Registration of head volume images using implantable fiducial markers

Improved multimodality data fusion of late gadolinium enhancement MRI to left ventricular voltage maps in ventricular tachycardia ablation

Electroanatomical voltage mapping (EAVM) is commonly performed prior to catheter ablation of scar-related ventricular tachycardia (VT) to locate the arrhythmic substrate and to guide the ablation procedure. EAVM is used to locate the position of the ablation catheter and to provide a 3-D reconstruction of left-ventricular anatomy and scar. However, EAVM measurements only represent the endocardial scar with no transmural or epicardial information. Furthermore, EAVM is a time-consuming procedure, with a high operator dependence and has low sampling density, i.e., spatial resolution. Late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) allows noninvasive assessment of scar morphology that can depict 3-D scar architecture. Despite the potential use of LGE as a roadmap for VT ablation for identification of arrhythmogenic substrate, its utility has been very limited. To allow for identification of VT substrate, a correlation is needed between the substrates identified by EAVM as the gold standard and LGE-MRI scar characteristics. To do so, a system must be developed to fuse the datasets from these modalities. In this study, a registration pipeline for the fusion of LGE-MRI and EAVM data is presented. A novel surface registration algorithm is proposed, integrating the matching of global scar areas as an additional constraint in the registration process. A preparatory landmark registration is initially performed to expedite the convergence of the algorithm. Numerical simulations were performed to evaluate the accuracy of the registration in the presence of errors in identifying landmarks in EAVM or LGE-MRI datasets as well as additional errors due to respiratory or cardiac motion. Subsequently, the accuracy of the proposed fusion system was evaluated in a cohort of ten patients undergoing VT ablation where both EAVM and LGE-MRI data were available. Compared to landmark registration and surface registration, the presented method achieved significant improvement in registration error. The proposed data fusion system allows the fusion of EAVM and LGE-MRI data in VT ablation with registration errors less than 3.5  mm.

Intraoperative patient registration using volumetric true 3D ultrasound without fiducials

PURPOSE

Accurate patient registration is crucial for effective image-guidance in open cranial surgery. Typically, it is accomplished by matching skin-affixed fiducials manually identified in the operating room (OR) with their counterparts in the preoperative images, which not only consumes OR time and personnel resources but also relies on the presence (and subsequent fixation) of the fiducials during the preoperative scans (until the procedure begins). In this study, the authors present a completely automatic, volumetric image-based patient registration technique that does not rely on fiducials by registering tracked (true) 3D ultrasound (3DUS) directly with preoperative magnetic resonance (MR) images.

METHODS

Multistart registrations between binary 3DUS and MR volumes were first executed to generate an initial starting point without incorporating prior information on the US transducer contact point location or orientation for subsequent registration between grayscale 3DUS and MR via maximization of either mutual information (MI) or correlation ratio (CR). Patient registration was then computed through concatenation of spatial transformations.

RESULTS

In ten (N = 10) patient cases, an average fiducial (marker) distance error (FDE) of 5.0 mm and 4.3 mm was achieved using MI or CR registration (FDE was smaller with CR vs MI in eight of ten cases), which are comparable to values reported for typical fiducial- or surface-based patient registrations. The translational and rotational capture ranges were found to be 24.0 mm and 27.0° for binary registrations (up to 32.8 mm and 36.4°), 12.2 mm and 25.6° for MI registrations (up to 18.3 mm and 34.4°), and 22.6 mm and 40.8° for CR registrations (up to 48.5 mm and 65.6°), respectively. The execution time to complete a patient registration was 12-15 min with parallel processing, which can be significantly reduced by confining the 3DUS transducer location to the center of craniotomy in MR before registration (an execution time of 5 min is achievable).

CONCLUSIONS

Because common features deep in the brain and throughout the surgical volume of interest are used, intraoperative fiducial-less patient registration is possible on-demand, which is attractive in cases where preoperative patient registration is compromised (e.g., from loss∕movement of skin-affixed fiducials) or not possible (e.g., in cases of emergency when external fiducials were not placed in time). CR registration was more robust than MI (capture range about twice as big) and appears to be more accurate, although both methods are comparable to or better than fiducial-based registration in the patient cases evaluated. The results presented here suggest that 3DUS image-based patient registration holds promise for clinical application in the future.

"Nonparametric Local Smoothing" is not image registration

BACKGROUND

Image registration is one of the most important and universally useful computational tasks in biomedical image analysis. A recent article by Xing & Qiu (IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(10):2081-2092, 2011) is based on an inappropriately narrow conceptualization of the image registration problem as the task of making two images look alike, which disregards whether the established spatial correspondence is plausible. The authors propose a new algorithm, Nonparametric Local Smoothing (NLS) for image registration, but use image similarities alone as a measure of registration performance, although these measures do not relate reliably to the realism of the correspondence map.

RESULTS

Using data obtained from its authors, we show experimentally that the method proposed by Xing & Qiu is not an effective registration algorithm. While it optimizes image similarity, it does not compute accurate, interpretable transformations. Even judged by image similarity alone, the proposed method is consistently outperformed by a simple pixel permutation algorithm, which is known by design not to compute valid registrations.

CONCLUSIONS

This study has demonstrated that the NLS algorithm proposed recently for image registration, and published in one of the most respected journals in computer science, is not, in fact, an effective registration method at all. Our results also emphasize the general need to apply registration evaluation criteria that are sensitive to whether correspondences are accurate and mappings between images are physically interpretable. These goals cannot be achieved by simply reporting image similarities.

