The Evolution of Spatial Computing in Spine Surgery: Tracing the Historical Arc to Present Day Implementation Galal A. Elsayed, Gabrielle Dykhouse, Chibuikem A. Ikwuegbuenyi, Noah Willett, Ibrahim Hussain, Mousa Hamad, Osama Nezar Kashlan, Roger Hä rtl The evolution of spatial computing in spine surgery rep- resents a significant advancement in surgical precision, patient care, and education. From the early days of ste- reotactic frames and rudimentary imaging techniques to the sophisticated integration of augmented reality, virtual reality, robotics, and artificial intelligence, spatial computing has fundamentally transformed spinal surgery. This article traces the historical development of these technologies, highlighting key milestones and imple- mentation in modern surgical practices. Intraoperative imaging modalities and robotic platforms have enhanced surgical accuracy and reduced complications. Moreover, artificial intelligence—driven preoperative planning tools and virtual reality—based simulations have refined surgical techniques, marking a paradigm shift toward safer and more precise procedures. The continuous integration of these spatial computing technologies underscores the ongoing evolution of spine surgery, promising further ad- vancements in patient outcomes and surgical education. INTRODUCTION Historical practices in spine surgery have consistently prioritized precision due to the intricate nature of spi- nal anatomy and the fact that errors could result in lasting damage or neurological impairments. Surgeons tradi- tionally relied upon their tactile and visual skills for accuracy. However, with the evolution of spine surgery encompassing more complex reconstructions and deformity corrections, the need for technological assistance became increasingly apparent. 1,2 Spatial computing refers to the set of technologies that enable interaction with digital information anchored in physical space. It encompasses tools such as augmented reality (AR), virtual reality (VR), artificial intelligence (AI), advanced imaging, and robotics, all of which allow users—particularly surgeons—to perceive, simulate, and manipulate anatomical and procedural data in 3 dimensions. In spine surgery, spatial computing facilitates more accurate preoperative planning, enhances intraoperative navigation and visualization, and enables personalized postoperative assessment, bridging the digital and physical domains to optimize surgical workflows and outcomes. These groundbreaking technologies not only enhance surgical precision but also have allowed us to reimagine patient care and surgical training. We herein detail the developmental trajectory of surgical imaging, navigation systems, radiology protocols, and the modern-day AI-driven technologies advancing spatial computing in the realm of spinal surgery. EARLY EXPLORATIONS AND PIONEERS The Beginnings of Imaging in Surgery More than a century ago, pioneering efforts in imaging for sur- gical guidance kickstarted a significant journey of technological milestones (Figure 1). In 1895, after Roentgen’s groundbreaking Key words ■ Augmented reality ■ Preoperative planning ■ Spatial computing ■ Virtual reality Abbreviations and Acronyms 3D: 3-dimensional AI: Artificial intelligence AR: Augmented reality CBCT: Cone beam computed tomography CT: Computed tomography FDA: Food and Drug Administration HU: Hounsfield units MR: Mixed reality MRI: Magnetic resonance imaging PC: Personal computer VR: Virtual reality XVS: xVision Spine Department of Neurological Surgery, Och Spine at New York Presbyterian Hospital, Weill Cornell Medicine, New York, New York, USA To whom correspondence should be addressed: Galal A. Elsayed, M.D. [E-mail: sbk9015@med.cornell.edu] Citation: World Neurosurg. (2025) 204:124514. https://doi.org/10.1016/j.wneu.2025.124514 Journal homepage: www.journals.elsevier.com/world-neurosurgery Available online: www.sciencedirect.com 1878-8750/© 2025 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). WORLD NEUROSURGERY 204: 124514, DECEMBER 2025 www.journals.elsevier.com/world-neurosurgery 1 From the Annals of Weill Cornell Neurological Surgery http://creativecommons.org/licenses/by/4.0/ Delta:1_given-name Delta:1_surname Delta:1_given-name Delta:1_surname Delta:1_given-name Delta:1_surname Delta:1_given-name Delta:1_surname mailto:sbk9015@med.cornell.edu https://doi.org/10.1016/j.wneu.2025.124514 www.journals.elsevier.com/world-neurosurgery www.sciencedirect.com/science/journal/18788750 http://creativecommons.org/licenses/by/4.0/ http://crossmark.crossref.org/dialog/?doi=10.1016/j.wneu.2025.124514&domain=pdf www.journals.elsevier.com/world-neurosurgery work on X-rays, a surgeon in England used X-ray imaging to assist in removing an industrial sewing needle from a patient’s hand. 3,4 Shortly thereafter, physicist John Cox, of McGill University in Montreal, employed radiography to identify the location of a bullet from a patient’s leg. 5 In 1908, Horsley and Clarke published the specifications for a stereotactic device that laid the foundation for modern image-guided interventions; this apparatus included a frame that could be affixed to a monkey’s head and aligned by means of external markers. This enabled the assignment of a Cartesian coordinate system to the animal’s brain. 