Accuracy Of Surgical Navigation Research Articles

Semi-Quantitative Assessment of Surgical Navigation Accuracy During Endoscopic Sinus Surgery in a Real-World Environment.

Although surgical navigation is commonly used in rhinologic surgery, data on real world performance are sparse because of difficulties in collecting measurements for target registration error (TRE). Despite publications showing submillimeter TRE, surgeons do report TRE of >3 mm. We describe a novel method for assessing TRE during surgery and report findings with this technique. The TruDi navigation system (Acclarent, Irving, CA) was registered using a contour-based protocol. The surgeon estimated target registration error (e-TRE) at up to 8 points (anatomic regions of interest [ROI]) during endoscopic sinus surgery (ESS). System logs were used to simulate the localization for quantitative assessment of TRE (q-TRE). We performed 98 localizations in 20 patients. The ROI in the sinuses were ethmoid (33 sites), maxillary (28 sites), frontal (17 sites), and sphenoid (22 sites). For localizations, mean qTRE and eTRE were 0.93 and 0.84 mm (P = .56). Notably, 80% of qTRE and 81% of eTRE were 1 mm or less. Mean qTRE and eTRE were less for attending-performed registrations at the maxillary, frontal and sphenoid. Surgical navigation accuracy, as measured by qTRE and eTRE, approaches 1 mm or better at all sinus sites in a real-world setting for 80% of localizations. The qTRE method provides a unique approach for assessing TRE. Surgeons underestimate TRE (overstate navigation accuracy), but this difference does not seem to be statistically significant. Registration performed by trainees yields higher TRE than registration performed by attendings. These data may be used to guide navigation optimization.

Surgical Navigation in the Anterior Skull Base Using 3-Dimensional Endoscopy and Surface Reconstruction

Image guidance is an important adjunct for endoscopic sinus and skull base surgery. However, current systems require bulky external tracking equipment, and their use can interrupt efficient surgical workflow. To evaluate a trackerless surgical navigation system using 3-dimensional (3D) endoscopy and simultaneous localization and mapping (SLAM) algorithms in the anterior skull base. This interventional deceased donor cohort study and retrospective clinical case study was conducted at a tertiary academic medical center with human deceased donor specimens and a patient with anterior skull base pathology. Participants underwent endoscopic endonasal transsphenoidal dissection and surface model reconstruction from stereoscopic video with registration to volumetric models segmented from computed tomography (CT) and magnetic resonance imaging. To assess the fidelity of surface model reconstruction and accuracy of surgical navigation and surface-CT model coregistration, 3 metrics were calculated: reconstruction error, registration error, and localization error. In deceased donor models (n = 9), high-fidelity surface models of the posterior wall of the sphenoid sinus were reconstructed from stereoscopic video and coregistered to corresponding volumetric CT models. The mean (SD; range) reconstruction, registration, and localization errors were 0.60 (0.24; 0.36-0.93), 1.11 (0.49; 0.71-1.56) and 1.01 (0.17; 0.78-1.25) mm, respectively. In a clinical case study of a patient who underwent a 3D endoscopic endonasal transsphenoidal resection of a tubercular meningioma, a high-fidelity surface model of the posterior wall of the sphenoid was reconstructed from intraoperative stereoscopic video and coregistered to a volumetric preoperative fused CT magnetic resonance imaging model with a root-mean-square error of 1.38 mm. The results of this study suggest that SLAM algorithm-based endoscopic endonasal surgery navigation is a novel, accurate, and trackerless approach to surgical navigation that uses 3D endoscopy and SLAM-based algorithms in lieu of conventional optical or electromagnetic tracking. While multiple challenges remain before clinical readiness, a SLAM algorithm-based endoscopic endonasal surgery navigation system has the potential to improve surgical efficiency, economy of motion, and safety.