Perk Tutor: an open-source training platform for ultrasound-guided needle insertions

Image-guided needle placement, including ultrasound (US)-guided techniques, have become commonplace in modern medical diagnosis and therapy. To ensure that the next generations of physicians are competent using this technology, efficient and effective educational programs need to be developed. This paper presents the Perk Tutor: a configurable, open-source training platform for US-guided needle insertions. The Perk Tutor was successfully tested in three different configurations to demonstrate its adaptability to different procedures and learning objectives. 1) The Targeting Tutor, designed to develop US-guided needle targeting skills, 2) the Lumbar Tutor, designed for practicing US-guided lumbar spinal procedures, and (3) the Prostate Biopsy Tutor, configured for US-guided prostate biopsies. The Perk Tutor provides the trainee with quantitative feedback on progress toward the specific learning objectives of each configuration. Configurations were implemented through simple rearrangement of hardware and software components, attesting to the modularity and ease of configuration. The Perk Tutor is provided as a free resource to enable research and development of educational programs for US-guided intervention.

Image-guided Navigation of Single-element Focused Ultrasound Transducer

The spatial specificity and controllability of focused ultrasound (FUS), in addition to its ability to modify the excitability of neural tissue, allows for the selective and reversible neuromodulation of the brain function, with great potential in neurotherapeutics. Intra-operative magnetic resonance imaging (MRI) guidance (in short, MRg) has limitations due to its complicated examination logistics, such as fixation through skull screws to mount the stereotactic frame, simultaneous sonication in the MRI environment, and restrictions in choosing MR-compatible materials. In order to overcome these limitations, an image-guidance system based on optical tracking and pre-operative imaging data is developed, separating the imaging acquisition for guidance and sonication procedure for treatment. Techniques to define the local coordinates of the focal point of sonication are presented. First, mechanical calibration detects the concentric rotational motion of a rigid-body optical tracker, attached to a straight rod mimicking the sonication path, pivoted at the virtual FUS focus. The spatial error presented in the mechanical calibration was compensated further by MRI-based calibration, which estimates the spatial offset between the navigated focal point and the ground-truth location of the sonication focus obtained from a temperature-sensitive MR sequence. MRI-based calibration offered a significant decrease in spatial errors (1.9±0.8 mm; 57% reduction) compared to the mechanical calibration method alone (4.4±0.9 mm). Using the presented method, pulse-mode FUS was applied to the motor area of the rat brain, and successfully stimulated the motor cortex. The presented techniques can be readily adapted for the transcranial application of FUS to intact human brain.

Positioning error evaluation of GPU-based 3D ultrasound surgical navigation system for moving targets by using optical tracking system

PURPOSE

A near real-time three-dimensional (3D) ultrasound navigation system has been developed for guiding surgery involving internal organs that move and change shape (e.g., abdominal surgery, fetal surgery). In practical applications, significant errors arise between the actual navigation-image positions depending on the time delay of the system. Therefore, the positioning error of the system relative to the target velocity was evaluated.

METHODS

We developed a method for evaluating the positioning error of a graphics processing unit-based 3D ultrasound surgical navigation system (with an optical tracking system) for moving targets. The effectiveness of this system was quantitatively evaluated in terms of its image processing runtime, target registration error (TRE), and positioning error for a moving target. The positioning error was evaluated for a phantom (with an optical tracking marker) moving at speeds of 5-25 mm/s, and the navigation target was the center point of the phantom. The imaging range of the volume data was set to the maximum angle and range of the ultrasound diagnostic system (update rate: 4 Hz).

RESULTS

The image processing runtime was 27.43 ± 4.80 ms, and the TRE was 1.50 ± 0.28 mm. The positioning error was 4.24 ± 0.12 mm for a target moving at a speed of 10 mm/s and 5.36 ± 0.10 mm for one moving at 15 mm/s.

CONCLUSION

The effectiveness of an ultrasound navigation system was quantitatively evaluated by using the positioning error for a moving target. This navigation system demonstrated high calculation speed and positioning accuracy for a moving target. Therefore, it is suitable to guide the surgery of abdominal internal organs (e.g., in fetal and abdominal surgeries) that move or change shape during breathing and surgical approaches.

Monitoring image guidance system accuracy during spinal surgery with mini-screw fiducials: technical note

STUDY DESIGN

A technical note.

OBJECTIVE

To describe a technique for measuring accuracy of intraoperative image guidance systems in spine surgery.

SUMMARY OF BACKGROUND DATA

Image guidance may be of use when performing complex procedures on the spine. However, as the operation progresses and, in particular, once any deformity has been corrected, the image guidance system may become unreliable. In practice, this often results in repeated image acquisitions thus increasing the radiation exposure to the patient.

METHODS

Small titanium, cranio-facial screws were placed on the dorsal aspect of the spine intraoperatively, before the acquisition of images and used as fiducials.

RESULTS

The authors were able to accurately discern the true precision of the image guidance system used with an intraoperative computed tomography scanner, throughout the procedure.

CONCLUSIONS

By using intraoperatively placed mini-screw fiducials, the surgeon may check and quantify the underlying system accuracy both initially and throughout the surgery. In the future, "auto-adjust" functions may be integrated into the computer software to automatically recalibrate the system when a probe is placed into the fiducials without the need for rescanning.

A fully sensorized cooperative robotic system for surgical interventions

In this research a fully sensorized cooperative robot system for manipulation of needles is presented. The setup consists of a DLR/KUKA Light Weight Robot III especially designed for safe human/robot interaction, a FD-CT robot-driven angiographic C-arm system, and a navigation camera. Also, new control strategies for robot manipulation in the clinical environment are introduced. A method for fast calibration of the involved components and the preliminary accuracy tests of the whole possible errors chain are presented. Calibration of the robot with the navigation system has a residual error of 0.81 mm (rms) with a standard deviation of ±0.41 mm. The accuracy of the robotic system while targeting fixed points at different positions within the workspace is of 1.2 mm (rms) with a standard deviation of ±0.4 mm. After calibration, and due to close loop control, the absolute positioning accuracy was reduced to the navigation camera accuracy which is of 0.35 mm (rms). The implemented control allows the robot to compensate for small patient movements.

