Current accuracy of surface matching compared to adhesive markers in patient-to-image registration

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.

Targeting accuracy of neuronavigation: a comparative evaluation of an innovative wearable AR platform vs. traditional EM navigation

Wearable augmented reality in neurosurgery offers significant advantages by enabling the visualization of navigation information directly on the patient, seamlessly integrating virtual data with the real surgical field. This ergonomic approach can facilitate a more intuitive understanding of spatial relationships and guidance cues, potentially reducing cognitive load and enhancing the accuracy of surgical gestures by aligning critical information with the actual anatomy in real-time. This study evaluates the benefits of a novel AR platform, VOSTARS, by comparing its targeting accuracy to that of the gold-standard electromagnetic (EM) navigation system, Medtronic StealthStation® S7®. Both systems were evaluated in phantom and human studies. In the phantom study, participants targeted 13 predefined landmarks using identical pointers to isolate system performance. In the human study, three facial landmarks were targeted in nine volunteers post-brain tumor surgery. The performance of the VOSTARS system was superior to that of the standard neuronavigator in both the phantom and human studies. In the phantom study, users achieved a median accuracy of 1.4 mm (IQR: 1.2 mm) with VOSTARS compared to 2.9 mm (IQR: 1.4 mm) with the standard neuronavigator. In the human study, the median targeting accuracy with VOSTARS was significantly better for selected landmarks in the outer eyebrow (3.7 mm vs. 6.6 mm, p = 0.05) and forehead (4.5 mm vs. 6.3 mm, p = 0.021). Although the difference for the pronasal point was not statistically significant (2.7 mm vs. 3.5 mm, p = 0.123), the trend towards improved accuracy with VOSTARS is clear. These findings suggest that the proposed AR technology has the potential to significantly improve surgical outcomes in neurosurgery.

Comparative analysis of intraoperative thermal and optical imaging for identification of the human primary sensory cortex

Significance

The precise identification and preservation of functional brain areas during neurosurgery are crucial for optimizing surgical outcomes and minimizing postoperative deficits. Intraoperative imaging plays a vital role in this context, offering insights that guide surgeons in protecting critical cortical regions.

Aim

We aim to evaluate and compare the efficacy of intraoperative thermal imaging (ITI) and intraoperative optical imaging (IOI) in detecting the primary somatosensory cortex, providing a detailed assessment of their potential integration into surgical practice.

Approach

Data from nine patients undergoing tumor resection in the region of the somatosensory cortex were analyzed. Both IOI and ITI were employed simultaneously, with a specific focus on the areas identified as the primary somatosensory cortex (S1 region). The methodologies included a combination of imaging techniques during distinct phases of rest and stimulation, confirmed by electrophysiological monitoring of somatosensory evoked potentials to verify the functional areas identified by both imaging methods. The data were analyzed using a Fourier-based analytical framework to distinguish physiological signals from background noise.

Results

Both ITI and IOI successfully generated reliable activity maps following median nerve stimulation. IOI showed greater consistency across various clinical scenarios, including those involving cortical tumors. Quantitative analysis revealed that IOI could more effectively differentiate genuine neuronal activity from artifacts compared with ITI, which was occasionally prone to false positives in the presence of cortical abnormalities.

Conclusions

ITI and IOI produce comparable functional maps with moderate agreement in Cohen's kappa values. Their distinct physiological mechanisms suggest complementary use in specific clinical scenarios, such as cortical tumors or impaired neurovascular coupling. IOI excels in spatial resolution and mapping reliability, whereas ITI provides additional insights into metabolic changes and tissue properties, especially in pathological areas. Combined, these modalities could enhance the understanding and analysis of functional and pathological processes in complex neurosurgical cases.

MRI free targeting of deep brain structures based on facial landmarks

Emerging neurostimulation methods aim to selectively modulate deep brain structures. Guiding these therapies has presented a substantial challenge, since imaging modalities such as MRI limit the spectrum of beneficiaries. In this study, we assess the guidance accuracy of a neuronavigation method that does not require taking MRI scans. The method is based on clearly identifiable anatomical landmarks of each subject's face. We compared this technique to the ideal case, MRI-based nonlinear brain registration, and evaluated the accuracy of both methods across ten targets located in deep brain structures: 7 targets in the anterior cingulate cortex as well as the anterior commissure and posterior commissure. Compared with the ideal case, the average localization error of the MRI-free method was 5.75 ± 2.98 mm (mean ± sd). These findings suggest that this method may provide sufficient compromise between practicality and the accuracy of targeting deep brain structures.

Noctopus: a novel device and method for patient registration and navigation in image-guided cranial surgery

PURPOSE

A patient registration and real-time surgical navigation system and a novel device and method (Noctopus) is presented. With any tracking system technology and a patient/target-specific registration marker configuration, submillimetric target registration error (TRE), high-precise application accuracy for single or multiple anatomical targets in image-guided neurosurgery or ENT surgery is realized.

METHODS

The system utilizes the advantages of marker-based registration technique and allows to perform automatized patient registration using on the device attached and with patient scanned four fiducial markers. The best possible sensor/marker positions around the patient's head are determined for single or multiple region(s) of interest (target/s) in the anatomy. Once brought at the predetermined positions the device can be operated with any tracking system for registration purposes.

RESULTS

Targeting accuracy was evaluated quantitatively at various target positions on a phantom skull. The target registration error (TRE) was measured on individual targets using an electromagnetic tracking system. The overall averaged TRE was 0.22 ± 0.08 mm for intraoperative measurements.

CONCLUSION

An automatized patient registration system using optimized patient-/target-specific marker configurations is proposed. High-precision and user-error-free intraoperative surgical navigation with minimum number of registration markers and sensors is realized. The targeting accuracy is significantly improved in minimally invasive neurosurgical and ENT interventions.

