosurgery visiting scholars and 20 neurosurgery residents tested and assessed the same models and virtual space. 92% of the participants strongly agreed that this system should be part of neurosurgery residency training and that virtual cadaver courses through this platform could be effective for education. Cloud-based VR enables interactive and remote neurosurgery education, strongly supported by neurosurgery residents. Toma Spiriev et al.(2022) Anatomical Study Three-Dimensional Immersive Photorealistic Layered Dissection N/A Blender, Sketchfab Back muscle anatomy One cadaver disected and every step of disection was 3D scanned by photogrametry. 3D models offer immersive, photorealistic visualization of back muscle anatomy, accessible via web, AR, and VR, enhancing educational possibilities. Toma Spiriev et al.(2023) Original Article Photorealistic 3D Scanning Operating microscope, mobile phone for photogrammetry Dedicated mobile app, open-source 3D modeling software Far lateral and anterolateral approaches to the vertebral artery (VA) 2 cadaver head were used. Anatomic layered dissections were performed on the first specimen. On the second specimen, the two classical approaches to the VA (far lateral and anterolateral) were realized. Every step of dissection was scanned using photogrammetry technology. 3D models of VA segments enhance anatomical understanding, aiding in education and preoperative planning. Tae Hoon Roh et al.(2021) Original Article Photographic 3D Models Integrated into Virtual Reality Head-mounted display and controllers Free VR application Skull base approaches One cadaver was dissected layer by layer, and each layer was 3D scanned by a photogrammetric method. The objects were imported to a free VR application and layered. After performing hands-on virtual surgery with photographic 3D models, a feedback survey was collected from 31 participants. Respondents rated a higher score for photographic 3D models than for conventional 3D models (4.3 ± 0.8 vs 3.2 ± 1.1, respectively; p = 0.001). Photographic 3D models in VR enhance educational impact, enabling more realistic surgical simulation and improving learning of surgical approaches and skills. Ioannis Kournoutas et al.(2019) Technical Note 3D Scanning Via Photogrammetry Endoscope with a 30° lens Photogrammetry software Endoscopic endonasal approaches Ten human cadaveric heads were dissected through the nasal corridor to expose anterior, middle, and posterior cranial fossi structures and the pterygopalatine and infratemporal fossi. An average of 174 photographs were used to construct each model. Endoscopic volumetric models represent a new way to depict the anatomy of the skull base, enhanced visualization of skull-base anatomy for educational and surgical planning purposes. André de Sá Braga de Oliveira et al.(2023) Technical Note 3D Models Using Photogrammetry Three cameras arranged vertically MeshLab, MedReality, SketchFab Neuroanatomy Seven specimens with different sizes,cadaveric tissues, and textures were used to demonstrate the step-by-step instruc-tions for specimen preparation, photogrammetry setup, post-processing, and displayof the 3D model. The photogrammetry scanning consists of three cameras arrangedvertically facing the specimen to be scanned in order to guidelines for creating high-quality 3D neuroanatomy models to enhance education, accessible on multiple platforms. Omar C. Quispe-Enriquez et al.(2023) Research Article Smartphone-Based Photogrammetry Samsung Galaxy S22 Agisoft Metashape, PhotoMeDAS Craniofacial Morphometry 3D craniofasial morphometric data can be obtained by photogrammetry, videogrammmetry and PhotoMeDAS. A comparison of the obtained 3D meshes was conducted, yielding the following results: 0.22 ± 1.29 mm for photogrammetry with camera photos, 0.47 ± 1.43 mm for videogrammetry with video frames, and 0.39 ± 1.02 mm for PhotoMeDAS. Similarly, anatomical points were measured and linear measurements extracted, yielding the following results: 0.75 mm for photogrammetry, 1 mm for videogrammetry, and 1.25 mm for PhotoMeDAS. Showcases smartphone photogrammetry’s potential for accurate 3D craniofacial models, benefiting neurosurgery and maxillofacial surgery. Omar C. Quispe-Enriquez et al.(2023) Research Article Smartphone-Based Photogrammetry for Head Measurements Samsung Galaxy S22, S22+, S22 Ultra PhotoMeDAS Cranial Deformation Assessment Twelve measurements are taken with each mobile device. With a homogeneous scale factor for all the smartphones, the results showed that the average accuracy for the S22 smartphone is −1.15 ± 0.53 mm, for the S22+, 0.95 ± 0.40 mm, and for the S22 Ultra, −1.8 ± 0.45 mm. It validates the accuracy of smartphone photogrammetry for cranial measurements, emphasizing the importance of applying a device-specific scale factor to ensure measurement reliability. Roberto Rodriguez Rubio et al.