MIND: modality independent neighbourhood descriptor for multi-modal deformable registration

Deformable registration of images obtained from different modalities remains a challenging task in medical image analysis. This paper addresses this important problem and proposes a modality independent neighbourhood descriptor (MIND) for both linear and deformable multi-modal registration. Based on the similarity of small image patches within one image, it aims to extract the distinctive structure in a local neighbourhood, which is preserved across modalities. The descriptor is based on the concept of image self-similarity, which has been introduced for non-local means filtering for image denoising. It is able to distinguish between different types of features such as corners, edges and homogeneously textured regions. MIND is robust to the most considerable differences between modalities: non-functional intensity relations, image noise and non-uniform bias fields. The multi-dimensional descriptor can be efficiently computed in a dense fashion across the whole image and provides point-wise local similarity across modalities based on the absolute or squared difference between descriptors, making it applicable for a wide range of transformation models and optimisation algorithms. We use the sum of squared differences of the MIND representations of the images as a similarity metric within a symmetric non-parametric Gauss-Newton registration framework. In principle, MIND would be applicable to the registration of arbitrary modalities. In this work, we apply and validate it for the registration of clinical 3D thoracic CT scans between inhale and exhale as well as the alignment of 3D CT and MRI scans. Experimental results show the advantages of MIND over state-of-the-art techniques such as conditional mutual information and entropy images, with respect to clinically annotated landmark locations.

An on-board surgical tracking and video augmentation system for C-arm image guidance

PURPOSE

Conventional tracker configurations for surgical navigation carry a variety of limitations, including limited geometric accuracy, line-of-sight obstruction, and mismatch of the view angle with the surgeon's-eye view. This paper presents the development and characterization of a novel tracker configuration (referred to as "Tracker-on-C") intended to address such limitations by incorporating the tracker directly on the gantry of a mobile C-arm for fluoroscopy and cone-beam CT (CBCT).

METHODS

A video-based tracker (MicronTracker, Claron Technology Inc., Toronto, ON, Canada) was mounted on the gantry of a prototype mobile isocentric C-arm next to the flat-panel detector. To maintain registration within a dynamically moving reference frame (due to rotation of the C-arm), a reference marker consisting of 6 faces (referred to as a "hex-face marker") was developed to give visibility across the full range of C-arm rotation. Three primary functionalities were investigated: surgical tracking, generation of digitally reconstructed radiographs (DRRs) from the perspective of a tracked tool or the current C-arm angle, and augmentation of the tracker video scene with image, DRR, and planning data. Target registration error (TRE) was measured in comparison with the same tracker implemented in a conventional in-room configuration. Graphics processing unit (GPU)-accelerated DRRs were generated in real time as an assistant to C-arm positioning (i.e., positioning the C-arm such that target anatomy is in the field-of-view (FOV)), radiographic search (i.e., a virtual X-ray projection preview of target anatomy without X-ray exposure), and localization (i.e., visualizing the location of the surgical target or planning data). Video augmentation included superimposing tracker data, the X-ray FOV, DRRs, planning data, preoperative images, and/or intraoperative CBCT onto the video scene. Geometric accuracy was quantitatively evaluated in each case, and qualitative assessment of clinical feasibility was analyzed by an experienced and fellowship-trained orthopedic spine surgeon within a clinically realistic surgical setup of the Tracker-on-C.

RESULTS

The Tracker-on-C configuration demonstrated improved TRE (0.87 ± 0.25) mm in comparison with a conventional in-room tracker setup (1.92 ± 0.71) mm (p < 0.0001) attributed primarily to improved depth resolution of the stereoscopic camera placed closer to the surgical field. The hex-face reference marker maintained registration across the 180° C-arm orbit (TRE = 0.70 ± 0.32 mm). DRRs generated from the perspective of the C-arm X-ray detector demonstrated sub- mm accuracy (0.37 ± 0.20 mm) in correspondence with the real X-ray image. Planning data and DRRs overlaid on the video scene exhibited accuracy of (0.59 ± 0.38) pixels and (0.66 ± 0.36) pixels, respectively. Preclinical assessment suggested potential utility of the Tracker-on-C in a spectrum of interventions, including improved line of sight, an assistant to C-arm positioning, and faster target localization, while reducing X-ray exposure time.

CONCLUSIONS

The proposed tracker configuration demonstrated sub- mm TRE from the dynamic reference frame of a rotational C-arm through the use of the multi-face reference marker. Real-time DRRs and video augmentation from a natural perspective over the operating table assisted C-arm setup, simplified radiographic search and localization, and reduced fluoroscopy time. Incorporation of the proposed tracker configuration with C-arm CBCT guidance has the potential to simplify intraoperative registration, improve geometric accuracy, enhance visualization, and reduce radiation exposure.

Marker-free registration for the accurate integration of CT images and the subject's anatomy during navigation surgery of the maxillary sinus

OBJECTIVE

This study compared three marker-free registration methods that are applicable to a navigation system that can be used for maxillary sinus surgery, and evaluated the associated errors, with the aim of determining which registration method is the most applicable for operations that require accurate navigation.

METHODS

The CT digital imaging and communications in medicine (DICOM) data of ten maxillary models in DICOM files were converted into stereolithography file format. All of the ten maxillofacial models were scanned three dimensionally using a light-based three-dimensional scanner. The methods applied for registration of the maxillofacial models utilized the tooth cusp, bony landmarks and maxillary sinus anterior wall area. The errors during registration were compared between the groups.

