Registration of head volume images using implantable fiducial markers

Multi-Operational Selective Computer-Assisted Targeting of hepatocellular carcinoma-Evaluation of a novel approach for navigated tumor ablation

Objective

To facilitate precise local ablation of hepatocellular carcinoma (HCC) in a setting of combined ablation and transarterial chemoembolization (TACE), we evaluated accuracy and efficiency of a novel technique for navigated positioning of ablation probes using intrahepatic tumor referencing and electromagnetic (EM) guidance, in a porcine model.

Methods

An angiographic wire with integrated EM reference sensor at its tip was inserted via a transarterial femoral access and positioned in the vicinity of artificial liver tumors. The resulting offset distance between the tumor center and the intrahepatic endovascular EM reference was calculated. Subsequently, EM tracked ablation probes were inserted percutaneously and navigated toward the tumor center, relying on continuous EM guidance via the intrahepatic reference. Targeting accuracy was assessed as the Euclidean distance between the tip of the ablation probe and the tumor center (Target Positioning Error, TPE). Procedural efficiency was assessed as time efforts for tumor referencing and tumor targeting.

Results

In 6 animals, 124 targeting measurements were performed with an offset distance < 30 mm (clinically most feasible position), resulting in a mean TPE of 2.9 ± 1.6 mm. No significant correlation between the TPE and different intrahepatic offset distances (range 21 to 61 mm, n = 365) was shown as long as the EM reference was placed within the liver. However, the mean TPE increased when placing the EM reference externally on the animal skin (p < 0.01). TPE was similar when targeting under continuous ventilation or in apnea (p = 0.50). Mean time for tumor referencing and navigated targeting was 6.5 ± 3.8 minutes and 14 ± 8 seconds, respectively.

Conclusion

The proposed technique allows precise and efficient navigated positioning of ablation probes into liver tumors in the animal model. We introduce a simple approach suitable for combined ablation and TACE of HCC in a single treatment session.

How does adding anatomical landmarks as fiducial points in the point-matching registration of neuronavigation influence registration accuracy?

Skin markers (SMs) are usually used as fiducial points in registration of neuronavigation, but the areas in which they can be adhered to are restricted, which usually results in poor distribution of the SMs and a large registration error. In this research, we studied whether the registration accuracy can be improved by adding anatomical landmarks (ALs), which are thought to have a larger localization error than SMs. A series of random SM configurations were generated, and for each SM configuration, we generated a corresponding SM-AL configuration by adding several ALs. We then compared the accuracy of the point-matching registration of the SM configurations with that of the corresponding SM-AL configurations. Experiment results indicated that adding ALs always made the mean target registration error of the whole head fall into a lower and narrower range, which meant that the registration became more accurate and more stable. In addition, adding more ALs resulted in a better performance.

Computer-Assisted Image-Guided Orbit Surgery

PURPOSE

Modern stereotaxy utilizes preoperative computed tomography (CT) and magnetic resonance imaging (MRI) to provide accurate localization information which can be very helpful in orbital surgery. The purpose of this report is to evaluate the usefulness of stereotactic surgery and application of this procedure in the orbit.

METHODS

Interventional case series of three patients with orbital tumors. All patients had tumor resection with the utilization of two frameless stereotactic systems: Cygnus and Stealth Station.

RESULTS

The applications of image-guided stereotactic surgery proved to be beneficial in three extensive orbital tumors, including optic nerve glioma, recurrent pleomorphic adenoma of lacrimal gland, and secondary orbital meningioma.

CONCLUSIONS

The interactive nature of image guidance can be useful in orbital surgery to orient the surgeon to the exact location within the surgical field and to determine the tumor margins.

Real-time probe tracking using EM-optical sensor for MRI-guided cryoablation

BACKGROUND

A method of real-time, accurate probe tracking at the entrance of the MRI bore is developed, which, fused with pre-procedural MR images, will enable clinicians to perform cryoablation efficiently in a large workspace with image guidance.

METHODS

Electromagnetic (EM) tracking coupled with optical tracking is used to track the probe. EM tracking is achieved with an MRI-safe EM sensor working under the scanner's magnetic field to compensate the line-of-sight issue of optical tracking. Unscented Kalman filter-based probe tracking is developed to smooth the EM sensor measurements when occlusion occurs and to improve the tracking accuracy by fusing the measurements of two sensors.

RESULTS

Experiments with a spine phantom show that the mean targeting errors using the EM sensor alone and using the proposed method are 2.21 mm and 1.80 mm, respectively.

CONCLUSION

The proposed method achieves more accurate probe tracking than using an EM sensor alone at the MRI scanner entrance.

A concept for electromagnetic navigated targeting of liver tumors using an angiographic approach

BACKGROUND

The benefits of using navigation technology for percutaneous local ablation of selected hepatocellular carcinoma (HCC) have been shown. Due to additional efforts in the procedural workflow, barriers to introducing navigation systems on a broad clinical level remain high. In this work, initial steps toward a novel concept for simple and precise targeting of HCC are evaluated.