Automatic Image Registration Provides Superior Accuracy Compared with Surface Matching in Cranial Navigation

OBJECTIVE

The precision of neuronavigation systems relies on the correct registration of the patient's position in space and aligning it with radiological 3D imaging data. Registration is usually performed by the acquisition of anatomical landmarks or surface matching based on facial features. Another possibility is automatic image registration using intraoperative imaging. This could provide better accuracy, especially in rotated or prone positions where the other methods may be difficult to perform. The aim of this study was to validate automatic image registration (AIR) using intraoperative cone-beam computed tomography (CBCT) for cranial neurosurgical procedures and compare the registration accuracy to the traditional surface matching (SM) registration method based on preoperative MRI. The preservation of navigation accuracy throughout the surgery was also investigated.

METHODS

Adult patients undergoing intracranial tumor surgery were enrolled after consent. A standard SM registration was performed, and reference points were acquired. An AIR was then performed, and the same reference points were acquired again. Accuracy was calculated based on the referenced and acquired coordinates of the points for each registration method. The reference points were acquired before and after draping and at the end of the procedure to assess the persistency of accuracy.

RESULTS

In total, 22 patients were included. The mean accuracy was 6.6 ± 3.1 mm for SM registration and 1.0 ± 0.3 mm for AIR. The AIR was superior to the SM registration (p < 0.0001), with a mean improvement in accuracy of 5.58 mm (3.71-7.44 mm 99% CI). The mean accuracy for the AIR registration pre-drape was 1.0 ± 0.3 mm. The corresponding accuracies post-drape and post-resection were 2.9 ± 4.6 mm and 4.1 ± 4.9 mm, respectively. Although a loss of accuracy was identified between the preoperative and end-of-procedure measurements, there was no statistically significant decline during surgery.

CONCLUSIONS

AIR for cranial neuronavigation consistently delivered greater accuracy than SM and should be considered the new gold standard for patient registration in cranial neuronavigation. If intraoperative imaging is a limited resource, AIR should be prioritized in rotated or prone position procedures, where the benefits are the greatest.

The 3-Dimensional Intelligent Structured Light Technique: A New Registration Method in Stereotactic Neurosurgery

BACKGROUND AND OBJECTIVES

Surface-based facial scanning registration emerged as an essential registration method in the robot-assisted neuronavigation surgery, providing a marker-free way to align a patient's facial surface with the imaging data. The 3-dimensional (3D) structured light was developed as an advanced registration method based on surface-based facial scanning registration. We aspire to introduce the 3D structured light as a new registration method in the procedure of the robot-assisted neurosurgery and assess the accuracy, efficiency, and safety of this method by analyzing the relative operative results.

METHODS

We analyzed the results of 47 patients who underwent Ommaya reservoir implantation (n = 17) and stereotactic biopsy (n = 30) assisted by 3D structured light at our hospital from January 2022 to May 2023. The accuracy and additional operative results were analyzed.

RESULTS

For the Ommaya reservoir implantation, the target point error was 3.2 ± 2.2 mm and the entry point error was 3.3 ± 2.4 mm, while the operation duration was 35.8 ± 8.3 minutes. For the stereotactic biopsy, the target point error was 2.3 ± 1.3 mm and the entry point error was 2.7 ± 1.2 mm, while the operation duration was 24.5 ± 6.3 minutes.

CONCLUSION

The 3D structured light technique reduces the patients' discomfort and offers the advantage of a simpler procedure, which can improve the clinical efficiency with the sufficient accuracy and safety to meet the clinical requirements of the puncture and navigation.

Surgical technique of 3D computer-assisted navigated posterior fixation of the upper cervical spine: illustration of three cases

Instrumentation of the upper cervical spine, such as cervical pedicle, lateral mass, pars, or translaminar screws, is considered high risk due to the specific challenges of this anatomic region, including the proximity of vertebral and carotid arteries and nerve roots, as well as its delicate bony architecture. In recent years, advanced three-dimensional (3D) imaging techniques, such as intraoperative computed tomography (iCT; AIRO CT), have emerged, enabling computer-assisted navigation (CAN). This integration of real-time imaging into navigation enhances screw accuracy and diminishes perioperative risks, extending to the postsurgical confirmation of screw placement. Although CAN utilization has become more prominent in lumbar and thoracic surgeries, its integration into cervical spine procedures has been constrained thus far. This can be ascribed to the variable screw trajectories necessary for cervical spine procedures, coupled with potential anatomical variations such as a high-riding vertebral artery, increasing the degree of challenge during surgery. To date, no study has comprehensively described in detail the technique of upper cervical instrumentation employing automatic image registration, navigation, and iCT validation of the positioned screws. In this manuscript, a detailed description of CAN in high cervical instrumentation is given, including C1 lateral mass screws with the notching technique, C2 and C3 pars screws, and translaminar screws guided by preoperative magnetic resonance imaging (MRI) data and iCT for assessment of screw position. For this purpose, three different patients suffering from distinct cervical pathologies, such as nonunion of a C2 fracture and atlantoaxial arthropathy with or without ankylosis, are presented, with a specific surgical approach tailored to the anatomical variations of each patient.

Deep Learning-Based Fine-Tuning Approach of Coarse Registration for Ear-Nose-Throat (ENT) Surgical Navigation Systems

Accurate registration between medical images and patient anatomy is crucial for surgical navigation systems in minimally invasive surgeries. This study introduces a novel deep learning-based refinement step to enhance the accuracy of surface registration without disrupting established workflows. The proposed method integrates a machine learning model between conventional coarse registration and ICP fine registration. A deep-learning model was trained using simulated anatomical landmarks with introduced localization errors. The model architecture features global feature-based learning, an iterative prediction structure, and independent processing of rotational and translational components. Validation with silicon-masked head phantoms and CT imaging compared the proposed method to both conventional registration and a recent deep-learning approach. The results demonstrated significant improvements in target registration error (TRE) across different facial regions and depths. The average TRE for the proposed method (1.58 ± 0.52 mm) was significantly lower than that of the conventional (2.37 ± 1.14 mm) and previous deep-learning (2.29 ± 0.95 mm) approaches (p < 0.01). The method showed a consistent performance across various facial regions and enhanced registration accuracy for deeper areas. This advancement could significantly enhance precision and safety in minimally invasive surgical procedures.

