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

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

Accuracy and precision of navigated transcranial magnetic stimulation

Objective.Transcranial magnetic stimulation (TMS) induces an electric field (E-field) in the cortex. To facilitate stimulation targeting, image-guided neuronavigation systems have been introduced. Such systems track the placement of the coil with respect to the head and visualize the estimated cortical stimulation location on an anatomical brain image in real time. The accuracy and precision of the neuronavigation is affected by multiple factors. Our aim was to analyze how different factors in TMS neuronavigation affect the accuracy and precision of the coil-head coregistration and the estimated E-field.Approach.By performing simulations, we estimated navigation errors due to distortions in magnetic resonance images (MRIs), head-to-MRI registration (landmark- and surface-based registrations), localization and movement of the head tracker, and localization of the coil tracker. We analyzed the effect of these errors on coil and head coregistration and on the induced E-field as determined with simplistic and realistic head models.Main results.Average total coregistration accuracies were in the range of 2.2-3.6 mm and 1°; precision values were about half of the accuracy values. The coregistration errors were mainly due to head-to-MRI registration with average accuracies 1.5-1.9 mm/0.2-0.4° and precisions 0.5-0.8 mm/0.1-0.2° better with surface-based registration. The other major source of error was the movement of the head tracker with average accuracy of 1.5 mm and precision of 1.1 mm. When assessed within an E-field method, the average accuracies of the peak E-field location, orientation, and magnitude ranged between 1.5 and 5.0 mm, 0.9 and 4.8°, and 4.4 and 8.5% across the E-field models studied. The largest errors were obtained with the landmark-based registration. When computing another accuracy measure with the most realistic E-field model as a reference, the accuracies tended to improve from about 10 mm/15°/25% to about 2 mm/2°/5% when increasing realism of the E-field model.Significance.The results of this comprehensive analysis help TMS operators to recognize the main sources of error in TMS navigation and that the coregistration errors and their effect in the E-field estimation depend on the methods applied. To ensure reliable TMS navigation, we recommend surface-based head-to-MRI registration and realistic models for E-field computations.

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.

Current status of augmented reality in cerebrovascular surgery: a systematic review

Augmented reality (AR) is an adjuvant tool in neuronavigation to improve spatial and anatomic understanding. The present review aims to describe the current status of intraoperative AR for the treatment of cerebrovascular pathology. A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The following databases were searched: PubMed, Science Direct, Web of Science, and EMBASE up to December, 2020. The search strategy consisted of "augmented reality," "AR," "cerebrovascular," "navigation," "neurovascular," "neurosurgery," and "endovascular" in both AND and OR combinations. Studies included were original research articles with intraoperative application. The manuscripts were thoroughly examined for study design, outcomes, and results. Sixteen studies were identified describing the use of intraoperative AR in the treatment of cerebrovascular pathology. A total of 172 patients were treated for 190 cerebrovascular lesions using intraoperative AR. The most common treated pathology was intracranial aneurysms. Most studies were cases and there was only a case-control study. A head-up display system in the microscope was the most common AR display. AR was found to be useful for tailoring the craniotomy, dura opening, and proper identification of donor and recipient vessels in vascular bypass. Most AR systems were unable to account for tissue deformation. This systematic review suggests that intraoperative AR is becoming a promising and feasible adjunct in the treatment of cerebrovascular pathology. It has been found to be a useful tool in the preoperative planning and intraoperative guidance. However, its clinical benefits remain to be seen.

Holographic patient tracking after bed movement for augmented reality neuronavigation using a head-mounted display

BACKGROUND

Holographic neuronavigation has several potential advantages compared to conventional neuronavigation systems. We present the first report of a holographic neuronavigation system with patient-to-image registration and patient tracking with a reference array using an augmented reality head-mounted display (AR-HMD).

METHODS

Three patients undergoing an intracranial neurosurgical procedure were included in this pilot study. The relevant anatomy was first segmented in 3D and then uploaded as holographic scene in our custom neuronavigation software. Registration was performed using point-based matching using anatomical landmarks. We measured the fiducial registration error (FRE) as the outcome measure for registration accuracy. A custom-made reference array with QR codes was integrated in the neurosurgical setup and used for patient tracking after bed movement.

RESULTS

Six registrations were performed with a mean FRE of 8.5 mm. Patient tracking was achieved with no visual difference between the registration before and after movement.

CONCLUSIONS

This first report shows a proof of principle of intraoperative patient tracking using a standalone holographic neuronavigation system. The navigation accuracy should be further optimized to be clinically applicable. However, it is likely that this technology will be incorporated in future neurosurgical workflows because the system improves spatial anatomical understanding for the surgeon.