(2019) Technical Note 3D Scanning Techniques (Photogrammetry and Structured Light Scanning) Various 3D scanners Multiple photogrammetry and 3D modeling software Neuroanatomical Dissections SLS and PGM were both applied to 3 dissected hemispheres to demonstrate the quality of the VMs and their applications.They produce detailed models for neuroeducation and planning, showing wide application potential in medical education and surgery. Roberto Rodriguez Rubio et al.(2021) Technical Report 3D volumetric model creation 3D scanning technology (photogrammetry and structured light scanning) Biomedical image processing software, VR platforms Surgical Anatomy of the Retrosigmoid Approach Five embalmed heads and one dry skull were used to generate stereoscopic images and volumetric models using 3D scanning technology to illustrate and simulate the RS approach. This is the first comprehensive 3D analysis of the retrosigmoid technique, offering a detailed, immersive understanding of posterolateral neuroanatomical landmarks and structures for surgical planning and education. Andre Payman et al.(2022) Technical Report 3D volumetric model creation 3D scanning technology (photogrammetry and structured light scanning) Biomedical image processing software, VR platforms Surgical Anatomy of the Far-Lateral Approach Five embalmed heads and two dry skulls were used to record and simulate the FL approach. Relevant steps and anatomy of the FL approach were recorded using 3D scanning technology to construct high-resolution volumetric models. It provides comprehensive 3D visualization of the far-lateral approach’s anatomy and technique, enhancing surgical planning and education through high-resolution volumetric models and stereoscopic media. Luciano César PC Leonel et al.(2021) Technical Report Specimen Preparation, Dissection, 3D-Photodocumentation HDR, 3D photodocumentation Photomatix Pro 6.1.1, Adobe Bridge, Adobe Photoshop Neuroanatomy Two formaldehyde-fixed cadaveric heads were injected with colored latex to demonstrate step-by-step specimen preparation for microscopic or endoscopic dissection. One formaldehyde-fixed brain was utilized to demonstrate optimal three-dimensional (3D) photodocumentation techniques. It provides a comprehensive update on neuroanatomic study techniques, emphasizing specimen preparation, dissection, and 3D photodocumentation; included insights from Rhoton’s fellowship and advancements in endoscopic dissection and HDR imaging. Markus E Krogager et al.(2023) Technical Note Intraoperative Videogrammetry and Photogrammetry Operating microscope N/A Various cranial microsurgeries One latex-injected cadaver head was dissected to depict the facial nerve from the meatal to the extracranial portion. Four 3D models were generated with the help of smart phone and cloud-based photogrammetry application. Two models showed the extracranial portions of the facial nerve before and after removal of the parotid gland; 1 model showed the facial nerve in the fallopian canal after mastoidectomy, and 1 model showed the intratemporal segments. It shows photorealistic 3D models enhance understanding of operative corridors and intraoperative orientation for educational purposes. Federico Nicolosi et al.(2020) Research Article 3D Photogrammetry Mobile devices with gyroscopic technology 3D virtual intraoperative reconstruction (VIR) application Neuroanatomy 3D VIR allows interactive exploration of the surgical field, enhancing the teaching and learning process in neurosurgical anatomy. Trandzhiev M et al.(2023) Literature Review Photogrammetry DSLR Camera, Endoscope, Smartphone Camera Agisoft Metashape, Autodesk ReCap Photo, Qlone, MeshLab, Blender Neuroanatomy, Surgical Anatomy, Scoliosis, Craniosynostosis 86 articles were included in the review from 315 papers identified. Photogrammetry is used in neurosurgery for creating 3D models, diagnosing and evaluating deformities, and facilitating education. Advances in technology have made it more accessible and efficient. Table 2: 3D Modeling Techniques and Simulations in Neurosurgical Training: Current Applications Alessandro Iop et al. (2022) Systematic Review Extended Reality in Neurosurgical Education Various (including HMDs like Oculus Quest 2, HTC VIVE Pro) NeuroVR, ImmersiveTouch, other VR and AR platforms Cranial neurosurgery Five databases were investigated, leading to the inclusion of 31 studies after a thorough reviewing process.XR enhances neurosurgical education by improving skill acquisition and procedural knowledge. Joseph et al. (2023) Original Article Mixed-Reality Patient-Specific Simulator for Aneurysm Clipping Training SurgTrain Simulator by SurgeonsLab® SurgView TM (SurgeonsLab AG) Aneurysm Clipping 2 patient-specific left-side unruptured middle cerebral artery-bifurcation IA models were simulated by two board-certified neurosurgeons. The mixed-reality simulator allows testing of multiple aneurysm clipping strategies in a realistic setting, showing potential for enhancing preoperative planning and training experiences. Samuel B Tomlinson et al. (2019) Original Article 3D Digital Modeling and Virtual Reality High-Performance Computing Systems Virtual Reality Headsets Graphic Tablets and Styluses Amira (Thermo Fisher Scientific) Maya (Autodesk) Graphic Design Software Cranial anatomy and operative techniques 3D and VR tools modernize neurosurgical anatomy learning outside the operating room. Peter J. Morone et al. (2019) Original Article Virtual, 3-Dimensional Temporal Bone Model High-Performance Computing Systems 3D Scanners Virtual Reality Headsets Amira Maya Zbrush Sketchfab Temporal bone anatomy The 3D temporal bone model was created with assistance of computer graphic designers and published online. Its educational value as a teaching was tool was assessed by querying 73 neurosurgery residents at 4 institutions and was compared with that of a standard, 2D temporal bone resource. 