RESULTS

There were differences between the three registration methods in the zygoma, sinus posterior wall, molar alveolar, premolar alveolar, lateral nasal aperture and the infraorbital areas. The error was smallest using the overlay method for the anterior wall of the maxillary sinus, and the difference was statistically significant.

CONCLUSION

The navigation error can be minimized by conducting registration using the anterior wall of the maxillary sinus during image-guided surgery of the maxillary sinus.

A self-developed and constructed robot for minimally invasive cochlear implantation

CONCLUSION

A robot built specifically for stereotactic cochlear implantation provides equal or better accuracy levels together with a better integration into a clinical environment, when compared with existing approaches based on industrial robots.

OBJECTIVES

To evaluate the technical accuracy of a robotic system developed specifically for lateral skull base surgery in an experimental set-up reflecting the intended clinical application. The invasiveness of cochlear electrode implantation procedures may be reduced by replacing the traditional mastoidectomy with a small tunnel slightly larger in diameter than the electrode itself.

METHODS

The end-to-end accuracy of the robot system and associated image-guided procedure was evaluated on 15 temporal bones of whole head cadaver specimens. The main components of the procedure were as follows: reference screw placement, cone beam CT scan, computer-aided planning, pair-point matching of the surgical plan, robotic drilling of the direct access tunnel, and postoperative cone beam CT scan for accuracy assessment.

RESULTS

The mean accuracy at the target point (round window) was 0.56 ± 0.41 mm with an angular misalignment of 0.88 ± 0.40°. The procedural time for the registration process through the completion of the drilling procedure was 25 ± 11 min. The robot was fully operational in a clinical environment.

Medical image registration: a review

This paper presents a review of automated image registration methodologies that have been used in the medical field. The aim of this paper is to be an introduction to the field, provide knowledge on the work that has been developed and to be a suitable reference for those who are looking for registration methods for a specific application. The registration methodologies under review are classified into intensity or feature based. The main steps of these methodologies, the common geometric transformations, the similarity measures and accuracy assessment techniques are introduced and described.

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.

Feasibility analysis of high resolution tissue image registration using 3-D synthetic data

BACKGROUND

Registration of high-resolution tissue images is a critical step in the 3D analysis of protein expression. Because the distance between images (~4-5μm thickness of a tissue section) is nearly the size of the objects of interest (~10-20μm cancer cell nucleus), a given object is often not present in both of two adjacent images. Without consistent correspondence of objects between images, registration becomes a difficult task. This work assesses the feasibility of current registration techniques for such images.

METHODS

We generated high resolution synthetic 3-D image data sets emulating the constraints in real data. We applied multiple registration methods to the synthetic image data sets and assessed the registration performance of three techniques (i.e., mutual information (MI), kernel density estimate (KDE) method [1], and principal component analysis (PCA)) at various slice thicknesses (with increments of 1μm) in order to quantify the limitations of each method.

RESULTS

Our analysis shows that PCA, when combined with the KDE method based on nuclei centers, aligns images corresponding to 5μm thick sections with acceptable accuracy. We also note that registration error increases rapidly with increasing distance between images, and that the choice of feature points which are conserved between slices improves performance.

CONCLUSIONS

We used simulation to help select appropriate features and methods for image registration by estimating best-case-scenario errors for given data constraints in histological images. The results of this study suggest that much of the difficulty of stained tissue registration can be reduced to the problem of accurately identifying feature points, such as the center of nuclei.

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.

Image-guided navigation: a cost effective practical introduction using the Image-Guided Surgery Toolkit (IGSTK)

Teaching the key technical aspects of image-guided interventions using a hands-on approach is a challenging task. This is primarily due to the high cost and lack of accessibility to imaging and tracking systems. We provide a software and data infrastructure which addresses both challenges. Our infrastructure allows students, patients, and clinicians to develop an understanding of the key technologies by using them, and possibly by developing additional components and integrating them into a simple navigation system which we provide. Our approach requires minimal hardware, LEGO blocks to construct a phantom for which we provide CT scans, and a webcam which when combined with our software provides the functionality of a tracking system. A premise of this approach is that tracking accuracy is sufficient for our purpose. We evaluate the accuracy provided by a consumer grade webcam and show that it is sufficient for educational use. We provide an open source implementation of all the components required for a basic image-guided navigation as part of the Image-Guided Surgery Toolkit (IGSTK). It has long been known that in education there is no substitute for hands-on experience, to quote Sophocles, "One must learn by doing the thing; for though you think you know it, you have no certainty, until you try.". Our work provides this missing capability in the context of image-guided navigation. Enabling a wide audience to learn and experience the use of a navigation system.

Automated longitudinal registration of high resolution structural MRI brain sub-volumes in non-human primates

Accurate anatomic co-registration is a prerequisite for identifying structural and functional changes in longitudinal studies of brain plasticity. Current MRI methods permit collection of brain images across multiple scales, ranging from whole brain at relatively low resolution (≥1 mm), to local brain areas at the level of cortical layers and columns (∼100 μm) in the same session, allowing detection of subtle structural changes on a similar spatial scale. To measure these changes reliably, high resolution structural and functional images of local brain regions must be registered accurately across imaging sessions. The present study describes a robust fully automated strategy for the registration of high resolution structural images of brain sub-volumes to lower resolution whole brain images collected within a session, and the registration of partially overlapping high resolution MRI sub-volumes ("slabs") across imaging sessions. In high field (9.4 T) reduced field-of-view high resolution structural imaging studies using a surface coil in an anesthetized non-human primate model, this fully automated coregistration pipeline was robust in the face of significant inhomogeneities in image intensity and tissue contrast arising from the spatially inhomogeneous transmit and receive properties of the surface coil, achieving a registration accuracy of 30±15 μm between sessions.

