Target Registration Error Values Research Articles

The Effect of Fiducial Marker Number and Configuration on Registration Error in Dynamic Implant Surgery.

Objective: To verify the effect of fiducial marker number and configuration on target registration error (TRE) for dynamic computer-aided zygomatic implant surgery. Material and Methods: All patients who underwent zygomatic implant surgery with navigation from January 2018 to December 2021 were enrolled. For each patient, 6 to 8 miniscrews were placed intraorally as fiducial markers before the surgery. After the registration procedure, the TRE, which represents the distance between the target of the image space and the real position of the fiducial markers, was calculated. SPSS (22.0) was used for statistical analysis. Results: A total of 325 titanium miniscrews were placed in 47 patients who underwent zygomatic implant placement by navigation. The lowest TRE was 0.2 mm, compared to the highest TRE of 1.9 mm. There was no significant difference in the mean TRE value among the different titanium miniscrew groups (P = .07). A total of 8 miniscrews in 7 patients were lost in the maxillary tuberosity area prior to and during navigation surgery, which resulted in an irregular polygonal distribution of fiducial markers. However, there was no statistically significant difference in TRE between a polygonal distribution (0.62 ± 0.35 mm) and an irregular polygonal distribution (0.68 ± 0.33 mm) (P = .35). Conclusion: A scattered, polygonal distribution with of a minimum of five fiducial markers in an edentulous maxilla could achieve acceptable TRE values in registration. It seems that the registration error was not influenced by the absence of one corner in a polygon distribution.

Automatic rigid image Fusion of preoperative MR and intraoperative US acquired after craniotomy

BackgroundNeuronavigation of preoperative MRI is limited by several errors. Intraoperative ultrasound (iUS) with navigated probes that provide automatic superposition of pre-operative MRI and iUS and three-dimensional iUS reconstruction may overcome some of these limitations. Aim of the present study is to verify the accuracy of an automatic MRI – iUS fusion algorithm to improve MR-based neuronavigation accuracy.MethodsAn algorithm using Linear Correlation of Linear Combination (LC2)-based similarity metric has been retrospectively evaluated for twelve datasets acquired in patients with brain tumor. A series of landmarks were defined both in MRI and iUS scans. The Target Registration Error (TRE) was determined for each pair of landmarks before and after the automatic Rigid Image Fusion (RIF). The algorithm has been tested on two conditions of the initial image alignment: registration-based fusion (RBF), as given by the navigated ultrasound probe, and different simulated course alignments during convergence test.Results Except for one case RIF was successfully applied in all patients considering the RBF as initial alignment. Here, mean TRE after RBF was significantly reduced from 4.03 (± 1.40) mm to (2.08 ± 0.96 mm) (p = 0.002), after RIF. For convergence test, the mean TRE value after initial perturbations was 8.82 (± 0.23) mm which has been reduced to a mean TRE of 2.64 (± 1.20) mm after RIF (p < 0.001).ConclusionsThe integration of an automatic image fusion method for co-registration of pre-operative MRI and iUS data may improve the accuracy in MR-based neuronavigation.

Modeling of Respiratory Motion to Support the Minimally Invasive Destruction of Liver Tumors.

Objective: Respiratory movements are a significant factor that may hinder the use of image navigation systems during minimally invasive procedures used to destroy focal lesions in the liver. This article aims to present a method of estimating the displacement of the target point due to respiratory movements during the procedure, working in real time. Method: The real-time method using skin markers and non-rigid registration algorithms has been implemented and tested for various classes of transformation. The method was validated using clinical data from 21 patients diagnosed with liver tumors. For each patient, each marker was treated as a target and the remaining markers as target position predictors, resulting in 162 configurations and 1095 respiratory cycles analyzed. In addition, the possibility of estimating the respiratory phase signal directly from intraoperative US images and the possibility of synchronization with the 4D CT respiratory sequence are also presented, based on ten patients. Results: The median value of the target registration error (TRE) was 3.47 for the non-rigid registration method using the combination of rigid transformation and elastic body spline curves, and an adaptation of the assessing quality using image registration circuits (AQUIRC) method. The average maximum distance was 3.4 (minimum: 1.6, maximum 6.8) mm. Conclusions: The proposed method obtained promising real-time TRE values. It also allowed for the estimation of the TRE at a given geometric margin level to determine the estimated target position. Directions for further quantitative research and the practical possibility of combining both methods are also presented.