3D model preferred over 2D for learning complex anatomy and potentially improving operative efficiency and safety. Serdar Onur Aydin et al. (2023) Original Article 3D Modeling and AR/VR Applications High-Performance Computing Systems 3D editing programs Microsurgical Training Three brains were used for white matter dissections and exported to the 3D models. This study demonstrates the use of 3D modeling and AR/VR in neuroanatomy training for enhanced spatial recognition. Nergiz Ercil Cagiltay et al.(2019) Original Article Endoscopic Surgery Skills in Educational Computer-Based Simulation Computer-based endo neurosurgery simulation module Haptic Devices High-Performance Computers 3D Display Technology Custom-developed Simulation Software Haptic Feedback Software Endoscopic neurosurgery training An educational computer-based simulation environment was used by 31 novice and intermediate-level residents from ENT (ear, nose, and throat) and neurosurgery departments. The results suggest that a 2-hour training during a 2-month period through computer-based simulation environment improves the surgical skills of the residents in both-hand tasks. Computer-based simulation environments improve surgical skills, with scenarios needing to adapt to individual skill levels. Peter Truckenmueller et al. (2024) Original Article Augmented 360° 3D Virtual Reality High-Performance Computing Systems, Virtual Reality Headsets Augmented 360° VR technology Lumbar discectomy, brain metastasis resection, clipping of an aneurysm Thirty-five third-year medical students participated to this study. Augmented 360 VR videos depicting three neurosurgical procedures (lumbar discectomy, brain metastasis resection, clipping of an aneurysm) were presented during elective seminars. 81% reported an increased interest in neurosurgery, and 47% acknowledged the potential influence of the videos on their future choice of specialization. Augmented 360° VR videos significantly enhance neurosurgical education for medical students, increasing interest and understanding in neurosurgery. Yilong Peng et al. (2023) Original Article Mixed Reality (MR) Device and 3D Printing Model Head-mounted MR device (HoloLens), 3D printer 3D Slicer software, MR neuronavigation application Neurosurgery ventricular and hematoma puncture training Image data of two patients (hydrocephalus and basal ganglia haemorrhage) were imported for 3D reconstruction and 3D models were constructed. A total of 16 junior physicians who studied under this specialty were selected. MR and 3D printing models improve training outcomes in neurosurgery, enhancing young doctors’ skills and confidence. Sonny Chan et al. (2013) Literature Review Virtual Reality Simulation VR Headsets and Stereoscopic Displays, Haptic Devices NeuroTouch, Dextroscope (Bracco AMT, Princeton, New Jersey Surgical training, planning, and rehearsal Virtual reality simulation offers significant benefits for neurosurgical training and planning, enhancing safety and efficacy in simulated settings. Timothée Jacquesson et al.(2020) Original Article Stereoscopic 3D visualization High-resolution camerasCanon EOS E700, double video projectorEPSON Power Lite W16SK 3D LCD Dual Projection System, passive 3D glasses Microsoft PowerPoint, Apple Keynote, Apple macOS Neuroanatomy Teaching 10 fresh cadaver heads were harvested. Dissections were performed by two senior neurosurgeons High-resolution specific pictures were taken on various specimen dissections.Stereoscopic neuroanatomy lecture was given by two neuroanatomists to the third-year medicine students. Feedbacks from students were collected. Stereoscopic 3D lectures significantly enhanced neuroanatomy comprehension and engagement among medical students. Ali Alaraj et al.(2015) Original Article Haptic-based VR Simulation Immersive Touch platform Virtual reality aneurysm clipping simulator (ITACS) Cerebral Aneurysm Clipping A prototype middle cerebral artery aneurysm simulation was created from a computed tomography angiogram. Seventeen neurosurgery residents from three residency programs tested the simulator and provided feedback on its usefulness and resemblance to real aneurysm clipping surgery. Neurosurgical residents found the VR simulator beneficial for training, providing a realistic experience in aneurysm clipping with real-time haptic feedback. Sébastien Delorme et al.