6 Remarkably, this concept remains in use even a century later. Although the principles of image-guided intervention are universally applicable to various body parts, their practical application was predominantly limited to neurosurgery due to the skull’s provision of a stable and rigid frame. Late 20th-Century Developments The later 20th century witnessed multiple pivotal developments in stereotactic surgery. First, the introduction of computed tomog- raphy (CT) scanning, developed by Godfrey Hounsfield of the Electrical and Musical Industry Limited Group in the early 1970s, revolutionized imaging capabilities. 7,8 In the pre-CT era, images were primarily recorded and displayed on film regardless of the imaging modality; the introduction of CT allowed images to be inherently represented as numerical data on a quantitative scale describing radiodensity. Appropriately named after their devel- oper, these Hounsfield units (HU) provide a standardized mea- surement for different tissue densities, where air is typically assigned a value of − 1000 HU, pure water is set at 0 HU, and dense cortical bone can reach values greater than +1000 HU. 9,10 This scale is essential for the accurate interpretation of CT images, and some spine surgeons have even come to use it as a surrogate measure for bone quality. 11 Second, the advent of personal computers (PCs) in 1981 played a crucial role in propelling stereotactic surgery into mainstream spine surgery practice. While some neurosurgery systems had previously integrated computers, they often required custom- made systems or extensive data reduction processes typically conducted at the tomographic imaging system’s console. 12 Notably, Peters et al. pioneered one of the initial PC-based sys- tems capable of planning stereotactic procedures using CT, magnetic resonance imaging (MRI), and digital subtraction angiography. 13,14 This development was closely intertwined with the increased computing power essential for the evolution of image-guided interventions. Early applications of MRI also pro- vided clear visualization of intervertebral disc pathology and epidural structures, representing a critical advance in spinal di- agnostics (Figure 2). In the late 1980s and early 1990s, frameless systems emerged, transcending the limitations of the stereotactic frame. This innovation was exemplified by the work of David Roberts’ labo- ratory at Dartmouth; employing a spark-gap sonic localization system coupled with the operating microscope, Roberts and his team achieved real-time target localization within the operative field using a dynamically updated tomographic image. 15-17 As computational and display technologies continued to advance, Maciunas et al. developed an articulated arm tailored for neuro- surgery that enabled simultaneous display of the surgical position on 3 dynamically updated orthogonal CT planes. 18,19 These advancements heralded a transformative era in surgical imaging, highlighting the integration of real-time visualization and improved target accuracy within the surgical arena. The greater freedom of motion in frameless systems permitted their implementation in spine surgery. 20,21 In the early 1990s, initial sonic-based prototypes for frameless navigation faced limitations in generating real-time visualizations, prompting the development of a new system. Dr. Kenneth R. Smith, the Director of Neurosurgery at Saint Louis University School of Medicine, introduced a development team at Southern Illinois University at Edwardsville to this project, leading to the creation named StealthStation; according to Bucholz et al., the StealthStation evolved from an audio-recording device project and was tailored to meet surgical needs. 22 The system’s optical version was thereafter tested in early 1992, initially using framed registration Figure 1. Timeline of key events in the development of spatial computing in spine surgery. AR, augmented reality; CT, computed tomography. 