Fiducial Registration Error Research Articles

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

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

Evaluation of spherical fiducial localization in C‐arm cone‐beam CT using patient data

C-arm based cone-beam CT (CBCT) has been recently introduced as an in-situ 3D soft tissue imaging modality. When combined with image-guided navigation, it provides a streamlined clinical workflow with, potentially, improved interventional accuracy. A key component in these systems is image to patient registration. The most common registration method relies on fiducial markers placed on the patient's skin. The fiducials are localized in the volumetric image and in the interventional environment. When using C-arm CBCT, the small spatial extent of the volumetric reconstruction makes this registration approach challenging, as the volume must include both the anatomy of interest and the fiducials. The authors have previously proposed a semiautomatic localization approach that addresses this challenge, with evaluation carried out using anthropomorphic phantoms. To truly evaluate the algorithm's utility, the evaluation must be carried out using clinical data. In this article, the authors extend the evaluation of the approach to data sets acquired in a clinical trial. Nine CBCT data sets were obtained in three interventional radiology procedures as part of a clinical trial evaluating a commercial navigation system. Fiducials were localized in the volumetric coordinate system directly from the projection images using the evaluated localization approach. Localization was assessed using two quality measures fiducial registration error to quantify precision and fiducial localization error to quantify accuracy. The fiducials used in this study are 6 mm spheres embedded in a custom registration phantom used by the navigation system. In all cases, the proposed approach was able to localize all five fiducial markers embedded in the registration phantom. The approach's mean (std) fiducial registration error was 0.29 (0.13) mm. The mean (std) localization difference as compared to direct volumetric localization was 0.82 (0.34) mm. Based on the current evaluation using data from clinical cases, the authors conclude that the localization approach is sufficiently accurate for use in thoracic-abdominal interventions, and that it can simplify the current workflow while reducing cumulative radiation to the patient due to repeated CBCT scans.

Geometrical analysis of registration errors in point-based rigid-body registration using invariants

Point-based rigid registration is the method of choice for aligning medical datasets in diagnostic and image-guided surgery systems. The most clinically relevant localization error measure is the Target Registration Error (TRE), which is the distance between the image-defined target and the corresponding target defined on another image or on the physical anatomy after registration. The TRE directly depends on the Fiducial Localization Error (FLE), which is the discrepancy between the selected and the actual (unknown) fiducial locations. Since the actual locations of targets usually cannot be measured after registration, the TRE is often estimated by the Fiducial Registration Error (FRE), which is the RMS distance between the fiducials in both datasets after registration, or with Fitzpatrick's TRE (FTRE) formula. However, low FRE-TRE and FTRE-TRE correlations have been reported in clinical practice and in theoretical studies. In this article, we show that for realistic FLE classes, the TRE and the FRE are uncorrelated, regardless of the target location and the number of fiducials and their configuration, and regardless of the FLE magnitude distribution. We use a geometrical approach and classical invariant theory to model the FLE and derive its relation to the TRE and FRE values. We show that, for these FLE classes, the FTRE and TRE are also uncorrelated. Finally, we show with simulations on clinical data that the FRE-TRE correlation is low also in the neighborhood of the FLE-FRE invariant classes. Consequently, and contrary to common practice, the FRE and FTRE may not always be used as surrogates for the TRE.

Image registration of pre-procedural MRI and intra-procedural CT images to aid CT-guided percutaneous cryoablation of renal tumors

To determine whether a non-rigid registration (NRR) technique was more accurate than a rigid registration (RR) technique when fusing pre-procedural contrast-enhanced MR images to unenhanced CT images during CT-guided percutaneous cryoablation of renal tumors. Both RR and NRR were applied retrospectively to 11 CT-guided percutaneous cryoablation procedures performed to treat renal tumors (mean diameter; 23 mm). Pre-procedural contrast-enhanced MR images of the upper abdomen were registered to unenhanced intra-procedural CT images obtained just prior to the ablation. RRs were performed manually, and NRRs were performed using an intensity-based approach with affine and Basis-Spline techniques used for modeling displacement. Registration accuracy for each technique was assessed using the 95% Hausdorff distance (HD), Fiducial Registration Error (FRE) and the Dice Similarity Coefficient (DSC). Statistical differences were analyzed using a two-sided Student's t-test. Time for each registration technique was recorded. Mean 95% HD (1.7 mm), FRE (1.7 mm) and DSC (0.96) using the NRR technique were significantly better than mean 95% HD (6.4 mm), FRE (5.0 mm) and DSC (0.88) using the RR technique (P < 0.05 for each analysis). Mean registration times of NRR and RR techniques were 15.2 and 5.7 min, respectively. The non-rigid registration technique was more accurate than the rigid registration technique when fusing pre-procedural MR images to intra-procedural unenhanced CT images. The non-rigid registration technique can be used to improve visualization of renal tumors during CT-guided cryoablation procedures.