(2012) Technical Note Virtual Reality Simulation Stereovision system, Bimanual haptic tool manipulators, High-end computer NeuroTouch Simulator Craniotomy-based Procedures The NeuroTouch simulator, developed with input from over 50 experts, offers realistic haptic and visual feedback for craniotomy-based procedure training, enhancing neurosurgery education. Fahad E Alotaibi et al.(2015) Original Article Virtual Reality Simulation and Metrics Analysis VR System (NeuroTouch) Excel Software for Data Analysis Brain Tumor Resection Based on the data contained in the NeuroTouch comma-separated values file, 13 novel NeuroTouch metrics were developed and classified.The introduction of NAJD metrics within the NeuroTouch platform allows for an enhanced assessment of neurosurgical skills, such as judgment and dexterity, during simulated brain tumor resections. Nicholas Gélinas-Phaneuf et al.(2013) Original Article Virtual Reality Simulation NeuroTouch VR System, Haptic Devices VR Simulation Software, Performance Metrics Analysis Software Convexity Meningioma Resection Seventy-two participants (10 medical students, 18 junior residents and 44 senior residents) were enrolled. Participants completed the internal resection of a simulated convexity meningioma and filled out questionnaires to provide feedback on the experience. Validated the effectiveness of NeuroTouch for surgical training, with performance metrics differing by experience level. Abdulgadir Bugdadi et al.(2017) Original Article Virtual Reality Simulation NeuroVR System Simulation Software Brain Tumor Resection Nine neurosurgeons, 10 senior residents and 8 junior residents resected 9 identical simulated tumors on 2 occasions. Neurosurgeons showed more consistent force application than residents, supporting the Fitts and Posner model of motor learning. Gmaan AlZhrani et al.(2015) Original Article Virtual reality simulation for neurosurgical training NeuroTouch simulator Tier 1 and Tier 2 metrics Simulated brain tumor resection A total of 33 participants (including 17 board-certified neurosurgeons, 7 senior and 9 junior neurosurgery residents), each participant performed the resection of 18 simulated brain tumors of different complexity using the NeuroTouch platform. Established proficiency performance benchmarks for neurosurgical skills, demonstrating significant differences between expert neurosurgeons and residents. Hamed Azarnoush et al.(2017) Original Article Spatial analysis of force application VR simulator (NeuroVR/NeuroTouch) Analysis tools for generating force pyramids Brain tumor resection simulation 16 neurosurgeons, 15 residents, and 84 medical students participated. Using a VR simulator, participants performed simulated resections of 18 brain tumors with different visual and haptic characteristics. Introduced ”force pyramid” for 3D force analysis in simulation; revealed distinct patterns of force application among neurosurgeons, residents, and students influenced by various factors. Brian Fiani et al.(2020) Literature Review VR, AR, MR ImmersiveTouch Simulator, Novint Falcon, Stealth 3D, Osso VR hardware Osso VR software, NeuroTouch software Various neurosurgical fields VR has expanded from early military applications to crucial roles in neurosurgery, enhancing education, planning, and execution of procedures. Despite its potential, challenges like cost and ethical concerns remain. Jakub Godzik et al.(2021) Literature Review VR and AR in spine surgery and education Xvision, Google Glass, MicroOptical, AlluraClarity FlexMove VR Operating System for Neurosurgical Education, Augmented Reality Surgical Navigation (ARSN) System, Mixed Reality Training Environment Software Spine Surgery Education Demonstrates VR and AR applicability in spine surgery education, highlighting the need for further studies to confirm their potential in enhancing surgical precision and educational depth. Benjamin K Hendricks et al.(2018) Original Article 3D and Virtual Reality Modelling N/A Virtual Reality Systems, 3D Slicer, NVidia Clara, Sketchfab Cerebrovascular anatomy and pathoanatomy illustration Detailed 3D virtual models of cerebrovascular structures enhance understanding of anatomical relationships and support education, research, and clinical applications. Matthias Gmeiner et al.(2018) Original Article Virtual aneurysm-clipping simulator with haptic force feedback and real-time deformation Forceps with haptic feedback, operating microscope Prototype simulator Software Cerebral aneurysm clipping A prototype simulator was developed. Evaluation of virtual clipping by blood flow simulation was integrated in this software, and the proto-type was evaluated by 18 neurosurgeons. In 4 patients with different medial cerebral artery aneurysms, virtual clipping was performed after real-life surgery. It improves anatomic understanding, realistic simulation of surgical procedures, recommended integration into neurosurgical education. Table 3: Advancing Neurosurgery: A Review of 3D Technology in Surgical Planning and Guidance Walter C. Jean et al.