Frameless stereotactic cerebral biopsy: our experience in 296 cases

AIMS

To evaluate the reliability, safety and accuracy of a the frameless stereotactic system in our clinical series and the differences between head fixation by means of a standard Mayfield head holder and the pinless FESS frame, and to evaluate the usefulness of biopsy targeting on the basis of magnetic resonance spectroscopy (MRS) data.

METHODS

The spectroscopic analysis was used to facilitate the targeting of the lesion. The fusion image function embedded in the Neuronavigation Unit was used postoperatively to assess the level of accuracy of the biopsy. The grading of the glioma specimens was correlated to the spectroscopic data.

RESULTS

296 patients underwent cerebral biopsy in 8 years. The diagnostic yield was 99.7%. The spectroscopic choline/N-acetyl aspartate ratio in different areas of the same tumor correlated well with the histological grading of the lesion.

CONCLUSION

The frameless stereotactic systems guarantee excellent biopsy results. Advanced imaging, in particular MRS, facilitates the correct targeting of nonenhancing lesions.

Evaluation of portable CT scanners for otologic image-guided surgery

PURPOSE

Portable CT scanners are beneficial for diagnosis in the intensive care unit, emergency room, and operating room. Portable fixed-base versus translating-base CT systems were evaluated for otologic image-guided surgical (IGS) applications based on geometric accuracy and utility for percutaneous cochlear implantation.

METHODS

Five cadaveric skulls were fitted with fiducial markers and scanned using both a translating-base, 8-slice CT scanner (CereTom(®)) and a fixed-base, flat-panel, volume CT (fpVCT) scanner (Xoran xCAT(®)). Images were analyzed for: (a) subjective quality (i.e., noise), (b) consistency of attenuation measurements (Hounsfield units) across similar tissue, and (c) geometric accuracy of fiducial marker positions. The utility of these scanners in clinical IGS cases was tested.

RESULTS

Five cadaveric specimens were scanned using each of the scanners. The translating-base, 8-slice CT scanner had spatially consistent Hounsfield units, and the image quality was subjectively good. However, because of movement variations during scanning, the geometric accuracy of fiducial marker positions was low. The fixed-base, fpVCT system had high spatial resolution, but the images were noisy and had spatially inconsistent attenuation measurements, while the geometric representation of the fiducial markers was highly accurate.

CONCLUSION

Two types of portable CT scanners were evaluated for otologic IGS. The translating-base, 8-slice CT scanner provided better image quality than a fixed-base, fpVCT scanner. However, the inherent error in three-dimensional spatial relationships by the translating-based system makes it suboptimal for otologic IGS use.

Automatic identification of landmarks for standard slice positioning in brain MRI

PURPOSE

To demonstrate a novel automatic slice-positioning technique based on three new anatomical landmarks and to standardize prospective scans by lowering rotational and translational variances.

MATERIALS AND METHODS

After defining the interpeduncular fossa corner and the eyeball centers as landmarks, they are manually labeled on 25 different T1 MRI scans. New scans are produced according to the Eyeball centers-Mesencephalon (EM) plane. The comparison of angular deviations at EM and original scans is based on the comparison of rotational angles according to manually labeled Talairach points on both scans. The same variability comparison is also done with automatically captured landmarks to see the effects of segmentation errors.

RESULTS

Analysis of variances proved significant lowering of intersubject variability for pitch and yaw angles (P(pitch) < 0.005, P(yaw) < 0.001), which are the two basic causes of misalignments. Automatic segmentation accuracy is proved by paired t-test and significance tests.

CONCLUSION

A new field of view and slice orientation proposed by the EM technique will have fixed the follow-up scans by significantly lowering the rotational and translational variances. The EM technique will precisely match the intrasubject scans and produce better standardized intersubject scans. The distinguishing features of landmarks are sufficient for robust automatic capture.

Evaluation of hardware-related geometrical distortion in structural MRI at 7 Tesla for image-guided applications in neurosurgery

RATIONALE AND OBJECTIVES

Geometrical distortion is a well-known problem in structural magnetic resonance imaging (MRI), leading to pixel shifts with variations up to several millimeters. Because the main factors of geometrical distortion are proportional to B(0), MRI spatial encoding distortions tend to increase with higher magnetic field strength. With the increasing prospects of utilizing ultra-high-field MRI (B(0) ≥ 7 Tesla) for neuroimaging and subsequently for image-guided neurosurgical therapy, the evaluation and correction of geometrical distortions occurring in ultra-high-field MRI are essential preconditions for the integration of these data. Hence, we conducted a phantom study to determine hardware-related geometrical distortion in clinically relevant sequences for structural imaging at 7 T MRI and compared the findings to 1.5 T MRI.

MATERIAL AND METHODS

Hardware-related geometrical distortion was evaluated using a MRI phantom (Elekta, Sweden). Both applied scanner systems (Magnetom Avanto 1.5 T and Magnetom 7 T, Siemens Healthcare, Erlangen, Germany) were equipped with similar gradient coils capable of delivering 45 mT/m of maximum amplitude and a slew rate of 220 mT/m/ms. Distortion analysis was performed for various clinically relevant gradient echo and spin echo sequences.

RESULTS

Overall, we found very low mean geometrical distortions at both 7 T and 1.5 T, although single values of up to 1.6 mm were detected. No major differences in mean distortion between the sequences could be found, except significantly higher distortions in turbo spin-echo sequences at 7 T, mainly caused by B(1) inhomogeneities.

CONCLUSION

Hardware-related geometrical distortions at 7 T MRI are relatively small, which may be acceptable for image coregistration or for direct tissue-targeting procedures. Using a subject-specific correction of object-related distortions, an integration of 7 T MRI data into image-guided applications may be feasible.

