Surface-based facial scan registration in neuronavigation procedures: a clinical study

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.

Navigating the future of guided dental implantology: A scoping review

BACKGROUND

The aim of this scoping review was to understand the development of robotics and its accuracy in placing dental implants when compared to other forms of guided surgery.

METHODS

An electronic search was conducted on the electronic databases of PubMed, Cochrane, and Science direct with the following queries: ((robotics) AND (dental implant)) AND (accuracy). The search timeline was between 2017 and 2022.

RESULTS

A total of 54 articles were screened for title and abstract, of which 16 were deemed eligible for inclusion. Thirty-one articles were excluded mainly because they were out of topic (not relevant) or not in English. In total, 16 articles were included for analysis.

CONCLUSIONS

This review thoroughly analyses 5 years of literature concerning the evolution of robotics in dental implant surgery, underscoring the necessity for additional research on nascent technologies reported and a comparative study with static and dynamic systems for clinical efficacy evaluation.

Image-to-Patient Registration in Computer-Assisted Surgery of Head and Neck: State-of-the-Art, Perspectives, and Challenges

Today, image-guided systems play a significant role in improving the outcome of diagnostic and therapeutic interventions. They provide crucial anatomical information during the procedure to decrease the size and the extent of the approach, to reduce intraoperative complications, and to increase accuracy, repeatability, and safety. Image-to-patient registration is the first step in image-guided procedures. It establishes a correspondence between the patient's preoperative imaging and the intraoperative data. When it comes to the head-and-neck region, the presence of many sensitive structures such as the central nervous system or the neurosensory organs requires a millimetric precision. This review allows evaluating the characteristics and the performances of different registration methods in the head-and-neck region used in the operation room from the perspectives of accuracy, invasiveness, and processing times. Our work led to the conclusion that invasive marker-based methods are still considered as the gold standard of image-to-patient registration. The surface-based methods are recommended for faster procedures and applied on the surface tissues especially around the eyes. In the near future, computer vision technology is expected to enhance these systems by reducing human errors and cognitive load in the operating room.

An incremental registration method for endoscopic sinus and skull base surgery navigation: From phantom study to clinical trials

PURPOSE

Surface-based image-to-patient registration in current surgical navigation is mainly achieved by a 3D scanner, which has several limitations in clinical practice such as uncontrollable scanning range, complicated operation, and even high failure rate. An accurate, robust, and easy-to-perform image-to-patient registration method is urgently required.

METHODS

An incremental point cloud registration method was proposed for surface-based image-to-patient registration. The point cloud in image space was extracted from the computed tomography (CT) image, and a template matching method was applied to remove the redundant points. The corresponding point cloud in patient space was incrementally collected by an optically tracked pointer, while the nearest point distance (NPD) constraint was applied to ensure the uniformity of the collected points. A coarse-to-fine registration method under the constraints of coverage ratio (CR) and outliers ratio (OR) was then proposed to obtain the optimal rigid transformation from image to patient space. The proposed method was integrated in the recently developed endoscopic navigation system, and phantom study and clinical trials were conducted to evaluate the performance of the proposed method.

RESULTS

The results of the phantom study revealed that the proposed constraints greatly improved the accuracy and robustness of registration. The comparative experimental results revealed that the proposed registration method significantly outperform the scanner-based method, and achieved comparable accuracy to the fiducial-based method. In the clinical trials, the average registration duration was 1.24 ± 0.43 min, the target registration error (TRE) of 294 marker points (59 patients) was 1.25 ± 0.40 mm, and the lower 97.5% confidence limit of the success rate of positioning marker points exceeds the expected value (97.56% vs. 95.00%), revealed that the accuracy of the proposed method significantly met the clinical requirements (TRE ⩽ 2 mm, p < 0.05).

CONCLUSIONS

The proposed method has both the advantages of high accuracy and convenience, which were absent in the scanner-based method and the fiducial-based method. Our findings will help improve the quality of endoscopic sinus and skull base surgery.

Global optimization point-set registration based on translation/rotation decoupling for image-guided surgery applications

PURPOSE

In image-guided surgery systems, image-to-patient spatial registration is to get the spatial transformation between the image space and the actual operating space. Although the image-to-patient spatial registration methods using paired point or surface matching are used in some image-guided neurosurgery systems, the key problem is that the global optimization registration result cannot be achieved. Therefore, this paper proposes a new rotation invariant feature for decoupling rotation and translation space, based on which global optimization point set registration method is proposed.

METHODS

The new rotation invariant features, constructed based on the edges and the angles, are the rotation invariant, which has high feature resolution. Some of them are not only the rotation invariant, but also the translation invariant. To obtain the global optimal solution, branch and bound search strategy is used to search the parameter space of the translation and the computational cost is reduced simultaneously. The registration accuracy of the spatial registration method is analyzed by comparing the difference between the estimated transform and the standard transform to calculate the registration error.

RESULTS

To validate the performance of the spatial registration method proposed, the registration performance was analyzed by comparing the experimental results with the results of the two mainstream registration methods (the iterative closest point [ICP] registration method and the coherent point drift method). In the experiments, the comparison was based on the registration accuracy and the execution time. We show our registration method can obtain higher accuracy in a shorter time in most cases. At the same time, when using ICP to further refine our results, the ICP method can converge in a very short time, which also shows that our method provides a good initial pose for the ICP method and can help the ICP converge to the global optimal solution faster. Our method can achieve an average rotation error of 0.124 degrees and an average translation error of 0.38 mm on 10 clinical data.

CONCLUSIONS

The results reveal that the surface registration method based on translation rotation decoupling can achieve superior performance regarding both the registration accuracy and the time efficiency in the image-to-patient spatial registration.

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.

Computer-assisted surgery in medical and dental applications

INTRODUCTION

Computer-assisted surgery (CAS) is a broad surgical methodology that utilizes computer technology to both plan and execute surgical intervention. CAS is widespread in both medicine and dentistry as it allows for minimally invasive and precise surgical procedures. Key innovations in volumetric imaging, virtual surgical planning software, instrument tracking, and robotics have assisted in facilitating the transfer of surgical plans to precise execution of surgical procedures. CAS has long been used in certain medical specialties including neurosurgery, cardiology, orthopedic surgery, otolaryngology, and interventional radiology, and has since expanded to oral and maxillofacial application, particularly for computer-assisted implant surgery.

AREAS COVERED

This review provides an updated overview of the most current research for CAS in medicine and dentistry, with a focus on neurosurgery and dental implant surgery. The MEDLINE electronic database was searched and relevant original and review articles from 2005 to 2020 were included.

EXPERT OPINION

Recent literature suggests that CAS performs favorably in both neurosurgical and dental implant applications. Computer-guided surgical navigation is well entrenched as standard of care in neurosurgery. Whereas static computer-assisted implant surgery has become established in dentistry, dynamic computer-assisted navigation is newly poised to trend upward in dental implant surgery.

Patient-to-robot registration: The fate of robot-assisted stereotaxy

BACKGROUND

Robot-assisted stereotaxy (RAS) promises higher stereotactic accuracy (SA) and time efficiency (TE) than frame-based stereotaxy. However, both aspects are attributed to the problem of patient-to-robot registration.

OBJECTIVE

To examine different registration techniques regarding their SA and TE.