A hybrid registration method using the mandibular bone surface for electromagnetic navigation in mandibular surgery.

To utilize navigated mandibular (reconstructive) surgery, accurate registration of the preoperative CT scan with the actual patient in the operating room (OR) is required. In this phantom study, the feasibility of a noninvasive hybrid registration method is assessed. This method consists of a point registration with anatomic landmarks for initialization and a surface registration using the bare mandibular bone surface for optimization. Three mandible phantoms with reference notches on two osteotomy planes were 3D printed. An electromagnetic tracking system in combination with 3D Slicer software was used for navigation. Different configurations, i.e., different surface point areas and number and configuration of surface points, were tested with a dentate phantom (A) in a metal-free environment. To simulate the intraoperative environment and different anatomies, the registration procedure was also performed with an OR bed using the dentate phantom and two (partially) edentulous phantoms with atypical anatomy (B and C). The accuracy of the registration was calculated using the notches on the osteotomy planes and was expressed as the target registration error (TRE). TRE values of less than 2.0mm were considered as clinically acceptable. In all experiments, the mean TRE was less than 2.0mm. No differences were found using different surface point areas or number or configurations of surface points. Registration accuracy in the simulated intraoperative setting was-mean (SD)-0.96 (0.22), 0.93 (0.26), and 1.50 (0.28) mm for phantom A, phantom B, and phantom C. Hybrid registration is a noninvasive method that requires only a small area of the bare mandibular bone surface to obtain high accuracy in phantom setting. Future studies should test this method in clinical setting during actual surgery.

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

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

A multivariable study of deformable image registration evaluation metrics in 4DCT of thoracic cancer patients

Deformable image registration (DIR) accuracy is often validated using manually identified landmarks or known deformations generated using digital or physical phantoms. In daily practice, the application of these approaches is limited since they are time-consuming or require additional equipment. An alternative is the use of metrics automatically derived from the registrations, but their interpretation is not straightforward. In this work we aim to determine the suitability of DIR-derived metrics to validate the accuracy of 4 commonly used DIR algorithms. First, we investigated the DIR accuracy using a landmark-based metric (target registration error (TRE)) and a digital phantom-based metric (known deformation recovery error (KDE)). 4DCT scans of 16 thoracic cancer patients along with corresponding pairwise anatomical landmarks (AL) locations were collected from two public databases. Digital phantoms with known deformations were generated by each DIR algorithm to test all other algorithms and compute KDE. TRE and KDE were evaluated at AL. KDE was additionally quantified in coordinates randomly sampled (RS) inside the lungs. Second, we investigated the associations of 5 DIR-derived metrics (distance discordance metric (DDM), inverse consistency error (ICE), transitivity (TE), spatial (SS) and temporal smoothness (TS)) with DIR accuracy through uni- and multivariable linear regression models. TRE values were found higher compared to KDE values and these varied depending on the phantom used. The algorithm with the best accuracy achieved average values of TRE = 1.1 mm and KDE ranging from 0.3 to 0.8 mm. DDM was the best predictor of DIR accuracy, with moderate correlations (R 2 < 0.61). Poor correlations were obtained at AL for algorithms with better accuracy, which improved when evaluated at RS. Only slight correlation improvement was obtained with a multivariable analysis (R 2 < 0.64). DDM can be a useful metric to identify inaccuracies for different DIR algorithms without employing landmarks or digital phantoms.

Navigation-guided fibula free flap for mandibular reconstruction: A proof of concept study

To analyze a novel technique of supporting fibula free flap harvest and fabrication with intraoperative navigation technology. In the first phase of the study, navigation accuracy achieved with two registration methods, namely, point-pair and hybrid technique utilizing point-pair with surface matching, were evaluated in the form of the fiducial (FRE) and target registration error (TRE). Next, a series of 42 simulated navigated fibular osteotomies were conducted on specially manufactured lower leg phantom. Postoperative results were analyzed in the form of the angular and position deviations between the virtually planned and the obtained osteotomies. Mean FRE values obtained with point-pair and hybrid registration methods were 1.82± 0.96mm and 1.41± 0.44mm, respectively. Mean TRE value in the fibula region was 2.00± 0.67mm for the first method and 1.51± 0.72mm for the second. For all performed surgeries, the total mean angular deviation between the planned and actual osteotomy trajectory equaled 3.66° ± 3.60°. The total mean position disparity of osteotomy control points was 1.85± 0.99mm. Navigation-guided free fibula flap harvest and fabrication, due to encouraging study results and its superiority over currently popular cutting guides in many clinical aspects, may become a routine operative procedure for the reconstruction of complex mandibular defects. The presented method is especially well suited for plastic and maxillofacial surgery.