MATERIAL AND METHODS

The proposed technique is based on an angiographic approach using an intrahepatic electromagnetic (EM) reference, for consecutive percutaneous navigated positioning of ablation probes. We evaluated the environmental influence of the angiography suite on EM tracking accuracy, the measurement of a 3 D offset from two 2 D fluoroscopy images, and the accuracy and efficiency of the proposed approach in a porcine liver model.

RESULTS

The C-arm had a major influence on EM tracking accuracy, with an error up to 3.8 mm. The methodology applied for measurement of a 3 D offset from 2 D fluoroscopy images was confirmed to be feasible with a mean error of 0.76 mm. In the porcine liver model experiment, the overall target positioning error (TPE) was 2.0 mm and time for navigated targeting was 17.9 seconds, when using a tracked ablation probe.

CONCLUSIONS

The initial methodology of the proposed technique was confirmed to be feasible, introducing a novel concept for simple and precise navigated targeting of HCC.

The improved differential demon algorithm

BACKGROUND

Differential demon is a fast and efficient registration algorithm. It drives the floating image to deform using the force based on the gradient between the reference and floating image. But it will cause abnormal deformation when the driving force approaches zero,which limits its practical applications.

OBJECTIVE

This paper proposed an improved differential demon algorithm, which aimed to enhance the registration performance of the existing demon algorithm.

METHODS

Firstly, we review the original differential demon algorithm. Then, we propose an improved differential demon algorithm and the process of mathematical deduction. Finally, we use experiment to prove that the improved differential demon algorithm is effective and it can improve the accuracy of registration.

RESULTS

We tested our method on data sets provided by Xuanwu Hospital Capital Medical University. The registration performance proved to be better than the original demon algorithm in terms of mutual information, normalized correlation coefficient, mean square error and iteration number.

CONCLUSIONS

Experiment results demonstrate the superiority of method proposed in this paper to the original demon algorithm.

Effects of Resolution and Registration Algorithm on the Accuracy of EPI vNavs for Real Time Head Motion Correction in MRI

Low-resolution, EPI-based Volumetric Navigators (vNavs) have been used as a prospective motion-correction system in a variety of MRI neuroimaging pulse sequences. The use of low-resolution volumes represents a trade-off between motion tracking accuracy and acquisition time. However, this means that registration must be accurate on the order of 0.2 voxels or less to be effective for motion correction. While vNavs have shown promising results in clinical and research use, the choice of navigator and registration algorithm have not previously been systematically evaluated. In this work we experimentally evaluate the accuracy of vNavs, and possible design choices for future improvements to the system, using real human data. We acquired navigator volumes at three isotropic resolutions (6.4 mm, 8 mm, and 10 mm) with known rotations and translations. The vNavs were then rigidly registered using trilinear, tricubic, and cubic B-spline interpolation. We demonstrate a novel refactoring of the cubic B-spline algorithm that stores pre-computed coefficients to reduce the per-interpolation time to be identical to tricubic interpolation. Our results show that increasing vNav resolution improves registration accuracy, and that cubic B-splines provide the highest registration accuracy at all vNav resolutions. Our results also suggest that the time required by vNavs may be reduced by imaging at 10 mm resolution, without substantial cost in registration accuracy.

Registration accuracy enhancement of a surgical navigation system for anterior cruciate ligament reconstruction: A phantom and cadaveric study

BACKGROUND

Recently, surgical navigation systems have been widely used to improve the results of various orthopaedic surgeries. However, surgical navigation has not been successful in anterior cruciate ligament reconstruction, owing to its inaccuracy and inconvenience. This study investigated the registration of preoperative and intraoperative data, which are the key components in improving accuracy of the navigation system.

METHODS

An accurate registration method was proposed using new optical tracking markers and landmark retake. A surgical planning and navigation system for anterior cruciate ligament reconstruction was developed and implemented. The accuracy of the proposed system has been evaluated using phantoms and eight cadaveric knees. The present study investigated only the registration accuracy excluding the errors of optical tracking hardware and surgeon.

RESULTS

The target registration errors of femoral tunnelling for anterior cruciate ligament reconstruction in phantoms were found to be 0.24±0.03mm and 0.19±0.10° for the tunnel entry position and tunnel direction, respectively. The target registration errors measured using cadavers were 0.9mm and 1.94°, respectively.

CONCLUSIONS

The preclinical experimental results showed that the proposed methods enhanced the registration accuracy of the developed system. As the system becomes more accurate, surgeons could more precisely position and orient the femoral and tibial tunnels to their original anatomical locations.

Fiducial-based registration with a touchable region model

PURPOSE

Image-guided surgery requires registration between an image coordinate system and an intraoperative coordinate system that is typically referenced to a tracking device. In fiducial-based registration methods, this is achieved by localizing points (fiducials) in each coordinate system. Often, both localizations are performed manually, first by picking a fiducial point in the image and then by using a hand-held tracked pointer to physically touch the corresponding fiducial on the patient. These manual procedures introduce localization error that is user-dependent and can significantly decrease registration accuracy. Thus, there is a need for a registration method that is tolerant of imprecise fiducial localization in the preoperative and intraoperative phases.

METHODS

We propose the iterative closest touchable point (ICTP) registration framework, which uses model-based localization and a touchable region model. This method consists of three stages: (1) fiducial marker localization in image space, using a fiducial marker model, (2) initial registration with paired-point registration, and (3) fine registration based on the iterative closest point method.