Real-Time 3-Dimensional Virtual Reality Navigation System with Open MRI for Breast-Conserving Surgery

The aim of this study was to report on the early experiences using a real-time 3-dimensional (3D) virtual reality navigation system with open MRI for breast-conserving surgery. We developed a real-time 3D virtual reality navigation system with open MRI, and evaluated the mismatch between the navigation system and real distance using a 3D phantom. Two patients with nonpalpable MRI-detected breast tumors underwent breast-conserving surgery under the guidance of the navigation system. An initial MRI for the breast tumor using skin-affixed markers was performed immediately before excision. A percutaneous intramammary dye marker was applied to delineate an excision line, and the computer software "3D Slicer" generated a real-time 3D virtual reality model of the tumor and the puncture needle in the breast. Excision of the tumor was performed in the usual manner along the excision line indicated with the dye. The resected specimens were carefully examined histopathologically. The mean mismatch between the navigation system and real distance was 2.01 +/- 0.32 mm when evaluated with the 3D phantom. Under guidance by the navigation system, a percutaneous intramammary dye marker was applied without any difficulty. Fiducial registration errors were 3.00 mm for patient no. 1, and 4.07 mm for patient no. 2. Histopathological examinations of the resected specimens of the 2 patients showed noninvasive ductal carcinoma in situ. The surgical margins were free of carcinoma cells. Real-time 3D virtual reality navigation system with open MRI is feasible for safe and accurate excision of nonpalpable MRI-detected breast tumors. Long-term outcomes of this technique should be evaluated further.

Electromagnetic Navigation for Thoracic Aortic Stent-graft Deployment: A Pilot Study in Swine

To determine the feasibility of electromagnetic tracking as a method to augment conventional imaging guidance for the safe delivery, precise positioning, and accurate deployment of thoracic aortic endografts. Custom guide wires were fabricated, and the delivery catheters for thoracic aortic endoprostheses were retrofitted with integrated electromagnetic coil sensors to enable real-time endovascular tracking. Preprocedure thoracic computed tomographic (CT) angiograms were obtained after the placement of fiducial skin patches on the chest wall of three anesthetized swine, enabling automatic registration. The stent-graft deployment location target near the subclavian artery was selected on the preprocedure CT angiogram. Two steps were analyzed: advancing a tracked glidewire to the aortic arch and positioning the tracked stent-graft assembly by using electromagnetic guidance alone. Multiple CT scans were obtained to evaluate the accuracy of the electromagnetic tracking system by measuring the target registration error, which compared the actual position of the tracked devices to the displayed "virtual" electromagnetic-tracked position. Postdeployment CT angiography and necropsy helped confirm stent-graft position and subclavian artery patency. A stent-graft was successfully delivered and deployed in each of the three animals by using real-time electromagnetic tracking alone. The mean fiducial registration error with autoregistration was 1.5 mm. Sixteen comparative scans were obtained to determine the target registration error, which was 4.3 mm +/- 0.97 (range, 3.0-6.0 mm) for the glidewire sensor coil. The mean target registration error for the stent-graft delivery catheter sensor coil was 2.6 mm +/- 0.7 (range, 1.9-3.8 mm). The mean deployment error for the stent-graft, defined as deployment deviation from the target, was 2.6 mm +/- 3.0. Delivery and deployment of customized thoracic stent-grafts with use of electromagnetic tracking alone is feasible and accurate in swine. Combining endovascular electromagnetic tracking with conventional fluoroscopy may further improve accuracy and be a more realistic multimodality approach.