Template Routed Patient-Specific Implant for 1-Stage Cranioplasty

BACKGROUND AND OBJECTIVES

Cranial reconstruction presents a significant challenge in cases involving pathologies with skull invasion, and various techniques have been used, including the intraoperative shaping of titanium mesh and the manual sculpting of bone cement serving as surrogates for the excised bone graft. In the context of prefabricated patient-specific implants (PSIs) for cranioplasty, precise surgical execution of craniotomies is paramount. This ensures optimal congruity between the implant and the defect created during the craniotomy, leading to a successful single-stage procedure encompassing both bone removal and reconstruction. This article presents a meticulous method for achieving such high-fidelity craniotomy and subsequent cranioplasty using PSIs in a single-stage surgery.

METHODS

The procedure was implemented for 2 cases of meningiomas with osseous invasion. Through meticulous preoperative planning, the craniotomy template and implant were designed using computer-assisted design and manufactured on a 3-dimensional printer using the patient's computed tomography scans. Intraoperative fabrication of sterile polymethyl methacrylate replicas was achieved through the creation of silicone molds and subsequent injection molding techniques. Predesignated screw holes facilitated neuronavigation-assisted positioning of the template, aligning it accurately with the target site using registration points. Mini-screws firmly secured the template to the skull. Guided by the template, a craniotomy router performed the bone resection. On completion, the implant was affixed into place using plates and screws.

RESULTS

This technique demonstrably facilitated a cost-effective, streamlined and precise application of prefabricated PSIs within a single-stage craniotomy-cranioplasty procedure. Subjective patient reports indicated high levels of satisfaction with the outcome.

CONCLUSION

The template routed patient-specific implant 1-stage cranioplasty technique refines previous approaches through precise template localization on the skull, enabling an accurate craniotomy to match a prefabricated PSI. This single-stage procedure rivals hand-shaped methods in aesthetics and compares with the outcomes of 2-stage PSI cranioplasties. Additional studies are needed to validate our results.

Mixed Reality Surgical Navigation System; Positional Accuracy Based on Food and Drug Administration Standard

BACKGROUND

Computer assisted surgical navigation systems are designed to improve outcomes by providing clinicians with procedural guidance information. The use of new technologies, such as mixed reality, offers the potential for more intuitive, efficient, and accurate procedural guidance. The goal of this study is to assess the positional accuracy and consistency of a clinical mixed reality system that utilizes commercially available wireless head-mounted displays (HMDs), custom software, and localization instruments.

METHODS

Independent teams using the second-generation Microsoft HoloLens© hardware, Medivis SurgicalAR© software, and localization instruments, tested the accuracy of the combined system at different institutions, times, and locations. The ASTM F2554-18 consensus standard for computer-assisted surgical systems, as recognized by the U.S. FDA, was utilized to measure the performance. 288 tests were performed.

RESULTS

The system demonstrated consistent results, with an average accuracy performance that was better than one millimeter (.75 ± SD .37 mm).

CONCLUSION

Independently acquired positional tracking accuracies exceed conventional in-market surgical navigation tracking systems and FDA standards. Importantly, the performance was achieved at two different institutions, using an international testing standard, and with a system that included a commercially available off-the-shelf wireless head mounted display and software.

Augmented Reality in Neurosurgery

Augmented Reality (AR) involves superimposing digital content onto the real environment. AR has evolved into a viable tool in neurosurgery, enhancing intraoperative navigation, medical education and surgical training by integrating anatomical data with the real world. Neurosurgical AR relies on several key techniques to be successful, which includes image segmentation, model rendering, AR projection, and image-to-patient registration. For each of these technical components, different solutions exist, with each having their own advantages and limitations.Intraoperative AR applications cover diverse neurosurgical disciplines including vascular, oncological, spinal, and functional surgeries. Preliminary studies indicate that AR may improve the understanding of complex anatomical structures and offer sufficient accuracy for use as a navigational tool. Additionally, AR shows promise in enhancing surgical training and patient education through interactive 3D models, aiding in the comprehension of intricate anatomical details. Despite its potential, the widespread adoption of AR in clinical settings depends on overcoming technical limitations and validating its clinical efficacy.

Image-guidance in endoscopic pituitary surgery: an in-silico study of errors involved in tracker-based techniques

Background

Endoscopic endonasal surgery is an established minimally invasive technique for resecting pituitary adenomas. However, understanding orientation and identifying critical neurovascular structures in this anatomically dense region can be challenging. In clinical practice, commercial navigation systems use a tracked pointer for guidance. Augmented Reality (AR) is an emerging technology used for surgical guidance. It can be tracker based or vision based, but neither is widely used in pituitary surgery.

Methods

This pre-clinical study aims to assess the accuracy of tracker-based navigation systems, including those that allow for AR. Two setups were used to conduct simulations: (1) the standard pointer setup, tracked by an infrared camera; and (2) the endoscope setup that allows for AR, using reflective markers on the end of the endoscope, tracked by infrared cameras. The error sources were estimated by calculating the Euclidean distance between a point's true location and the point's location after passing it through the noisy system. A phantom study was then conducted to verify the in-silico simulation results and show a working example of image-based navigation errors in current methodologies.

Results

The errors of the tracked pointer and tracked endoscope simulations were 1.7 and 2.5 mm respectively. The phantom study showed errors of 2.14 and 3.21 mm for the tracked pointer and tracked endoscope setups respectively.

Discussion

In pituitary surgery, precise neighboring structure identification is crucial for success. However, our simulations reveal that the errors of tracked approaches were too large to meet the fine error margins required for pituitary surgery. In order to achieve the required accuracy, we would need much more accurate tracking, better calibration and improved registration techniques.