Evaluation of deformation parameters for deformable image registration-based ventilation imaging using an air-ventilating non-rigid phantom

PurposeThis study aimed to evaluate different deformable image registration (DIR) parameters for the open-source NiftyReg package in its application to DIR-based ventilation imaging. MethodsTwo three-dimensional (3D)-computed tomography (CT) scans of a non-rigid air-ventilating phantom were acquired at peak exhalation and peak inhalation, with xenon (Xe) gas being used as an air-based contrast agent. We compared four different sets of DIR parameters, including one set with two-step deformation and three sets with four-step deformation. For spatial accuracy, the target registration error (TRE) was calculated for 16 landmarks. For ventilation imaging accuracy, DIR-based ventilation images were generated using Jacobian determinant (JD) metrics, and changes in Hounsfield unit (HU) values between the two exhalation and inhalation CT images were subsequently measured. The correlation coefficients between the JD metrics and changes in HU values were calculated. ResultsThe mean TRE values were 4.5 ± 4.7 mm (maximum, 12.3 mm), 1.47 ± 0.71 mm (maximum, 2.6 mm), 1.56 ± 0.70 mm (maximum, 2.8 mm), and 1.53 ± 0.66 mm (maximum, 2.5 mm) for the two-step deformation and three four-step deformations, respectively. The four-step deformations (R = − 0.71, −0.65, and −0.61) showed stronger correlation coefficients than the two-step deformation (R = −0.40). ConclusionsThe accuracy of DIR-based ventilation imaging may vary with different DIR parameter settings, even though spatial accuracy may be tolerable and within guidelines. We found adequate parameter settings for four-step NiftyReg DIR for visualization of simulated pulmonary ventilation function.

Evaluation of a novel software application for magnetic resonance distortion correction in cranial stereotactic radiosurgery

This study aimed to validate a novel commercially available software for correcting spatial distortion in cranial magnetic resonance (MR) images. This software has been used to assess the dosimetric impact of MR distortion in stereotactic radiosurgery (SRS) treatments of vestibular schwannomas (VSs). Five MR datasets were intentionally distorted. Each distorted MR dataset was corrected using the Cranial Distortion software, obtaining a new corrected MR dataset (MRcorr). The accuracy of the correction was quantified by calculating the target registration error (TRE) for 6 anatomical landmarks identified in the co-registered MRcorr and planning computed tomography (pCT) images. Nine VS cases were included to investigate the impact of the MR distortion in SRS plans. Each SRS plan was calculated on the pCT (1 × 1 × 1 mm3 voxel) with the target and organs at risk (OARs) delineated using the planning MR dataset. This MR dataset was then corrected (MRcorr) using the Cranial Distortion software. Geometrical agreement between the original target and the corresponding corrected target was assessed using several metrics: MacDonald criteria, mean distance to agreement (MDA), and Dice similarity coefficient (DSC). Target coverage (D99%) and maximum doses (D2%) to ipsilateral cochlea and brainstem resulting on the MRcorr dataset were compared with the original values. TRE values (0.6 mm ± 0.3 mm) and differences found in Macdonald criteria (0.3 mm ± 0.4 mm and 0.3 mm ± 0.3 mm) and MDA (0.8 mm ± 0.2 mm) were mostly within the voxel size dimension of the pCT scan (1 × 1 × 1 mm3). High similarity (DSC > 0.7) between the original and corrected targets was found. Small dose differences for the original and corrected structures were found: 0.1 Gy ± 0.1 Gy for target D99%, 0.2 Gy ± 0.3 Gy for cochlea D2%, and 0.1 Gy ± 0.1 Gy for brainstem D2%. Our study shows that Distortion Correction software can be a helpful tool to detect and adequately correct brain MR distortions. However, a negligible dosimetric impact of MR distortion has been detected in our clinical practice.