METHODS

This study enrolled 57 patients undergoing RAS with bone fiducial registration (BFR) or laser surface registration (LSR). SA was measured by the entry point error (EPE). Additionally, predictors of SA (registration error [RegE], distance-to-registration plane [DTC]) and TE (imaging, skin-to-skin) were assessed.

RESULTS

The mean SA was 1.0 ± 0.8 mm. BFR increased SA by reducing RegE and DTC. In LSR, EPE depended on DTC (face and forehead) with highest accuracy for DTC ≤100 mm. CT-based LSR exerted a higher SA than MR-based LSR. In BFR, TE was confined by the additional imaging.

CONCLUSION

Every registration technique counteracts one of the promises of RAS. New solutions are needed to increase the acceptance of RAS in neurosurgery.

ROBUST SURFACE-MATCHING REGISTRATION BASED ON THE STRUCTURE INFORMATION FOR IMAGE-GUIDED NEUROSURGERY SYSTEM

Image-to-patient space registration is to make the accurate alignment between the actual operating space and the image space. Although the image-to-patient space registration using paired-point is used in some image-guided neurosurgery systems, the current paired-point registration method has some drawbacks and usually cannot achieve the best registration result. Therefore, surface-matching registration is proposed to solve this problem. This paper proposes a surface-matching method that accomplishes image-to-patient space registration automatically. We represent the surface point clouds by the Gaussian Mixture Model (GMM), which can smoothly approximate the probability density distribution of an arbitrary point set. We also use mutual information as the similarity measure between the point clouds and take into account the structure information of the points. To analyze the registration error, we introduce a method for the estimation of Target Registration Error (TRE) by generating simulated data. In the experiments, we used the point sets of the cranium surface and the model of the human head determined by a CT and laser scanner. The TRE was less than 2[Formula: see text]mm, and the TRE had better accuracy in the front and the posterior region. Compared to the Iterative Closest Point algorithm, the surface registration based on GMM and the structure information of the points proved superior in registration robustness and accurate implementation of image-to-patient registration.

Using non-invasive neuroimaging to enhance the care, well-being and experimental outcomes of laboratory non-human primates (monkeys)

Over the past 10-20 years, neuroscience witnessed an explosion in the use of non-invasive imaging methods, particularly magnetic resonance imaging (MRI), to study brain structure and function. Simultaneously, with access to MRI in many research institutions, MRI has become an indispensable tool for researchers and veterinarians to guide improvements in surgical procedures and implants and thus, experimental as well as clinical outcomes, given that access to MRI also allows for improved diagnosis and monitoring for brain disease. As part of the PRIMEatE Data Exchange, we gathered expert scientists, veterinarians, and clinicians who treat humans, to provide an overview of the use of non-invasive imaging tools, primarily MRI, to enhance experimental and welfare outcomes for laboratory non-human primates engaged in neuroscientific experiments. We aimed to provide guidance for other researchers, scientists and veterinarians in the use of this powerful imaging technology as well as to foster a larger conversation and community of scientists and veterinarians with a shared goal of improving the well-being and experimental outcomes for laboratory animals.

Validation of a novel method for canine eruption assessment in unilateral cleft lip and palate patients

Objective

The aim of this study was to propose and validate a three‐dimensional (3D) methodology for the assessment of canine eruption in patients born with unilateral cleft lip and palate (UCLP) following secondary alveolar bone graft (SABG).

Methods and Materials

A total of 10 patients (four females, six males; mean age: 8.8 years) with UCLP who underwent SABG were recruited. Pre‐ and 6‐month post‐operative cone‐beam computed tomography (CBCT) was acquired for all patients. Post‐operative data was registered onto pre‐operative data utilizing voxel‐based registration. Following superimposition, a segmentation process was applied to segment maxillary canine on both cleft and non‐cleft side. Thereafter, translational and rotational changes in canine position were assessed for both cleft and non‐cleft side by two observers.

Results

The intra‐class correlation coefficient (ICC) indicated excellent reliability (≥0.90) with inter and intra‐observer error of less than 0.05 mm. The overall ICC was found to be high for assessing both translational and rotational changes. The mean absolute inter‐ and intra‐observer difference for translational and rotational changes was found to be less than 1 mm and 3°.

Conclusion

The present method was found to be reliable proving to be clinically applicable for assessing maxillary canine eruption changes in both cleft and non‐cleft bone.

Virtually-Planned Orthognathic Surgery Achieves an Accurate Condylar Position

PURPOSE

Accuracy in orthognathic surgery with virtual planning has been reported, but detailed analysis of accuracy according to anatomic location, including the mandibular condyle, is insufficient. The purpose of this study was to compare the virtual plan and surgical outcomes and analyze the degree and distribution of errors according to each anatomic location.

PATIENTS AND METHODS

This retrospective cohort study evaluated skeletal class III patients, treated with bimaxillary surgery. The primary predictor was anatomic locations that consisted of right and left condyles, maxilla, and the distal segment of the mandible. Other variables were age and gender. The primary outcome was surgical accuracy, defined as mean 3-dimensional distance error, mean absolute error, and mean error along the horizontal, vertical, and anteroposterior axes between the virtual plan and surgical outcomes. Landmarks were compared using a computational method based on affine transformation with a 1-time landmark setting. The mean errors were visualized with multidimensional scattergrams. Bivariate and regression statistics were computed.

RESULTS

This study included 52 patients, 26 men and 26 women, with a mean age of 21 years and 3 months. The mean 3D distance errors for condylar landmarks, maxillary landmarks, and landmarks on the distal segment of the mandible were 1.03, 1.25, and 2.24 mm, respectively. Condylar landmarks, maxillary landmarks, and the landmarks on the distal segment of the mandible were positioned at 0.49 mm inferior, 0.28 mm anterior, and 1.25 mm inferior, respectively. The landmark errors for the distal segment of the mandible exhibited a wider distribution than those for condylar and maxillary landmarks.

CONCLUSIONS

Agreement between the planned and actual outcome aided by virtual surgical planning was highest for the condyles, followed by the maxilla, and the distal segment of the mandible. It is important to consider the tendency for surgical errors in each anatomic location during operations.

Markerless robotic pedicle screw placement based on structured light tracking

PURPOSE

Most existing robot systems for pedicle screw placement rely on optical markers to establish the spatial relationship between the surgical tool and the surgical path. Marker installation and registration are time-consuming, and error may also accumulate along the complicated coordinate transformation chain. Therefore, we proposed a markerless structured light-based method to simplify the surgery workflow and the coordinate transformation chain.

METHODS

Firstly, a structured light camera is used to directly track both the surgical tool and the bone anatomy without using markers. Secondly, a markerless "two-direction" approach for robot-camera registration together with a feedback robot control method is developed. Lastly, a prototype system is built and examined with precision validation experiments and pedicle screw drilling experiments.

RESULTS

Precision validation experiments show satisfactory positioning accuracy of the system. In drilling experiments, 42 paths were drilled on three synthesized cervical vertebrae phantoms and all the paths successfully went through the pedicles. The mean position error of the entry point was 0.28 ± 0.16 mm, and the mean angle error was 0.49 ± 0.24°, which can meet the clinical requirement.