Accuracy of surgical navigation for patient-specific reconstructions of orbital fractures: A systematic review and meta-analysis

This systematic review and meta-analysis aimed to review the recent literature on the technical accuracy of surgical navigation for patient-specific reconstruction of orbital fractures using a patient-specific implant, and to compare surgical navigation with conventional techniques. A systematic literature search was conducted in PubMed (Medline), Embase, Web of Science, and Cochrane (Core Collection) databases on May 16, 2023. Literature comparing surgical navigation with a conventional method using postoperative three-dimensional computed tomography imaging was collected. Only articles that studied at least one of the following outcomes were included: technical accuracy (angular accuracy, linear accuracy, volumetric accuracy, and degree of enophthalmos), preoperative and perioperative times, need for revision, complications, and total cost of the intervention. MINORS criteria were used to evaluate the quality of the articles. After screening 3733 articles, 696 patients from 27 studies were included. A meta-analysis was conducted to evaluate volumetric accuracy and revision rates. Meta-analysis proved a significant better volumetric accuracy (0.93 cm3 ± 0.47 cm3) when surgical navigation was used compared with conventional surgery (2.17 cm3 ± 1.35 cm3). No meta-analysis of linear accuracy, angular accuracy, or enophthalmos was possible due to methodological heterogeneity. Surgical navigation had a revision rate of 4.9%, which was significantly lower than that of the conventional surgery (17%). Costs were increased when surgical navigation was used. Studies with higher MINORS scores demonstrated enhanced volumetric precision compared with traditional approaches. Surgical navigation has proven effective in reducing revision rates compared to conventional approaches, despite increased costs.

Model-based image updating in deep brain stimulation with assimilation of deep brain sparse data.

Accuracy of electrode placement for deep brain stimulation (DBS) is critical to achieving desired surgical outcomes and impacts the efficacy of treating neurodegenerative diseases. Intraoperative brain shift degrades the accuracy of surgical navigation based on preoperative images. We extended a model-based image updating scheme to address intraoperative brain shift in DBS surgery and improved its accuracy in deepbrain. We evaluated 10 patients, retrospectively, who underwent bilateral DBS surgery and classified them into groups of large and small deformation based on a 2 mm subsurface movement threshold and brain shift index of 5%. In each case, sparse brain deformation data were used to estimate whole brain displacements and deform preoperative CT (preCT) to generate updated CT (uCT). Accuracy of uCT was assessed using target registration errors (TREs) at the Anterior Commissure (AC), Posterior Commissure (PC), and four calcification points in the sub-ventricular area by comparing their locations in uCT with their ground truth counterparts in postoperative CT (postCT). In the large deformation group, TREs were reduced from 2.5 mm in preCT to 1.2 mm in uCT (53% compensation); in the small deformation group, errors were reduced from 1.25 to 0.74 mm (41%). Average reduction of TREs at AC, PC and pineal gland were significant, statistically (p ⩽ 0.01). With more rigorous validation of model results, this study confirms the feasibility of improving the accuracy of model-based image updating in compensating for intraoperative brain shift during DBS procedures by assimilating deep brain sparsedata.

Limitations of surgical navigation in minimally invasive surgery for colorectal cancer

Background: Surgical navigation could give direct benefits due to an improvement in the quality of surgery. Well-targeted and guided cancer resection could improve patient survival, lead to a significant reduction of intraoperative complications and improvement of patient quality of life by reducing the incidence of nerve and vessel injuries. The objective of the study is to evaluate the feasibility and accuracy of surgical navigation during colorectal cancer surgery.

A Vision-Based Navigation System With Markerless Image Registration and Position-Sensing Localization for Oral and Maxillofacial Surgery