(2024) Case Series Mixed Reality in Cranial Surgery Preoperative CT and MRI, Microscope-integrated AR Surgical Theater SRP and SyncAR, StealthStation S8 Various This series includes the first 100 consecutive complex cranial cases of a single surgeon for which MxR was intended for use. Effectiveness of the VR rehearsal and AR guidance was analyzed for four specific contributions: (1) opening size, (2) precise craniotomy placement, (3) guidance toward anatomic landmarks or target, and (4) antitarget avoidance. MxR facilitates surgical planning and execution,with a learning curve but no surgery or hospitalization extension. Diego F. Gómez Amarillo et al.(2023) Mini-Review AR for Intracranial Meningioma Resection Microscopes with integrated HUDs, HMDs AR platforms, 3D reconstruction software Meningioma resection, especially skull base AR enhances surgery by improving visualization of critical structures and tumor boundaries. Teodoro Martín-Noguerol et al.(2019) Review Hybrid CT and MRI 3D Printed Models for Neurosurgery Planning Various 3D printers and materials Advanced segmentation and registration software Various neurosurgical applications Hybrid 3D models enhance surgical planning by integrating anatomical and functional data from CT and MRI, improving patient outcomes. Kimia Kazemzadeh et al.(2023) Narrative Review AI, Robotics, AR, and VR in Neurosurgery Various (High-resolution 4K 3D exoscopes, Head-Mounted Devices (HMDs) - Microsoft HoloLens, Google Glass AI, robotics, VR, and AR platforms Various(Artificial Neural Networks (ANNs) Surgical Theatre, Synaptive Medical, VPI Reveal Hybrid angio-suites, IBIS (Intraoperative Brain Imaging System) Enhances outcomes, decision-making, and training. Faces challenges like data privacy and the ”black box” issue. Research ongoing. Richard Gonzalo Párraga et al.(2016) Original Article Microsurgical Anatomy and 3D Imaging M900 D.F. Vasconcellos microscope, Nikon D40 camera Callipygian software(Callipyan 3D, Copyright 2003, Robert Swirsky) Brainstem Surgery Enhances understanding of brainstem surgery through detailed anatomy review and 3D images, highlighting surgical approaches and safe entry zones. Raniel Tagaytayan et al.(2018) Literature Review Augmented Reality PCs, monitors, cameras, tracking tools, 3D image software N/A Neuro-oncology, spinal surgery, neurovascular surgery A total of 196 articles were retrieved, 25 of which were reviewed, and 10 primary research papers were included in this review. As a result, AR in neurosurgery enhances planning and execution. Its clinical application is promising yet still experimental. Fenil R. Bhatt et al. (2023) Prospective Cohort Study Augmented Reality (AR) FDA-approved head-mounted device Xvision-Spine (XVS) system Thoracolumbar Fusion Consecutive thirty-two adult patients undergoing AR-assisted thoracolumbar fusion (with a total of 222 screws executed using HMD-AR.) between October 2020 and August 2021 with 2 -week follow-up were included. Intraoperative 3D imaging was used to assess screw accuracy using the Gertzbein-Robbins (G-R) grading scale. AR-assisted surgery demonstrated 97.1% screw placement accuracy with no intra or early postoperative complications across 218 screws. Yanting Liu, Min-Gi Lee, Jin-Sung Kim(2022) Systematic Review Augmented Reality (AR) Various, including FDA-approved HoloLens and xVision Spine System Various, including ImmersiveTouch software and ARSurgical Navigation Spinal Surgery (Pedicle Screw Instrumentation, Spinal Injection, Vertebroplasty, Tumor Resection, Osteotomy) 45 AR-related articles were included. Shows potential in clinical application for spinal surgery, especially for pedicle screw instrumentation. Further research needed for robust data. Augustus J. Rush, III, et al.(2022) Review Augmented Reality (AR) Augmedics XVision, Holosurgical ARIA XVision system, ARAI surgical navigation system Spine Surgery (instrumentation,decompressions, osteotomies, tumor resections) Discusses the benefits of AR including decreased attention shift, more minimally invasive approaches, reduced radiation exposure, and improved pedicle screw accuracy. Highlights institutional experiences with Augmedics and Holosurgical products. Henrik Frisk, et al.(2022) Original Research Augmented Reality Navigation Magic Leap Head Mounted Device (HMD) combined with a conventional surgical navigation system Curve® 1.0 navigation platform (Brainlab AG) integrated with Magic Leap HMD for AR-navigation Minimally Invasive Thoracolumbar Pedicle Screw Placement Forty-eight screws were planned and inserted into Th11-L4 of the phantoms using the AR-HMD and navigated instruments. Postprocedural CT scans were used to grade the technical (deviation from the plan) and clinical (Gertzbein grade) accuracy of the screws. Achieved 94% clinical accuracy for minimally invasive thoracolumbar pedicle screw placement with a mean deviation of 1.9 mm at the entry point and 1.4 mm at the screw tip. Noah Pierzchajlo,et al. (2023) Narrative Review Augmented Reality in Minimally Invasive Spinal Surgery (MISS) Augmedics xVision Spine System (XVS), Microsoft HoloLens, ImmersiveTouch Augmedics xVision Spine System (XVS), Microsoft HoloLens, ImmersiveTouch MISS for pedicle screw placement and other spinal procedures AR technology shows promise in enhancing surgical training and MISS outcomes, with studies indicating its effectiveness in both educational and operative settings, surpassing traditional free-hand methods without introducing unique complications. Alexander J Butler et al.