Assessment of Accuracy of Mixed Reality Device for Neuronavigation: Proposed Methodology and Results

Intraoperative neuronavigation is currently an essential component of neurosurgical operations in several contexts. Recent progress in mixed reality (MR) technology has attempted to overcome the disadvantages of standard neuronavigation systems allowing the surgeon to superimpose a 3D rendered image onto the patient's anatomy. We present the first study in the literature to assess the surface matching accuracy of MR rendered image. For the purposes of this study, we used HoloLens 2 with virtual surgery intelligence providing the software capability for image rendering. To assess the accuracy of using mixed reality device for neuronavigation intraoperatively. This study seeks to assess the accuracy of rendered holographic images from a mixed reality device as a means for neuronavigation intraoperatively. We used the Realistic Operative Workstation for Educating Neurosurgical Apprentices to represent a patient's skull with intracranial components which underwent standardized computed tomography (CT) and MRI imaging. Eleven predefined points were used for purposes of assessing the accuracy of the rendered image, compared with the intraoperative gold standard neuronavigation. The mean HoloLens values against the ground truth were significantly higher when compared with Stealth using CT scan as the imaging modality. Using extracranial anatomic landmarks, the HoloLens error values continued to be significantly higher in magnitude when compared with Stealth across CT and MRI. This study provides a relatively easy and feasible method to assess accuracy of MR-based navigation without requiring any additions to the established imaging protocols. We failed to show the equivalence of MR-based navigation over the current neuronavigation systems.

Influence of surgical position and registration methods on clinical accuracy of navigation systems in brain tumor surgery

The aim of this study was to evaluate the influence of skin distortion due to surgical positioning on the clinical accuracy of the navigation system. The distance errors were measured in four fiducial markers (anterior, posterior, right, and left of the head) after the registration of the navigation system. The distance errors were compared between the surface-merge registration (SMR) method using preoperative imaging and the automatic intraoperative registration (AIR) method using intraoperative imaging. The comparison of the distance errors were performed in various surgical positions. The AIR method had the significant accuracy in the lateral markers than the SMR method (lateral position, 3.8 mm vs. 8.95 mm; p < 0.0001; prone position, 4.5 mm vs. 13.9 mm; p = 0.0001; 5.2 mm vs. 11.5 mm; p = 0.0070). The smallest distance errors were obtained close to the surgical field in the AIR method (3.25-3.85 mm) and in the forehead in the SMR method (3.3-8.1 mm). The AIR method was accurate and recommended for all the surgical positions if intraoperative imaging was available. The SMR method was only recommended for the supine position, because skin distortion was frequently observed in the lateral region.

Development of an ultrafast brain MR neuronavigation protocol for ventricular shunt placement

OBJECTIVE

Advancements in MRI technology have provided improved ways to acquire imaging data and to more seamlessly incorporate MRI into modern pediatric surgical practice. One such situation is image-guided navigation for pediatric neurosurgical procedures, including intracranial catheter placement. Image-guided surgery (IGS) requires acquisition of CT or MR images, but the former carries the risk of ionizing radiation and the latter is associated with long scan times and often requires pediatric patients to be sedated. The objective of this project was to circumvent the use of CT and standard-sequence MRI in ventricular neuronavigation by investigating the use of fast MR sequences on the basis of 3 criteria: scan duration comparable to that of CT acquisition, visualization of ventricular morphology, and image registration with surface renderings comparable to standard of care. The aim of this work was to report image development, implementation, and results of registration accuracy testing in healthy subjects.

METHODS

The authors formulated 11 candidate MR sequences on the basis of the standard IGS protocol, and various scan parameters were modified, such as k-space readout direction, partial k-space acquisition, sparse sampling of k-space (i.e., compressed sensing), in-plane spatial resolution, and slice thickness. To evaluate registration accuracy, the authors calculated target registration error (TRE). A candidate sequence was selected for further evaluation in 10 healthy subjects.

RESULTS

The authors identified a candidate imaging protocol, termed presurgical imaging with compressed sensing for time optimization (PICO). Acquisition of the PICO protocol takes 25 seconds. The authors demonstrated noninferior TRE for PICO (3.00 ± 0.19 mm) in comparison with the default MRI neuronavigation protocol (3.35 ± 0.20 mm, p = 0.20).

CONCLUSIONS

The developed and tested sequence of this work allowed accurate intraoperative image registration and provided sufficient parenchymal contrast for visualization of ventricular anatomy. Further investigations will evaluate use of the PICO protocol as a substitute for CT and conventional MRI protocols in ventricular neuronavigation.

Use of Mixed Reality in Neuro-Oncology: A Single Centre Experience

(1) Background: Intra-operative neuronavigation is currently an essential component to most neurosurgical operations. Recent progress in mixed reality (MR) technology has attempted to overcome the disadvantages of the neuronavigation systems. We present our experience using the HoloLens 2 in neuro-oncology for both intra- and extra-axial tumours. (2) Results: We describe our experience with three patients who underwent tumour resection. We evaluated surgeon experience, accuracy of superimposed 3D image in tumour localisation with standard neuronavigation both pre- and intra-operatively. Surgeon training and usage for HoloLens 2 was short and easy. The process of image overlay was relatively straightforward for the three cases. Registration in prone position with a conventional neuronavigation system is often difficult, which was easily overcome during use of HoloLens 2. (3) Conclusion: Although certain limitations were identified, the authors feel that this system is a feasible alternative device for intra-operative visualization of neurosurgical pathology. Further studies are being planned to assess its accuracy and suitability across various surgical disciplines.

Augmented Reality to Compensate for Navigation Inaccuracies

This study aims to report on the capability of microscope-based augmented reality (AR) to evaluate registration and navigation accuracy with extracranial and intracranial landmarks and to elaborate on its opportunities and obstacles in compensation for navigation inaccuracies. In a consecutive single surgeon series of 293 patients, automatic intraoperative computed tomography-based registration was performed delivering a high initial registration accuracy with a mean target registration error of 0.84 ± 0.36 mm. Navigation accuracy is evaluated by overlaying a maximum intensity projection or pre-segmented object outlines within the recent focal plane onto the in situ patient anatomy and compensated for by translational and/or rotational in-plane transformations. Using bony landmarks (85 cases), there was two cases where a mismatch was seen. Cortical vascular structures (242 cases) showed a mismatch in 43 cases and cortex representations (40 cases) revealed two inaccurate cases. In all cases, with detected misalignment, a successful spatial compensation was performed (mean correction: bone (6.27 ± 7.31 mm), vascular (3.00 ± 1.93 mm, 0.38° ± 1.06°), and cortex (5.31 ± 1.57 mm, 1.75° ± 2.47°)) increasing navigation accuracy. AR support allows for intermediate and straightforward monitoring of accuracy, enables compensation of spatial misalignments, and thereby provides additional safety by increasing overall accuracy.