RESULTS

We perform phantom experiments with a fiducial marker design that is commonly used in neurosurgery. The results demonstrate that ICTP can provide accuracy improvements compared to the standard paired-point registration method that is widely used for surgical navigation and surgical robot systems, especially in cases where the surgeon introduces large localization errors.

CONCLUSIONS

The results demonstrate that the proposed method can reduce the effect of the surgeon's localization performance on the accuracy of registration, thereby producing more consistent and less user-dependent registration outcomes.

Brain shift in neuronavigation of brain tumors: A review

PURPOSE

Neuronavigation based on preoperative imaging data is a ubiquitous tool for image guidance in neurosurgery. However, it is rendered unreliable when brain shift invalidates the patient-to-image registration. Many investigators have tried to explain, quantify, and compensate for this phenomenon to allow extended use of neuronavigation systems for the duration of surgery. The purpose of this paper is to present an overview of the work that has been done investigating brain shift.

METHODS

A review of the literature dealing with the explanation, quantification and compensation of brain shift is presented. The review is based on a systematic search using relevant keywords and phrases in PubMed. The review is organized based on a developed taxonomy that classifies brain shift as occurring due to physical, surgical or biological factors.

RESULTS

This paper gives an overview of the work investigating, quantifying, and compensating for brain shift in neuronavigation while describing the successes, setbacks, and additional needs in the field. An analysis of the literature demonstrates a high variability in the methods used to quantify brain shift as well as a wide range in the measured magnitude of the brain shift, depending on the specifics of the intervention. The analysis indicates the need for additional research to be done in quantifying independent effects of brain shift in order for some of the state of the art compensation methods to become useful.

CONCLUSION

This review allows for a thorough understanding of the work investigating brain shift and introduces the needs for future avenues of investigation of the phenomenon.

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration

Purpose

A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed.

Methods

We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm.

Results

The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera.

Conclusion

The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers.

Image-guided Localization of the Internal Auditory Canal via the Middle Cranial Fossa Approach

OBJECTIVE: We sought to determine the accuracy of an electromagnetic image guidance surgical navigation system in localizing the midpoint of the internal auditory canal (IAC) and other structures of the temporal bone through the middle cranial fossa approach.

MATERIALS AND METHODS: Seven fresh cadaveric whole heads were dissected via a middle cranial fossa approach. High-resolution CT scans were used with an InstaTrak 3500 Plus electromagnetic image guidance system (General Electric, Fairfield, CT). We evaluated the accuracy of identifying several middle cranial fossa landmarks including the midpoint of the IAC; the labyrinthine segment of the facial nerve; and the arcuate eminence, the carotid artery, and foramen spinosum.

RESULTS: We were able to identify the middle of the IAC within 2.31 mm (range 0.65-7.52 mm, SD 2.39 mm). The arcuate eminence could be identified within 1.86 mm (range 1.49-2.37 mm, SD 0.36 mm). We noted some interference when the handpiece was within 6 to 8 cm of the microscope.

CONCLUSION: Although computer-aided navigational tools are no substitute for thorough knowledge of temporal bone anatomy, we found the InstaTrak system reliable in identifying the midpoint of the IAC to within 2.4 mm through a middle fossa approach.

A Novel Augmented Reality Navigation System for Endoscopic Sinus and Skull Base Surgery: A Feasibility Study

Objective

To verify the reliability and clinical feasibility of a self-developed navigation system based on an augmented reality technique for endoscopic sinus and skull base surgery.

Materials and Methods

In this study we performed a head phantom and cadaver experiment to determine the display effect and accuracy of our navigational system. We compared cadaver head-based simulated operations, the target registration error, operation time, and National Aeronautics and Space Administration Task Load Index scores of our navigation system to conventional navigation systems.

Results

The navigation system developed in this study has a novel display mode capable of fusing endoscopic images to three-dimensional (3-D) virtual images. In the cadaver head experiment, the target registration error was 1.28 ± 0.45 mm, which met the accepted standards of a navigation system used for nasal endoscopic surgery. Compared with conventional navigation systems, the new system was more effective in terms of operation time and the mental workload of surgeons, which is especially important for less experienced surgeons.

Conclusion

The self-developed augmented reality navigation system for endoscopic sinus and skull base surgery appears to have advantages that outweigh those of conventional navigation systems. We conclude that this navigational system will provide rhinologists with more intuitive and more detailed imaging information, thus reducing the judgment time and mental workload of surgeons when performing complex sinus and skull base surgeries. Ultimately, this new navigational system has potential to increase the quality of surgeries. In addition, the augmented reality navigational system could be of interest to junior doctors being trained in endoscopic techniques because it could speed up their learning. However, it should be noted that the navigation system serves as an adjunct to a surgeon’s skills and knowledge, not as a substitute.