CONCLUSION

The results show the feasibility of the proposed structured light-based method for pedicle screw placement, which has a simple workflow and can achieve good accuracy without using optical markers.

How accurate is digital-assisted Le Fort I maxillary osteotomy? A three-dimensional perspective

The aim of this study was to evaluate the surgical accuracy of Le Fort I surgery compared to the three-dimensional (3D) virtual planning. Fifty-five patients (29 males, 26 females; age range 15-58 years) with skeletal class III malocclusion, who underwent bimaxillary surgery were included. A validated 3D accuracy assessment tool was utilized to assess the surgical accuracy of the maxillary positioning. For translational movements, the least amount of error was associated with mediolateral translation, whereas the surgical accuracy for anteroposterior and superoinferior translation showed a tendency towards a more posterior and inferior positioning of the maxilla compared to the planning. For rotational movements, the highest discrepancy was observed for pitch. Linear regression showed increased inaccuracy with increasing advancement for anteroposterior, superoinferior and pitch movements. To conclude, 3D virtual planning of maxilla was generally accurate when compared to achieved outcome for skeletal class III patients undergoing bimaxillary surgery.

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

Object

In the past, the accuracy of surface matching has been shown to be disappointing. We aimed to determine whether this had improved over the years by assessing application accuracy of current navigation systems, using either surface matching or point-pair matching.

Methods

Eleven patients, scheduled for intracranial surgery, were included in this study after a power analysis had shown this small number to be sufficient. Prior to surgery, one additional fiducial marker was placed on the scalp, the “target marker,” where the entry point of surgery was to be expected. Using one of three different navigation systems, two patient-to-image registration procedures were performed: one based on surface matching and one based on point-pair matching. Each registration procedure was followed by the digitization of the target marker’s location, allowing calculation of the target registration error. If the system offered surface matching improvement, this was always used; and for the two systems that routinely offer an estimate of neuronavigation accuracy, this was also recorded.

Results

The error in localizing the target marker using point-pair matching or surface matching was respectively 2.49 mm and 5.35 mm, on average (p < 0.001). In those four cases where an attempt was made to improve the surface matching, the error increased to 6.35 mm, on average. For the seven cases where the system estimated accuracy, this estimate did not correlate with target registration error (R² = 0.04, p = 0.67).

Conclusion

The accuracy of navigation systems has not improved over the last decade, with surface matching consistently yielding errors that are twice as large as when point-pair matching with adhesive markers is used. These errors are not reliably reflected by the systems own prediction, when offered. These results are important to make an informed choice between image-to-patient registration strategies, depending on the type of surgery at hand.

Geometric calibration of markerless optical surgical navigation system

BACKGROUND

Patient-to-image registration is required for image-guided surgical navigation, but marker-based registration is time consuming and is subject to manual error. Markerless registration is an alternative solution to avoid these issues.

METHODS

This study designs a calibration board and proposes a geometric calibration method to calibrate the near-infrared tracking and structured light components of the proposed optical surgical navigation system simultaneously.

RESULTS

A planar board and a cylinder are used to evaluate the accuracy of calibration. The mean error for the board experiment is 0.035 mm, and the diameter error for the cylinder experiment is 0.119 mm. A calibration board is reconstructed to evaluate the accuracy of the calibration, and the measured mean error is 0.012 mm. A head phantom is reconstructed and tracked by the proposed optical surgical navigation system. The tracking error is less than 0.3 mm.

CONCLUSIONS

Experimental results show that the proposed method obtains high accessibility and accuracy and satisfies application requirements.

A Surface-Based Spatial Registration Method Based on Sense Three-Dimensional Scanner

OBJECTIVE

The purpose of this study was to investigate the feasibility of a surface-based registration method based on a low-cost, hand-held Sense three-dimensional (3D) scanner in image-guided neurosurgery system.

METHODS

The scanner was calibrated prior and fixed on a tripod before registration. During registration, a part of the head surface was scanned at first and the spatial position of the adapter was recorded. Then the scanner was taken off from the tripod and the entire head surface was scanned by moving the scanner around the patient's head. All the scan points were aligned to the recorded spatial position to form a unique point cloud of the head by the automatic mosaic function of the scanner. The coordinates of the scan points were transformed from the device space to the adapter space by a calibration matrix, and then to the patient space. A 2-step patient-to-image registration method was then performed to register the patient space to the image space.

RESULTS

The experimental results showed that the mean target registration error of 15 targets on the surface of the phantom was 1.61±0.09 mm. In a clinical experiment, the mean target registration error of 7 targets on the patient's head surface was 2.50±0.31 mm, which was sufficient to meet clinical requirements.

CONCLUSIONS

It is feasible to use the Sense 3D scanner for patient-to-image registration, and the low-cost Sense 3D scanner can take the place of the current used scanner in the image-guided neurosurgery system.

Intraoperative navigation in complex head and neck resections: indications and limits

PURPOSE

The surgical removal of head and neck tumors often represents a highly complex surgery. The three-dimensionality and the anatomy of the head and neck area make sometimes difficult a correct intraoperative orientation and the obtaining of an adequate oncological safety. In the present pilot study, the authors propose a protocol of application of intraoperative navigation in the resection of head and neck tumors. The purpose is to develop a methodology that can be helpful to ensure oncologic free margins of resection and to facilitate the orientation of the specimen by pathologists.

MATERIALS AND METHODS

A sample of 16 patients with head and neck tumors was selected, and they were differentiated into two groups: a "study group" treated with CT computer-assisted surgery and a "control group" surgically treated without the use of technology. The following data were analyzed: operative and pre-surgical planning times, issues related to the use of the technologies, respect of the planned landmarks, description and orientation of the surgical specimen and distance of the tumor from the margins of resection.

RESULTS

In the "study group" were noticed a reduced rate of errors in the specimen orientation and an increased distance of the tumor from the margins of resection. Similar operative times were observed in both groups.

CONCLUSIONS

Intraoperative navigation resulted to be a reliable method to improve oncological safety in a selected group of patients.

Automatic deformable surface registration for medical applications by radial basis function-based robust point-matching

Deformable surface mesh registration is a useful technique for various medical applications, such as intra-operative treatment guidance and intra- or inter-patient study. In this paper, we propose an automatic deformable mesh registration technique. The proposed method iteratively deforms a source mesh to a target mesh without manual feature extraction. Each iteration of the registration consists of two steps, automatic correspondence finding using robust point-matching (RPM) and local deformation using a radial basis function (RBF). The proposed RBF-based RPM algorithm solves the interlocking problems of correspondence and deformation using a deterministic annealing framework with fuzzy correspondence and RBF interpolation. Simulation tests showed promising results, with the average deviations decreasing by factors of 21.2 and 11.9, respectively. In the human model test, the average deviation decreased from 1.72±1.88mm to 0.57±0.66mm. We demonstrate the effectiveness of the proposed method by presenting some medical applications.

Markerless surgical robotic system for intracerebral hemorrhage surgery

Conventional intracerebral hemorrhage (ICH) surgery uses a stereotactic frame to access an intracerebral hematoma. Using a stereotactic frame for ICH surgery requires a long preparation time. In order to resolve this problem, we propose a markerless surgical robotic system. This system uses weighted iterative closest point technology for surface registration, hand-eye calibration for needle insertion, and 3D surface scanning for registration. We need calibration to integrate the technologies: calibration of robot and needle coordinates and calibration of 3D surface scanning and needle coordinates. These calibrations are essential elements of the markerless surgical robotic system. This system has the advantages of being non-invasive, a short total operation time, and low radiation exposure compared to conventional ICH surgery.