The quality of oral and maxillofacial surgery (OMS) significantly depends on the accuracy of surgical navigation. In this article, a vision-based markerless surgical navigation system is developed to overcome the shortcomings in the currently available technologies. Registration methods both for patient and surgical instrument tracking are improved to increase the navigation performance. For patient-image registration, we propose an efficient texture-less pose estimation method using only shape information. An innovative strategy is developed to effectively reject the outliers and improve the pose accuracy, which is the first attempt at introducing geometric matching information to guide PnP calculation. For surgical instrument tracking, a position-sensing marker is used to achieve robust and convenient instrument localization with high accuracy. Experiments were conducted on the 3-D-printed maxilla and mandible models to evaluate the navigation performance. Evaluation results validate the effectiveness of the proposed pose estimation method in improving the pose accuracy for texture-less teeth. Besides, it is revealed that the position-sensing marker can be localized with high accuracy even under nonideal visibility conditions, which expands the motion range of the instrument and decreases the size of the tool. The entire system has a sufficiently small target registration error (TRE). These experimental results have verified that the proposed surgical navigation system can provide practical guidance for OMS with satisfactory accuracy.

Database-driven patient-specific registration error compensation method for image-guided laparoscopic surgery

A surgical navigation system helps surgeons understand anatomical structures in the operative field during surgery. Patient-to-image registration, which aligns coordinate systems between the CT volume and a positional tracker, is vital for accurate surgical navigation. Although a point-based rigid registration method using fiducials on the body surface is often utilized for laparoscopic surgery navigation, precise registration is difficult due to such factors as soft tissue deformation. We propose a method that compensates a transformation matrix computed using fiducials on the body surface based on the analysis of positional information in the database. We built our database by measuring the positional information of the fiducials and the guidance targets in both the CT volume and positional tracker coordinate systems through previous surgeries. We computed two transformation matrices: using only the fiducials and using only the guidance targets in all the data in the database. We calculated the differences between the two transformation matrices in each piece of data. The compensation transformation matrix was computed by averaging these difference matrices. In this step, we selected the data from the database based on the similarity of the fiducials and the configuration of the guidance targets. We evaluated our proposed method using 20 pieces of data acquired during laparoscopic gastrectomy for gastric cancer. The locations of blood vessels were used as guidance targets for computing target registration error. The mean target registration errors significantly decreased from 33.0 to 17.1 mm before and after the compensation. This paper described a registration error compensation method using a database for image-guided laparoscopic surgery. Since our proposed method reduced registration error without additional intraoperative measurements during surgery, it increases the accuracy of surgical navigation for laparoscopic surgery.

Dynamic navigation for prosthetically driven zygomatic implant placement in extensive maxillary defects: Results of a prospective case series.

Zygomatic implants (ZIs) that are anchored in remote locations can significantly improve the retention and stability of prosthetic obturation in maxillary defect sites without the need for complex surgical reconstruction. However, ZI placement without alveolar bone guidance is challenging, especially when identifying the ideal three-dimensional location of the "coronal part" of the implant fixture for further rehabilitation. To investigate the feasibility and accuracy of surgical navigation for ZI placement using prosthetically driven plans to treat extensive maxillary defects. Software was used to virtually plan the number and distribution of ZIs for maxillary defect patients according to the existing residual maxillofacial bone. The "coronal part" of the ZI was identified based on the existing maxillodental prosthetic flange, virtually planned infrastructure framework and superstructure. ZI placement was fully guided by surgical navigation. Ten patients were enrolled. One patient had loose reflective spheres, which resulted in an inaccurate back-reflection of the position during navigation. A total of 27 ZIs in the remaining 9 patients were placed uneventfully. The mean of the "coronal part" of the ZI, entry point of the zygomatic bone, apical deviation, and apical angle deviation were 1.50 mm, 1.39 mm, 1.95 mm, and 2.32°, respectively. A Computer-aided design and computer-aided manufacture milled bar and additional attachments were fabricated according to preoperative planning. No osseointegrated implant loss was detected. Six ZIs in three patients received implant surface polishing to reduce soft tissue irritation, and one ZI was submerged. Surgical navigation facilitated the accurate and feasible placement of prosthetically driven ZIs that were preoperatively planned in patients with extensive maxillary defects.