Volumetric compensation of accuracy errors in a multi-robot surgical platform

A multi-robot platform, made of a hybrid parallel kinematic machine and 2 KUKA LWR arms, is dedicated to open skull neuro-surgical tasks. Sub-millimeter accuracy is clearly required for both the absolute tool tracking and for good performances in motion compensation when the head is set free to move. An analysis of the sources of inaccuracies, mostly derived from the calibration phase, illustrates that errors are insufficiently reduced by stand-alone calibrations of the single robots. A method for volumetric compensation of errors is reported. A compensation transform is, in fact, computed during an offline training phase for a set of discretized subregions of the constrained head workspace. At runtime, a compensation motion is applied to robots so as to reach the desired real targets on anatomical parts. The resulting end-to-end static accuracy is distributed with median 0.75 mm and below 1 mm for the 95% of tests, with a 1:36 reduction factor from the starting conditions. The accuracy is evaluated also in dynamic tests with mild oscillatory patterns.

Intraoperative fiducial-less patient registration using volumetric 3D ultrasound: a prospective series of 32 neurosurgical cases

OBJECT

Fiducial-based registration (FBR) is used widely for patient registration in image-guided neurosurgery. The authors of this study have developed an automatic fiducial-less registration (FLR) technique to find the patient-to-image transformation by directly registering 3D ultrasound (3DUS) with MR images without incorporating prior information. The purpose of the study was to evaluate the performance of the FLR technique when used prospectively in the operating room and to compare it with conventional FBR.

METHODS

In 32 surgical patients who underwent conventional FBR, preoperative T1-weighted MR images (pMR) with attached fiducial markers were acquired prior to surgery. After craniotomy but before dural opening, a set of 3DUS images of the brain volume was acquired. A 2-step registration process was executed immediately after image acquisition: 1) the cortical surfaces from pMR and 3DUS were segmented, and a multistart sum-of-squared-intensity-difference registration was executed to find an initial alignment between down-sampled binary pMR and 3DUS volumes; and 2) the alignment was further refined by a mutual information-based registration between full-resolution grayscale pMR and 3DUS images, and a patient-to-image transformation was subsequently extracted.

RESULTS

To assess the accuracy of the FLR technique, the following were quantified: 1) the fiducial distance error (FDE); and 2) the target registration error (TRE) at anterior commissure and posterior commissure locations; these were compared with conventional FBR. The results showed that although the average FDE (6.42 ± 2.05 mm) was higher than the fiducial registration error (FRE) from FBR (3.42 ± 1.37 mm), the overall TRE of FLR (2.51 ± 0.93 mm) was lower than that of FBR (5.48 ± 1.81 mm). The results agreed with the intent of the 2 registration techniques: FBR is designed to minimize the FRE, whereas FLR is designed to optimize feature alignment and hence minimize TRE. The overall computational cost of FLR was approximately 4-5 minutes and minimal user interaction was required.

CONCLUSIONS

Because the FLR method directly registers 3DUS with MR by matching internal image features, it proved to be more accurate than FBR in terms of TRE in the 32 patients evaluated in this study. The overall efficiency of FLR in terms of the time and personnel involved is also improved relative to FBR in the operating room, and the method does not require additional image scans immediately prior to surgery. The performance of FLR and these results suggest potential for broad clinical application.

Optimal marker placement in hadrontherapy: intelligent optimization strategies with augmented Lagrangian pattern search

PURPOSE

In high precision photon radiotherapy and in hadrontherapy, it is crucial to minimize the occurrence of geometrical deviations with respect to the treatment plan in each treatment session. To this end, point-based infrared (IR) optical tracking for patient set-up quality assessment is performed. Such tracking depends on external fiducial points placement. The main purpose of our work is to propose a new algorithm based on simulated annealing and augmented Lagrangian pattern search (SAPS), which is able to take into account prior knowledge, such as spatial constraints, during the optimization process.

MATERIAL AND METHODS

The SAPS algorithm was tested on data related to head and neck and pelvic cancer patients, and that were fitted with external surface markers for IR optical tracking applied for patient set-up preliminary correction. The integrated algorithm was tested considering optimality measures obtained with Computed Tomography (CT) images (i.e. the ratio between the so-called target registration error and fiducial registration error, TRE/FRE) and assessing the marker spatial distribution. Comparison has been performed with randomly selected marker configuration and with the GETS algorithm (Genetic Evolutionary Taboo Search), also taking into account the presence of organs at risk.

RESULTS

The results obtained with SAPS highlight improvements with respect to the other approaches: (i) TRE/FRE ratio decreases; (ii) marker distribution satisfies both marker visibility and spatial constraints. We have also investigated how the TRE/FRE ratio is influenced by the number of markers, obtaining significant TRE/FRE reduction with respect to the random configurations, when a high number of markers is used.

CONCLUSIONS

The SAPS algorithm is a valuable strategy for fiducial configuration optimization in IR optical tracking applied for patient set-up error detection and correction in radiation therapy, showing that taking into account prior knowledge is valuable in this optimization process. Further work will be focused on the computational optimization of the SAPS algorithm toward fast point-of-care applications.