2 www.SCIENCEDIRECT.com WORLD NEUROSURGERY, https://doi.org/10.1016/j.wneu.2025.124514 FROM THE ANNALS OF WEILL CORNELL NEUROLOGICAL SURGERY GALAL A. ELSAYED ET AL. SPATIAL COMPUTING FOUNDATIONS IN SPINE www.sciencedirect.com/science/journal/18788750 https://doi.org/10.1016/j.wneu.2025.124514 and subsequently adopting frameless registration with light- emitting diodes retrofitted onto sound emitters. The Neuro- station, a second-generation navigational system, emerged after several prototype refinements. Additionally, collaboration with Moeller-Wedel (Germany) in 1993 resulted in the development of a computer-tracked microscope, further expanding the system’s capabilities. Dr. Kevin Foley of the University of Tennessee later applied the Neurostation to spinal procedures in 1994, leading to its broader adoption in cranial and spinal surgeries. 23 The United States Food and Drug Administration (FDA) granted approval in 1996, and Sofamor Danek (Memphis, Tennessee, USA) acquired the system in the same year. 22 After Medtronic (Minneapolis, Minnesota, USA) took over Sofamor Danek in 1999, StealthStation became the benchmark spine navigation system through its integration of fluoroscopy in addition to CT and MRI. MODERN-DAY IMPLEMENTATIONS Overview of Intraoperative Imaging Modalities Intraoperative imaging modalities are a critical aspect affecting spatial computing in spine surgery, offering real-time visualiza- tion that alters the surgeon’s perspective. Among the myriad imaging techniques available, CT and fluoroscopy have become prominent in the realms of neurosurgery and orthopedics. Such quintessential navigation systems encompass several compo- nents: a reference frame attached to the patient, acting as a steadfast point of reference; typically a tracking system, usually using infrared cameras, detecting the position of specialized in- struments; a display monitor which superimposes the real-time position of instruments on preoperative or intraoperative images; and a computational unit that harmonizes these data points. 24,25 The clarity and depth of visualization allows surgeons to achieve their objectives with smaller incisions, enabling minimally invasive procedures. These advancements have ripple effects, leading to fewer complications and abbreviated hospital stays. 26-28 However, it is important to note that CT and fluoros- copy expose both the patient and the surgical team to radiation; for reference, natural background radiation is about 2—3 mSv/ year, while a complex fluoroscopic procedure can range from 1 to 10 mSv. 29 Cumulative exposure can therefore increase risk of malignancies such as breast cancer and skin diseases for both patient and surgeon, emphasizing the importance of dose optimization and protective measures. 30-34 Intraoperative Imaging Devices Used in Spine Navigation The importance of modern imaging devices, such as the O-arm (Medtronic, Minneapolis, Minnesota, USA), Ziehm systems (Nuremberg, Germany), and OEC 9900 and Elite (GE Healthcare, Chicago, Illinois, USA), to name a few, is anchored in their ability to provide precise, high-resolution, dynamic imaging during sur- gical interventions. 35 The O-arm was developed by Breakaway Imaging (Littleton, Massachusetts, USA) in the early 2000s and has been distributed by Medtronic. After gaining FDA clearance in 2005, the University of California, San Francisco became one of the first institutions to take advantage of the system’s 360 ◦ imaging capabilities. 36 The O-arm combines cone beam computed tomography (CBCT) with fluoroscopy to create 3-dimensional (3D) reconstructions, underscoring a philosophy of integrating multiple imaging modalities to streamline surgical workflows. 37,38 Although it cannot show real-time changes, an Figure 2. Early magnetic resonance imaging of spine. (A) T2-weighted spin-echo 2000/60 image shows displacement of epidural fat between the fourth and fifth lumbar vertebrae (upper arrow), indicative of a herniated disc. Disc herniation or bulging of the annulus fibrosus is also apparent between the fifth lumbar and first sacral vertebrae (lower arrow). (B) Magnified T1-weighted surface coil image shows the protruding disc more clearly. Public domain material from https:// www-ncbi-nlm-nih-gov.ezproxy.med.cornell.edu/pmc/ articles/PMC1345865/?page=9. WORLD NEUROSURGERY 204: 124514, DECEMBER 2025 www.journals.elsevier.com/world-neurosurgery 3 FROM THE ANNALS OF WEILL CORNELL NEUROLOGICAL SURGERY GALAL A. ELSAYED ET AL. SPATIAL COMPUTING FOUNDATIONS IN SPINE https://www-ncbi-nlm-nih-gov.ezproxy.med.cornell.edu/pmc/articles/PMC1345865/?page=9 https://www-ncbi-nlm-nih-gov.ezproxy.med.cornell.edu/pmc/articles/PMC1345865/?page=9 https://www-ncbi-nlm-nih-gov.ezproxy.med.cornell.edu/pmc/articles/PMC1345865/?page=9 www.journals.elsevier.com/world-neurosurgery image from this system can account for shifts or nuances in the patient’s anatomy as compared to preoperative scans. Meanwhile, Ziehm fluoroscopy systems emphasize high-resolution images and enhanced visualization, ensuring that minute details are not overlooked. 