Personalized biomechanical modeling of prostate deformation based on elastography for MRI three-dimensional transrectal ultrasound(TRUS) image registration

Objective To evaluate the clinical significance of personalized biomechanical modeling of prostate deformation based on ultrasound elastography for magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) image registration. Methods A total number of 5 patients and 1 commercial prostate phantom were imaged via transrectal ultrasound elastography, 3D-TRUS and MRI from June 2016 to December 2016. A personalized biomechanical model via the patient-specific ultrasound elastography was made for the deformable registration of prostate MRI and 3D-TRUS images. The registration accuracy was evaluated by the target registration error (TRE) and also the t-test was conducted to validate the statistical significance of our results. Results All the 5 sets of patient data as well as the phantom data were successfully registered. The TRE value of the phantom data was 1.65 mm. The mean TRE value of 5 patients was 1.31 mm, compared with the 2.52 mm TRE value of the registration method without patient-specific biomechanical properties via elastography, was approximately 48% lower(P<0.05). Conclusions Personalized biomechanical modeling of prostate deformation based on ultrasound elastography for MRI-TRUS image registration possesses important clinical significance and is a promising way to provide more quality guidance and improve the accuracy of prostate biopsy. Key words: Elasticity imaging techniques; Three-dimensional transrectal ultrasound; Medical image registration; Biomechanical model

Personalized Biomechanical Modeling of Prostate Deformation Based on Elastography For Mr-Trus Image Registration

To evaluate the clinical significance of personalized biomechanical modeling of prostate deformation based on ultrasound elastography for magnetic resonance imaging (MRI)-Transrectal Ultrasound (TRUS) image registration. A total number of 35 patients and 5 commercial prostate phantom were imaged via transrectal ultrasound elastography, TRUS and MRI at the first affiliated hospital of SYSU from June 2014 to December 2015. We propose a personalized biomechanical model via the patient-specific ultrasound elastography for the deformable registration of prostate MR and 3D TRUS images. The registration accuracy was evaluated by the target registration error (TRE) and also the t-test was conducted to validate the statistical significance of our results. All the 35 sets of patient data, as well as the phantom data, were successfully registered. The TRE value of the phantom data was 1.69mm. The mean TRE value of 35 patients was 1.29 mm, compared with the 2.56 mm TRE value of the registration method without patient-specific biomechanical properties via elastography, was approximately 48% lower. The improvement was with statistical significance validated by t-test (p-value was 1.45e-8). Personalized biomechanical modeling of prostate deformation based on ultrasound elastography for MR- TRUS image registration is with clinical significance and is a promising way to provide more quality guidance and improve the accuracy of prostate biopsy.

SU‐C‐202‐06: Design and Development of a Non‐Rigid Phantom Ventilating Air Quantitatively Evaluating CT‐Based Pulmonary Ventilation Imaging

Purpose:A validation study using human or sheep for CT pulmonary ventilation (CT‐V) imaging are inefficient and partially unstable. In this study, we designed and developed non‐rigid phantom ventilating air to quantitatively evaluate the CT‐V image.Methods:The phantom consisted of an acryl cylinder filled with polyurethane foam designed to pulmonic alveoli and a polyurethane membrane was attached to the inferior end of the phantom to simulate a lung diaphragm. Also, trachea‐shaped polyurethane tubes were covered by the foam and the tubes passed through the outside in order to exchange a gas. Lung arteries were also modeled with polyurethane and were located adjacent to the trachea model. Two 3D‐CT scans were performed at exhale and inhale using an air contrast agent of xenon gas, respectively. The exhale 3D‐CT was deformed to the inhale 3D‐CT using the in‐house program with the NiftyReg. Sixteen landmarks were assigned around trachea and lung arteries in the inhale image and the deformed exhale image. Target Registration Error (TRE) for each landmark between the two images was calculated for commissioning of our program. CT‐V image was generated using Jacobian determinant metrics (JD). Subsequently, HU value change between the two images was measured. The correlation coefficient was calculated between the JD and the HU change.Results:The deformable and ventilation phantom shows a variety of displacement for each landmark (1 mm − 20 mm). The mean TRE was 4.5 ± 4.7 mm (Maximum: 12.3 mm). The relationship between the JD and the HU change shows high correlation. (R = −0.86). At the several landmarks where TRE values were over 3 mm, the correlation was poor.Conclusion:The phantom may be a useful QA tool to validate CT‐V imaging. We will improve our deformable image registration program for CT‐V imaging with the efficient way using the phantom.