(2023) Research Article Augmented Reality in Minimally Invasive Spinal Surgery (MISS) Wireless headset with transparent near-eye display N/A Percutaneous pedicle screw instrumentation (MISS) 3 senior surgeons at 2 institutions contributed cases from June, 2020 - March, 2022. 164 total MISS cases in which AR used for placement of percutaneous pedicle screw instrumentation with spinal navigation were identified prospectively. This is the first report of AR for spinal pedicle screws placement in MISS, demonstrating efficiency and safety with an average time of 3:54 per screw and no postoperative neurologic deficits. Phillipp Brockmeyer et al. (2023) Review Article Augmented Reality in Minimally Invasive Spinal Surgery (MISS) N/A N/A Various, including spine and orthopedic surgery, endoscopic/laparoscopic procedures A total of 359 studies were screened and 31 articles were reviewed in depth. AR improves ergonomics, visualization, and reduces surgical time and blood loss, but faces precision and real-time data processing challenges. Viktor Vörös et al.(2022) Research Article AR-based robotic control for PSP HoloLens 2, KUKA Robot LWR Unity, ROS, eTaSL Robotic Pedicle Screw Placement Proposed AR-robot interaction for surgical plan adjustments and execution with mean calibration error of 3.61 mm, enhancing robotic-assisted surgery in OR. Barbara Carl et al.(2019) Research Article Augmented Reality (AR) Head-up displays (HUDs) of operating microscopes Head-up displays (HUDs) of operating microscopes Intradural spinal tumor surgery Between July 2018 and April 2019, 10 patients underwent AR supported surgery for intradural tumors of the spine. Microscope-based AR can be reliably applied to intradural spinal tumor surgery. Kadri Emre Caliskan et al.(2024) Research Article Mixed-Reality Neurosurgical Navigation 3D-printed marker, mobile device LIDAR camera Patient-specific, surgeon-facilitated mobile application Spinal intradural pathologies 3D-printed marker-based mixed-reality neuronavigation is feasible, easy to use for surgeons, time-saving, cost-effective, and highly precise for spinal surgery. Fabian Sommer et al.(2022) Research Article Augmented Reality Assistance Surgical microscope, intraoperative CT AR software for intraoperative localization Minimally Invasive and Open Resection of benign intradural extramedullary tumors A prospective case study of AR-assisted BIET resection was conducted at a single tertiary medical center, 8 patients were enrolled. AR assistance in BIET resection is feasible, precise, and integrates well with existing workflows, potentially improving surgical outcomes. Walter C Jean et al.(2021) Case Report Augmented Reality AR navigation-tracked microscope Virtual reality rendering software Anterior Petrosectomy AR provides critical visual cues during AP, enhancing safety and protecting neurovascular structures. Walter C Jean(2024) 2D Operative Video AR/VR Surgical exoscope, hand-held endoscopes Virtual reality (VR) for visualization Exposure of the Pineal region) Paramedian Supracerebellar Infratentorial Approach) Four cases in which surgery was performed using the paramedian supracerebellar infratentorial approach were reviewed. Careful handling of deep veins and patient positioning are critical for avoiding complications. Walter C Jean(2022) 2D Operative Video AR/VR Navigation-tracked microscope Augmented reality (AR) template, Virtual reality (VR) rendering Resection of Clinoid Meningioma AR and VR enhance surgical planning and execution, ensuring precise and minimally invasive approaches. Walter C Jean, Ameet Singh (2020) 2D Operative Video VR Endoscope,VR Virtual reality (VR) rendering Endoscopic endonasal approach for Tuberculum Sellae Meningioma Preoperative planning and surgical rehearsal in VR can improve the efficiency of endoscopic skull base surgery. Frederick Van Gestel et al.(2023) Research Article Augmented Reality (AR) Planning for Intracranial Tumor Resection Microsoft HoloLens II AR-based workflow software Intracranial tumor resection Developed an AR-based workflow for intracranial tumor resection planning deployed on the Microsoft HoloLens II, which exploits the built-in infrared-camera for tracking the patient. This planning step was performed by 12 surgeons and trainees with varying degrees of experience.AR navigation is accurate for tumor resection planning, is quicker, and more intuitive than conventional neuronavigation. Guo-chen Sun et al.