Multimodal navigated skull base tumor resection using image-based vascular and cranial nerve segmentation: A prospective pilot study

Background:

Skull base tumors frequently encase or invade adjacent normal neurovascular structures. For this reason, optimal tumor resection with incomplete knowledge of patient anatomy remains a challenge.

Methods:

To determine the accuracy and utility of image-based preoperative segmentation in skull base tumor resections, we performed a prospective study. Ten patients with skull base tumors underwent preoperative 3T magnetic resonance imaging, which included thin section three-dimensional (3D) space T2, 3D time of flight, and magnetization-prepared rapid acquisition gradient echo sequences. Imaging sequences were loaded in the neuronavigation system for segmentation and preoperative planning. Five different neurovascular landmarks were identified in each case and measured for accuracy using the neuronavigation system. Each segmented neurovascular element was validated by manual placement of the navigation probe, and errors of localization were measured.

Results:

Strong correspondence between image-based segmentation and microscopic view was found at the surface of the tumor and tumor-normal brain interfaces in all cases. The accuracy of the measurements was 0.45 ± 0.21 mm (mean ± standard deviation). This information reassured the surgeon and prevented vascular injury intraoperatively. Preoperative segmentation of the related cranial nerves was possible in 80% of cases and helped the surgeon localize involved cranial nerves in all cases.

Conclusion:

Image-based preoperative vascular and neural element segmentation with 3D reconstruction is highly informative preoperatively and could increase the vigilance of neurosurgeons for preventing neurovascular injury during skull base surgeries. Additionally, the accuracy found in this study is superior to previously reported measurements. This novel preliminary study is encouraging for future validation with larger numbers of patients.

Electromagnetic navigation-guided surgery in the semi-sitting position for posterior fossa tumours: a safety and feasibility study

BACKGROUND

Electromagnetic (EM)-guided neuronavigation is an innovative technique and a viable alternative to opto-electric navigation. We have performed a safety and feasibility study using EM-guided neuronavigation for posterior fossa surgery in the semi-sitting position in a selected subset of patients.

METHODS

Out of 284 patients with posterior fossa tumours operated upon over a period of 40 months, a subset of 15 patients was thought to possibly benefit from EM navigational guidance and was included in this study. There were six children and nine adults (aged between 8 and 84 years; mean age, 34.6 years) with different neoplasms in the brainstem or close to the midline. All patients had contrast-enhanced three-dimensional (3D) magnetic resonance imaging (MRI) of the head preoperatively. EM-guided navigation was used to identify and preserve the venous sinuses during craniotomy and to determine the trajectory to the lesion using various approaches. Neuronavigation accuracy was repeatedly checked for deviations measured in millimetres on screen shots during surgery before and after dural opening in the coronal (z = vertical), axial (x = mediolateral) and sagittal (y = anteroposterior) plane.

RESULTS

Referencing of the patient in the supine position was fast and easy. There was no loss of navigation accuracy after repositioning of the patient in the semi-sitting position (mean, 2.5 mm ± 0.92 mm). Identification of the pathological structure using EM navigation was achieved in all instances. Optimal angulation of the neck was selected individually to permit a comfortable position for the surgeon with full access to the lesion avoiding over-flexion. Deviation of accuracy at the surface of the target lesion ranged between 2.5 and 5.8 mm (mean, 3.9 mm ± 1.1 mm).

CONCLUSIONS

EM-guided neuronavigation in the semi-sitting position was safe and technically feasible. It enabled fast and accurate referencing without loss of navigation accuracy despite repositioning of the patient. In contrast to conventional opto-electric neuronavigation there were no line of sight problems.

A new markerless patient-to-image registration method using a portable 3D scanner

PURPOSE

Patient-to-image registration is critical to providing surgeons with reliable guidance information in the application of image-guided neurosurgery systems. The conventional point-matching registration method, which is based on skin markers, requires expensive and time-consuming logistic support. Surface-matching registration with facial surface scans is an alternative method, but the registration accuracy is unstable and the error in the more posterior parts of the head is usually large because the scan range is limited. This study proposes a new surface-matching method using a portable 3D scanner to acquire a point cloud of the entire head to perform the patient-to-image registration.

METHODS

A new method for transforming the scan points from the device space into the patient space without calibration and tracking was developed. Five positioning targets were attached on a reference star, and their coordinates in the patient space were measured prior. During registration, the authors moved the scanner around the head to scan its entire surface as well as the positioning targets, and the scanner generated a unique point cloud in the device space. The coordinates of the positioning targets in the device space were automatically detected by the scanner, and a spatial transformation from the device space to the patient space could be calculated by registering them to their coordinates in the patient space that had been measured prior. A three-step registration algorithm was then used to register the patient space to the image space. The authors evaluated their method on a rigid head phantom and an elastic head phantom to verify its practicality and to calculate the target registration error (TRE) in different regions of the head phantoms. The authors also conducted an experiment with a real patient's data to test the feasibility of their method in the clinical environment.

RESULTS

In the phantom experiments, the mean fiducial registration error between the device space and the patient space, the mean surface registration error, and the mean TRE of 15 targets on the surface of each phantom were 0.34 ± 0.01 mm and 0.33 ± 0.02 mm, 1.17 ± 0.02 mm and 1.34 ± 0.10 mm, and 1.06 ± 0.11 mm and 1.48 ± 0.21 mm, respectively. When grouping the targets according to their positions on the head, high accuracy was achieved in all parts of the head, and the TREs were similar across different regions. The authors compared their method with the current surface registration methods that use only a part of the facial surface on the elastic phantom, and the mean TRE of 15 targets was 1.48 ± 0.21 mm and 1.98 ± 0.53 mm, respectively. In a clinical experiment, the mean TRE of seven targets on the patient's head surface was 1.92 ± 0.18 mm, which was sufficient to meet clinical requirements.

CONCLUSIONS

The proposed surface-matching registration method provides sufficient registration accuracy even in the posterior area of the head. The 3D point cloud of the entire head, including the facial surface and the back of the head, can be easily acquired using a portable 3D scanner. The scanner does not need to be calibrated prior or tracked by the optical tracking system during scanning.

The role of automatic computer-aided surgical trajectory planning in improving the expected safety of stereotactic neurosurgery

PURPOSE

Minimal invasion computer-assisted neurosurgical procedures with various tool insertions into the brain may carry hemorrhagic risks and neurological deficits. The goal of this study is to investigate the role of computer-based surgical trajectory planning tools in improving the potential safety of image-based stereotactic neurosurgery.

METHODS

Multi-sequence MRI studies of eight patients who underwent image-guided neurosurgery were retrospectively processed to extract anatomical structures-head surface, ventricles, blood vessels, white matter fibers tractography, and fMRI data of motor, sensory, speech, and visual areas. An experienced neurosurgeon selected one target for each patient. Five neurosurgeons planned a surgical trajectory for each patient using three planning methods: (1) conventional; (2) visualization, in which scans are augmented with overlays of anatomical structures and functional areas; and (3) automatic, in which three surgical trajectories with the lowest expected risk score are automatically computed. For each surgeon, target, and method, we recorded the entry point and its surgical trajectory and computed its expected risk score and its minimum distance from the key structures.