Validation of non-rigid point-set registration methods using a porcine bladder pelvic phantom

The problem of accurate dose accumulation in fractionated radiotherapy treatment for highly deformable organs, such as bladder, has garnered increasing interest over the past few years. However, more research is required in order to find a robust and efficient solution and to increase the accuracy over the current methods. The purpose of this study was to evaluate the feasibility and accuracy of utilizing non-rigid (affine or deformable) point-set registration in accumulating dose in bladder of different sizes and shapes. A pelvic phantom was built to house an ex vivo porcine bladder with fiducial landmarks adhered onto its surface. Four different volume fillings of the bladder were used (90, 180, 360 and 480 cc). The performance of MATLAB implementations of five different methods were compared, in aligning the bladder contour point-sets. The approaches evaluated were coherent point drift (CPD), gaussian mixture model, shape context, thin-plate spline robust point matching (TPS-RPM) and finite iterative closest point (ICP-finite). The evaluation metrics included registration runtime, target registration error (TRE), root-mean-square error (RMS) and Hausdorff distance (HD). The reference (source) dataset was alternated through all four points-sets, in order to study the effect of reference volume on the registration outcomes. While all deformable algorithms provided reasonable registration results, CPD provided the best TRE values (6.4 mm), and TPS-RPM yielded the best mean RMS and HD values (1.4 and 6.8 mm, respectively). ICP-finite was the fastest technique and TPS-RPM, the slowest.

Correction of a Depth-Dependent Lateral Distortion in 3D Super-Resolution Imaging.

Three-dimensional (3D) localization-based super-resolution microscopy (SR) requires correction of aberrations to accurately represent 3D structure. Here we show how a depth-dependent lateral shift in the apparent position of a fluorescent point source, which we term `wobble`, results in warped 3D SR images and provide a software tool to correct this distortion. This system-specific, lateral shift is typically > 80 nm across an axial range of ~ 1 μm. A theoretical analysis based on phase retrieval data from our microscope suggests that the wobble is caused by non-rotationally symmetric phase and amplitude aberrations in the microscope’s pupil function. We then apply our correction to the bacterial cytoskeletal protein FtsZ in live bacteria and demonstrate that the corrected data more accurately represent the true shape of this vertically-oriented ring-like structure. We also include this correction method in a registration procedure for dual-color, 3D SR data and show that it improves target registration error (TRE) at the axial limits over an imaging depth of 1 μm, yielding TRE values of < 20 nm. This work highlights the importance of correcting aberrations in 3D SR to achieve high fidelity between the measurements and the sample.

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

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

4D-CT Lung registration using anatomy-based multi-level multi-resolution optical flow analysis and thin-plate splines

The accuracy of 4D-CT registration is limited by inconsistent Hounsfield unit (HU) values in the 4D-CT data from one respiratory phase to another and lower image contrast for lung substructures. This paper presents an optical flow and thin-plate spline (TPS)-based 4D-CT registration method to account for these limitations. The use of unified HU values on multiple anatomy levels (e.g., the lung contour, blood vessels, and parenchyma) accounts for registration errors by inconsistent landmark HU value. While 3D multi-resolution optical flow analysis registers each anatomical level, TPS is employed for propagating the results from one anatomical level to another ultimately leading to the 4D-CT registration. 4D-CT registration was validated using target registration error (TRE), inverse consistency error (ICE) metrics, and a statistical image comparison using Gamma criteria of 1 % intensity difference in 2 mm(3) window range. Validation results showed that the proposed method was able to register CT lung datasets with TRE and ICE values <3 mm. In addition, the average number of voxel that failed the Gamma criteria was <3 %, which supports the clinical applicability of the propose registration mechanism. The proposed 4D-CT registration computes the volumetric lung deformations within clinically viable accuracy.

Continuous registration based on computed tomography for breathing motion compensation.