Comparison of procedures for co-registering scalp-recording locations to anatomical magnetic resonance images

Functional brain imaging techniques require accurate co-registration to anatomical images to precisely identify the areas being activated. Many of them, including diffuse optical imaging, rely on scalp-placed recording sensors. Fiducial alignment is an effective and rapid method for co-registering scalp sensors onto anatomy, but is quite sensitive to placement errors. Surface Euclidean distance minimization using the Levenberq-Marquart algorithm (LMA) has been shown to be very accurate when based on good initial guesses, such as precise fiducial alignment, but its accuracy drops substantially with fiducial placement errors. Here we compared fiducial and LMA co-registration methods to a new procedure, the iterative closest point-to-plane (ICP2P) method, using simulated and real data. An advantage of ICP2P is that it eliminates the need to identify fiducials and is, therefore, entirely automatic. We show that, typically, ICP2P is as accurate as fiducial-based LMA, but is less sensitive to initial placement errors. However, ICP2P is more sensitive to spatially correlated noise in the description of the head surface. Hence, the best technique for co-registration depends on the type of data available to describe the scalp and the surface defined by the recording sensors. Under optimal conditions, co-registration error using surface-fitting procedures can be reduced to ~ 3 mm.

An advanced navigational surgery system for dental implants completed in a single visit: an in vitro study

In this study, we have developed an advanced navigational implant surgery system to overcome some disadvantages of the conventional method and have evaluated the accuracy of the system under in vitro environment. The patient splint for registration and tracking was improvised using a bite splint without laboratory work and the offset of an exchanged drill was calibrated directly without pivoting during surgery. The mean target registration errors (TRE) were 0.35 ± 0.11 mm using the registration body, 0.34 ± 0.18 mm for the registration method with prerecorded fiducials, and 0.35 ± 0.16 mm for the direct calibration of a drill offset. The mean positional deviations between the planned and placed implants in 110 implant surgeries were 0.41 ± 0.12 mm at the center point of the platform and 0.56 ± 0.14 mm at the center point of the apex. The mean angular deviation was 2.64°± 1.31 for the long axis of the implant. In conclusion, the developed system exhibited high accuracy, and the improved tools and simplified procedures increased the convenience and availability. With this advanced approach, it will be possible to complete dental implant surgery during a single visit at local clinics using a navigational guidance involving cone-beam computed tomographic images.

Quantitative evaluation of atlas-based high-density diffuse optical tomography for imaging of the human visual cortex

Image recovery in diffuse optical tomography (DOT) of the human brain often relies on accurate models of light propagation within the head. In the absence of subject specific models for image reconstruction, the use of atlas based models are showing strong promise. Although there exists some understanding in the use of some limited rigid model registrations in DOT, there has been a lack of a detailed analysis between errors in geometrical accuracy, light propagation in tissue and subsequent errors in dynamic imaging of recovered focal activations in the brain. In this work 11 different rigid registration algorithms, across 24 simulated subjects, are evaluated for DOT studies in the visual cortex. Although there exists a strong correlation (R(2) = 0.97) between geometrical surface error and internal light propagation errors, the overall variation is minimal when analysing recovered focal activations in the visual cortex. While a subject specific mesh gives the best results with a 1.2 mm average location error, no single algorithm provides errors greater than 4.5 mm. This work demonstrates that the use of rigid algorithms for atlas based imaging is a promising route when subject specific models are not available.

Cortical surface shift estimation using stereovision and optical flow motion tracking via projection image registration

Stereovision is an important intraoperative imaging technique that captures the exposed parenchymal surface noninvasively during open cranial surgery. Estimating cortical surface shift efficiently and accurately is critical to compensate for brain deformation in the operating room (OR). In this study, we present an automatic and robust registration technique based on optical flow (OF) motion tracking to compensate for cortical surface displacement throughout surgery. Stereo images of the cortical surface were acquired at multiple time points after dural opening to reconstruct three-dimensional (3D) texture intensity-encoded cortical surfaces. A local coordinate system was established with its z-axis parallel to the average surface normal direction of the reconstructed cortical surface immediately after dural opening in order to produce two-dimensional (2D) projection images. A dense displacement field between the two projection images was determined directly from OF motion tracking without the need for feature identification or tracking. The starting and end points of the displacement vectors on the two cortical surfaces were then obtained following spatial mapping inversion to produce the full 3D displacement of the exposed cortical surface. We evaluated the technique with images obtained from digital phantoms and 18 surgical cases - 10 of which involved independent measurements of feature locations acquired with a tracked stylus for accuracy comparisons, and 8 others of which 4 involved stereo image acquisitions at three or more time points during surgery to illustrate utility throughout a procedure. Results from the digital phantom images were very accurate (0.05 pixels). In the 10 surgical cases with independently digitized point locations, the average agreement between feature coordinates derived from the cortical surface reconstructions was 1.7-2.1mm relative to those determined with the tracked stylus probe. The agreement in feature displacement tracking was also comparable to tracked probe data (difference in displacement magnitude was <1mm on average). The average magnitude of cortical surface displacement was 7.9 ± 5.7 mm (range 0.3-24.4 mm) in all patient cases with the displacement components along gravity being 5.2 ± 6.0 mm relative to the lateral movement of 2.4 ± 1.6 mm. Thus, our technique appears to be sufficiently accurate and computationally efficiency (typically ∼15 s), for applications in the OR.

Surgical task analysis of simulated laparoscopic cholecystectomy with a navigation system

PURPOSE

   Advanced surgical procedures, which have become complex and difficult, increase the burden of surgeons. Quantitative analysis of surgical procedures can improve training, reduce variability, and enable optimization of surgical procedures. To this end, a surgical task analysis system was developed that uses only surgical navigation information.

