Augmented Reality to Compensate for Navigation Inaccuracies

Frameless Stereotaxy in Stereoelectroencephalography Using Intraoperative Computed Tomography

Background: Pharmacoresistant epilepsy affects approximately one-third of all epilepsy patients, and resective surgery may offer favorable outcomes for carefully selected patients with focal epilepsy. The accurate identification of the epileptogenic zone (EZ) is essential for successful surgery, particularly in cases where non-invasive diagnostics are inconclusive. Invasive diagnostics with stereoelectroencephalography (SEEG) offer a reliable approach to localizing the EZ, especially in MRI-negative cases. Methods: This retrospective study analyzed the data of 22 patients with pharmacoresistant epilepsy who underwent frameless stereotactic SEEG electrode implantation with automated CT-based registration between September 2016 and November 2024. For measuring accuracy, Euclidean distance, radial deviation, angular deviation, and depth deviation were calculated for each electrode. Results: A total of 153 depth electrodes were implanted, targeting various cortical regions. The median Euclidean distance at the entry point was 1.54 mm (IQR 1.31), with a radial deviation of 1.33 mm (IQR 1.32). At the target level, the median Euclidean distance was 2.61 mm (IQR 1.53), with a radial deviation of 1.67 mm (IQR 1.54) and depth deviation of 0.95 mm (IQR 2.43). Accuracy was not significantly affected by electrode order, anatomical location, skull thickness, or intracranial length. Conclusions: These findings demonstrate that frameless stereotactic SEEG electrode implantation is safe and feasible for identifying the EZ. The integration of automatic intraoperative CT-based registration ensures precision. While maintaining workflow efficiency, it achieves accuracy comparable to frame-based methods. Further studies with larger cohorts are warranted to validate these results and assess their impact on surgical outcomes.

Computed tomography and structured light imaging guided orthopedic navigation puncture system: effective reduction of intraoperative image drift and mismatch

Background

Image-guided surgical navigation systems are widely regarded as the benchmark for computer-assisted surgical robotic platforms, yet a persistent challenge remains in addressing intraoperative image drift and mismatch. It can significantly impact the accuracy and precision of surgical procedures. Therefore, further research and development are necessary to mitigate this issue and enhance the overall performance of these advanced surgical platforms.

Objective

The primary objective is to improve the precision of image guided puncture navigation systems by developing a computed tomography (CT) and structured light imaging (SLI) based navigation system. Furthermore, we also aim to quantifying and visualize intraoperative image drift and mismatch in real time and provide feedback to surgeons, ensuring that surgical procedures are executed with accuracy and reliability.

Methods

A CT-SLI guided orthopedic navigation puncture system was developed. Polymer bandages are employed to pressurize, plasticize, immobilize and toughen the surface of a specimen for surgical operations. Preoperative CT images of the specimen are acquired, a 3D navigation map is reconstructed and a puncture path planned accordingly. During surgery, an SLI module captures and reconstructs the 3D surfaces of both the specimen and a guiding tube for the puncture needle. The SLI reconstructed 3D surface of the specimen is matched to the CT navigation map via two-step point cloud registrations, while the SLI reconstructed 3D surface of the guiding tube is fitted by a cylindrical model, which is in turn aligned with the planned puncture path. The proposed system has been tested and evaluated using 20 formalin-soaked lower limb cadaver specimens preserved at a local hospital.

Results

The proposed method achieved image registration RMS errors of 0.576 ± 0.146 mm and 0.407 ± 0.234 mm between preoperative CT and intraoperative SLI surface models and between preoperative and postoperative CT surface models. In addition, preoperative and postoperative specimen surface and skeletal drifts were 0.033 ± 0.272 mm and 0.235 ± 0.197 mm respectively.

Conclusion

The results indicate that the proposed method is effective in reducing intraoperative image drift and mismatch. The system also visualizes intraoperative image drift and mismatch, and provides real time visual feedback to surgeons.