Surgical Navigation System for Hypertensive Intracerebral Hemorrhage Based on Mixed Reality

Hypertensive intracerebral hemorrhage (HICH) is an intracerebral bleeding disease that affects 2.5 per 10,000 people worldwide each year. An effective way to cure this disease is puncture through the dura with a brain puncture drill and tube; the accuracy of the insertion determines the quality of the surgery. In recent decades, surgical navigation systems have been widely used to improve the accuracy of surgery and minimize risks. Augmented reality- and mixed reality-based surgical navigation is a promising new technology for surgical navigation in the clinic, aiming to improve the safety and accuracy of the operation. In this study, we present a novel multimodel mixed reality navigation system for HICH surgery in which medical images and virtual anatomical structures can be aligned intraoperatively with the actual structures of the patient in a head-mounted device and adjusted when the patient moves in real time while under local anesthesia; this approach can help the surgeon intuitively perform intraoperative navigation. A novel registration method is used to register the holographic space and serves as an intraoperative optical tracker, and a method for calibrating the HICH surgical tools is used to track the tools in real time. The results of phantom experiments revealed a mean registration error of 1.03 mm and an average time consumption of 12.9 min. In clinical usage, the registration error was 1.94 mm, and the time consumption was 14.2 min, showing that this system is sufficiently accurate and effective for clinical application.

The application of augmented reality-based navigation for accurate target acquisition of deep brain sites: advances in neurosurgical guidance

OBJECTIVE

The objective of this study is to quantify the navigational accuracy of an advanced augmented reality (AR)-based guidance system for neurological surgery, biopsy, and/or other minimally invasive neurological surgical procedures.

METHODS

Five burr holes were drilled through a plastic cranium, and 5 optical fiducials (AprilTags) printed with CT-visible ink were placed on the frontal, temporal, and parietal bones of a human skull model. Three 0.5-mm-diameter targets were mounted in the interior of the skull on nylon posts near the level of the tentorium cerebelli and the pituitary fossa. The skull was filled with ballistic gelatin to simulate brain tissue. A CT scan was taken and virtual needle tracts were annotated on the preoperative 3D workstation for the combination of 3 targets and 5 access holes (15 target tracts). The resulting annotated study was uploaded to and launched by VisAR software operating on the HoloLens 2 holographic visor by viewing an encrypted, printed QR code assigned to the study by the preoperative workstation. The DICOM images were converted to 3D holograms and registered to the skull by alignment of the holographic fiducials with the AprilTags attached to the skull. Five volunteers, familiar with the VisAR, used the software/visor combination to navigate an 18-gauge needle/trocar through the series of burr holes to the target, resulting in 70 data points (15 for 4 users and 10 for 1 user). After each attempt the needle was left in the skull, supported by the ballistic gelatin, and a high-resolution CT was taken. Radial error and angle of error were determined using vector coordinates. Summary statistics were calculated individually and collectively.

RESULTS

The combined angle of error of was 2.30° ± 1.28°. The mean radial error for users was 3.62 ± 1.71 mm. The mean target depth was 85.41 mm.

CONCLUSIONS

The mean radial error and angle of error with the associated variance measures demonstrates that VisAR navigation may have utility for guiding a small needle to neural lesions, or targets within an accuracy of 3.62 mm. These values are sufficiently accurate for the navigation of many neurological procedures such as ventriculostomy.

High-density single-unit human cortical recordings using the Neuropixels probe

The action potential is a fundamental unit of neural computation. Even though significant advances have been made in recording large numbers of individual neurons in animal models, translation of these methodologies to humans has been limited because of clinical constraints and electrode reliability. Here, we present a reliable method for intraoperative recording of dozens of neurons in humans using the Neuropixels probe, yielding up to ∼100 simultaneously recorded single units. Most single units were active within 1 min of reaching target depth. The motion of the electrode array had a strong inverse correlation with yield, identifying a major challenge and opportunity to further increase the probe utility. Cell pairs active close in time were spatially closer in most recordings, demonstrating the power to resolve complex cortical dynamics. Altogether, this approach provides access to population single-unit activity across the depth of human neocortex at scales previously only accessible in animal models.

Facial landmark-guided surface matching for image-to-patient registration with an RGB-D camera

BACKGROUND

Fiducial marker-based image-to-patient registration is the most common way in image-guided neurosurgery, which is labour-intensive, time consuming, invasive and error prone.

METHODS

We proposed a method of facial landmark-guided surface matching for image-to-patient registration using an RGB-D camera. Five facial landmarks are localised from preoperative magnetic resonance (MR) images using deep learning and RGB image using Adaboost with multi-scale block local binary patterns, respectively. The registration of two facial surface point clouds derived from MR images and RGB-D data is initialised by aligning these five landmarks and further refined by weighted iterative closest point algorithm.

RESULTS

Phantom experiment results show the target registration error is less than 3 mm when the distance from the camera to the phantom is less than 1000 mm. The registration takes less than 10 s.

CONCLUSIONS

The proposed method is comparable to the state-of-the-arts in terms of the accuracy yet more time-saving and non-invasive.

Automated Machine Learning (AutoML)-based Surface Registration Methodology for Image-guided Surgical Navigation System

BACKGROUND

While the surface registration technique has the advantage of being relatively safe and the operation time is short, it generally has the disadvantage of low accuracy.

PURPOSE

This research proposes automated machine learning (AutoML)-based surface registration to improve the accuracy of image-guided surgical navigation systems.

METHODS

The state-of-the-art surface registration concept is that first, using a neural network model, a new point-cloud that matches the facial information acquired by a passive probe of an optical tracking system (OTS) is extracted from the facial information obtained by computerized tomography (CT). Target registration error (TRE) representing the accuracy of surface registration is then calculated by applying the iterative closest point (ICP) algorithm to the newly extracted point-cloud and OTS information. In this process, the hyperparameters used in the neural network model and ICP algorithm are automatically optimized using Bayesian Optimization with Expected Improvement to yield improved registration accuracy.