Minimally invasive supratentorial neurosurgical approaches guided by Smartphone app and compass

The precise location in the scalp of specifically planned points can help to achieve less invasive approaches. This study aims to develop a smartphone app, evaluate the precision and accuracy of the developed tool, and describe a series of cases using the referred technique. The application was developed with the React Native framework for Android and iOS. A phantom was printed based on the patient's CT scan, which was used for the calculation of accuracy and precision of the method. The points of interest were marked with an "x" on the patient's head, with the aid of the app and a compass attached to a skin marker pen. Then, two experienced neurosurgeons checked the plausibility of the demarcations based on the anatomical references. Both evaluators marked the frontal, temporal and parietal targets with a difference of less than 5 mm from the corresponding intended point, in all cases. The overall average accuracy observed was 1.6 ± 1.0 mm. The app was used in the surgical planning of trepanations for ventriculoperitoneal (VP) shunts and for drainage of abscesses, and in the definition of craniotomies for meningiomas, gliomas, brain metastases, intracranial hematomas, cavernomas, and arteriovenous malformation. The sample consisted of 88 volunteers who exhibited the following pathologies: 41 (46.6%) had brain tumors, 17 (19.3%) had traumatic brain injuries, 16 (18.2%) had spontaneous intracerebral hemorrhages, 2 (2.3%) had cavernomas, 1 (1.1%) had arteriovenous malformation (AVM), 4 (4.5%) had brain abscesses, and 7 (7.9%) had a VP shunt placement. In cases approached by craniotomy, with the exception of AVM, straight incisions and minicraniotomy were performed. Surgical planning with the aid of the NeuroKeypoint app is feasible and reliable. It has enabled neurological surgeries by craniotomy and trepanation in an accurate, precise, and less invasive manner.

Time Efficiency in Stereotactic Robot-Assisted Surgery: An Appraisal of the Surgical Procedure and Surgeon's Learning Curve

BACKGROUND

Frame-based stereotactic procedures are still the gold standard in neurosurgery. However, there is an increasing interest in robot-assisted technologies. Introducing these increasingly complex tools in the clinical setting raises the question about the time efficiency of the system and the essential learning curve of the surgeon.

METHODS

This retrospective study enrolled a consecutive series of patients undergoing a robot-assisted procedure after first system installation at one institution. All procedures were performed by the same neurosurgeon to capture the learning curve. The objective read-out were the surgical procedure time (SPT), the skin-to-skin time, and the intraoperative registration time (IRT) after laser surface registration (LSR), bone fiducial registration (BFR), and skin fiducial registration (SFR), as well as the quality of the registration (as measured by the fiducial registration error [FRE]). The time measures were compared to those for a patient group undergoing classic frame-based stereotaxy.

RESULTS

In the first 7 months, we performed 31 robot-assisted surgeries (26 biopsies, 3 stereotactic electroencephalography [SEEG] implantations, and 2 endoscopic procedures). The SPT was depending on the actual type of surgery (biopsies: 85.0 ± 36.1 min; SEEG: 154.9 ± 75.9 min; endoscopy: 105.5 ± 1.1 min; p = 0.036). For the robot-assisted biopsies, there was a significant reduction in SPT within the evaluation period, reaching the level of frame-based surgeries (58.1 ± 17.9 min; p < 0.001). The IRT was depending on the applied registration method (LSR: 16.7 ± 2.3 min; BFR: 3.5 ± 1.1 min; SFR: 3.5 ± 1.6 min; p < 0.001). In contrast to BFR and SFR, there was a significant reduction in LSR time during that period (p = 0.038). The FRE differed between the applied registration methods (LSR: 0.60 ± 0.17 mm; BFR: 0.42 ± 0.15 mm; SFR: 2.17 ± 0.78 mm; p < 0.001). There was a significant improvement in LSR quality during the evaluation period (p = 0.035).

CONCLUSION

Introducing stereotactic, robot-assisted surgery in an established clinical setting initially necessitates a prolonged intraoperative preparation time. However, there is a steep learning curve during the first cases, reaching the time level of classic frame-based stereotaxy. Thus, a stereotactic robot can be integrated into daily routine within a decent period of time, thereby expanding the neurosurgeons' armamentarium, especially for procedures with multiple trajectories.

sEVD-smartphone-navigated placement of external ventricular drains

BACKGROUND

Currently, the trajectory for insertion of an external ventricular drain (EVD) is mainly determined using anatomical landmarks. However, non-assisted implantations frequently require multiple attempts and are associated with EVD malpositioning and complications. The authors evaluated the feasibility and accuracy of a novel smartphone-guided, angle-adjusted technique for assisted implantations of an EVD (sEVD) in both a human artificial head model and a cadaveric head.