Augmented Reality in Extratemporal Lobe Epilepsy Surgery

Background: Epilepsy surgery for extratemporal lobe epilepsy (ETLE) is challenging, particularly when MRI findings are non-lesional and seizure patterns are complex. Invasive diagnostic techniques are crucial for accurately identifying the epileptogenic zone and its relationship with surrounding functional tissue. Microscope-based augmented reality (AR) support, combined with navigation, may enhance intraoperative orientation, particularly in cases involving subtle or indistinct lesions, thereby improving patient outcomes and safety (e.g., seizure freedom and preservation of neuronal integrity). Therefore, this study was conducted to prove the clinical advantages of microscope-based AR support in ETLE surgery. Methods: We retrospectively analyzed data from ten patients with pharmacoresistant ETLE who underwent invasive diagnostics with depth and/or subdural grid electrodes, followed by resective surgery. AR support was provided via the head-up displays of the operative microscope, with navigation based on automatic intraoperative computed tomography (iCT)-based registration. The surgical plan included the suspected epileptogenic lesion, electrode positions, and relevant surrounding functional structures, all of which were visualized intraoperatively. Results: Six patients reported complete seizure freedom following surgery (ILAE 1), one patient was seizure-free at the 2-year follow-up, and one patient experienced only auras (ILAE 2). Two patients developed transient neurological deficits that resolved shortly after surgery. Conclusions: Microscope-based AR support enhanced intraoperative orientation in all cases, contributing to improved patient outcomes and safety. It was highly valued by experienced surgeons and as a training tool for less experienced practitioners.

Enhancing Surgical Approach: Breakthrough Markerless Surface Registration With Augmented Reality for Zygomatic Complex Fracture Surgeries

BACKGROUND

Innovative technologies with surgical navigation have been used for enhancing surgical accuracies for zygomaticomaxillary complex (ZMC) fractures and offers advantages in precision, accuracy, effectiveness, predictability, and symmetry improvement. Moreover, augmented reality (AR) navigation technology combines virtual reality, 3-dimensional (3D) reconstruction, and real-time interaction, making it ideal for bone tissue operations. Our study explored the usefulness and clinical efficacy of AR technology in intraoperative guidance for reducing ZMC fractures.

METHODS

We retrospectively studied 35 patients with zygomatic complex fractures, comparing outcomes of AR-guided and conventional methods. Furthermore, the AR system provided real-time visualization and guidance. The evaluation included reduction accuracy using root mean square (RMS) value and symmetry analysis using a mirror image of 3D models. Results demonstrated the feasibility and effectiveness of the AR-guided method in improving outcomes and patient satisfaction.

RESULTS

In 35 patients (25 males, 10 females), AR-guided (n = 19) and conventional (n = 16) approaches were compared. Age, sex, and fracture type exhibited no significant differences between groups. No complications occurred, and postoperative RMS error significantly decreased ( P < 0.001). The AR group had a lower postoperative RMS error ( P = 0.034).

CONCLUSIONS

Augmented reality-guided surgery improved accuracy and outcomes in zygomatic complex fractures. Real-time visualization enhanced precision during reduction and fixation. This innovative approach promises enhanced surgical accuracy and patient outcomes in craniofacial surgery.

Head model dataset for mixed reality navigation in neurosurgical interventions for intracranial lesions

Mixed reality navigation (MRN) technology is emerging as an increasingly significant and interesting topic in neurosurgery. MRN enables neurosurgeons to "see through" the head with an interactive, hybrid visualization environment that merges virtual- and physical-world elements. Offering immersive, intuitive, and reliable guidance for preoperative and intraoperative intervention of intracranial lesions, MRN showcases its potential as an economically efficient and user-friendly alternative to standard neuronavigation systems. However, the clinical research and development of MRN systems present challenges: recruiting a sufficient number of patients within a limited timeframe is difficult, and acquiring low-cost, commercially available, medically significant head phantoms is equally challenging. To accelerate the development of novel MRN systems and surmount these obstacles, the study presents a dataset designed for MRN system development and testing in neurosurgery. It includes CT and MRI data from 19 patients with intracranial lesions and derived 3D models of anatomical structures and validation references. The models are available in Wavefront object (OBJ) and Stereolithography (STL) formats, supporting the creation and assessment of neurosurgical MRN applications.