A Deep Learning-Based Approach for Automated Coarse Registration (ACR) of Image-Guided Surgical Navigation

Coarse registration is the first step in determining the accuracy of surgical navigation. The purpose of this study was to present an automated coarse registration (ACR) methodology to improve the convenience and accuracy. For this purpose, a deep learning model based on a convolutional neural network was used. The input variable used for learning was virtual patient point-cloud (VPPC) generated based on medical image. Output variables were values of coordinate transformation obtained in the process of sending the VPPC to the surrounding space of a medical image. The ACR model consisted of a step of extracting global features of point-clouds from medical image and patient space and a step of predicting the information of 3-dimensional coordinate transformation through global features. The coefficients of determination that evaluated the similarity between predicted and actual rotation values on the x, y, and z axes were 0.993, 0.989, and 0.990, respectively. The coefficients of determination of the predicted and actual translation values on x, y, and z were 0.993, 0.989, and 0.994, respectively. As a result of coarse registration of three phantoms using the ACR, the registration errors between the patient and the computed tomography point-cloud were 3.813 ± 0.792, 3.786 ± 0.734, and 3.653 ± 0.668 mm, which were significantly improved over the conventional method’s registration error (4.671 ± 0.738, 4.865 ± 0.776, and 4.670 ± 0.455 mm). The proposed method can provide convenience in the pre-operative preparation stage by automating coarse registration. It is expected that repeatability and reproducibility can be provided by eliminating random errors that might occur by the operator.

Contour Map Point Distribution and Surgeon Experience Level Affect Accuracy of Surgical Navigation in a Pilot Study.

Reliable use of surgical navigation depends upon the registration process. The gold standard is paired-point registration with bone-anchored fiducials, but contour-map registration is more practical. Surgeons may employ variable contour maps and less experienced team members often perform this critical step. The impact of these practices on target registration error (TRE) is not well-studied. A dry lab set-up consisting of a navigation system (Fusion ENT, Medtronic, Jacksonville, FL) and a sinus phantom with 2 mm radiopaque spheres in the sphenoid and ethmoid regions was developed. A CT (0.625 mm slice thickness) was obtained. Registration was performed with a contour-based protocol. Accuracy was determined using the software's distance measurement tool. Registration was performed with narrow-field (NF; forehead points medial to the mid-pupillary line) and wide field (WF; entire forehead) contour maps. An experienced rhinologist and a resident surgeon performed each registration in triplicate and TRE at the sphenoid and ethmoid markers was measured in triplicate. WF mapping had a lower TRE than NF (1.09 mm [95% Confidence Interval (CI) 0.96-1.22] vs 1.68 mm [95% CI 1.50-1.86]). The experienced surgeon had a lower TRE compared to the resident (1.21 mm [95% CI 1.08-1.34] vs 1.54 mm [95% CI 1.35-1.74]). In this navigation model, wide field mapping offers better accuracy than narrow-field mapping, and an experienced surgeon seemed to achieve better accuracy than a resident surgeon. These observations have potential implications for the use of this technology in the operating room.

Development and Evaluation of CT-to-3D Ultrasound Image Registration Algorithm in Vertebral Phantoms for Spine Surgery.

Posterior spinal fusion surgery requires careful insertion of screws into the spine to avoid neurologic injury. While current systems use CT-scans, three-dimensional ultrasound (3DUS) could provide guidance by reconstructing the vertebral surface, and then registering a pre-operative vertebral model to that surface for localization. The aim of this study was to evaluate the accuracy and processing time of a custom CT-3DUS registration algorithm. A phantom human vertebra was 3D-printed and scanned with a motion capture-based 3D ultrasound (3DUS) system. Image registration was performed that included a pre-alignment phase using vertebral symmetry information, and then comparing Gaussian pyramid intensity-based registration with iterative-closest-point registration for final transformations. Image registration was performed 192 times while surgical registration between CT and real-world position was performed 84 times. The accuracy of image registration (CT-to-3DUS) was 0.3 ± 0.2mm and 0.9 ± 0.8° completed in 13.3 ± 2.9s. The surgical navigation accuracy (CT model to real-world position) of the system was 1.2 ± 0.5mm and 2.2 ± 2.0° completed in 16.2 ± 3.0s. Both meet accuracy thresholds of < 2mm and < 5° required for the surgery. A feasibility study on porcine spine qualitatively showed appropriate overlapping anatomy in CT-3DUS registrations. The usage of 3D ultrasound for navigation has demonstrated accuracy to provide radiation-free image guidance for spine surgery.