RESULTS

A total of 120 surgical trajectories were collected (5 surgeons, 8 targets, 3 methods). The surgical trajectories expected risk scores improved by 76% ([Formula: see text], two-sample student's t test); the average distance of a trajectory from nearby blood vessels increased by 1.6 mm ([Formula: see text]) from 0.6 to 2.2 mm (243%). The initial surgical trajectories were changed in 85% of the cases based on the expected risk score and the trajectory distance from blood vessels.

CONCLUSIONS

Computer-based patient-specific preoperative planning of surgical trajectories that minimize the expected risk of vascular and neurological damage due to incorrect tool placement is a promising technique that yields consistent improvements.

A robust automated markerless registration framework for neurosurgery navigation

BACKGROUND

The registration of a pre-operative image with the intra-operative patient is a crucial aspect for the success of navigation in neurosurgery.

METHODS

First, the intra-operative face is reconstructed, using a structured light technique, while the pre-operative face is segmented from head CT/MRI images. In order to perform neurosurgery navigation, a markerless surface registration method is designed by aligning the intra-operative face to the pre-operative face. We propose an efficient and robust registration approach based on the scale invariant feature transform (SIFT), and compare it with iterative closest point (ICP) and coherent point drift (CPD) through a new evaluation standard.

RESULTS

Our registration method was validated by studies of 10 volunteers and one synthetic model. The average symmetrical surface distances (ASDs) for ICP, CPD and our registration method were 2.24 ± 0.53, 2.18 ± 0.41 and 2.30 ± 0.69 mm, respectively. The average running times of ICP, CPD and our registration method were 343.46, 3847.56 and 0.58 s, respectively.

CONCLUSION

Our system can quickly reconstruct the intra-operative face, and then efficiently and accurately align it to the pre-operative image, meeting the registration requirements in neurosurgery navigation. It avoids a tedious set-up process for surgeons.

Accuracy assessment of a marker-free method for registration of CT and stereo images applied in image-guided implantology: a phantom study

To assess the accuracy of a proposed marker-free registration method as opposed to the conventional marker-based method using an image-guided dental system, and investigating the best configurations of anatomical landmarks for various surgical fields in a phantom study, a CT-compatible dental phantom consisting of implanted targets was used. Two marker-free registration methods were evaluated, first using dental anatomical landmarks and second, using a reference marker tool. Six implanted markers, distributed in the inner space of the phantom were used as the targets; the values of target registration error (TRE) for each target were measured and compared with the marker-based method. Then, the effects of different landmark configurations on TRE values, measured using the Parsiss IV Guided Navigation system (Parsiss, Tehran, Iran), were investigated to find the best landmark arrangement for reaching the minimum registration error in each target region. It was proved that marker-free registration can be as precise as the marker-based method. This has a great impact on image-guided implantology systems whereby the drawbacks of fiducial markers for patient and surgeon are removed. It was also shown that smaller values of TRE could be achieved by using appropriate landmark configurations and moving the center of the landmark set closer to the surgery target. Other common factors would not necessarily decrease the TRE value so the conventional rules accepted in the clinical community about the ways to reduce TRE should be adapted to the selected field of dental surgery.

Near Real-Time Computer Assisted Surgery for Brain Shift Correction Using Biomechanical Models

Conventional image-guided neurosurgery relies on preoperative images to provide surgical navigational information and visualization. However, these images are no longer accurate once the skull has been opened and brain shift occurs. To account for changes in the shape of the brain caused by mechanical (e.g., gravity-induced deformations) and physiological effects (e.g., hyperosmotic drug-induced shrinking, or edema-induced swelling), updated images of the brain must be provided to the neuronavigation system in a timely manner for practical use in the operating room. In this paper, a novel preoperative and intraoperative computational processing pipeline for near real-time brain shift correction in the operating room was developed to automate and simplify the processing steps. Preoperatively, a computer model of the patient's brain with a subsequent atlas of potential deformations due to surgery is generated from diagnostic image volumes. In the case of interim gross changes between diagnosis, and surgery when reimaging is necessary, our preoperative pipeline can be generated within one day of surgery. Intraoperatively, sparse data measuring the cortical brain surface is collected using an optically tracked portable laser range scanner. These data are then used to guide an inverse modeling framework whereby full volumetric brain deformations are reconstructed from precomputed atlas solutions to rapidly match intraoperative cortical surface shift measurements. Once complete, the volumetric displacement field is used to update, i.e., deform, preoperative brain images to their intraoperative shifted state. In this paper, five surgical cases were analyzed with respect to the computational pipeline and workflow timing. With respect to postcortical surface data acquisition, the approximate execution time was 4.5 min. The total update process which included positioning the scanner, data acquisition, inverse model processing, and image deforming was ~11-13 min. In addition, easily implemented hardware, software, and workflow processes were identified for improved performance in the near future.

A region-based anatomical landmark configuration for sinus surgery using image guided navigation system: a phantom-study

PURPOSE

To evaluate the current beliefs about the ways to reduce target registration error (TRE) values in image guided Sinus surgery by rearranging the fiducial configuration, and investigating the best configurations for various surgical fields in a phantom study.

METHODS

A new CT-compatible skull phantom consisting of implanted targets was designed to enable direct measurement of TRE in four fields of sinus surgery, Frontal, Ethmoid, Sphenoid and Maxillary. The effects of different landmark configurations on TRE values, measured by the Parsiss-IV navigation system were investigated to find the best landmark arrangement for each region, and compared to the TRE prediction formula to assess the clinically accepted landmark selection approaches based on this formula.

RESULTS

It was shown that smaller values of TRE could be attained by arranging the center of the fiducials to be more focused on the surgery target. The addition of more fiducials and keeping non-linear arrangement of landmark would not necessarily decrease the TRE value.

CONCLUSION

Optimizing the landmark configuration is important for increasing the localization accuracy in image guided sinus surgery. The common beliefs accepted in the clinical community about the ways to reduce the TRE are very general and should be adapted to specific field of image guided surgery.

The silent loss of neuronavigation accuracy: a systematic retrospective analysis of factors influencing the mismatch of frameless stereotactic systems in cranial neurosurgery

BACKGROUND

Neuronavigation has become an intrinsic part of preoperative surgical planning and surgical procedures. However, many surgeons have the impression that accuracy decreases during surgery.

OBJECTIVE

To quantify the decrease of neuronavigation accuracy and identify possible origins, we performed a retrospective quality-control study.

METHODS

Between April and July 2011, a neuronavigation system was used in conjunction with a specially prepared head holder in 55 consecutive patients. Two different neuronavigation systems were investigated separately. Coregistration was performed with laser-surface matching, paired-point matching using skin fiducials, anatomic landmarks, or bone screws. The initial target registration error (TRE1) was measured using the nasion as the anatomic landmark. Then, after draping and during surgery, the accuracy was checked at predefined procedural landmark steps (Mayfield measurement point and bone measurement point), and deviations were recorded.