Enabling Navigation and Augmented Reality in the Sitting Position in Posterior Fossa Surgery Using Intraoperative Ultrasound

Despite its broad use in cranial and spinal surgery, navigation support and microscope-based augmented reality (AR) have not yet found their way into posterior fossa surgery in the sitting position. While this position offers surgical benefits, navigation accuracy and thereof the use of navigation itself seems limited. Intraoperative ultrasound (iUS) can be applied at any time during surgery, delivering real-time images that can be used for accuracy verification and navigation updates. Within this study, its applicability in the sitting position was assessed. Data from 15 patients with lesions within the posterior fossa who underwent magnetic resonance imaging (MRI)-based navigation-supported surgery in the sitting position were retrospectively analyzed using the standard reference array and new rigid image-based MRI-iUS co-registration. The navigation accuracy was evaluated based on the spatial overlap of the outlined lesions and the distance between the corresponding landmarks in both data sets, respectively. Image-based co-registration significantly improved (p < 0.001) the spatial overlap of the outlined lesion (0.42 ± 0.30 vs. 0.65 ± 0.23) and significantly reduced (p < 0.001) the distance between the corresponding landmarks (8.69 ± 6.23 mm vs. 3.19 ± 2.73 mm), allowing for the sufficient use of navigation and AR support. Navigated iUS can therefore serve as an easy-to-use tool to enable navigation support for posterior fossa surgery in the sitting position.

The Feasibility and Accuracy of Holographic Navigation with Laser Crosshair Simulator Registration on a Mixed-Reality Display

Addressing conventional neurosurgical navigation systems' high costs and complexity, this study explores the feasibility and accuracy of a simplified, cost-effective mixed reality navigation (MRN) system based on a laser crosshair simulator (LCS). A new automatic registration method was developed, featuring coplanar laser emitters and a recognizable target pattern. The workflow was integrated into Microsoft's HoloLens-2 for practical application. The study assessed the system's precision by utilizing life-sized 3D-printed head phantoms based on computed tomography (CT) or magnetic resonance imaging (MRI) data from 19 patients (female/male: 7/12, average age: 54.4 ± 18.5 years) with intracranial lesions. Six to seven CT/MRI-visible scalp markers were used as reference points per case. The LCS-MRN's accuracy was evaluated through landmark-based and lesion-based analyses, using metrics such as target registration error (TRE) and Dice similarity coefficient (DSC). The system demonstrated immersive capabilities for observing intracranial structures across all cases. Analysis of 124 landmarks showed a TRE of 3.0 ± 0.5 mm, consistent across various surgical positions. The DSC of 0.83 ± 0.12 correlated significantly with lesion volume (Spearman rho = 0.813, p < 0.001). Therefore, the LCS-MRN system is a viable tool for neurosurgical planning, highlighting its low user dependency, cost-efficiency, and accuracy, with prospects for future clinical application enhancements.

A Novel Registration Method for a Mixed Reality Navigation System Based on a Laser Crosshair Simulator: A Technical Note

Mixed Reality Navigation (MRN) is pivotal in augmented reality-assisted intelligent neurosurgical interventions. However, existing MRN registration methods face challenges in concurrently achieving low user dependency, high accuracy, and clinical applicability. This study proposes and evaluates a novel registration method based on a laser crosshair simulator, evaluating its feasibility and accuracy. A novel registration method employing a laser crosshair simulator was introduced, designed to replicate the scanner frame's position on the patient. The system autonomously calculates the transformation, mapping coordinates from the tracking space to the reference image space. A mathematical model and workflow for registration were designed, and a Universal Windows Platform (UWP) application was developed on HoloLens-2. Finally, a head phantom was used to measure the system's target registration error (TRE). The proposed method was successfully implemented, obviating the need for user interactions with virtual objects during the registration process. Regarding accuracy, the average deviation was 3.7 ± 1.7 mm. This method shows encouraging results in efficiency and intuitiveness and marks a valuable advancement in low-cost, easy-to-use MRN systems. The potential for enhancing accuracy and adaptability in intervention procedures positions this approach as promising for improving surgical outcomes.