METHODS

   Division of the surgical procedure, task progress analysis, and task efficiency analysis were done. First, the procedure was divided into five stages. Second, the operating time and progress rate were recorded to document task progress during specific stages, including the dissecting task. Third, the speed of the surgical instrument motion (mean velocity and acceleration), as well as the size and overlap ratio of the approximate ellipse of the location log data distribution, was computed to estimate the task efficiency during each stage. These analysis methods were evaluated based on experimental validation with two groups of surgeons, i.e., skilled and "other" surgeons. The performance metrics and analytical parameters included incidents during the operation, the surgical environment, and the surgeon's skills or habits.

RESULTS

   Comparison of groups revealed that skilled surgeons tended to perform the procedure in less time and involved smaller regions; they also manipulated the surgical instruments more gently.

CONCLUSION

   Surgical task analysis developed for quantitative assessment of surgical procedures and surgical performance may provide practical methods and metrics for objective evaluation of surgical expertise.

3D-2D registration for surgical guidance: effect of projection view angles on registration accuracy

An algorithm for intensity-based 3D-2D registration of CT and x-ray projections is evaluated, specifically using single- or dual-projection views to provide 3D localization. The registration framework employs the gradient information similarity metric and covariance matrix adaptation evolution strategy to solve for the patient pose in six degrees of freedom. Registration performance was evaluated in an anthropomorphic phantom and cadaver, using C-arm projection views acquired at angular separation, Δθ, ranging from ∼0°-180° at variable C-arm magnification. Registration accuracy was assessed in terms of 2D projection distance error and 3D target registration error (TRE) and compared to that of an electromagnetic (EM) tracker. The results indicate that angular separation as small as Δθ ∼10°-20° achieved TRE <2 mm with 95% confidence, comparable or superior to that of the EM tracker. The method allows direct registration of preoperative CT and planning data to intraoperative fluoroscopy, providing 3D localization free from conventional limitations associated with external fiducial markers, stereotactic frames, trackers and manual registration.

Registration for frameless brain surgery based on stereo imaging

This paper presents an implementation of stereo vision techniques to capture the geometric model of patient's face for registration in the frameless neurosurgery. A distance transform is applied on 2D CT/MRI multi-slices for on-site registration, further reducing requisite computation. In order to validate accuracy of the system, we designed a phantom to directly measure its target registration error (TRE). Experimental results show that the TRE is 2.72 ± 0.735 mm.

Quantitative error analysis for computer assisted navigation: a feasibility study

PURPOSE

The benefit of computer-assisted navigation depends on the registration process, at which patient features are correlated to some preoperative imagery. The operator-induced uncertainty in localizing patient features-the user localization error (ULE)-is unknown and most likely dominating the application accuracy. This initial feasibility study aims at providing first data for ULE with a research navigation system.

METHODS

Active optical navigation was done in CT-images of a plastic skull, an anatomic specimen (both with implanted fiducials), and a volunteer with anatomical landmarks exclusively. Each object was registered ten times with 3, 5, 7, and 9 registration points. Measurements were taken at 10 (anatomic specimen and volunteer) and 11 targets (plastic skull). The active NDI Polaris system was used under ideal working conditions (tracking accuracy 0.23 mm root-mean-square, RMS; probe tip calibration was 0.18 mm RMS). Variances of tracking along the principal directions were measured as 0.18 mm(2), 0.32 mm(2), and 0.42 mm(2). ULE was calculated from predicted application accuracy with isotropic and anisotropic models and from experimental variances, respectively.

RESULTS

The ULE was determined from the variances as 0.45 mm (plastic skull), 0.60 mm (anatomic specimen), and 4.96 mm (volunteer). The predicted application accuracy did not yield consistent values for the ULE.

CONCLUSIONS

Quantitative data of application accuracy could be tested against prediction models with iso- and anisotropic noise models and revealed some discrepancies. This could potentially be due to the facts that navigation and one prediction model wrongly assume isotropic noise (tracking is anisotropic), while the anisotropic noise prediction model assumes an anisotropic registration strategy (registration is isotropic in typical navigation systems). The ULE data are presumably the first quantitative values for the precision of localizing anatomical landmarks and implanted fiducials. Submillimetric localization is possible for implanted screws; anatomic landmarks are not suitable for high-precision clinical navigation.

Surgical Robots

Information technology and robotics have been integrated into interventional medicine for over 25 years. Their primary aim has always been to provide patient benefits through increased precision, safety, and minimal invasiveness. Nevertheless, robotic devices should allow for sophisticated treatment methods that are not possible by other means. Several hundreds of different surgical robot prototypes have been developed, while only a handful passed clearance procedures, and was released to the market. This is mostly due to the difficulties associated with medical device development and approval, especially in those cases when some form of manipulation and automation is involved. This chapter is intended to present major aspects of surgical robotic prototyping and current trends through the analysis of various international projects. It spans across the phases from system planning, to development, validation, and clearance.

A hydrophilic gel matrix for single-molecule super-resolution microscopy

Background

Novel microscopic techniques which bypass the resolution limit in light microscopy are becoming routinely established today. The higher spatial resolution of super-resolution microscopy techniques demands for precise correction of drift, spectral and spatial offset of images recorded at different axial planes.