(2016) Original Article AR/VR based on Intraoperative MRI and Functional Neuronavigation Intraoperative MRI (iMRI), Functional Neuronavigation System Diffusion Tensor Tractography, BOLD fMRI Glioma Surgery Involving Eloquent Areas A total of 134 consecutive patients with gliomas affecting eloquent areas were prospectively enrolled in the study between February 2009 and January 2014. Functional neuronavigation and iMRI were used in 79 of these patients. Combining VR and AR with iMRI and neuronavigation facilitates glioma resection and preserves neural function. Mohammad Mofatteh et al.(2022) Systematic Review AR/VR AR headsets (e.g., HoloLens), VR headsets (e.g., Oculus, HTC VIVE), head-up displays Custom software for field assessment, VR cognitive mapping platforms, eye-tracking apps, neuronavigation systems Awake Craniotomy A total of six articles, comprising 118 patients, were included in this review. Four articles used VR, and the other two used AR. AR and VR enhance the mapping of cognitive functions and can potentially replace some conventional methods, leading to improved intraoperative assessments and patient engagement. Nicola Montemurro et al.(2021) Preliminary Laboratory Report AR-Assisted Craniotomy VOSTARS head-mounted display EndoCAS Segmentation Pipeline, ITK-SNAP, MeshLab, Creo Parametric CAD, 3D Printing Craniotomy for Parasagittal and Convexity En Plaque Meningiomas, Custom-Made Cranioplasty AR headsets show potential for precision in craniotomy and fitting custom-made bone flaps, indicating their usefulness in planning and executing complex neurosurgeries. Sabino Luzzi et al.(2024) Research Study Augmented Reality Intraoperative Fiber Tractography (AR-iFT) N/A Diffusion tensor imaging-based software Surgery for Primary Motor Area (M1) Tumors This study included 34 and 31 patients in the AR-iFT and unAR-iFT groups, respectively. AR-iFT is feasible, effective, and safe, improving the extent of resection, reducing intraoperative seizures, and positively affecting motor outcomes and progression-free survival in M1 tumor surgeries. Sabino Luzzi et al.(2022) Research Article Augmented Reality with Fiber Tractography and Fluorescein BrainLAB Curve navigation platform, KINEVO 900 surgical microscope, YELLOW 560 filter Smartbrush software (BrainLAB AG) Maximal Safe Anatomic Resection of Postcentral Gyrus High-Grade Glioma AR HDFT-F technique integrates AR into the microscope, overlaid onto the surgical field, enhancing the safety and efficacy of resection in eloquent brain areas. Sabino Luzzi et al.(2021) Research Article Augmented Reality with High-Definition Fiber Tractography and Fluorescein (HDFT-F) AR-equipped surgical microscope, infrared neuronavigation N/A Maximal Safe Anatomic Resection of Supratentorial High-Grade Gliomas(HGG) A total of 54 patients underwent surgery using the AR HDFT-F technique, and 63 underwent conventional white-light surgery assisted by infrared neuronavigation. AR HDFT-F technique is effective in maximizing extent of resection and progression-free survival, optimizing patient functional outcomes in HGG surgery. Ivan Cabrilo et al.(2014) Technical Report Augmented Reality Operating microscope N/A Cerebral aneurysm surgery Twenty-eight patients with 39 unruptured aneurysms were operated on in a prospective manner with AR. AR facilitates tailored surgical approaches and optimal aneurysm clipping with minimal exposure, enhancing procedure efficiency. Ivan Cabrilo et al.(2014) Technical Report Augmented Reality Operating microscope N/A Cerebral arteriovenous malformations surgery 5 patients underwent surgery for resection of AVMs assisted by AR, in a hybrid neurointerventional suite equipped with flat-panel display technology, allowing for intraoperative 3-D digital subtraction angiography (DSA) for resection control. AR helped in tailored craniotomies and locating drainage veins, but was less informative for feeder vessels due to AVM complexity. Integration of hemodynamic data may enhance AR’s effectiveness in AVM surgery. Ivan Cabrilo et al.(2015) Technical Report Augmented Reality Operating microscope’s eyepiece N/A Extracranial-to-Intracranial Bypass Surgery 3 female patients with Moya-Moya disease underwent superficial temporal artery- middle cerebral artery bypass procedures, and 1 male patient underwent an occipital artery-posterior inferior cerebellar artery bypass. All procedures were performed in a hybrid neurointerventional suite equipped with a Flat-Panel system allowing intraoperative 3-dimensional DSA control of bypass patency. AR precisely localized donor and recipient vessels, tailored craniotomies to injected images, and helped perform minimally invasive procedures. Ralf A. Kockro et al.(2016) Original Article Aneurysm surgery planning in VR Dextroscope VR workstation Dextroscope planning software Clipping of intracranial aneurysms Between 2006 and 2015, clipping of 115 intracranial aneurysms in 105 patients was preoperatively planned with the Dextroscope, a stereoscopic, patient-specific VR environment. Demonstrated that meticulous 3D surgical planning in VR enhances spatial understanding of vascular anatomy, leading to excellent clinical outcomes and high rates of complete aneurysm closure. A. Jessey Chugh et al.