Estimation of Optimal Fiducial Target Registration Error in the Presence of Heteroscedastic Noise

We study the effect of point dependent (heteroscedastic) and identically distributed anisotropic fiducial localization noise on fiducial target registration error (TRE). We derive an analytic expression, based on the concept of mechanism spatial stiffness, for predicting TRE. The accuracy of the predicted TRE is compared to simulated values where the optimal registration transformation is computed using the heteroscedastic errors in variables algorithm. The predicted values are shown to be contained by the 95% confidence intervals of the root mean square TRE obtained from the simulations.

Computer-Assisted Surgery in the Edentulous Jaw Based on 3 Fixed Intraoral Reference Points

In computer-assisted implantation surgery, the transfer of prosthodontic-guided planning to the operative site is usually based on a registration template. The precise repositioning of the registration template is crucial for high accuracy and is compromised in edentulous jaws. The purpose was to determine the in vitro registration and targeting accuracy for surgical navigation in the edentulous jaw based on 3 fixed intraoral reference points. Edentulous maxilla and mandible cadaver specimens were provided with 3 fixed reference-point screws. A resin template with matrices for the fixed reference-point screws was produced and connected to a Vogele-Bale-Hohner registration mouthpiece and external registration frame with a snap-lock system. Surgical implants were planned on computed tomographic data and the corresponding dental stone casts were drilled under guidance of an optical navigation system. For evaluation of the registration accuracy, fiducial registration error was recorded and application accuracy was evaluated by fusion of postsurgical computed tomographic scans of the drilled dental stone casts with the presurgical planning computed tomogram. In 9 maxillas and 5 mandibles, 14 registrations and 104 stone cast drillings were performed. The mean fiducial registration error was 0.49 +/- 0.14 mm (0.37 to 0.9 mm). The mean total error at the tip of the borehole was 0.88 +/- 0.65 mm (0.0 to 4.24 mm). The mean lateral errors were 0.51 +/- 0.49 mm (0.0 to 2.80 mm) at the base and 0.46 +/- 0.34 mm (0.0 to 1.5 mm) at the tip of the borehole, respectively. The mean angular error was 0.83 +/- 0.60 degrees (0.0 to 2.5 degrees ). Three fixed intraoral reference points successfully support a registration mouthpiece and provide in vitro registration and targeting accuracy that is comparable to tooth-supported registration templates or bone marker registration.

Guidelines for the placement of fiducial points in image‐guided neurosurgery

Point-pair registration is widely used to register the patient and the image space in image-guided neurosurgery. The registration accuracy at the target point is influenced by the distribution of the fiducial points, and it is not always easy to achieve a good distribution in clinical practice. We propose one original configuration and three variants of the distribution of the fiducial points, in which each fiducial point has a definite position on the head surface. These configurations are conceived by considering both the theoretical value of the target registration error (TRE) and practical constraints on the positioning of the fiducial points. These configurations can guide the surgeon to place fiducial points directly onto the patient's head. Experiments with real clinical data showed that when using the original configuration, the TRE in the whole skull was < 2 mm and the TRE in the whole brain was < 1.5 mm if the fiducial registration error was 2.5 mm. When using variants of the original configuration, small TRE can also be achieved in the corresponding surgical field. This study provides an easy-to-use approach to achieving good distribution of fiducial points in image-guided neurosurgery.

The implementation of an integrated computer‐assisted system for minimally invasive cardiac surgery

Preoperative planning and surgical navigation are two crucial aspects of a computer-assisted system for the success of minimally invasive cardiac surgery. In the first part, port placement planning was mainly discussed. We proposed an algorithm based on four criteria to achieve optimized placement. In the second part, an optical tracker was used to locate the thoracoscope and surgical instruments accurately and to show the relative positions between the thoracoscope, surgical instruments and the patient's anatomical structures. An image-matching technique was employed to help the surgeon locate the target, using real-time thoracoscopic video images during the procedure. In order to verify our proposed algorithms, several clinical planning cases were performed to compare our port placement algorithm to the traditional method. Both phantom test and animal study experiments were also done to demonstrate the validity of the target tracking of the system. Both the phantom test and the animal study revealed that the fiducial registration error (FRE) was 1.08 +/- 0.16 mm and system error was 5.05 +/- 0.67 mm, respectively. A novel computer-assisted system for minimally invasive cardiac surgery has been developed. This method has shown its capability to achieve the preoperative planning and real-time surgery navigation.