Evolutionarily Optimized Electromagnetic Sensor Measurements for Robust Surgical Navigation

Miniaturized electromagnetic sensors are increasingly introduced to navigate surgical instruments to anatomical targets during minimally invasive procedures, such as endoscopic surgery. These sensors are usually attached at the distal tips of surgical instruments to track their three-dimensional motion represented by the position and orientation in six degrees of freedom. Unfortunately, these sensors suffer from inaccurate measurements and jitter errors due to the patient movement (e.g., respiratory motion) and magnetic field distortion. This paper proposes an evolutionary computing strategy to optimize the sensor measurements and improve the tracking accuracy of surgical navigation. We modified two evolutionary computation algorithms and proposed adaptive particle swarm optimization (APSO) and observation-boosted differential evolution (OBDE) to enhance the navigation accuracy. The experimental results demonstrate that our modified algorithms to evolutionarily optimize electromagnetic sensor measurements can critically reduce the tracking error from 4.8 to 2.9 mm. In particular, OBDE outperforms APSO for electromagnetic endoscopic navigation.

Augmented reality navigation for spinal pedicle screw instrumentation using intraoperative 3D imaging

BACKGROUND CONTEXTDue to recent developments in augmented reality with head-mounted devices, holograms of a surgical plan can be displayed directly in the surgeon's field of view. To the best of our knowledge, three dimensional (3D) intraoperative fluoroscopy has not been explored for the use with holographic navigation by head-mounted devices in spine surgery. PURPOSETo evaluate the surgical accuracy of holographic pedicle screw navigation by head-mounted device using 3D intraoperative fluoroscopy. STUDY DESIGNIn this experimental cadaver study, the accuracy of surgical navigation using a head-mounted device was compared with navigation with a state-of-the-art pose-tracking system. METHODSThree lumbar cadaver spines were embedded in nontransparent agar gel, leaving only commonly visible anatomy in sight. Intraoperative registration of preoperative planning was achieved by 3D fluoroscopy and fiducial markers attached to lumbar vertebrae. Trackable custom-made drill sleeve guides enabled real-time navigation. In total, 20 K-wires were navigated into lumbar pedicles using AR-navigation, 10 K-wires by the state-of-the-art pose-tracking system. 3D models obtained from postexperimental CT scans were used to measure surgical accuracy. MF is the founder and shareholder of Incremed AG, a Balgrist University Hospital start-up focusing on the development of innovative techniques for surgical executions. The other authors declare no conflict of interest concerning the contents of this study. No external funding was received for this study. RESULTSNo significant difference in accuracy was measured between AR-navigated drillings and the gold standard with pose-tracking system with mean translational errors between entry points (3D vector distance; p=.85) of 3.4±1.6 mm compared with 3.2±2.0 mm, and mean angular errors between trajectories (3D angle; p=.30) of 4.3°±2.3° compared with 3.5°±1.4°. CONCLUSIONSIn conclusion, holographic navigation by use of a head-mounted device achieve accuracy comparable to the gold standard of high-end pose-tracking systems. CLINICAL SIGNIFICANCEThese promising results could result in a new way of surgical navigation with minimal infrastructural requirements but now have to be confirmed in clinical studies.

The effect of the configurations of fiducial markers on accuracy of surgical navigation in zygomatic implant placement: An in vitro study.