METHODS

After computed tomography (CT), optimal insertion angles and lengths of intracranial trajectories of the EVDs were determined. A smartphone was calibrated to the mid-cranial sagittal line. Twenty EVDs were placed using both the premeasured data and smartphone-adjusted insertion angles, targeting the center of the ipsilateral ventricular frontal horn. The EVD positions were verified with post-interventional CT.

RESULTS

All 20 sEVDs (head model, 8/20; cadaveric head, 12/20) showed accurate placement in the ipsilateral ventricle. The sEVD tip locations showed a mean target deviation of 1.73° corresponding to 12 mm in the plastic head model, and 3.45° corresponding to 33 mm in the cadaveric head. The mean duration of preoperative measurements on CT data was 3 min, whereas sterile packing, smartphone calibration, drilling, and implantation required 9 min on average.

CONCLUSIONS

By implementation of an innovative navigation technique, a conventional smartphone was used as a protractor for the insertion of EVDs. Our ex vivo data suggest that smartphone-guided EVD placement offers a precise, rapidly applicable, and patient-individualized freehand technique based on a standard procedure with a simple, cheap, and widely available multifunctional device.

Challenging the osseous component of sphenoorbital meningiomas

Background

Intraosseous growth is a unique feature of sphenoorbital meningiomas (SOM). Its close relation to neurovascular structures limits complete surgical resection and possibly contributes to the high recurrence rate.

Objective

To evaluate the growth behavior of intraosseous remnants and develop a protocol for precise intraoperative visualization of intraosseous SOM.

Methods

We included 31 patients operated for SOM from 2004 to 2017. The growth velocity of the intraosseous tumor component was volumetrically calculated in 20 cases. To improve accuracy of image guidance, we implemented a specialized bone surface-based registration algorithm. For intraoperative bone visualization, we included CT in multimodality continuous image guidance in 23 patients. The extent of resection (EOR) was compared with a standard MR-only navigation group (n = 8).

Results

In 11/20 cases (55%), a progressive regrowth of the intraosseous SOM remnant was noted during a mean follow-up of 52 months (range 20–132 months). We observed a mean increase of 6.2 cm³ (range 0.2–23.7 cm³) per patient and side during the follow-up period. Bone surface-based registration was significantly more accurate than skin surface-based registration (mean 0.7 ± 0.4 mm and 1.9 ± 0.7 mm, p < 0.001). The EOR of the intraosseous component was significantly higher using CT + MRI navigation compared with controls (96% vs. 81%, p = 0.044).

Conclusion

Quantitative assessment of the biological behavior of intraosseous remnants revealed a continuous slow growth rate independent of the soft tumor component of more than half of SOM. According to our data, application of a multimodal image guidance provided high accuracy and significantly increased the resection rate of the intraosseous component of SOM.

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.

Intraoperative computed tomography as reliable navigation registration device in 200 cranial procedures

BACKGROUND

Registration accuracy is a main factor influencing overall navigation accuracy. Standard fiducial- or landmark-based patient registration is user dependent and error-prone. Intraoperative imaging offers the possibility for user-independent patient registration. The aim of this paper is to evaluate our initial experience applying intraoperative computed tomography (CT) for navigation registration in cranial neurosurgery, with a special focus on registration accuracy and effective radiation dose.

METHODS

A total of 200 patients (141 craniotomy, 19 transsphenoidal, and 40 stereotactic burr hole procedures) were investigated by intraoperative CT applying a 32-slice movable CT scanner, which was used for automatic navigation registration. Registration accuracy was measured by at least three skin fiducials that were not part of the registration process.

RESULTS

Automatic registration resulted in high registration accuracy (mean registration error: 0.93 ± 0.41 mm). Implementation of low-dose scanning protocols did not impede registration accuracy (registration error applying the full dose head protocol: 0.87 ± 0.36 mm vs. the low dose sinus protocol 0.72 ± 0.43 mm) while a reduction of the effective radiation dose by a factor of 8 could be achieved (mean effective radiation dose head protocol: 2.73 mSv vs. sinus protocol: 0.34 mSv).

CONCLUSION

Intraoperative CT allows highly reliable navigation registration with low radiation exposure.