(2017) Randomized Controlled Trial Surgical rehearsal platform N/A SuRgical Planner (SRP) Clipping of aneurysms A total of 40 patients participated. Preoperative SRP rehearsal improved aneurysm surgery efficiency, shown by better operative time per clip used, hinting at potential safety and efficiency boosts. Thomas C Steineke, et al.(2021) Research Article VR for preoperative planning N/A N/A Clipping of Middle Cerebral Artery Aneurysms A retrospective review of 21 patients from 2016 to 2019 was conducted to determine the impact on the procedure time of MCA aneurysm clipping after implementing VR for preoperative planning and rehearsal. Utilizing VR for preoperative planning and rehearsal significantly reduced procedure time by 80 minutes for microsurgical clipping of MCA aneurysms, demonstrating VR’s potential to enhance surgical efficiency and safety. Samer Zawy Alsofy et al.(2020) Research Article 3D VR reconstructions from CTA VR headset (HTC Vive), workstation 3D Slicer Clipping of unruptured ACoA aneurysms Twenty-six patients were included. Ten experienced, board-certified neurosurgeons used VR headset and filled questionnaire. 520 answer sheets were evaluated. 3D-VR improved detection of vascular structures, influenced surgical approach, and enhanced anatomy understanding for unruptured ACoA aneurysm surgery planning. Caglar et al. (2024) Technical Note Mixed Reality in Cranial Surgery Preoperative CT and MRI, AR BrainLab Navigation System, Magic Leap eyewear, and MxR technology Excision of inferior temporal AVM, cerebellar glial tumor and sphenoid wing meningioma Three patients with different pathologies were icluded this study. It demonstrates the possible use of MxR technology in neurosurgery for multiple purposes, including preoperative planning, training, and 3D navigation Figure Legends Figure 1 : Pipeline to create 3D models from radiological images and photogrammetry. Figure 2 : Anatomic segmentation and 3D reconstruction of anatomic layers and structures from radiological images A: Skin captured through detailed T1W MRI for surface topography. B: Cranium and vessels outlined by CT Angiography for structural clarity. C: White matter and D: Grey matter extracted using T1W and/or T2W MRI. E: Veins and sinuses delineated via contrast-enhanced T1W MRI or MR venography. F: Arteries extracted using time of flight (TOF) MR angiography, emphasizing blood flow. G: Tumor and peritumoral edema distinguished by contrast-enhanced T1W, T2W, and FLAIR MRI. H: After careful alignment of different modalities, 3D model integration displays full anatomical complexity. Figure 3: Surgical planning and intraoperative guidance using patient-specific 3D model in a brain tumor case A: Preoperative axial FLAIR MRI delineates the temporoinsular tumor glioma. B: Tractography outlines intersecting neural pathways in relation to the tumor. C: Virtual dissection in 3D from the skull to the tumor, through lateral sagittal perspective. D: Adjusting the transparency of the hemisphere in the 3D model exhibits the deep portions of the tumor in relation to underlying neural structures and vasculature. E: Coronal view in 3D supplements the tumor’s spatial orientation. F: The rotated 3D model simulates the surgical viewpoint. G: The operative photography verifies the 3D model’s precision in depicting the tumor and associated neurovascular structures. Figure 4: Surgical planning and intraoperative guidance using a patient-specific 3D model in an intracranial aneurysm case A: T2 sequence MRI B: CT angiography C: Anteroposterior view of Digital Subtraction Angiography(DSA) D: 3D reconstruction of DSA displays a large thrombosed left middle cerebral artery(MCA) aneurysm with the vascular details. E & F: Patient-specific 3D models showing the aneurysm from a lateral perspective. G: Intraoperative microscope view compared with the 3D model in the same surgical position pre- and post-clipping. Information & Authors Information Version history V1 Version 1 27 October 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords augmented reality (ar) neurosurgery patient-specific simulations surgical planning three-dimensional (3d) modeling virtual reality (vr) Authors Affiliations Efecan Cekic Hacettepe Universitesi View all articles by this author Gulsah Cetin Hacettepe Universitesi View all articles by this author Ayse Ozer Hacettepe Universitesi View all articles by this author Baylar Baylarov Hitit University Erol Olcok Education and Research Hospital View all articles by this author Ilkan Tatar Hacettepe Universitesi View all articles by this author Sahin Hanalioglu 0000-0003-4988-4938 [email protected] Hacettepe Universitesi View all articles by this author Metrics & Citations Metrics Article Usage 345 views 144 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Efecan Cekic, Gulsah Cetin, Ayse Ozer, et al. Digital 3D Models in Neurosurgical Training, Surgical Planning, and Intraoperative Guidance: Comprehensive Review of the Literature. Authorea . 27 October 2025. 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