Real-time surgical navigation has been increasingly applied in implant placement. The initial registration procedures were found to substantially affect the overall accuracy of the system for zygomatic implant placement, but the exact number and distribution of fiducial markers was yet undetermined. This study aimed to determine the minimal numbers and optimal distributions of fiducial markers to achieve clinically acceptable accuracy in surgical navigation, through systematically analyzing the effects of different setups of fiducial markers on target registration errors (TRE). A maxillary phantom with bone-anchored fiducial markers was scanned using cone beam computed tomography, followed by data processing on Brainlab, a commercially available navigation system. A total of 10 mini-screws were inserted in the edentulous maxilla for configuration of fiducial markers, with another two mini-screws as implant targets to assess TRE in zygomatic bone. Data were then collected in nine configurations with distinct fiducial numbers and positions. Statistical analyses were performed with SPSS. Accuracy of the surgical navigation system was found to depend on both the numbers and positions of fiducial markers. No significant difference was observed in accuracy among groups with eight fiducials and with polygon span distribution (P > .05). When the fiducial numbers decreased to less than six, the markers inserted in a regular triangle area were more precise than in an inverse triangle configuration. When the number of fiducials was five with a polygonal distribution, a low TRE value of 0.59 mm was detected, which was comparable to the accuracy with more than eight fiducials in the study. A scattered distribution with a polygon span with at least five fiducial markers in the edentulous maxilla for registration seems to achieve an acceptable TRE value with a high accuracy for navigation in zygomatic implant placement.

Noninvasive Registration Strategies and Advanced Image Guidance Technology for Submillimeter Surgical Navigation Accuracy in the Lateral Skull Base.

Combining novel registration strategies and advanced image guidance technology enable submillimeter accurate and noninvasive navigation for middle ear and lateral skull base surgery. Surgery in the internal auditory canal and the petrous apex present a cognitive and motoric challenge for the surgeon. To date, image guidance rarely assists these procedures, mainly due to the lack of navigation solutions providing submillimeter accuracy associated with low cost in terms of invasiveness, radiation, and time. This study proposes an approach to clinically viable image guidance by using a combination of advanced image guidance technology and noninvasive registration strategies. Based on accuracy-optimized optical tracking hardware (accuracy: 0.05 ± 0.025 mm), 14 novel registration strategies were investigated. In human cadaveric temporal bone specimens n = 36 registration attempts per strategy were conducted. Target registration errors at 10 anatomical targets were measured. The most accurate registration strategies were identified as paired-point-matching using eight landmarks located in the external auditory canal and middle ear and surface matching using combined surfaces of the middle ear, the external auditory canal and the mastoid cortex yielding target registration errors of 0.51 ± 0.28 mm and 0.36 ± 0.13 mm respectively. This study demonstrates submillimeter TREs achieved with noninvasive, anatomy-based registration strategies in combination with advanced image guidance technology. Clinically viable LSB and ME navigation is realized without additional invasiveness, radiation and time associated with artificial fiducials. The appropriate registration strategy can be chosen by the surgeon depending on the pathology and surgical approach.

Progressive internal landmark registration for surgical navigation in laparoscopic gastrectomy for gastric cancer.

A surgical navigation system supports the comprehension of anatomical information during surgery. Patient-to-image registration is the alignment process between CT volume and patient coordinate systems. Achieving accurate registration in the surgical navigation of laparoscopic surgery is very challenging due to soft tissue deformation. This paper presents a new patient-to-image registration method based on internal anatomical landmarks for improving registration accuracy in the surgical navigation of laparoscopic gastrectomy for gastric cancer. Our proposed registration method progressively utilizes internal anatomical landmarks. In laparoscopic gastrectomy for gastric cancer, the surgeon cuts the blood vessels around the stomach. The positions of the cut vessels are sequentially used as fiducials for registration during surgery. The proposed method uses a weighted point-based registration method for computing the transformation matrix using the fiducials both on the body surface and on the blood vessels. When a blood vessel is cut during surgery, the proposed progressive registration method measures the cut vessel's position and computes a transformation matrix by adding the cut vessel as a fiducial. We applied our proposed progressive registration method using the positional information of the blood vessels acquired during laparoscopic gastrectomy in 20 cases. We evaluated it using target registration error in four blood vessels. The average target registration error in the four blood vessels was 12.6mm and ranged from 2.1 to 32.9mm. Since the proposed progressive registration can reduce registration error, our proposed method is very useful for the surgical navigation of laparoscopic gastrectomy. Our proposed progressive registration method might increase the accuracy of surgical navigation in laparoscopic gastrectomy.