Prospects and limitations of different registration modalities in electromagnetic ENT navigation

The present study examined electromagnetic tracking technology for ENT navigation. Five different registration modalities were compared and navigation accuracy was assessed. Four skull models were individually fabricated with a three-dimensional printer, based on patients' computer tomography datasets. Individual silicone masks were fitted for skin and soft tissue simulation. Five registration modalities were examined: (1) invasive marker, (2) automatic, (3) surface matching (AccuMatch), (4) anatomic landmarks, and (5) oral splint registration. Overall navigation accuracy and accuracy on selected anatomic locations were assessed by targeting 26 titanium screws previously placed over the skull. Overall navigation accuracy differed significantly between all registration modalities. The target registration error was 0.94 ± 0.06 mm (quadratic mean ± standard deviation) for the invasive marker registration, 1.41 ± 0.04 mm for the automatic registration, 1.59 ± 0.14 mm for the surface matching registration, and 5.15 ± 0.66 mm (four landmarks) and 4.37 ± 0.73 mm (five landmarks) for the anatomic landmark registration. Oral splint registration proved itself to be inapplicable to this navigation system. Invasive marker registration was superior on most selected anatomic locations. However, on the ethmoid and sphenoid sinus the automatic registration process revealed significantly lower target registration error values. Only automatic and surface registration met the accuracy requirements for noninvasive registration. Particularly, the automatic image-to-world registration reaches target registration error values on the anterior skull base which are comparable with the gold standard of invasive screw registration.

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.

A novel method for implementation of frameless StereoEEG in epilepsy surgery

BACKGROUND:

Stereoelectroencephalography (SEEG) is an invasive diagnostic procedure in epilepsy surgery that is usually implemented with frame-based methods.

OBJECTIVE:

To describe a new technique of frameless SEEG and report a prospective case series at a single center.

METHODS:

Image integration and planning of electrode trajectories were performed preoperatively on specialized software and exported to a Medtronic S7 StealthStation. Trajectories were implemented by frameless stereotaxy using percutaneous drilling and bolt insertion.

RESULTS:

Twenty-two patients went this technique, with the insertion of 187 intracerebral electrodes. Of 187 electrodes, 175 accurately reached their neurophysiological target, as measured by postoperative computed tomography reconstruction and multimodal image integration with preoperative magnetic resonance imaging. Four electrodes failed to hit their target due to extradural deflection, and 3 were subsequently resited satisfactorily. Eight electrodes were off target by a mean of 3.6 mm (range, 0.9-6.8 mm) due to a combination of errors in bolt trajectory implementation and bending of the electrode. There was 1 postoperative hemorrhage that was clinically asymptomatic and no postoperative infections. Sixteen patients were offered definitive cortical resections, and 6 patients were excluded from resective surgery.

CONCLUSION:

Frameless SEEG is a novel and safe method for implementing SEEG and is easily translated into clinical practice.

ABBREVIATIONS:

EA, accuracy of electrode delivery

SEEG, stereoelectroencephalography

Effect of registration mode on neuronavigation precision: an exploration of the role of random error

The aim of this paper is to analyze the variations in registration accuracy for computer-assisted surgical navigation using three different modes of registration, in order to explore the behavior of random error, and to highlight the precision of neuronavigation as a concept distinct from accuracy. The operational accuracy of three different registration modes (bone fiducials, scalp adhesive fiducials and an auto-registration mask) was evaluated in a total of 20 fresh cadaveric heads. The precision of the neuronavigation system was then assessed by evaluating the variation in the accuracy measurements associated with each registration mode. The coefficient of variation was employed to quantify the degree of variation in the attained accuracy using the following formula: Coefficient of variation = standard deviation/mean * 100. For external targets, the precision of the neuronavigation system was greatest with mask registration (43.75 and 51.41 for anterior and posterior external targets, respectively) and lowest with bone registration (65.30 and 67.17 for anterior and posterior external targets, respectively). For internal targets, the precision of the neuronavigation system was greatest with bone registration (47.69 and 42.6 for anterior and posterior internal targets, respectively) and lowest with mask registration (62.9 and 58.67 for anterior and posterior internal targets, respectively). The precision (reproducibility) of the neuronavigation system is another important quantity besides accuracy that characterizes the performance of the system. Understanding both of these quantities for a given registration mode enhances the use of a neuronavigation system in neurosurgery.

New prototype neuronavigation system based on preoperative imaging and intraoperative freehand ultrasound: system description and validation

PURPOSE

The aim of this report is to present IBIS (Interactive Brain Imaging System) NeuroNav, a new prototype neuronavigation system that has been developed in our research laboratory over the past decade that uses tracked intraoperative ultrasound to address surgical navigation issues related to brain shift. The unique feature of the system is its ability, when needed, to improve the initial patient-to-preoperative image alignment based on the intraoperative ultrasound data. Parts of IBIS Neuronav source code are now publicly available on-line.