RESULTS

After initial coregistration, the mean (SD) TRE1 was 2.9 (3.3) mm. The TRE1 was significantly dependent on patient positioning, lesion localization, type of neuroimaging, and coregistration method. The following procedures decreased neuronavigation accuracy: attachment of surgical drapes (DTRE2 = 2.7 [1.7] mm), skin retractor attachment (DTRE3 = 1.2 [1.0] mm), craniotomy (DTRE3 = 1.0 [1.4] mm), and Halo ring installation (DTRE3 = 0.5 [0.5] mm). Surgery duration was a significant factor also; the overall DTRE was 1.3 [1.5] mm after 30 minutes and increased to 4.4 [1.8] mm after 5.5 hours of surgery.

CONCLUSION

After registration, there is an ongoing loss of neuronavigation accuracy. The major factors were draping, attachment of skin retractors, and duration of surgery. Surgeons should be aware of this silent loss of accuracy when using neuronavigation.

Intraoperative patient registration using volumetric true 3D ultrasound without fiducials

PURPOSE

Accurate patient registration is crucial for effective image-guidance in open cranial surgery. Typically, it is accomplished by matching skin-affixed fiducials manually identified in the operating room (OR) with their counterparts in the preoperative images, which not only consumes OR time and personnel resources but also relies on the presence (and subsequent fixation) of the fiducials during the preoperative scans (until the procedure begins). In this study, the authors present a completely automatic, volumetric image-based patient registration technique that does not rely on fiducials by registering tracked (true) 3D ultrasound (3DUS) directly with preoperative magnetic resonance (MR) images.

METHODS

Multistart registrations between binary 3DUS and MR volumes were first executed to generate an initial starting point without incorporating prior information on the US transducer contact point location or orientation for subsequent registration between grayscale 3DUS and MR via maximization of either mutual information (MI) or correlation ratio (CR). Patient registration was then computed through concatenation of spatial transformations.

RESULTS

In ten (N = 10) patient cases, an average fiducial (marker) distance error (FDE) of 5.0 mm and 4.3 mm was achieved using MI or CR registration (FDE was smaller with CR vs MI in eight of ten cases), which are comparable to values reported for typical fiducial- or surface-based patient registrations. The translational and rotational capture ranges were found to be 24.0 mm and 27.0° for binary registrations (up to 32.8 mm and 36.4°), 12.2 mm and 25.6° for MI registrations (up to 18.3 mm and 34.4°), and 22.6 mm and 40.8° for CR registrations (up to 48.5 mm and 65.6°), respectively. The execution time to complete a patient registration was 12-15 min with parallel processing, which can be significantly reduced by confining the 3DUS transducer location to the center of craniotomy in MR before registration (an execution time of 5 min is achievable).

CONCLUSIONS

Because common features deep in the brain and throughout the surgical volume of interest are used, intraoperative fiducial-less patient registration is possible on-demand, which is attractive in cases where preoperative patient registration is compromised (e.g., from loss∕movement of skin-affixed fiducials) or not possible (e.g., in cases of emergency when external fiducials were not placed in time). CR registration was more robust than MI (capture range about twice as big) and appears to be more accurate, although both methods are comparable to or better than fiducial-based registration in the patient cases evaluated. The results presented here suggest that 3DUS image-based patient registration holds promise for clinical application in the future.

Comparison study of intraoperative surface acquisition methods for surgical navigation

Soft-tissue image-guided interventions often require the digitization of organ surfaces for providing correspondence from medical images to the physical patient in the operating room. In this paper, the effect of several inexpensive surface acquisition techniques on target registration error and surface registration error (SRE) for soft tissue is investigated. A systematic approach is provided to compare image-to-physical registrations using three different methods of organ spatial digitization: 1) a tracked laser-range scanner (LRS), 2) a tracked pointer, and 3) a tracked conoscopic holography sensor (called a conoprobe). For each digitization method, surfaces of phantoms and biological tissues were acquired and registered to CT image volume counterparts. A comparison among these alignments demonstrated that registration errors were statistically smaller with the conoprobe than the tracked pointer and LRS (p<0.01). In all acquisitions, the conoprobe outperformed the LRS and tracked pointer: for example, the arithmetic means of the SRE over all data acquisitions with a porcine liver were 1.73 ± 0.77 mm, 3.25 ± 0.78 mm, and 4.44 ± 1.19 mm for the conoprobe, LRS, and tracked pointer, respectively. In a cadaveric kidney specimen, the arithmetic means of the SRE over all trials of the conoprobe and tracked pointer were 1.50 ± 0.50 mm and 3.51 ± 0.82 mm, respectively. Our results suggest that tissue displacements due to contact force and attempts to maintain contact with tissue, compromise registrations that are dependent on data acquired from a tracked surgical instrument and we provide an alternative method (tracked conoscopic holography) of digitizing surfaces for clinical usage. The tracked conoscopic holography device outperforms LRS acquisitions with respect to registration accuracy.

Navigation-guided endoscopic biopsy for intraparenchymal brain tumor

To evaluate the efficacy of intraparenchymal brain tumor biopsy using endoscopy and a navigation system (navigation-guided endoscopic biopsy) as a diagnostic tool, a case series of intraparenchymal tumor biopsies was reviewed. Navigation-guided endoscopic biopsy was applied in 9 cases, stereotactic needle biopsy in 16 cases, and open biopsy with or without navigation system in 34 cases. In all biopsy cases, 84.7% of biopsy points were sampled accurately, and 93.2% of diagnoses by biopsy were correct. Comparison of each type of biopsy showed that the resected volumes in navigation-guided endoscopic biopsy and open biopsy tended to be larger than those in stereotactic biopsy, and the mean operation time for the open biopsy procedure was the longest. To define the most applicable device or examination method to increase sampling accuracy, various factors were analyzed in 59 procedures. Navigation-guided endoscopic biopsy was the most accurate of the three types of biopsy, although the statistical difference was not significant. Older patients, histological diagnosis of high-grade glioma or malignant lymphoma, positive photodynamic diagnosis, and positive intraoperative pathology were significant factors in improving the sampling accuracy. Navigation-guided endoscopic biopsy could provide a larger sample volume within a relatively short operation time. The biopsy can be easily combined with both photodynamic diagnosis and intraoperative pathology, significantly improving the histological diagnostic yield.

Design and evaluation of an optically-tracked single-CCD laser range scanner

PURPOSE

Acquisition of laser range scans of an organ surface has the potential to efficiently provide measurements of geometric changes to soft tissue during a surgical procedure. A laser range scanner design is reported here which has been developed to drive intraoperative updates to conventional image-guided neurosurgery systems.

METHODS

The scanner is optically-tracked in the operating room with a multiface passive target. The novel design incorporates both the capture of surface geometry (via laser illumination) and color information (via visible light collection) through a single-lens onto the same charge-coupled device (CCD). The accuracy of the geometric data was evaluated by scanning a high-precision phantom and comparing relative distances between landmarks in the scans with the corresponding ground truth (known) distances. The range-of-motion of the scanner with respect to the optical camera was determined by placing the scanner in common operating room configurations while sampling the visibility of the reflective spheres. The tracking accuracy was then analyzed by fixing the scanner and phantom in place, perturbing the optical camera around the scene, and observing variability in scan locations with respect to a tracked pen probe ground truth as the camera tracked the same scene from different positions.