RESULTS

Using the proposed surface registration methodology, the average TRE for the targets located in the sinus space and nasal cavity of the soft phantoms is (0.939 ± 0.375) mm, which shows 57.8 % improvement compared to the average TRE of (2.227 ± 0.193) mm calculated by the conventional surface registration method (p < 0.01). The performance of the proposed methodology is evaluated, and the average TREs computed by the proposed methodology and the conventional method are (0.767 ± 0.132) mm and (2.615 ± 0.378) mm, respectively. Additionally, for one healthy adult, the clinical applicability of the AutoML-based surface registration is also presented.

CONCLUSION

Our findings showed that the registration accuracy could be improved while maintaining the advantages of the surface registration technique. This article is protected by copyright. All rights reserved.

Use of Image-Guided Surgical Navigation during Resection of Locally Recurrent Rectal Cancer

Surgery for locally recurrent rectal cancer (LRRC) presents several challenges, which is why the percentage of inadequate resections of these tumors is high. In this exploratory study, we evaluate the use of image-guided surgical navigation during resection of LRRC. Patients who were scheduled to undergo surgical resection of LRRC who were deemed by the multidisciplinary team to be at a high risk of inadequate tumor resection were selected to undergo surgical navigation. The risk of inadequate surgery was further determined by the proximity of the tumor to critical anatomical structures. Workflow characteristics of the surgical navigation procedure were evaluated, while the surgical outcome was determined by the status of the resection margin. In total, 20 patients were analyzed. For all procedures, surgical navigation was completed successfully and demonstrated to be accurate, while no complications related to the surgical navigation were discerned. Radical resection was achieved in 14 cases (70%). In five cases (25%), a tumor-positive resection margin (R1) was anticipated during surgery, as extensive radical resection was determined to be compromised. These patients all received intraoperative brachytherapy. In one case (5%), an unexpected R1 resection was performed. Surgical navigation during resection of LRRC is thus safe and feasible and enables accurate surgical guidance.

Novel microscope-based visual display and nasopharyngeal registration for auditory brainstem implantation: a feasibility study in an ex vivo model

Purpose

An auditory brainstem implant (ABI) represents an alternative for patients with profound hearing loss who are constrained from receiving a cochlear implant. The positioning of the ABI electrode influences the patient’s auditory capacity and, therefore, quality of life and is challenging even with available intraoperative electrophysiological monitoring. This work aims to provide and assess the feasibility of visual-spatial assistance for ABI positioning.

Methods

The pose of the forceps instrument that grasps the electrode was electromagnetically navigated and interactively projected in the eyepieces of a surgical microscope with respect to a target point. Intraoperative navigation was established with an experimental technique for automated nasopharyngeal patient registration. Two ABI procedures were completed in a human specimen head.

Results

An intraoperative usability study demonstrated lower localization error when using the proposed visual display versus standard cross-sectional views. The postoperative evaluations of the preclinical study showed that the center of the electrode was misplaced to the planned position by 1.58 mm and 3.16 mm for the left and the right ear procedure, respectively.

Conclusion

The results indicate the potential to enhance intraoperative feedback during ABI positioning with the presented system. Further improvements consider estimating the pose of the electrode itself to allow for better orientation during placement.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11548-021-02514-x.

How precise are oral splints for frameless stereotaxy in guided ear, nose, throat, and maxillofacial surgery: a cadaver study

Background

Computer-assisted surgery optimises accuracy and serves to improve precise surgical procedures. We validated oral splints with fiducial markers by testing them against rigid bone markers.

Methods

We screwed twenty bone anchors as fiducial markers into different regions of a dried skull and measured the distances. After computed tomography (CT) scanning, the accuracy was evaluated by determining the markers’ position using frameless stereotaxy on a dry cadaver and indicated on the CT scan. We compared the accuracy of chairside fabricated oral splints to standard registration with bone markers immediately after fabrication and after a ten-time use. Accuracy was calculated as deviation (mean ± standard deviation). For statistical analysis, t test, Kruskal-Wallis, Tukey's, and various linear regression models, such as the Pearson's product–moment correlation coefficient, were used.

Results

Oral splints showed an accuracy of 0.90 mm ± 0.27 for viscerocranium, 1.10 mm ± 0.39 for skull base, and 1.45 mm ± 0.59 for neurocranium. We found an accuracy of less than 2 mm for both splints for a distance of up to 152 mm. The accuracy persisted even after ten times removing and reattaching the splints.

Conclusions

Oral splints offer a non-invasive indicator to improve the accuracy of image-guided surgery. The precision is dependent on the distance to the target. Up to 150-mm distance, a precision of fewer than 2 mm is possible. Dental splints provide sufficient accuracy than bone markers and may opt for higher precision combined with other non-invasive registration methods.

The Use of Skin Staples as Fiducial Markers to Confirm Intraoperative Spinal Navigation Registration and Accuracy

BACKGROUND

With the advent of intraoperative computed tomography (CT) for image guidance, numerous examples of accurate navigation being applied to cranial and spinal pathology have come to light. For spinal disorders, the utilization of image guidance for the placement of percutaneous spinal instrumentation, complex osteotomies, and minimally invasive approaches are frequently utilized in trauma, degenerative, and oncological pathologies. The use of intraoperative CT for navigation, however, requires a low target registration error that must be verified throughout the procedure to confirm the accuracy of image guidance.

OBJECTIVE

To present the use of skin staples as a sterile, economical fiducial marker for minimally invasive spinal procedures requiring intraoperative CT navigation.

METHODS

Staples are applied to the skin prior to obtaining the registration CT scan and maintained throughout the remainder of the surgery to facilitate confirmation of image guidance accuracy.

RESULTS

This low-cost, simple, sterile approach provides surface landmarks that allow reliable verification of navigation accuracy during percutaneous spinal procedures using intraoperative CT scan image guidance.

CONCLUSION

The utilization of staples as a fiducial marker represents an economical and easily adaptable technique for ensuring accuracy of image guidance with intraoperative CT navigation.