Prostate multimodality image registration based on B-splines and quadrature local energy

PURPOSE

Needle biopsy of the prostate is guided by Transrectal Ultrasound (TRUS) imaging. The TRUS images do not provide proper spatial localization of malignant tissues due to the poor sensitivity of TRUS to visualize early malignancy. Magnetic Resonance Imaging (MRI) has been shown to be sensitive for the detection of early stage malignancy, and therefore, a novel 2D deformable registration method that overlays pre-biopsy MRI onto TRUS images has been proposed.

METHOD

The registration method involves B-spline deformations with Normalized Mutual Information (NMI) as the similarity measure computed from the texture images obtained from the amplitude responses of the directional quadrature filter pairs. Registration accuracy of the proposed method is evaluated by computing the Dice Similarity coefficient (DSC) and 95% Hausdorff Distance (HD) values for 20 patients prostate mid-gland slices and Target Registration Error (TRE) for 18 patients only where homologous structures are visible in both the TRUS and transformed MR images.

RESULTS

The proposed method and B-splines using NMI computed from intensities provide average TRE values of 2.64 ± 1.37 and 4.43 ± 2.77 mm respectively. Our method shows statistically significant improvement in TRE when compared with B-spline using NMI computed from intensities with Student's t test p = 0.02. The proposed method shows 1.18 times improvement over thin-plate splines registration with average TRE of 3.11 ± 2.18 mm. The mean DSC and the mean 95% HD values obtained with the proposed method of B-spline with NMI computed from texture are 0.943 ± 0.039 and 4.75 ± 2.40 mm respectively.

CONCLUSIONS

The texture energy computed from the quadrature filter pairs provides better registration accuracy for multimodal images than raw intensities. Low TRE values of the proposed registration method add to the feasibility of it being used during TRUS-guided biopsy.

Development of a robotic FD-CT-guided navigation system for needle placement-preliminary accuracy tests

BACKGROUND

A needle placement system using a serial robot arm for manipulation of biopsy and/or treatment needles is introduced. A method for fast calibration of the robot and the preliminary accuracy tests of the robotic system are presented.

METHODS

The setup consists of a DLR/KUKA Light Weight Robot III especially designed for safe human/robot interaction mounted on a mobile platform, a robot-driven angiographic C-arm system and a navigation system.

RESULTS

Calibration of the robot with the navigation system has a residual error of 0.23 mm (rms) with a standard deviation of ± 0.1 mm. Needle targeting accuracy with different trajectories was 1.2 mm (rms) with a standard deviation of ± 0.4 mm.

CONCLUSIONS

Robot absolute positioning accuracy was reduced to the navigation camera accuracy. The approach includes control strategies that may be very useful for interventional applications.

Frame-Based vs Frameless Placement of Intrahippocampal Depth Electrodes in Patients With Refractory Epilepsy: A Comparative in Vivo (Application) Study

BACKGROUND:

Despite progress in imaging technologies, documentation of unifocal electrical excitability is pivotal in patient selection for epilepsy surgery.

OBJECTIVE:

To compare the application accuracy of the Vogele-Bale-Hohner system (VBH), a maxillary fixation system with an external fiducial frame permitting frameless stereotactic guidance, with that of conventional frame-based stereotaxy for placement of intrahippocampal depth electrodes (DEs) in patients with refractory epilepsy.

METHODS:

Retrospective study. Comparison of two patient cohorts with DEs implanted along the occipitotemporal axis (group A, VBH; group B, frame-based stereotaxy). In vivo accuracy (lateral target localization error [TLE]), determined postoperatively by measuring the normal distance between virtual target and real electrode position at the tip and at 4cm from the tip, number of electrode contacts within the target structure, and diagnostic quality of electroencephalogram recordings were compared.

RESULTS:

Seventeen DEs (A, 6 electrodes, 60 contacts; B, 11 electrodes, 90 contacts) were placed. electroencephalogram recordings via DEs supported further treatment decisions in all patients. TLE was 2.433 ± 0.977 mm (SD) (95% confidence interval [CI], 1.715-3.214 mm) (A) and 1.803 ± 0.392 mm (SD) (95% CI,1.511-2.195 mm) (B) (P = .185). Maximal error was 4 mm (A) and 3.2 mm (B). TLE 4 cm from the tip was 2.166 ± 2.188 mm (SD) (95% CI,0.438-3.916 mm) (A) and 1.372 ± 0.548 mm (SD) (95% CI,1.049-1.695 mm) (B) (P = .39). Maximal error 4 cm from the tip was 6.4 mm (A) and 2.14 mm (B). On average, 7 (A) and 5 (B) electrode contacts were placed in the target region.

CONCLUSION:

The VBH and frame-based systems offer similar in vivo accuracy for intrahippocampal DE placement. With frame-based methods, accuracy is higher but the number of contacts per side is lower. This does not translate to clinically important differences.

Classification and Analysis of the Errors in Neuronavigation

There are many different types of errors in neuronavigation, and the reasons and results of these errors are complex. For a neurosurgeon using the neuronavigation system, it is important to have a clear understanding of when an error may occur, what the magnitude of it is, and how to avoid it or reduce its influence on the final application accuracy. In this article, we classify all the errors into 2 groups according to the working principle of neuronavigation systems. The first group contains the errors caused by the differences between the anatomic structures in the images and that of the real patient, and the second group contains the errors occurring in transforming the position of surgical tools from the patient space to the image space. Each group is further divided into 2 subgroups. We discuss 16 types of errors and classify each of them into one of the subgroups. The classification and analysis of these errors should help neurosurgeons understand the power and limits of neuronavigation systems and use them more properly.