The accuracy of surgical navigation in urologic surgery – a preliminary study

The accuracy of surgical navigation in urologic surgery – a preliminary study

A hybrid method to improve target registration accuracy in surgical navigation

Background: The accuracy of surgical navigation depends greatly on that of registration between the patient and the medical image. Point-based registration has been the most common and reliable method, which typically uses skin markers. Unfortunately, high registration accuracy around the markers is not sustained at targets deeply seated within the body. To address such increase in target registration error (TRE), we proposed a hybrid point-based registration method that incorporates anatomical landmarks near the target. Material and methods: Ultrasound calibration is performed with an optical tracker for coordinate frame conversion of image coordinates into the real world. With the calibrated ultrasound probe, we could non-invasively obtain landmark positions near the target, being used together with skin markers for registration. Results: In the experiment, we examined registration accuracies achieved with and without use of an anatomical landmark. We confirmed that using an additional anatomical landmark in registration resulted in an increase in fiducial regsitration error (FRE), but a significant decrease in TRE (p < 0.001). Conclusion: We proposed and demonstrated the effectiveness of a hybrid method that uses both artificial and anatomical landmarks for patient-to-image registration. The experimental results confirmed that an improvement in TRE was evident by the proposed method, suggesting its feasibility in various spinal surgeries.

Assessment of the accuracy of infrared and electromagnetic navigation using an industrial robot: Which factors are influencing the accuracy of navigation?

Our objectives were to detect factors that influence the accuracy of surgical navigation (magnitude of deformity, plane of deformity, position of the navigation bases) and compare the accuracy of infrared with electromagnetic navigation. Human cadaveric femora were used. A robot connected with a computer moved one of the bony fragments in a desired direction. The bases of the infrared navigation (BrainLab) and the receivers of the electromagnetic device (Fastrak-Pohlemus) were attached to the proximal and distal parts of the bone. For the first part of the study, deformities were classified in eight groups (e.g., 0 to 5(°)). For the second part, the bases were initially placed near the osteotomy and then far away. The mean absolute differences between both navigation system measurements and the robotic angles were significantly affected by the magnitude of angulation with better accuracy for smaller angulations (p < 0.001). The accuracy of infrared navigation was significantly better in the frontal and sagittal plane. Changing the position of the navigation bases near and far away from the deformity apex had no significant effect on the accuracy of infrared navigation; however, it influenced the accuracy of electromagnetic navigation in the frontal plane (p < 0.001). In conclusion, the use of infrared navigation systems for corrections of small angulation-deformities in the frontal or sagittal plane provides the most accurate results, irrespectively from the positioning of the navigation bases.

Accuracy of surgical navigation for localization and orientation of femoral stem in total hip arthroplasty

Objective To evaluate the accuracy of surgical navigation for localization and orientation of the femoral stem component in total hip arthroplasty, nethods In the hypothesized space, 3-D images of femoral stem were reconstructed. The coronal, sagittal and horizontal axes and scale divisions were established to calculate the displacement and rotation of the stem. Matching between the stem and its 3-D images was performed while the stem was moved in various distances and angles on the digital motion-platform. Then the actual change in the position of the implant and the caleulative data obtained from the navigation system were compared to evaluate the accuracy. Results The mean difference in displacement between the measurements and the actual changes was (1.01 ±0.47) mm, and the mean difference in the measured and actual angles was 1.09°±0.62°. The duplicate test found no significant difference (t = 0.238, P > 0.05). Conclusion Precise placement of the stem in the desired location and orientation can be achieved by the navigation system in the total hip arthroplasty. Key words: Arthroplasty, replacement, hip; Prosthesis fitting; Surgery, computer-assisted