RESULTS

The geometric accuracy test produced a mean error and standard deviation of 0.25 ± 0.40 mm with an RMS error of 0.47 mm. The tracking tests showed that the scanner could be tracked at virtually all desired orientations required in the OR set up, with an overall tracking error and standard deviation of 2.2 ± 1.0 mm with an RMS error of 2.4 mm. There was no discernible difference between any of the three faces on the lasers range scanner (LRS) with regard to tracking accuracy.

CONCLUSIONS

A single-lens laser range scanner design was successfully developed and implemented with sufficient scanning and tracking accuracy for image-guided surgery.

Fiducial optimization for minimal target registration error in image-guided neurosurgery

This paper presents new methods for the optimal selection of anatomical landmarks and optimal placement of fiducial markers in image-guided neurosurgery. These methods allow the surgeon to optimally plan fiducial marker locations on routine diagnostic images before preoperative imaging and to intraoperatively select the set of fiducial markers and anatomical landmarks that minimize the expected target registration error (TRE). The optimization relies on a novel empirical simulation-based TRE estimation method built on actual fiducial localization error (FLE) data. Our methods take the guesswork out of the registration process and can reduce localization error without additional imaging and hardware. Our clinical experiments on five patients who underwent brain surgery with a navigation system show that optimizing one marker location and the anatomical landmarks configuration reduced the TRE. The average TRE values using the usual fiducials setup and using the suggested method were 4.7 mm and 3.2 mm, respectively. We observed a maximum improvement of 4 mm. Reducing the target registration error has the potential to support safer and more accurate minimally invasive neurosurgical procedures.

Markerless registration for intracerebral hemorrhage surgical system using weighted Iterative Closest Point (ICP)

It is required to use a stereotactic frame on a patient's crainial surface to access an intracerebral hematoma in conventional ICH (Intracerebral Hemorrhage) removal surgery. Since ICH using a stereotactic frame is an invasive procedure and also takes a long time, we attempt to develop a robotic ICH removal procedure with a markerless registration system using an optical 3-D scanner. Preoperative planning is performed using a patient's CT (Computed Tomography) images, which include the patient's 3-D geometrical information on the hematoma and internal structures of brain. To register the preplanned data and the intraoperative patient's data, the patient's facial surface is scanned by an optical 3-D scanner on the bed in the operating room. The intraoperatively scanned facial surface is registered to the pose of the patient's preoperative facial surface. The conventional ICP (Iterative Closest Point) algorithm can be used for the registration. In this paper, we propose a weighted ICP in order to improve the accuracy of the registration results. We investigated facial regions that can be used as anatomical landmarks. The facial regions for the landmarks in the preoperative 3-D model are weighted for more accurate registration. We increase weights at the relatively undeformed facial regions, and decrease weights at the other regions. As a result, more accurate and robust registration can be achieved from the preoperative data even with local facial shape changes.

Recent advances in pituitary tumor management

PURPOSE OF REVIEW

Advances in the neurosurgical management of pituitary tumors have included the refinement of surgical access and significant progress in navigation technology to help further reduce morbidity and improve outcome. Similarly, stereotactic radiosurgery has evolved to become an integral part in pituitary tumors not amenable to medical or surgical treatment.

RECENT FINDINGS

The evolution of minimally invasive surgery has evolved toward endoscopic versus microscopic trans-sphenoidal approaches for pituitary tumors. Debate exists regarding each approach, with advocates for both championing their cause. Stereotactic and fractional radiosurgery have been shown to be a safe and effective means of controlling tumor growth and ensuring hormonal stabilization, with longer-term data available for GammaKnife compared with CyberKnife.

SUMMARY

The advances in trans-sphenoidal surgical approaches, navigation technological improvements and the current results of stereotactic radiosurgery are discussed.

Properties of the target registration error for surface matching in neuronavigation

OBJECTIVE

Surface matching is a relatively new method of spatial registration in neuronavigation. Compared to the traditional point matching method, surface matching does not use fiducial markers that must be fixed to the surface of the head before image scanning, and therefore does not require an image acquisition specifically dedicated for navigation purposes. However, surface matching is not widely used clinically, mainly because there is still insufficient knowledge about its application accuracy. This study aimed to explore the properties of the Target Registration Error (TRE) of surface matching in neuronavigation.

MATERIALS AND METHODS

The surface matching process was simulated in the image space of a neuronavigation system so that the TRE could be calculated at any point in that space. For each registration, two point clouds were generated to represent the surface extracted from preoperative images (PC(image)) and the surface obtained intraoperatively by laser scanning (PC(laser)). The properties of the TRE were studied by performing multiple registrations with PC(laser) point clouds at different positions and generated by adding different types of error.

RESULTS

For each registration, the TRE had a minimal value at a point in the image space, and the iso-valued surface of the TRE was approximately ellipsoid with smaller TRE on the inner surfaces. The position of the point with minimal TRE and the shape of the iso-valued surface were highly random across different registrations, and the surface registration error between the two point clouds was irrelevant to the TRE at a specific point. The overall TRE tended to increase with the increase in errors in PC(laser), and a larger PC(laser) made it less sensitive to these errors. With the introduction of errors in PC(laser), the points with minimal TRE tended to be concentrated in the anterior and inferior part of the head.

CONCLUSION

The results indicate that the alignment between the two surfaces could not provide reliable information about the registration accuracy at an arbitrary target point. However, according to the spatial distribution of the target registration error of a single registration, enough application accuracy could be guaranteed by proper visual verification after registration. In addition, surface matching tends to achieve high accuracy in the inferior and anterior part of the head, and a relatively large scanning area is preferable.

Navigated Transcranial Magnetic Stimulation and Functional Magnetic Resonance Imaging: Advanced Adjuncts in Preoperative Planning for Central Region Tumors

BACKGROUND:

Tumor resection in the vicinity of the motor cortex poses a challenge to all neurosurgeons. For preoperative assessment of eloquent cortical areas, functional magnetic resonance imaging (fMRI) is used, whereas intraoperatively, direct cortical stimulation (DCS) is performed. Navigated transcranial magnetic stimulation (nTMS) is comparable to DCS in activating cortical pyramidal neurons.

OBJECTIVE:

To evaluate the reliability of nTMS compared with fMRI and DCS for preoperative resection planning of centrally located tumors.

METHODS:

In a prospective series, 11 patients (ages, 20-63 years; mean, 41.9 ± 14.9 years, 2 women) with tumors located in or adjacent to the motor cortex were evaluated for surgery. fMRI and nTMS were applied for preoperative assessment of the extent of tumor resection. A 3-dimensional anatomic data set with superimposed fMRI data was integrated in the eXimia Navigated Brain Stimulation station for ensuing motor cortex mapping by nTMS. Responses from nTMS were evaluated by electromyographic response. During surgery, the coordinates of each DCS site were unambiguously defined and integrated into neuronavigation. A post hoc comparison of the coordinates of nTMS, fMRI, and DCS was performed.

RESULTS:

Distances from nTMS to DCS (10.5 ± 5.67 mm) were significantly smaller than those from fMRI to DCS (15.0 ± 7.6 mm).

CONCLUSION:

nTMS anticipates information usually only enabled by DCS and therefore allows surgical planning in eloquent cortex surgery.