Automated detection of fiducial screws from CT/DVT volume data for image-guided ENT surgery

This paper presents an automated solution for precise detection of fiducial screws from three-dimensional (3D) Computerized Tomography (CT)/Digital Volume Tomography (DVT) data for image-guided ENT surgery. Unlike previously published solutions, we regard the detection of the fiducial screws from the CT/DVT volume data as a pose estimation problem. We thus developed a model-based solution. Starting from a user-supplied initialization, our solution detects the fiducial screws by iteratively matching a computer aided design (CAD) model of the fiducial screw to features extracted from the CT/DVT data. We validated our solution on one conventional CT dataset and on five DVT volume datasets, resulting in a total detection of 24 fiducial screws. Our experimental results indicate that the proposed solution achieves much higher reproducibility and precision than the manual detection. Further comparison shows that the proposed solution produces better results on the DVT dataset than on the conventional CT dataset.

Robotic mastoidectomy

HYPOTHESIS

Using image-guided surgical techniques, we propose that an industrial robot can be programmed to safely, effectively, and efficiently perform a mastoidectomy.

BACKGROUND

Whereas robotics is a mature field in many surgical applications, robots have yet to be clinically used in otologic surgery despite significant advantages including reliability and precision.

METHODS

We designed a robotic system that incorporates custom software with an industrial robot to manipulate a surgical drill through a complex milling profile. The software controls the movements of the robot based on real-time feedback from a commercially available optical tracking system. The desired path of the drill to remove the desired volume of mastoid bone was planned using computed tomographic scans of cadaveric specimens and then implemented using the robotic system. Bone-implanted fiducial markers were used to provide accurate registration between computed tomographic and physical space.

RESULTS

A mastoid cavity was milled on 3 cadaveric specimens with a 5-mm fluted ball bit. Postmilling computed tomographic scans showed that, for the 3 specimens, 97.70%, 99.99%, and 96.05% of the target region was ablated without violation of any critical feature.

CONCLUSION

To the best of our knowledge, this is the first time that a robot has been used to perform a mastoidectomy. Although significant hurdles remain to translate this technology to clinical use, we have shown that it is feasible. The prospect of reducing surgical time and enhancing patient safety by replacing human hand-eye coordination with machine precision motivates future work toward translating this technique to clinical use.

Co-registration of high resolution MRI scans with partial brain coverage in non-human primates

Dynamic structural and functional remodeling of the Central Nervous System occurs throughout the lifespan of the organism from the molecular to the systems level. MRI offers several advantages to observe this phenomenon: it is non-invasive and non-destructive, the contrast can be tuned to interrogate different tissue properties and imaging resolution can range from cortical columns to whole brain networks in the same session. To measure these changes reliably, functional maps generated over time with high resolution fMRI need to be registered accurately. This article presents a new method for the automatic registration of thin cortical MR volumes that are aligned with the functional maps. These acquisitions focus on the primary somato-sensory cortex, a region in the anterior parietal part of the brain, responsible for fine touch and proprioception. Currently, these slabs are acquired in approximately the same orientation from acquisition to acquisition and then registered by hand. Because they only cover a small portion of the cortex, their direct automatic registration is difficult. To address this issue, we propose a method relying on an intermediate image, acquired with a surface coil that covers a larger portion of the head to which the slabs can be registered. Because images acquired with surface coils suffer from severe intensity attenuation artifact, we also propose a method to register these. The results from data sets obtained with 3 squirrel monkeys show a registration accuracy of 30 micrometers.).

Target and Trajectory Clinical Application Accuracy in Neuronavigation

BACKGROUND:

Catheter, needle, and electrode misplacement in navigated neurosurgery can result in ineffective treatment and severe complications.

OBJECTIVE:

To assess the Ommaya ventricular catheter localization accuracy both along the planned trajectory and at the target.

METHODS:

We measured the localization error along the ventricular catheter and on its tip for 15 consecutive patients who underwent insertion of the Ommaya catheter surgery with a commercial neuronavigation system. The preoperative computed tomography/magnetic resonance images and the planned trajectory were aligned with the postoperative computed tomography images showing the Ommaya catheter. The localization errors along the trajectory and at the target were then computed by comparing the preoperative planned trajectory with the actual postoperative catheter position. The measured localization errors were also compared with the error reported by the navigation system.

RESULTS:

The mean localization errors at the target and entry point locations were 5.9 ± 4.3 and 3.3 ± 1.9 mm, respectively. The mean shift and angle between planned and actual trajectories were 1.6 ± 1.9 mm and 3.9 ± 4.7°, respectively. The mean difference between the localization error at the target and entry point was 3.9 ± 3.7 mm. The mean difference between the target localization error and the reported navigation system error was 4.9 ± 4.8 mm.

CONCLUSION:

The catheter localization errors have significant variations at the target and along the insertion trajectory. Trajectory errors may differ significantly from the errors at the target. Moreover, the single registration error number reported by the navigation system does not appropriately reflect the trajectory and target errors and thus should be used with caution to assess the procedure risk.

Customized, miniature rapid-prototype stereotactic frames for use in deep brain stimulator surgery: initial clinical methodology and experience from 263 patients from 2002 to 2008

BACKGROUND

The microTargeting™ platform (MTP) stereotaxy system (FHC Inc., Bowdoin, Me., USA) was FDA approved in 2001 utilizing rapid-prototyping technology to create custom platforms for human stereotaxy procedures. It has also been called the STarFix (surgical targeting fixture) system since it is based on the concept of a patient- and procedure-specific surgical fixture. This is an alternative stereotactic method by which planned trajectories are incorporated into custom-built, miniature stereotactic platforms mounted onto bone fiducial markers. Our goal is to report the clinical experience with this system over a 6-year period.

METHODS

We present the largest reported series of patients who underwent deep brain stimulation (DBS) implantations using customized rapidly prototyped stereotactic frames (MTP). Clinical experience and technical features for the use of this stereotactic system are described. Final lead location analysis using postoperative CT was performed to measure the clinical accuracy of the stereotactic system.