Methods

We employ a hydrophilic gel matrix for super-resolution microscopy of cellular structures. The matrix allows distributing fiducial markers in 3D, and using these for drift correction and multi-channel registration. We demonstrate single-molecule super-resolution microscopy with photoswitchable fluorophores at different axial planes. We calculate a correction matrix for each spectral channel, correct for drift, spectral and spatial offset in 3D.

Results and discussion

We demonstrate single-molecule super-resolution microscopy with photoswitchable fluorophores in a hydrophilic gel matrix. We distribute multi-color fiducial markers in the gel matrix and correct for drift and register multiple imaging channels. We perform two-color super-resolution imaging of click-labeled DNA and histone H2B in different axial planes, and demonstrate the quality of drift correction and channel registration quantitatively. This approach delivers robust microscopic data which is a prerequisite for data interpretation.

Interactive CT-video registration for the continuous guidance of bronchoscopy

Bronchoscopy is a major step in lung cancer staging. To perform bronchoscopy, the physician uses a procedure plan, derived from a patient's 3D computed-tomography (CT) chest scan, to navigate the bronchoscope through the lung airways. Unfortunately, physicians vary greatly in their ability to perform bronchoscopy. As a result, image-guided bronchoscopy systems, drawing upon the concept of CT-based virtual bronchoscopy (VB), have been proposed. These systems attempt to register the bronchoscope's live position within the chest to a CT-based virtual chest space. Recent methods, which register the bronchoscopic video to CT-based endoluminal airway renderings, show promise but do not enable continuous real-time guidance. We present a CT-video registration method inspired by computer-vision innovations in the fields of image alignment and image-based rendering. In particular, motivated by the Lucas-Kanade algorithm, we propose an inverse-compositional framework built around a gradient-based optimization procedure. We next propose an implementation of the framework suitable for image-guided bronchoscopy. Laboratory tests, involving both single frames and continuous video sequences, demonstrate the robustness and accuracy of the method. Benchmark timing tests indicate that the method can run continuously at 300 frames/s, well beyond the real-time bronchoscopic video rate of 30 frames/s. This compares extremely favorably to the ≥ 1 s/frame speeds of other methods and indicates the method's potential for real-time continuous registration. A human phantom study confirms the method's efficacy for real-time guidance in a controlled setting, and, hence, points the way toward the first interactive CT-video registration approach for image-guided bronchoscopy. Along this line, we demonstrate the method's efficacy in a complete guidance system by presenting a clinical study involving lung cancer patients.

Electromagnetic servoing-a new tracking paradigm

Electromagnetic (EM) tracking is highly relevant for many computer assisted interventions. This is in particular due to the fact that the scientific community has not yet developed a general solution for tracking of flexible instruments within the human body. Electromagnetic tracking solutions are highly attractive for minimally invasive procedures, since they do not require line of sight. However, a major problem with EM tracking solutions is that they do not provide uniform accuracy throughout the tracking volume and the desired, highest accuracy is often only achieved close to the center of tracking volume. In this paper, we present a solution to the tracking problem, by mounting an EM field generator onto a robot arm. Proposing a new tracking paradigm, we take advantage of the electromagnetic tracking to detect the sensor within a specific sub-volume, with known and optimal accuracy. We then use the more accurate and robust robot positioning for obtaining uniform accuracy throughout the tracking volume. Such an EM servoing methodology guarantees optimal and uniform accuracy, by allowing us to always keep the tracked sensor close to the center of the tracking volume. In this paper, both dynamic accuracy and accuracy distribution within the tracking volume are evaluated using optical tracking as ground truth. In repeated evaluations, the proposed method was able to reduce the overall error from 6.64±7.86 mm to a significantly improved accuracy of 3.83±6.43 mm. In addition, the combined system provides a larger tracking volume, which is only limited by the reach of the robot and not the much smaller tracking volume defined by the magnetic field generator.

Two phase non-rigid multi-modal image registration using Weber local descriptor-based similarity metrics and normalized mutual information

Non-rigid multi-modal image registration plays an important role in medical image processing and analysis. Existing image registration methods based on similarity metrics such as mutual information (MI) and sum of squared differences (SSD) cannot achieve either high registration accuracy or high registration efficiency. To address this problem, we propose a novel two phase non-rigid multi-modal image registration method by combining Weber local descriptor (WLD) based similarity metrics with the normalized mutual information (NMI) using the diffeomorphic free-form deformation (FFD) model. The first phase aims at recovering the large deformation component using the WLD based non-local SSD (wldNSSD) or weighted structural similarity (wldWSSIM). Based on the output of the former phase, the second phase is focused on getting accurate transformation parameters related to the small deformation using the NMI. Extensive experiments on T1, T2 and PD weighted MR images demonstrate that the proposed wldNSSD-NMI or wldWSSIM-NMI method outperforms the registration methods based on the NMI, the conditional mutual information (CMI), the SSD on entropy images (ESSD) and the ESSD-NMI in terms of registration accuracy and computation efficiency.