39 Furthermore, the OEC series, with its 9900 and Elite models, are traditional fluoroscopic C-arm devices, but the OEC 3D facilitates a 3D scan that can offer axial plane navigation. The OEC series’ overall emphasis on maneuverability signifies consideration for the adaptability and responsiveness of surgical setups, catering to diverse surgical environments and challenges. In the early 2000s, Medtronic adopted the StealthStation, a pivotal point in navigation development. Combining the O-arm with StealthStation facilitated a rapid solution for gathering intraoperative imaging and facilitating surgical approaches in near real-time. 40 Over the years, this system underwent enhancements like the incorporation of touchless interaction, improved imaging modalities, and integration with intraoperative MRI and CT. Although it provides a high degree of precision, it also has a steep learning curve and high equipment costs. 41 Stryker (Kalamazoo, Michigan, USA) also made its mark in the early 2000s with the creation of the SpineMap 3D. Advanced iterations such as SpineMask Tracker and SpineMap Go provide streamlined fluoroscopic solutions that eliminate the requirement for additional incisions, especially those typically needed to place bone-anchored trackers. 42 NuVasive (San Diego, California, USA) unveiled Pulse in 2018. This system was designed to amalgamate multiple surgical instruments into one comprehensive platform, covering stages from surgical preparation to rod bending and neuromonitoring. 43 All in all, general intraoperative imaging modalities like CT and fluoroscopy have laid a strong foundation for enhanced navigation and future integrated spatial computing technologies. With intraoperative CT systems, a distinction arises between fan beam CT and CBCT. While CBCT is often lauded for its compact design and lower cost, fan beam CT, with its traditional linear X-ray beam, delivers higher-resolution images at a lower radiation dosage. 44,45 Fan beam CT systems like the Stryker Airo TruCT provide high-resolution, diagnostic-quality imaging with a 32-slice detector, offering substantial scanning range and preci- sion in spinal segmentation. 46 Its compact design facilitates mobility within clinical settings, although the integrated bed design could limit patient positioning during surgery. Similarly, the Brainlab (Munich, Germany) LoopX delivers high-resolution images with adaptive collimation and radiation-level custom- ization for patient-specific needs. Smart laser projections in LoopX aid in surgical planning and verification, improving the precision of procedures such as screw placement. While Airo excels in image clarity, LoopX’s design prioritizes operational efficiency and patient-centered imaging, overcoming some of the limitations posed by fixed-bed designs, although still limited for spinal correction applications due to bed design. On the other hand, CBCT uses a cone-shaped X-ray beam and a 2-dimensional detector, resulting in a significant reduction in scan time with a single rotation but with diminished quality and smaller scan area. 47 In 2021, Globus Medical (Audubon, Pennsylvania, USA) released their Excelsius3D system which melds robotics and CBCT navigation. It uses 3D imaging for real-time navigation and modality integration, especially for minimally invasive techniques. However, high costs, specialized training needs, and variations in implant compatibility remain considerations. Solid-state CT is a newer entrant to CT navigation systems. While traditional detectors are often based on photomultiplier tubes or scintillation crystals coupled with photodiodes, the newer solid-state CT replaces these components with semi- conductor materials like cadmium zinc telluride or amorphous silicon to directly convert X-ray photons into electrical signals without additional conversion steps. 48 Benefits include a faster imaging process, reduced motion artifacts, and potential for lower radiation exposure. 