METHODS

Four aspects of the system are characterized in this paper: the ultrasound probe calibration, the temporal calibration, the patient-to-image registration and the MRI-ultrasound registration. In order to characterize its real clinical precision and accuracy, the system was tested in a series of adult brain tumor cases.

RESULTS

Three metrics were computed to evaluate the precision and accuracy of the ultrasound calibration. 1) Reproducibility: 1.77 mm and 1.65 mm for the bottom corners of the ultrasound image, 2) point reconstruction precision 0.62-0.90 mm: and 3) point reconstruction accuracy: 0.49-0.74 mm. The temporal calibration error was estimated to be 0.82 ms. The mean fiducial registration error (FRE) of the homologous-point-based patient-to-MRI registration for our clinical data is 4.9 ± 1.1 mm. After the skin landmark-based registration, the mean misalignment between the ultrasound and MR images in the tumor region is 6.1 ± 3.4 mm.

CONCLUSIONS

The components and functionality of a new prototype system are described and its precision and accuracy evaluated. It was found to have an accuracy similar to other comparable systems in the literature.

Image-guided surgical planning using anatomical landmarks in the retrosigmoid approach

OBJECTIVE

The suboccipital lateral or retrosigmoid approach is the main neurosurgical approach to the cerebellopontine angle (CPA). It is mainly used in the treatment of CPA tumors and vascular decompression of cranial nerves. A prospective study using navigation registered with anatomical landmarks in order to identify the transverse and sigmoid sinuses junction (TSSJ) was carried out in a series of 30 retrosigmoid craniotomies. The goal of this study was to determine the accuracy of this navigation technique and to establish the relationship between the location of the asterion and the TSSJ.

METHODS

From March through November 2008, 30 patients underwent a retrosigmoid craniotomy for removal of CPA tumors or for surgical treatment of neurovascular syndromes. Magnetic resonance imaging (MRI) T1 sequences with gadolinium (FSPGR with FatSst, 1.5 T GE Signa) and frameless navigation (Vector vision, Brainlab) were used for surgical planning. Registration was performed using six anatomical landmarks. The position of the TSSJ indicated by navigation was the landmark to guide the craniotomy. The location of the asterion was compared with the position of the TSSJ. After craniotomy, the real TSSJ position was compared with the virtual position, as demonstrated by navigation.

RESULTS

There were 19 cases of vestibular schwannomas, 5 petroclival meningiomas, 3 trigeminal neuralgias, 1 angioblastoma, 1 epidermoid cyst and 1 hemifacial spasm. In all cases, navigation enabled the location of the TSSJ and the emissary vein, with an accuracy flaw below 2 mm. The asterion was located directly over the TSSJ in only seven cases. One patient had a laceration of the sigmoid sinus during the craniotomy.

CONCLUSIONS

Navigation using anatomical landmarks for registration is a reliable method in the localization of the TSSJ for retrosigmoid craniotomies and thereby avoiding unnecessary sinus exposure. In addition, the method proved to be fast and accurate. The asterion was found to be a less accurate landmark for the localization of the TSSJ using navigation.

Image-guided, stereotactic perforator flap surgery: a prospective comparison of current techniques and review of the literature

BACKGROUND

Image-guided stereotaxy is a recent advancement in imaging technology, allowing computer guidance to aid surgical planning and accuracy. Despite the use of multiple techniques for patient registration in several surgical specialities, only fiducial marker registration has been described for use in soft tissue reconstructive surgery. The current study comprises an evaluation of the current techniques available for this purpose.

METHODS

A cohort of nine consecutive patients planned for elective free flaps were recruited, with the first five patients (four for the abdominal wall and one anterolateral thigh donor site) undergoing fiducial marker registration with a variable number of fiducial markers in order to determine the optimal number of fiducial markers to be used. Four subsequent patients undergoing perforator flap surgery underwent registration using three available registration modalities: fiducial marker registration, surface matching pointer/landmark and surface matching laser registration.

RESULTS

For the abdominal wall, registration was not able to be achieved with five fiducial markers, and was successfully achieved in all cases with either six or seven fiducial markers. For the anterolateral thigh, registration was achieved with either nine or ten markers. The four patients who also underwent surface-landmark registration and 'Z-touch' laser surface matching registration all failed the registration process.

CONCLUSION

Stereotactic navigation is a useful adjunct to the preoperative imaging of perforator flaps. Fiducial marker registration was able to be achieved in all cases, can be successfully achieved with a low and predictable number of fiducial markers, is highly accurate, and was the only reliable registration process in our experience.