脳神経外科画像誘導手術におけるナビゲーション精度自動計測ソフトウェアの開発

An image-guided neurosurgery and neuronavigation system based on magnetic resonance imaging has been used as an indispensable tool for resection of brain tumors. Therefore, accuracy of the neuronavigation system, provided by periodic quality assurance (QA), is essential for image-guided neurosurgery. Two types of accuracy index, fiducial registration error (FRE) and target registration error (TRE), have been used to evaluate navigation accuracy. FRE shows navigation accuracy on points that have been registered. On the other hand, TRE shows navigation accuracy on points such as tumor, skin, and fiducial markers. This study shows that TRE is more reliable than FRE. However, calculation of TRE is a time-consuming, subjective task. Software for QA was developed to compute TRE. This software calculates TRE automatically by an image processing technique, such as automatic template matching. TRE was calculated by the software and compared with the results obtained by manual calculation. Using the software made it possible to achieve a reliable QA system.

MRI signal intensity based B‐Spline nonrigid registration for pre‐ and intraoperative imaging during prostate brachytherapy

To apply an intensity-based nonrigid registration algorithm to MRI-guided prostate brachytherapy clinical data and to assess its accuracy. A nonrigid registration of preoperative MRI to intraoperative MRI images was carried out in 16 cases using a Basis-Spline algorithm in a retrospective manner. The registration was assessed qualitatively by experts' visual inspection and quantitatively by measuring the Dice similarity coefficient (DSC) for total gland (TG), central gland (CG), and peripheral zone (PZ), the mutual information (MI) metric, and the fiducial registration error (FRE) between corresponding anatomical landmarks for both the nonrigid and a rigid registration method. All 16 cases were successfully registered in less than 5 min. After the nonrigid registration, DSC values for TG, CG, PZ were 0.91, 0.89, 0.79, respectively, the MI metric was -0.19 +/- 0.07 and FRE presented a value of 2.3 +/- 1.8 mm. All the metrics were significantly better than in the case of rigid registration, as determined by one-sided t-tests. The intensity-based nonrigid registration method using clinical data was demonstrated to be feasible and showed statistically improved metrics when compare to only rigid registration. The method is a valuable tool to integrate pre- and intraoperative images for brachytherapy.

CPOL: Complex phase order likelihood as a similarity measure for MR–CT registration

A novel similarity measure for registering magnetic resonance (MR) and computed tomography (CT) images has been designed and built. MR-CT registration methods often rely on the statistical intensity relationship between the images. The proposed similarity measure instead depends on the statistical relationship between the complex phase order between the images. By utilizing the complex phase order likelihood (CPOL) as a similarity measure, structural relationships instead of intensity relationships are explicitly used. This approach can be advantageous for MR-CT registration, where the intensities of the CT imagery have highly complex and nonlinear relationships with the intensities of corresponding MR imagery but simpler linear structural relationships. This new similarity measure has been tested on real MR-CT 3D volumes and has been evaluated based on fiducial registration error to determine alignment accuracy. Quantitative results show that CPOL is capable of achieving comparable alignment accuracy when compared to normalized mutual information, while being more robust to imaging artifacts such as noise.

The role of registration in accurate surgical guidance

Registration is presented as the central issue of surgical guidance. The focus is on the accuracy of approaches employed today, all of which use pre-operative images to guide surgery on rigid anatomy. The three most well-established approaches to guidance, namely the stereotactic frame, point fiducials, and surface matching, are examined in detail, together with two new approaches based on microstereotactic frames. It is shown that each method relies on the registration of points in the image to corresponding points in the operating room, and therefore that the error patterns associated with point registration are similar for all of them. Three types of registration error, namely fiducial localization error (FLE), fiducial registration error (FRE), and target registration error (TRE), are highlighted, as well as two additional guidance errors, namely target localization error and total targeting error, the latter of which is the overall error of the guidance system. Statistical relationships between TRE and FLE, between FRE and FLE, and between TRE, TLE, and TTE are given. Finally some myths concerning fiducial registration are highlighted.