49 The current state-of-the-art can be exemplified by GE Healthcare’s NM/CT 870 cadmium zinc tellu- ride, which provides homogeneous image replication and up to 75% reduction in scan time. 50 Robotic Surgery Robotic surgery is another technology that has begun to revolu- tionize the surgical landscape (Figure 3). These robots are considered end effectors for a navigation platform. Gaining FDA approval in 2000, the da Vinci surgical system by Intuitive (Sunnyvale, California, USA) was originally introduced to facilitate remote surgeries. Although the da Vinci systems are more commonly used in general surgical practice, Beutler et al. described the use of a da Vinci system for the transperitoneal approach to the anterior lumbar spine, laying precedent for its use in spinal procedures. 51 Zimmer Biomet (Warsaw, Indiana, USA) marked its entry into the sphere through the acquisition of MedTech in 2016. MedTech had originally developed ROSA, a robot crafted for brain sur- geries, which Zimmer Biomet fine-tuned and evolved into ROSA Spine. Mazor Robotics (Caesarea, Israel) introduced MazorX in 2016. This state-of-the-art system married preoperative planning utili- ties with intraoperative guidance, offering an unparalleled level of accuracy in spine surgeries. Brainlab’s Cirq is a robotic arm system known for its modular design, ease of use, and adaptability to various applications. Figure 3. The use of a robotic drill guide to place pedicle screws. 4 www.SCIENCEDIRECT.com WORLD NEUROSURGERY, https://doi.org/10.1016/j.wneu.2025.124514 FROM THE ANNALS OF WEILL CORNELL NEUROLOGICAL SURGERY GALAL A. ELSAYED ET AL. SPATIAL COMPUTING FOUNDATIONS IN SPINE www.sciencedirect.com/science/journal/18788750 https://doi.org/10.1016/j.wneu.2025.124514 Shortcomings involve it not being a standalone solution, neces- sitating integration with other navigation systems. Medtronic released its own robotic solution called Autoguide in 2019. It is particularly known for its precise instrument guid- ance and consistent repeatability, and its seamless integration with existing Medtronic navigation systems like StealthStation presents both an advantage and a potential reliance limitation. The ExcelsiusGPS, a Globus Medical technology approved in 2017, is another popular choice. This system advances the rigid robotic arm beyond the need to use K-wires for screw place- ment. 52 The rigid arm allows for screw placement directly through the guide tube. Such a fusion also eliminates the need for a table-mounted system and maximizes retractor and port stability. The ExcelsiusGPS excels due to its precise robotics and navigation, minimally invasive techniques, and adaptability for various procedures while minimizing radiation exposure. Before the development of the mobile CBCT Excelsius E3D, the Globus ExcelsiusGPS depended on either the use of an intraoperative image collected by other vendors’ imaging modality or fluoroscopic-to-preoperative-CT merger technology based on mutual information algorithm protocols to help develop reliable navigation during surgery. 53 To summarize, the combination of a mobile CT system with an end effector robotic function or freehand navigation platform by the surgeon is the current state-of-the-art technology in spinal surgery. Desktop-Based Preoperative Planning Preoperative planning is another critical cornerstone of spine surgery whose progressive refinement has mirrored the broader technological trajectory. As the second decade of the 21st century ushered in significant advancements in machine learning, neural network tools catalyzed developments in diverse domains, from natural language processing to image recognition. 54 Neural networks trace back to the 1940s and 1950s with the introduction of the perceptron, a simple artificial neuron, by Frank Rosenblatt in 1958. 55,56 While the concept had inherent limitations in addressing complex problems, renewed interest in the 1980s was sparked by the rediscovery of the backpropagation algorithm, adept at computing gradients in multilayered networks; seminal contributions from Rumelhart, Hinton, and Williams in 1986 were instrumental in this context. 57 However, the widespread application and success of neural networks was not realized until after 2010 due in part to the computational prowess of graphics processing units. 58 Together, these developments rejuvenated the role of neural networks and revolutionized a multitude of disciplines. Neural networks are the foundation of current preoperative spine planning software and require appropriate preoperative imaging. Once preoperative imaging is acquired, sophisticated platforms like Surgimap (Nemaris, New York, New York, USA) have revolutionized 3D preoperative planning by providing intri- cate evaluations of spinopelvic parameters and preparations for osteotomies and cages for deformity corrections. 