Anatomical landmarks for point-matching registration in image-guided neurosurgery

BACKGROUND

Accurate patient to image registration is the core for successful image-guided neurosurgery. While skin adhesive markers (SMs) are widely used in point-matching registration, a proper implementation of anatomical landmarks (ALs) may overcome the inconvenience brought by the use of SMs.

METHODS

Using nine ALs, a set of three configurations of different combinations of them is proposed. These configurations are defined according to the required positioning of the patient's head during surgery and the resulting distribution of the expected target registration error (TRE). These configurations were first evaluated by simulation experiment using the data of 20 patients from two hospitals, and then testing the applicability of them in eight real clinical surgeries of neuronavigation.

RESULTS

The results of the simulation experiment showed that, by incorporating a fiducial registration error (FRE) of 3.5 mm measured in the clinical setting, the expected TRE in the whole skull was less than 2.5 mm, and the expected TRE in the whole brain was less than 1.75 mm when using all the nine ALs. A small TRE could also be achieved in the corresponding surgical field by using the other three configurations with less ALs. In the clinical experiment, the FLE ranges in the image and the patient space were 1.4-3.6 mm and 1.6-5.5 mm, respectively. The measured TRE and FRE were 3.1 ± 0.75 mm and 3.5 ± 0.17 mm, respectively.

CONCLUSIONS

The AL configurations proposed in this investigation provide sufficient registration accuracy and can help to avoid the disadvantages of SMs if used clinically.

Bayesian characterization of uncertainty in intra-subject non-rigid registration

In settings where high-level inferences are made based on registered image data, the registration uncertainty can contain important information. In this article, we propose a Bayesian non-rigid registration framework where conventional dissimilarity and regularization energies can be included in the likelihood and the prior distribution on deformations respectively through the use of Boltzmann's distribution. The posterior distribution is characterized using Markov Chain Monte Carlo (MCMC) methods with the effect of the Boltzmann temperature hyper-parameters marginalized under broad uninformative hyper-prior distributions. The MCMC chain permits estimation of the most likely deformation as well as the associated uncertainty. On synthetic examples, we demonstrate the ability of the method to identify the maximum a posteriori estimate and the associated posterior uncertainty, and demonstrate that the posterior distribution can be non-Gaussian. Additionally, results from registering clinical data acquired during neurosurgery for resection of brain tumor are provided; we compare the method to single transformation results from a deterministic optimizer and introduce methods that summarize the high-dimensional uncertainty. At the site of resection, the registration uncertainty increases and the marginal distribution on deformations is shown to be multi-modal.

High-accuracy patient-to-image registration for the facilitation of image-guided robotic microsurgery on the head

Image-guided microsurgery requires accuracies an order of magnitude higher than today's navigation systems provide. A critical step toward the achievement of such low-error requirements is a highly accurate and verified patient-to-image registration. With the aim of reducing target registration error to a level that would facilitate the use of image-guided robotic microsurgery on the rigid anatomy of the head, we have developed a semiautomatic fiducial detection technique. Automatic force-controlled localization of fiducials on the patient is achieved through the implementation of a robotic-controlled tactile search within the head of a standard surgical screw. Precise detection of the corresponding fiducials in the image data is realized using an automated model-based matching algorithm on high-resolution, isometric cone beam CT images. Verification of the registration technique on phantoms demonstrated that through the elimination of user variability, clinically relevant target registration errors of approximately 0.1 mm could be achieved.

Deep brain stimulation surgical techniques

Stereotactic techniques for placement of deep brain stimulation (DBS) electrodes have undergone continuous refinement since the introduction of human stereotaxis in the 1940s. Volumetric imaging techniques, including magnetic resonance imaging and computed tomography, have replaced ventriculography, and increasingly sophisticated computer systems now allow highly refined targeting of subcortical structures. This chapter reviews the underlying principles of stereotactic surgery, including imaging, targeting, and registration, and describes the surgical approach to DBS placement using both framed and frameless techniques.

Nonrigid image registration with crystal dislocation energy

The goal of nonrigid image registration is to find a suitable transformation such that the transformed moving image becomes similar to the reference image. The image registration problem can also be treated as an optimization problem, which tries to minimize an objective energy function that measures the differences between two involved images. In this paper, we consider image matching as the process of aligning object boundaries in two different images. The registration energy function can be defined based on the total energy associated with the object boundaries. The optimal transformation is obtained by finding the equilibrium state when the total energy is minimized, which indicates the object boundaries find their correspondences and stop deforming. We make an analogy between the above processes with the dislocation system in physics. The object boundaries are viewed as dislocations (line defects) in crystal. Then the well-developed dislocation energy is used to derive the energy assigned to object boundaries in images. The newly derived registration energy function takes the global gradient information of the entire image into consideration, and produces an orientation-dependent and long-range interaction between two images to drive the registration process. This property of interaction endows the new registration framework with both fast convergence rate and high registration accuracy. Moreover, the new energy function can be adapted to realize symmetric diffeomorphic transformation so as to ensure one-to-one matching between subjects. In this paper, the superiority of the new method is theoretically proven, experimentally tested and compared with the state-of-the-art SyN method. Experimental results with 3-D magnetic resonance brain images demonstrate that the proposed method outperforms the compared methods in terms of both registration accuracy and computation time.