IntroductionImage guidance for intervention is applied for complex and difficult anatomical regions. Nowadays, it is typically used in neurosurgery, otolaryngology, orthopedics and dentistry. The application of the image-guided system for soft tissues is challenging due to various deformations caused by respiratory motion, tissue elasticity and peristalsis.AimThe main task for the presented approach is continuous registration of preoperative computed tomography (CT) and patient position in the operating room (OR) without touching the patient and compensation of breathing motion. This approach is being developed as a step to image-guided percutaneous liver RF tumor ablation.Material and methodsUp to ten integrated radiological markers are placed on the patient's skin before CT scans. Then the anatomical model based on CT images is calculated. Point-to-point registration based on the Horn algorithm during a few breathing cycles is performed using a videometric tracking system. The transformation which corresponds to the minimum fiducial registration error (FRE) is found during the registration and it is treated as the initial transformation for calculating local deformation field of breathing motion compensation based on the spline approach.ResultsFor manual registration of the abdominal phantom, the mean values of target registration error (TRE), fiducial localization error (FLE) and FRE are all below 4 mm for the rigid transformation and are below 1 mm for the affine transformation. For the patient's data they are all below 9 mm and 6 mm, respectively. For the automatic method, different marker configurations have been evaluated while dividing the respiratory cycle into inhale and exhale. Average median values for FRE, TRE rigid estimation and TRE based on spline deformation were 15.56 mm, 0.82 mm and 7.21 mm respectively.ConclusionsIn this application two registration methods of abdominal preoperative CT anatomical model and physical patient position in OR were presented and compared. The presented approach is being developed as a step to image-guided percutaneous liver radiofrequency ablation tumor ablation. Implementation of the automated registration method to clinical practice is easier because of shortening of preparation time in OR, no necessity of touching the patient, and no dependency on the physician's experience.

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

PurposeTo evaluate the current beliefs about the ways to reduce target registration error (TRE) values in image guided Sinus surgery by rearranging the fiducial configuration, and investigating the best configurations for various surgical fields in a phantom study. MethodsA new CT-compatible skull phantom consisting of implanted targets was designed to enable direct measurement of TRE in four fields of sinus surgery, Frontal, Ethmoid, Sphenoid and Maxillary. The effects of different landmark configurations on TRE values, measured by the Parsiss-IV navigation system were investigated to find the best landmark arrangement for each region, and compared to the TRE prediction formula to assess the clinically accepted landmark selection approaches based on this formula. ResultsIt was shown that smaller values of TRE could be attained by arranging the center of the fiducials to be more focused on the surgery target. The addition of more fiducials and keeping non-linear arrangement of landmark would not necessarily decrease the TRE value. ConclusionOptimizing the landmark configuration is important for increasing the localization accuracy in image guided sinus surgery. The common beliefs accepted in the clinical community about the ways to reduce the TRE are very general and should be adapted to specific field of image guided surgery.

Minimization of target registration error for vertebra in image-guided spine surgery

The accuracy of pedicle screw placement during image-guided spine surgery (IGSS) can be characterized by estimating the target registration error (TRE). The major factors that influence TRE were identified, minimized, and verified with in vitro experiments. Computed-tomography-compatible markers are placed over anatomical landmarks of lumbar vertebral segments in locations that are feasible and routinely used in surgical procedures. TRE was determined directly for markers placed on the pedicles of vertebra segments. First, optimum selections of landmarks are proposed for different landmarks according to the minimum achievable TRE values in different configurations. These anatomical landmarks are feasible and accessible to overcome constraints that may be imposed during surgical procedures. Second, the effect of fiducial weighting on corresponding points to overcome anisotropic localization error based on maximum likelihood approach is evaluated. Third, an experimental model for fiducial localization error (FLE) is derived to obtain the weights. At the end, an error zone was obtained for each marker to indicate the possible acceptable deviation from the marker's exact location in practice. This study was performed in vitro on a spine phantom. Optimal landmark selection led to a 30% reduction in TRE. In addition, optimum weighting of the fiducials in an FLE model that incorporates anisotropic localization error in the registration algorithm led to a 28% reduction in the TRE. Landmark configuration, transformation parameters, and fiducial localization error are factors that significantly affect the total TRE. These factors should be optimized to minimize the TRE. Both the optimum configuration of landmarks and the anisotropic weighing of fiducials have significant impact on the registration accuracy for IGSS.

Fiducial Optimization for Minimal Target Registration Error in Image-Guided Neurosurgery

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