59 Another platform is UNiD, developed by Medicrea (Lyon, France), which is now part of Medtronic. This platform was designed with the aim of revolutionizing patient-specific spinal rod implantation. It facilitates a comprehensive preoperative planning process that relies on a database of over thousands of spinal surgical cases, assisting surgeons in predicting optimal spinal alignment based on individual patient anatomy. Virtual Reality—Based Preoperative Planning A solution to implementing presurgical planning in a 3D envi- ronment is VR-based preoperative planning. VR headsets offer a holistic immersion into digital realms and have undergone tremendous advancement in the recent decade, slowly earning their way into more clinics. The surge in improvements can be attributed to significant progress in display resolutions, reduced latency, better tracking technologies, and enhanced graphics processing unit performance, inching closer to delivering real- time immersion. 60 At the most basic end of the industry, the Google Cardboard headset (Mountainview, California, USA) provides an affordable entry-level experience by using a smart- phone’s display and sensors to immerse users into a digital realm. A step up the hierarchy is the Quest line, manufactured by Oculus, an acquired subsidiary of Meta (Menlo Park, California, USA). These devices offer standalone VR experiences with real- istic immersion and convenience. Other systems, such as Sony’s PlayStation VR (San Mateo, California, USA), bring VR to console gaming, while the HTC Vive (Taoyuan City, Taiwan) and Oculus Rift, as well as their subsequent iterations such as the Vive Pro (Taoyuan City, Taiwan), have pushed toward higher-end PC-based VR. Yet, the revolution in PC-based VR was the 2019 release of the Valve Index (Bellevue, Washington, USA), with its infrared base station technology and submillimeter finger tracking and full- body tracking using the high-quality infrared base stations. Finally, at the pinnacle of quality stands the Varjo XR3 (Helsinki, Finland). This system integrates both VR and mixed reality (MR) functionalities while boasting human-eye resolution, setting it apart in terms of immersion, and allowing it to gain traction in medical implementations. Announced in November 2023, the Varjo XR4 is expected to build on the success of its predecessor; it offers dual 4K × 4K displays with a resolution of 51 pixels per degree and a 50% wider field of view (120 ◦ × 105 ◦ ). With this technology available, surgeons can practice spinal procedures and deconstruct virtual renditions of individualized patient anatomy before even stepping foot into the operating room. Radiology Protocols and Spatial Computing The success of spatial computing in 3D reconstructions is contingent upon the chosen scanner and corresponding radiology protocol. CT and CT angiography are particularly suited due to their high-resolution imaging capabilities, especially in capturing detailed bony structures. 61,62 Their ability to offer thin slices and isotropic resolution makes them an ideal choice for meticulous reconstructions. 63 On the other hand, while MRI excels in differentiating soft tissue due to its contrast-rich images, it may fall short in terms of the sharpness required for precise 3D spatial computing. Moreover, factors such as patient movement or intrinsic scanner attributes can introduce artifacts or distortions in MRI data. 64 WORLD NEUROSURGERY 204: 124514, DECEMBER 2025 www.journals.elsevier.com/world-neurosurgery 5 FROM THE ANNALS OF WEILL CORNELL NEUROLOGICAL SURGERY GALAL A. ELSAYED ET AL. SPATIAL COMPUTING FOUNDATIONS IN SPINE www.journals.elsevier.com/world-neurosurgery On the AI forefront, the conversion of MRI data into CT-like images can merge the superior soft tissue imaging of MRI with the detailed skeletal visualization of CT, representing a notable innovation in radiology. 65 This transformation is primarily driven by generative adversarial networks, a type of AI in which 2 neural networks compete and evolve together. 66 While one neural network crafts images, the other discerns between real and fabricated ones. State-of-the-art methods, such as CycleGAN and pix2pix, are refining this synthesis, 67 but ensuring the accuracy of these synthetic CT images across various patient anatomies remains a challenge. Volumetric analysis is a key aspect of modern radiology that can be enhanced by spatial computing. As CT and MRI evolved, the rise in computational capabilities enabled 3D reconstructions from 2-dimensional images, a breakthrough for radiologists. 68 Furthermore, functional imaging methods, such as positron emission tomography and functional MRI, capture physiological processes in 3D, and even 4-dimensional, to facilitate volu- metric analysis of functional regions. 