Registration accuracy of three-dimensional surface and cone beam computed tomography data for virtual implant planning

OBJECTIVE

Virtual wax-ups based on three-dimensional (3D) surface models can be matched (i.e. registered) to cone beam computed tomography (CBCT) data of the same patient for dental implant planning. Thereby, implant planning software can visualize anatomical and prosthetic information simultaneously. The aim of this study is to assess the accuracy of a newly developed registration process.

MATERIAL AND METHODS

Data pairs of CBCT and 3D surface data of 16 patients for dental implant planning were registered and the discrepancy between the visualized 3D surface data and the corresponding CBCT data were measured on 64 teeth at seven points by two investigators in two iterations with a total of 1792 measurements.

RESULTS

All data pairs were matched successfully and mean distances between CBCT and 3D surface data were between 0.03(±0.33) and 0.14(±0.18) mm. At two of seven measuring points, statistically significant correlations were determined between the measured error and the presence and type of restorations. Registration errors in maxilla and mandible were not statistically significantly different.

CONCLUSION

According to the results of this study, registration of 3D surface data and CBCT data works reliably and is sufficiently accurate for dental implant planning. Thereby, barium-sulfate scanning templates can be avoided and dental implant planning can be accomplished fully virtual.

Target and Trajectory Clinical Application Accuracy in Neuronavigation

BACKGROUND:

Catheter, needle, and electrode misplacement in navigated neurosurgery can result in ineffective treatment and severe complications.

OBJECTIVE:

To assess the Ommaya ventricular catheter localization accuracy both along the planned trajectory and at the target.

METHODS:

We measured the localization error along the ventricular catheter and on its tip for 15 consecutive patients who underwent insertion of the Ommaya catheter surgery with a commercial neuronavigation system. The preoperative computed tomography/magnetic resonance images and the planned trajectory were aligned with the postoperative computed tomography images showing the Ommaya catheter. The localization errors along the trajectory and at the target were then computed by comparing the preoperative planned trajectory with the actual postoperative catheter position. The measured localization errors were also compared with the error reported by the navigation system.

RESULTS:

The mean localization errors at the target and entry point locations were 5.9 ± 4.3 and 3.3 ± 1.9 mm, respectively. The mean shift and angle between planned and actual trajectories were 1.6 ± 1.9 mm and 3.9 ± 4.7°, respectively. The mean difference between the localization error at the target and entry point was 3.9 ± 3.7 mm. The mean difference between the target localization error and the reported navigation system error was 4.9 ± 4.8 mm.

CONCLUSION:

The catheter localization errors have significant variations at the target and along the insertion trajectory. Trajectory errors may differ significantly from the errors at the target. Moreover, the single registration error number reported by the navigation system does not appropriately reflect the trajectory and target errors and thus should be used with caution to assess the procedure risk.

Intraoperative computed tomography registration and electromagnetic neuronavigation for transsphenoidal pituitary surgery: accuracy and time effectiveness

Object

The authors assessed the feasibility, anatomical accuracy, and cost effectiveness of frameless electromagnetic (EM) neuronavigation in conjunction with portable intraoperative CT (iCT) registration for transsphenoidal adenomectomy (TSA).

Methods

A prospective database was established for data obtained in 208 consecutive patients who underwent TSA in which the iCT/EM navigation technique was used. Data were compared with those acquired in a retrospective cohort of 65 consecutive patients in whom fluoroscope-assisted TSA had been performed by the same surgeon. All patients in both groups underwent transnasal removal of pituitary adenomas or neuroepithelial cysts, using identical surgical techniques with an operating microscope. In the iCT/EM technique–treated cases, a portable iCT scan was obtained immediately prior to surgery for registration to the EM navigation system, which did not require rigid head fixation. Preexisting (nonnavigation protocol) MR imaging studies were fused with the iCT scans to enable 3D navigation based on MR imaging data. The accuracy of the navigation system was determined in the first 50 iCT/EM cases by visual concordance of the navigation probe location to 5 preselected bony landmarks. For all patients in both cohorts, total operating room time, incision-to-closure time, and relative costs of imaging and surgical procedures were determined from hospital records.

Results

In every case, iCT registration was successful and preoperative MR images were fused to iCT scans without affecting navigation accuracy. There was 100% concordance between probe tip location and predetermined bony loci in the first 50 cases involving the iCT/EM technique. Total operating room time was significantly less in the iCT/EM cases (mean 108.9 ± 24.3 minutes [208 patients]) compared with the fluoroscopy group (mean 121.1 ± 30.7 minutes [65 patients]; p < 0.001). Similarly, incision-to-closure time was significantly less for the iCT/EM cases (mean 61.3 ± 18.2 minutes) than for the fluoroscopy cases (mean 71.75 ± 19.0 minutes; p < 0.001). Relative overall costs for iCT/EM technique and intraoperative C-arm fluoroscopy were comparable; increased costs for navigation equipment were offset by savings in operating room costs for shorter procedures.

Conclusions

The use of iCT/MR imaging–guided neuronavigation for transsphenoidal surgery is a time-effective, cost-efficient, safe, and technically beneficial technique.

Skull-fixated fiducial markers improve accuracy in staged frameless stereotactic epilepsy surgery in children

OBJECT

Surgery to monitor and resect epileptogenic foci may be undertaken in 2 stages, providing an opportunity to use skull-fixated fiducials implanted during the first stage to improve the accuracy of cortical resection during the second stage. This study compared the intrinsic accuracy of skin-based and skull-fixated fiducial markers in registering frameless stereotaxy during pediatric epilepsy surgery. To the authors' knowledge, these modalities of registration have not previously been directly compared in this population.

METHODS

The authors undertook a retrospective review of pediatric patients who underwent resection of epileptogenic foci in 2 stages with frameless stereotactic assistance, performed by a single surgeon at Oregon Health & Science University. For the first stage (subdural grid implantation), 9 skin fiducial markers were used to register anatomical data in a frameless stereotactic station. Intraoperatively, four 3-mm screws were placed circumferentially around the craniotomy. Postoperatively, thin-slice brain MR and CT images were obtained and fused. For the second stage, the 4 screws were used as fiducial markers to register the stereotactic anatomical data. For both stages, accuracy (difference in millimeters from zero of the manual fiducial registration compared with the computer model) was determined using navigation software. The intrinsic accuracy of these 2 methods of fiducial registration was compared using a paired Student t-test.

RESULTS

Between 2004 and 2009, 40 pediatric patients with epilepsy underwent frameless stereotactic surgical procedures. Fourteen patients who had 2-stage procedures using skin-based and skull-fixated registration with complete accuracy data were included in this retrospective review. Mean registration error was significantly lower using skull-fixated fiducials (1.35 mm, 95% CI 1.09-1.60 mm) than using skin-based fiducials (1.85 mm, 95% CI 1.56-2.13 mm; p = 0.0016).

CONCLUSIONS

A significantly higher degree of accuracy was achieved using 4 skull-fixated fiducials compared with using 9 skin-based fiducials. This simple and accurate method for registering frameless stereotactic anatomical data does not involve the potential time, expense, discomfort, and morbidity of extraoperative skull-fixated fiducial placement. The method described in this paper could also be extrapolated to other planned 2-stage cranial surgical procedures such as combined skull base approaches.