Mapping ligament insertion sites onto bone surfaces in knee by co-registration of CT and digitization data

This paper describes a new methodology that enables mapping of the ligament insertion sites onto bone surfaces in the knee joint by co-registration of the data acquired using digitization and computed tomography (CT). Local coordinate systems on the distal femur and proximal tibia were established by three spherical fiducial markers rigidly affixed to each bone. The fiducial marker centroid locations were identified by a least-squares sphere-fitting algorithm. An optimization correction procedure was proposed to mitigate the effect of the target registration error (TRE) on the alignment of coordinate systems for co-registration. A test with four cadaveric specimens demonstrated successful mapping of insertion sites for five ligaments. Fiducial registration error (FRE) as measured by the differences in inter-marker distances between the two modalities was smaller than 2%. The optimization procedure corrected the insertion site invisibility or partial visibility problem and improved the overall mapping quality, as indicated by substantial reduction of the mean and dispersion of distances from digitized insertion site points to the bone surfaces.

An effective point-based registration tool for surgical navigation

Surgical navigation assists in endoscopic surgeries by enabling surgeons to see concealed lesions and surrounding organs. Successful surgical navigation depends on accurate registration between a medical image and a patient. For accurate point-based registration, it is important to determine the matching order and positions of the markers correctly. It is particularly difficult to determine the order and positions when part of the markers cannot be located on the patient's body or when they cannot be identified in the images. By using the automatic marker-matching option of the proposed tool, an optimum registration result can be obtained even with the partial loss of markers. In addition, this tool provides an intuitive marker selection interface that displays the registration error of each marker pair in different colors. The efficiency of the described tool in terms of the registration accuracy and time has been confirmed in more than 70 clinical applications. The fiducial registration errors were 1.28 + or - 1.09 mm in ear, nose, and throat surgery and 3.55 + or - 1.30 mm in liver tumor ablation therapy. The proposed automatic matching scheme with marker selection interface was particularly effective where the markers were partly lost or incorrectly identified.

Automatic image‐to‐world registration based on x‐ray projections in cone‐beam CT‐guided interventions

Intraoperative imaging offers a means to account for morphological changes occurring during the procedure and resolve geometric uncertainties via integration with a surgical navigation system. Such integration requires registration of the image and world reference frames, conventionally a time consuming, error-prone manual process. This work presents a method of automatic image-to-world registration of intraoperative cone-beam computed tomography (CBCT) and an optical tracking system. Multimodality (MM) markers consisting of an infrared (IR) reflective sphere with a 2 mm tungsten sphere (BB) placed precisely at the center were designed to permit automatic detection in both the image and tracking (world) reference frames. Image localization is performed by intensity thresholding and pattern matching directly in 2D projections acquired in each CBCT scan, with 3D image coordinates computed using backprojection and accounting for C-arm geometric calibration. The IR tracking system localized MM markers in the world reference frame, and the image-to-world registration was computed by rigid point matching of image and tracker point sets. The accuracy and reproducibility of the automatic registration technique were compared to conventional (manual) registration using a variety of marker configurations suitable to neurosurgery (markers fixed to cranium) and head and neck surgery (markers suspended on a subcranial frame). The automatic technique exhibited subvoxel marker localization accuracy (< 0.8 mm) for all marker configurations. The fiducial registration error of the automatic technique was (0.35 +/-0.01) mm, compared to (0.64 +/- 0.07 mm) for the manual technique, indicating improved accuracy and reproducibility. The target registration error (TRE) averaged over all configurations was 1.14 mm for the automatic technique, compared to 1.29 mm for the manual in accuracy, although the difference was not statistically significant (p = 0.3). A statistically significant improvement in precision was observed-specifically, the standard deviation in TRE was 0.2 mm for the automatic technique versus 0.34 mm for the manual technique (p = 0.001). The projection-based automatic registration technique demonstrates accuracy and reproducibility equivalent or superior to the conventional manual technique for both neurosurgical and head and neck marker configurations. Use of this method with C-arm CBCT eliminates the burden of manual registration on surgical workflow by providing automatic registration of surgical tracking in 3D images within approximately 20 s of acquisition, with registration automatically updated with each CBCT scan. The automatic registration method is undergoing integration in ongoing clinical trials of intraoperative CBCT-guided head and neck surgery.