Virtual splint registration for electromagnetic and optical navigation in orbital and craniofacial surgery

In intra-operative navigation, a registration procedure is performed to register the patient's position to the pre-operative imaging data. The registration process is the main factor that determines accuracy of the navigation feedback. In this study, a novel registration protocol for craniofacial surgery is presented, that utilizes a virtual splint with marker points. The accuracy of the proposed method was evaluated by two observers in five human cadaver heads, for optical and electromagnetic navigation, and compared to maxillary bone-anchored fiducial registration (optical and electromagnetic) and surface-based registration (electromagnetic). The results showed minimal differences in accuracy compared to bone-anchored fiducials at the level of the infra-orbital rim. Both point-based techniques had lower error estimates at the infraorbital rim than surface-based registration, but surface-based registration had the lowest loss of accuracy over target distance. An advantage over existing point-based registration methods (bone-anchored fiducials, existing splint techniques) is that radiological imaging does not need to be repeated, since the need for physical fiducials to be present in the image volume is eradicated. Other advantages include reduction of invasiveness compared to bone-achnored fiducials and a possible reduction of human error in the registration process.

Microscopic Navigation-Guided Fence Post Technique for Maximal Tumor Resection During Glioma Surgery

BACKGROUND

The fence post technique, which involves insertion of catheters as fence posts around a tumor, has been widely used to demarcate the tumor border for maximal resection of intraparenchymal tumors, such as gliomas. However, a standard procedure for fence post insertion has not been established, and there are some limitations. To overcome this problem, a simple microscopic navigation-guided fence post technique was developed. The feasibility and efficacy of this novel technique during glioma surgery were assessed.

METHODS

The microscopic navigation-guided fence post technique was used in 46 glioma surgeries performed in 42 patients. Intraoperatively, the preplanned trajectory was overlaid on the microscopic surgical field, and the microscope angle was changed until the entry and target points of the trajectory overlapped. A fence post catheter was inserted as planned under microscopic view, and the tumor was resected with fence post guidance. Preoperative tumor characteristics and surgical outcomes were evaluated.

RESULTS

Mean age of patients was 50 years (range, 16-78 years), and 19 (45%) of 42 patients were women. Maximal safe resection was successfully achieved in 45 surgeries (97.8%), which was planned preoperatively with identification of the tumor border with fence posts without adverse effects of brain shift. No surgical complications attributable to fence post insertion occurred.

CONCLUSIONS

Clinical experience indicated that the microscopic navigation-guided fence post technique, in which fence posts can be placed without requiring the surgeon to take their eyes off the microscope, is safe and useful in glioma surgery.

Are fiducial registration error and target registration error correlated? SciKit-SurgeryFRED for teaching and research

Understanding the relationship between fiducial registration error (FRE) and target registration error (TRE) is important for the correct use of interventional guidance systems. Whilst it is well established that TRE is statistically independent of FRE, system users still struggle against the intuitive assumption that a low FRE indicates a low TRE. We present the SciKit-Surgery Fiducial Registration Educational Demonstrator and describe its use. SciKit-SurgeryFRED was developed to enable remote teaching of key concepts in image registration. SciKit-SurgeryFRED also supports research into user interface design for image registration systems. SciKit-SurgeryFRED can be used to enable remote tutorials covering the statistics relevant to image guided interventions. Students are able to place fiducial markers on pre and intra-operative images and observe the effects of changes in marker geometry, marker count, and fiducial localisation error on TRE and FRE. SciKit-SurgeryFRED also calculates statistical measures for the expected values of TRE and FRE. Because many registrations can be performed quickly the students can then explore potential correlations between the different statistics. SciKit-SurgeryFRED also implements a registration based game, where participants are rewarded for complete treatment of a clinical target, whilst minimising the treatment margin. We used this game to perform a remote study on registration and simulated ablation, measuring how user performance changes depending on what error statistics are made available. The results support the assumption that knowing the exact value of target registration error leads to better treatment. Display of other statistics did not have a significant impact on the treatment performance.

Current Accuracy of Augmented Reality Neuronavigation Systems: Systematic Review and Meta-Analysis

BACKGROUND

Augmented reality neuronavigation (ARN) systems can overlay three-dimensional anatomy and disease without the need for a two-dimensional external monitor. Accuracy is crucial for their clinical applicability. We performed a systematic review regarding the reported accuracy of ARN systems and compared them with the accuracy of conventional infrared neuronavigation (CIN).

METHODS

PubMed and Embase were searched for ARN and CIN systems. For ARN, type of system, method of patient-to-image registration, accuracy method, and accuracy of the system were noted. For CIN, navigation accuracy, expressed as target registration error (TRE), was noted. A meta-analysis was performed comparing the TRE of ARN and CIN systems.

RESULTS

Thirty-five studies were included, 12 for ARN and 23 for CIN. ARN systems could be divided into head-mounted display and heads-up display. In ARN, 4 methods were encountered for patient-to-image registration, of which point-pair matching was the one most frequently used. Five methods for assessing accuracy were described. Ninety-four TRE measurements of ARN systems were compared with 9058 TRE measurements of CIN systems. Mean TRE was 2.5 mm (95% confidence interval, 0.7-4.4) for ARN systems and 2.6 mm (95% confidence interval, 2.1-3.1) for CIN systems.

CONCLUSIONS

In ARN, there seems to be lack of agreement regarding the best method to assess accuracy. Nevertheless, ARN systems seem able to achieve an accuracy comparable to CIN systems. Future studies should be prospective and compare TREs, which should be measured in a standardized fashion.

One-Stage Computer-Guided Customized Management of Skeletal Asymmetry by Concomitant Proportional Condylectomy and Orthognathic Surgery in Patients With Unilateral Condylar Hyperplasia

PURPOSE

Facial asymmetry associated with unilateral condylar hyperplasia can benefit from condylectomy, which aims to arrest the pathologic condylar growth and restore an appropriate posterior height. However, there are several cases in which condylar hyperplasia is combined with various dentofacial deformities, for which joint surgery has to be accompanied by concomitant orthognathic surgery. The literature is relatively poor of examples in which virtual planning for orthognathic surgery includes the evaluation of condylectomy, which is often manually performed. The aim of this study was to present and discuss a workflow for 1-stage computer-guided customized management of skeletal asymmetry by simultaneous condylectomy and orthognathic surgery.

MATERIALS AND METHODS

Five patients were enrolled in this study from 2018 to 2019. All patients underwent combined virtual planning of orthognathic surgery and condylectomy. Virtual surgery was translated into real surgical coordinates using patient-specific surgical guides and custom-designed osteosynthesis plates.