69 AI has accelerated this field with automated volumetry. For example, Brainlab’s AccuBrain software can delineate and compute the volume of tumors or other structures, minimizing the need for human analysis. 70 Radiomics (Liège, Belgium) tools extract numerous quantitative features from images, 71 supporting a shift toward quantitative and personalized radiology. Software like 3D Slicer (free, open-source software available from www. slicer.org) can offer 3D visualization of volumetric data, enhancing surgical planning. 72,73 In spine surgery, volumetric analysis supports planning and monitoring—for example, spinal tumor volume tracking, nerve root quantification in stenosis, and muscle density evaluation to understand back pain and recovery. 74-77 Despite these radiological advancements, several challenges remain. Accurate volume estimations, especially in automated methods, can be influenced by such factors as partial volume effects and image noise. 78 Advances in tissue segmentation with the use of AI and large language models have the promise to help overcome these current challenges. As the field progresses, integrated and real-time volumetric analyses will become more commonplace, further integrating imaging with spine procedures. Intraoperative Augmented Reality and Mixed Reality The resurgence of AR, whose antecedents can be traced to Morton Heilig’s 1960s Sensorama, has been democratized by the ubiquity of contemporary smartphones, enabling real-world dig- ital data superimposition. 79 An example of this democratization is Google Glass, originally released in 2012. With its head-mounted display, voice control, and AR capabilities, Google Glass repre- sents a tangible manifestation of AR’s potential in enhancing how individuals interact with digital information, bridging the gap between the physical and digital realms. Such a concept quickly attracted the healthcare industry, but application by medical professionals encountered significant challenges due to limita- tions in display technology. Intraoperatively, once real-time patient imaging is captured, AR utilization can enable the overlay of digital data onto a pa- tient’s physical anatomy during surgery. Augmedics (Arlington Heights, Illinois, USA) developed the xVision Spine (XVS) system around 2014, introducing a combined navigation and AR system that can superimpose a 3D virtual image of a patient’s spine over the real anatomy and granting surgeons the capability to “see through” the patient’s body with digital guidance. After intensive trials, XVS became reality with the first FDA-approved AR-assis- ted spine surgery in June 2020 and has since gained popularity in operating rooms nationwide. 80 However, despite being radiation- free after the mobile CT scan is obtained and providing instant setup with any imaging, XVS has a low application range and poor long-segment navigation that is inadequate for complex spine surgery. An extension of AR, MR, or extended reality creates a similar environment, with the exception that physical and digital ele- ments can interact. In 2016, Microsoft (Redmond, Washington, USA) launched HoloLens, the first self-contained holographic computer that permitted users to interact with digital content seamlessly blended with their physical environment. Surgical teams such as Liebmann et al. incorporated HoloLens intra- operatively to place the guiding wire for pedicle screw insertion, establishing groundwork for further implementations. 81 Magic Leap One (Plantation, Florida, USA), first released in 2018, is a similar technology, although its high costs and limited field of vision have challenged its widespread implementation. Despite currently being less popular than their AR counterparts, MR and extended reality technologies warrant further investigation for their optimization in spinal procedures. Current State of the Art of Spatial Computing in Spine Surgery Overall, spatial computing has had revolutionary impact and still holds significant potential in spinal surgery. 82 AR has been incorporated into navigation-assisted spine surgery to ensure that instrument placement is optimal and risks to adjacent structures are minimized. Notably, these advancements have been integrated into both neurological and orthopedic proced- ures; in lumbar and cervical fusions, AR can be instrumental in guiding the precise placement of pedicle screws, with some studies showing up to 21% improvement in placement accuracy compared to free-hand techniques. 