RESULTS

Our series included 263 patients who underwent 284 DBS implantation surgeries at one institution over a 6-year period. The clinical targeting error without accounting for brain shift in this series was found to be 1.99 mm (SD 0.9). Operating room time was reduced through earlier incision time by 2 h per case.

CONCLUSION

Customized, miniature stereotactic frames, namely STarFix platforms, are an acceptable and efficient alternative method for DBS implantation. Its clinical accuracy and outcome are comparable to those associated with traditional stereotactic frame systems.

Optimal Fiducial Configuration in Image-Guided Neurosurgery Using a Genetic Algorithm

Image-guided neurosurgery allows surgeons to navigate and localize lesion through the patient’s cranium with a 3D image guidance. The model of the head is reconstructed using preoperative computed tomography or magnetic resonance images and real and virtual spaces are aligned by means of fiducial markers placed on the patient. In this paper, a new method for the optimal placement of the fiducial markers in order to reduce misalignment is presented. Using routine diagnostic images, a customized 3D model of the patient’s cranium is reconstructed. A genetic algorithm calculates optimal positions of the marker in order to minimize the target registration error. The fiducial set is shown to the surgeons on the 3D model to help him/her in placement of them.

Stochastic approach to error estimation for image-guided robotic systems

Image-guided surgical systems and surgical robots are primarily developed to provide patient safety through increased precision and minimal invasiveness. Even more, robotic devices should allow for refined treatments that are not possible by other means. It is crucial to determine the accuracy of a system, to define the expected overall task execution error. A major step toward this aim is to quantitatively analyze the effect of registration and tracking-series of multiplication of erroneous homogeneous transformations. First, the currently used models and algorithms are introduced along with their limitations, and a new, probability distribution based method is described. The new approach has several advantages, as it was demonstrated in our simulations. Primarily, it determines the full 6 degree of freedom accuracy of the point of interest, allowing for the more accurate use of advanced application-oriented concepts, such as Virtual Fixtures. On the other hand, it becomes feasible to consider different surgical scenarios with varying weighting factors.

Understanding the effect of bias in fiducial localization error on point-based rigid-body registration

Image registration is a single point of failure in the image-guided computer-assisted surgery. Registration is primarily used to align and fuse the data sets taken from patient's anatomy before and during surgeries. Point-based rigid-body registration is usually performed by identifying corresponding fiducials (either natural landmarks or implanted ones) in the data sets. Since the localization of fiducials is imprecise and is generally perturbed by random noise, the performed registration is imperfect and has some error. Previous work has extensively analyzed the behavior of this error when the fiducial localization error has zero-mean over the entire set of fiducials. However, if noise has a nonzero-mean or a bias, no formulation yet exists to determine the effect of noise on the overall registration accuracy. In this work, we derive novel formulations that relate the bias in the localized fiducials to the accuracy of the performed registration. We analytically and numerically demonstrate that by eliminating the estimated bias from the measured fiducial locations, one can effectively increase the accuracy of the performed registration.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

Distribution templates of the fiducial points in image-guided neurosurgery

BACKGROUND

Point-pair registration is widely used in an image-guided neurosurgery system. Poor distribution of the fiducial points leads to an increase in the target registration error (TRE).

OBJECTIVE

This study aimed to provide templates consisting of optimized positioning of the fiducial points to reduce the TRE in image-guided neurosurgery.

METHODS

We divided the head into 6 regions and provided distribution templates of the fiducial points for each of them. A variable termed TREM(r) was used to express the approximate expected square of the TRE at the target point with a specified distribution of fiducial points. We randomly selected 85 patients from 5 hospitals who underwent image-guided neurosurgery and compared the TREM(r) of the real fiducial points with that of the templates.

RESULTS

We grouped the patients by hospitals and regions. The mean TREM(r)s of the templates were much smaller than those of the real fiducial points. In each group, the range of the TREM(r) values of the templates was much smaller than that of the real fiducial points.

CONCLUSION

This study provides an easy method to implement a good distribution of the fiducial points to help reduce TRE in image-guided neurosurgery. The templates are simple and exact and can be easily integrated into current workflow.

Integration and evaluation of a needle-positioning robot with volumetric microcomputed tomography image guidance for small animal stereotactic interventions

PURPOSE

Preclinical research protocols often require insertion of needles to specific targets within small animal brains. To target biologically relevant locations in rodent brains more effectively, a robotic device has been developed that is capable of positioning a needle along oblique trajectories through a single burr hole in the skull under volumetric microcomputed tomography (micro-CT) guidance.

METHODS

An x-ray compatible stereotactic frame secures the head throughout the procedure using a bite bar, nose clamp, and ear bars. CT-to-robot registration enables structures identified in the image to be mapped to physical coordinates in the brain. Registration is accomplished by injecting a barium sulfate contrast agent as the robot withdraws the needle from predefined points in a phantom. Registration accuracy is affected by the robot-positioning error and is assessed by measuring the surface registration error for the fiducial and target needle tracks (FRE and TRE). This system was demonstrated in situ by injecting 200 microm tungsten beads into rat brains along oblique trajectories through a single burr hole on the top of the skull under micro-CT image guidance. Postintervention micro-CT images of each skull were registered with preintervention high-field magnetic resonance images of the brain to infer the anatomical locations of the beads.

RESULTS

Registration using four fiducial needle tracks and one target track produced a FRE and a TRE of 96 and 210 microm, respectively. Evaluation with tissue-mimicking gelatin phantoms showed that locations could be targeted with a mean error of 154 +/- 113 microm.

CONCLUSIONS

The integration of a robotic needle-positioning device with volumetric micro-CT image guidance should increase the accuracy and reduce the invasiveness of stereotactic needle interventions in small animals.