Real-Time Estimation of FLE Statistics for 3-D Tracking With Point-Based Registration

Target registration error (TRE) has become a widely accepted error metric in point-based registration since the error metric was introduced in the 1990s. It is particularly prominent in image-guided surgery (IGS) applications where point-based registration is used in both image registration and optical tracking. In point-based registration, the TRE is a function of the fiducial marker geometry, location of the target and the fiducial localizer error (FLE). While the first two items are easily obtained, the FLE is usually estimated using an a priori technique and applied without any knowledge of real-time information. However, if the FLE can be estimated in real-time, particularly as it pertains to optical tracking, then the TRE can be estimated more robustly. In this paper, a method is presented where the FLE statistics are estimated from the latest measurement of the fiducial registration error (FRE) statistics. The solution is obtained by solving a linear system of equations of the form Ax=b for each marker at each time frame where x are the six independent FLE covariance parameters and b are the six independent estimated FRE covariance parameters. The A matrix is only a function of the tool geometry and hence the inverse of the matrix can be computed a priori and used at each instant in which the FLE estimation is required, hence minimizing the level of computation at each frame. When using a good estimate of the FRE statistics, Monte Carlo simulations demonstrate that the root mean square of the FLE can be computed within a range of 70-90 microm. Robust estimation of the TRE for an optically tracked tool, using a good estimate of the FLE, will provide two enhancements in IGS. First, better patient to image registration will be obtained by using the TRE of the optical tool as a weighting factor of point-based registration used to map the patient to image space. Second, the directionality of the TRE can be relayed back to the surgeon giving the surgeon the option of changing their strategy in order to improve the overall system accuracy and, in turn, the quality of procedure.

Error analysis for determination of accuracy of an ultrasound navigation system for head and neck surgery

Objective: The use of conventional CT- or MRI-based navigation systems for head and neck surgery is unsatisfactory due to tissue shift. Moreover, changes occurring during surgical procedures cannot be visualized. To overcome these drawbacks, we developed a novel ultrasound-guided navigation system for head and neck surgery. A comprehensive error analysis was undertaken to determine the accuracy of this new system.Materials and Methods: The evaluation of the system accuracy was essentially based on the method of error definition for well-established fiducial marker registration methods (point-pair matching) as used in, for example, CT- or MRI-based navigation. This method was modified in accordance with the specific requirements of ultrasound-guided navigation. The Fiducial Localization Error (FLE), Fiducial Registration Error (FRE) and Target Registration Error (TRE) were determined.Results: In our navigation system, the real error (the TRE actually measured) did not exceed a volume of 1.58 mm3 with a probability of 0.9. A mean value of 0.8 mm (standard deviation: 0.25 mm) was found for the FRE. The quality of the coordinate tracking system (Polaris localizer) could be defined with an FLE of 0.4 ± 0.11 mm (mean ± standard deviation). The quality of the coordinates of the crosshairs of the phantom was determined with a deviation of 0.5 mm (standard deviation: 0.07 mm).Conclusion: The results demonstrate that our newly developed ultrasound-guided navigation system shows only very small system deviations and therefore provides very accurate data for practical applications.

Image guided oral implantology and its application in the placement of zygoma implants

The application of zygoma implants proposes a successful treatment for functional reconstruction of maxillary defects. However, the placement of zygoma implants is not without risk due to anatomically complex operation sites. Aiming at minimizing the risks and improving the precision of the surgery, an image guided oral implantology system (IGOIS) is presented in this study to transfer the preoperative plan accurately to the operating theatre. The principle of IGOIS is introduced in detail, including the framework, 3D-reconstruction, preoperative planning, registration, and the motion tracking algorithm. The phantom experiment shows that fiducial registration error (FRE) and TRE (target registration error) of IGOIS are, respectively, 1.12 mm and 1.35 mm. With respect to the overall accuracy, the average distance deviations at the coronal and apical point of the implant are, respectively, 1.36 ± 0.59 mm and 1.57 ± 0.59 mm, while average angle deviation between the axes of the planned and the actual implant is 4.1° ± 0.9°. A clinical report for a patient with a severely atrophic maxilla demonstrates that the major advantage of this computer-aided navigation technology lies in its accuracy, reliability, and flexibility.