RESULTS

All surgical procedures were uneventful, and in all patients, virtual planning was successfully brought into the operating room with high accuracy, as confirmed by superimposition analyses. Symmetrization of the face and achievement of correct occlusion were observed in all cases.

CONCLUSIONS

The presented protocol is a reliable solution for the combined planning of orthognathic surgery and condylectomy. Virtual planning, surgical guides, and custom-designed plates allow computerized simulations to be replicated in the real patient.

Mapping of language and motor function during awake neurosurgery with intraoperative optical imaging

Intraoperative optical imaging (IOI) is a marker-free, contactless, and noninvasive imaging technique that is able to visualize metabolic changes of the brain surface following neuronal activation. Although it has been used in the past mainly for the identification of functional brain areas under general anesthesia, the authors investigated the potential of the method during awake surgery. Measurements were performed in 10 patients who underwent resection of lesions within or adjacent to cortical language or motor sites. IOI was applied in 3 different scenarios: identification of motor areas by using finger-tapping tasks, identification of language areas by using speech tasks (overt and silent speech), and a novel approach-the application of IOI as a feedback tool during direct electrical stimulation (DES) mapping of language. The functional maps, which were calculated from the IOI data (activity maps), were qualitatively compared with the functional MRI (fMRI) and the electrophysiological testing results during the surgical procedure to assess their potential benefit for surgical decision-making.The results reveal that the intraoperative identification of motor sites with IOI in good agreement with the preoperatively acquired fMRI and the intraoperative electrophysiological measurements is possible. Because IOI provides spatially highly resolved maps with minimal additional hardware effort, the application of the technique for motor site identification seems to be beneficial in awake procedures. The identification of language processing sites with IOI was also possible, but in the majority of cases significant differences between fMRI, IOI, and DES were visible, and therefore according to the authors' findings the IOI results are too unspecific to be useful for intraoperative decision-making with respect to exact language localization. For this purpose, DES mapping will remain the method of choice.Nevertheless, the IOI technique can provide additional value during the language mapping procedure with DES. Using a simple difference imaging approach, the authors were able to visualize and calculate the spatial extent of activation for each stimulation. This might enable surgeons in the future to optimize the mapping process. Additionally, differences between tumor and nontumor stimulation sites were observed with respect to the spatial extent of the changes in cortical optical properties. These findings provide further evidence that the method allows the assessment of the functional state of neurovascular coupling and is therefore suited for the delineation of pathologically altered tissue.

Simultaneous Optimization of Patient-Image Registration and Hand-Eye Calibration for Accurate Augmented Reality in Surgery

OBJECTIVE

Augmented reality (AR) navigation using a position sensor in endoscopic surgeries relies on the quality of patient-image registration and hand-eye calibration. Conventional methods collect the necessary data to compute two output transformation matrices separately. However, the AR display setting during surgery generally differs from that during preoperative processes. Although conventional methods can identify optimal solutions under initial conditions, AR display errors are unavoidable during surgery owing to the inherent computational complexity of AR processes, such as error accumulation over successive matrix multiplications, and tracking errors of position sensor.

METHODS

We propose the simultaneous optimization of patient-image registration and hand-eye calibration in an AR environment before surgery. The relationship between the endoscope and a virtual object to overlay is first calculated using an endoscopic image, which also functions as a reference during optimization. After including the tracking information from the position sensor, patient-image registration and hand-eye calibration are optimized in terms of least-squares.

RESULTS

Experiments with synthetic data verify that the proposed method is less sensitive to computation and tracking errors. A phantom experiment with a position sensor is also conducted. The accuracy of the proposed method is significantly higher than that of the conventional method.

CONCLUSION

The AR accuracy of the proposed method is compared with those of the conventional ones, and the superiority of the proposed method is verified.

SIGNIFICANCE

This study demonstrates that the proposed method exhibits substantial potential for improving AR navigation accuracy.

Reliable navigation registration in cranial and spine surgery based on intraoperative computed tomography

OBJECTIVE

Low registration errors are an important prerequisite for reliable navigation, independent of its use in cranial or spinal surgery. Regardless of whether navigation is used for trajectory alignment in biopsy or implant procedures, or for sophisticated augmented reality applications, all depend on a correct registration of patient space and image space. In contrast to fiducial, landmark, or surface matching–based registration, the application of intraoperative imaging allows user-independent automatic patient registration, which is less error prone. The authors’ aim in this paper was to give an overview of their experience using intraoperative CT (iCT) scanning for automatic registration with a focus on registration accuracy and radiation exposure.

METHODS

A total of 645 patients underwent iCT scanning with a 32-slice movable CT scanner in combination with navigation for trajectory alignment in biopsy and implantation procedures (n = 222) and for augmented reality (n = 437) in cranial and spine procedures (347 craniotomies and 42 transsphenoidal, 56 frameless stereotactic, 59 frame-based stereotactic, and 141 spinal procedures). The target registration error was measured using skin fiducials that were not part of the registration procedure. The effective dose was calculated by multiplying the dose length product with conversion factors.

RESULTS

Among all 1281 iCT scans obtained, 1172 were used for automatic patient registration (645 initial registration scans and 527 repeat iCT scans). The overall mean target registration error was 0.86 ± 0.38 mm (± SD) (craniotomy, 0.88 ± 0.39 mm; transsphenoidal, 0.92 ± 0.39 mm; frameless, 0.74 ± 0.39 mm; frame-based, 0.84 ± 0.34 mm; and spinal, 0.80 ± 0.28 mm). Compared with standard diagnostic scans, a distinct reduction of the effective dose could be achieved using low-dose protocols for the initial registration scan with mean effective doses of 0.06 ± 0.04 mSv for cranial, 0.50 ± 0.09 mSv for cervical, 4.12 ± 2.13 mSv for thoracic, and 3.37 ± 0.93 mSv for lumbar scans without impeding registration accuracy.

CONCLUSIONS

Reliable automatic patient registration can be achieved using iCT scanning. Low-dose protocols ensured a low radiation exposure for the patient. Low-dose scanning had no negative effect on navigation accuracy.