83 In discectomies, AR offers invaluable real-time visualization, assisting surgeons in discerning between the herniated disc and healthy tissue; in spinal tumor resections, AI offers potential in the differentiation between tumor and adjacent healthy tissue, while AR provides real-time guidance to ensure comprehensive tumor removal with minimal collateral damage; 84 in interbody fusions, AR can assist in identifying anatomical landmarks and facilitating surgical workflows. 85 Laminectomies may also benefit from AI and AR insights, which guide surgeons to limit bone and soft tissue removal. This real-time feedback has dramatically decreased the number of surgical errors while enhancing the overall safety of spine surgeries by reducing radiation and fluoroscopy usage. 86,87 Furthermore, the use of VR in preoperative planning has allowed surgeons to anticipate potential challenges that they might encounter during the procedure. By practicing in a simulated environment, they can refine their techniques, allowing for a smoother and more predictable surgical process 88 (Figure 4). Additional studies are needed to evaluate 6 www.SCIENCEDIRECT.com WORLD NEUROSURGERY, https://doi.org/10.1016/j.wneu.2025.124514 FROM THE ANNALS OF WEILL CORNELL NEUROLOGICAL SURGERY GALAL A. ELSAYED ET AL. SPATIAL COMPUTING FOUNDATIONS IN SPINE http://www.slicer.org http://www.slicer.org www.sciencedirect.com/science/journal/18788750 https://doi.org/10.1016/j.wneu.2025.124514 the effect of VR technology usage on patient outcomes. With AI augmentation, those who combine VR in the preoperative environment, AR in the intraoperative environment, and mobile native wearable integration platforms in the postoperative environment will define the future of spine surgery. CONCLUSIONS The trajectory of spinal surgery has witnessed a paradigmatic shift from its traditional reliance on tactile and visual cues to the integration of advanced technological tools. Spatial computing, incorporating the synergistic power of AR, VR, and AI, has her- alded a transformative era in the field. From early endeavors in image-guided surgery to sophisticated imageless navigation sys- tems and AR-assisted interventions, there has been a continuous endeavor to enhance precision, reduce complications, and improve patient outcomes. Notably, industry leaders and tech giants have responded dynamically to the evolving demands of spinal surgery, with numerous new systems standing as testa- ments to the unprecedented advancements in the field. Such technological leaps not only promote minimally invasive pro- cedures but also reflect a broader trend toward the intertwining of digital and physical worlds, optimizing patient-centric care and surgeon efficacy. The confluence of technological advancements and surgical innovation beckons an exciting future for spine surgery and emphasizes the continual pursuit of progress and most importantly, patient safety and high-quality care. CRediT AUTHORSHIP CONTRIBUTION STATEMENT Galal A. Elsayed: Conceptualization, Resources, Validation, Writing — review & editing. Gabrielle Dykhouse: Investigation, Writing — original draft. Chibuikem A. Ikwuegbuenyi: Writing — review & editing. Noah Willett: Writing — review & editing. Ibrahim Hussain: Writing — review & editing. Mousa Hamad: Writing — review & editing. Osama Nezar Kashlan: Writing — review & editing. Roger Härtl: Resources, Validation, Writing — review & editing. 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Conflict of interest statement: Dr. Roger Härtl is a consultant for Depuy Synthes, Brainlab, and Aclarion; receives research support from AOSpine, Nuvasive, and Brainlab; and invests in Realists and Onpoint. No other authors have any declaration of interest to include. Received 21 September 2025; accepted 22 September 2025 Citation: World Neurosurg. (2025) 204:124514. https://doi.org/10.1016/j.wneu.2025.124514 Journal homepage: www.journals.elsevier.com/world- neurosurgery Available online: www.sciencedirect.com 1878-8750/© 2025 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). WORLD NEUROSURGERY 204: 124514, DECEMBER 2025 www.journals.elsevier.com/world-neurosurgery 9 FROM THE ANNALS OF WEILL CORNELL NEUROLOGICAL SURGERY GALAL A. ELSAYED ET AL. 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Tracing the Historical Arc to Present Day Implementation Introduction Early Explorations and Pioneers The Beginnings of Imaging in Surgery Late 20th-Century Developments Modern-Day Implementations Overview of Intraoperative Imaging Modalities Intraoperative Imaging Devices Used in Spine Navigation Robotic Surgery Desktop-Based Preoperative Planning Virtual Reality–Based Preoperative Planning Radiology Protocols and Spatial Computing Intraoperative Augmented Reality and Mixed Reality Current State of the Art of Spatial Computing in Spine Surgery Conclusions flink5 References