Robert Johannes Frederik Homan

Live 3D Guidance in the Interventional Radiology Suite

OBJECTIVE The development of a C-arm cone-beam CT unit coupled with flat detectors has markedly increased anatomic visualization capabilities for interventional radiology procedures. We present technology in which fluoroscopy and 3D imaging from a cone-beam CT-flat-detector C-arm unit are combined with an integrated tracking and navigation system. A description of the technology and representative clinical cases are presented. CONCLUSION This new combination further increases interventional radiologic capabilities because it provides real-time procedural evaluation and tracking.

3D roadmap in neuroangiography: technique and clinical interest

We present the first clinical results obtained with a novel technique: the three-dimensional [3D] roadmap. The major difference from the standard 2D digital roadmap technique is that the newly developed 3D roadmap is based on a rotational angiography acquisition technique with the two-dimensional [2D] fluoroscopic image as an overlay. Data required for an accurate superimposition of the previously acquired 3D reconstructed image on the interactively made 2D fluoroscopy image, in real time, are stored in the 3D workstation and constitute the calibration dataset. Both datasets are spatially aligned in real time; thus, the 3D image is accurately superimposed on the 2D fluoroscopic image regardless of any change in C-arm position or magnification. The principal advantage of the described roadmap method is that one contrast injection allows the C-arm to be positioned anywhere in the space and allows alterations in the distance between the x-ray tube and the image intensifier as well as changes in image magnification. In the clinical setting, the 3D roadmap facilitated intravascular neuronavigation with concurrent reduction of procedure time and use of contrast medium.

Validation of 3D multimodality roadmapping in interventional neuroradiology

Three-dimensional multimodality roadmapping is entering clinical routine utilization for neuro-vascular treatment. Its purpose is to navigate intra-arterial and intra-venous endovascular devices through complex vascular anatomy by fusing pre-operative computed tomography (CT) or magnetic resonance (MR) with the live fluoroscopy image. The fused image presents the real-time position of the intra-vascular devices together with the patients 3D vascular morphology and its soft-tissue context. This paper investigates the effectiveness, accuracy, robustness and computation times of the described methods in order to assess their suitability for the intended clinical purpose: accurate interventional navigation. The mutual information-based 3D-3D registration proved to be of sub-voxel accuracy and yielded an average registration error of 0.515 mm and the live machine-based 2D-3D registration delivered an average error of less than 0.2 mm. The capture range of the image-based 3D-3D registration was investigated to characterize its robustness, and yielded an extent of 35 mm and 25° for >80% of the datasets for registration of 3D rotational angiography (3DRA) with CT, and 15 mm and 20° for >80% of the datasets for registration of 3DRA with MR data. The image-based 3D-3D registration could be computed within 8 s, while applying the machine-based 2D-3D registration only took 1.5 µs, which makes them very suitable for interventional use.

Utility of VasoCT in the treatment of intracranial aneurysm with flow-diverter stents.

OBJECT The small size and tortuous anatomy of intracranial arteries require that flow-diverter stents in the intracranial vasculature have a low profile, high flexibility, and excellent trackability. However, these features limit the degree of radiopacity that can be incorporated into the stents. Visualization of these stents and the degree of stent deployment using conventional radiographic techniques is suboptimal. To overcome this drawback, the authors used a new combined angiography/CT suite that uses flat-panel detector technology for higher resolution angiography. METHODS The authors present their preliminary experience in the imaging of flow-diverter stents in 31 patients in whom VasoCT was used with a new flat-panel detector angiographic system. RESULTS Intraarterial VasoCT was performed after flow-diverter stent deployment in all cases. In 4 of these cases, balloon angioplasty or telescopic stent deployment-related decisions were made after checking VasoCT images. At 3- and 6-month follow-up in 27 patients, digital subtraction angiography was performed in 12 patients and intravenous VasoCT in 11 patients. Twenty-three of 31 patients had their aneurysm occluded during short-term follow-up, and 4 of the 31 patients still had minimal residual filling of the aneurysms. None of the 27 patients had stenosis of the parent artery. CONCLUSIONS The authors found that VasoCT provides clear visualization of flow-diverter stents. The images obtained both intraarterially and intravenously are very promising. The initial results provide a high confidence and reproducibility rate for further utilization of this new technique.

Evaluation of optimization methods for intensity-based 2D-3D registration in x-ray guided interventions

The advantage of 2D-3D image registration methods versus direct image-to-patient registration, is that these methods generally do not require user interaction (such as manual annotations), additional machinery or additional acquisition of 3D data. A variety of intensity-based similarity measures has been proposed and evaluated for different applications. These studies showed that the registration accuracy and capture range are influenced by the choice of similarity measure. However, the influence of the optimization method on intensity-based 2D-3D image registration has not been investigated. We have compared the registration performance of seven optimization methods in combination with three similarity measures: gradient difference, gradient correlation, and pattern intensity. Optimization methods included in this study were: regular step gradient descent, Nelder-Mead, Powell-Brent, Quasi-Newton, nonlinear conjugate gradient, simultaneous perturbation stochastic approximation, and evolution strategy. Registration experiments were performed on multiple patient data sets that were obtained during cerebral interventions. Various component combinations were evaluated on registration accuracy, capture range, and registration time. The results showed that for the same similarity measure, different registration accuracies and capture ranges were obtained when different optimization methods were used. For gradient difference, largest capture ranges were obtained with Powell-Brent and simultaneous perturbation stochastic approximation. Gradient correlation and pattern intensity had the largest capture ranges in combination with Powell-Brent, Nelder-Mead, nonlinear conjugate gradient, and Quasi-Newton. Average registration time, expressed in the number of DRRs required for convergence, was the lowest for Powell-Brent. Based on these results, we conclude that Powell-Brent is a reliable optimization method for intensity-based 2D-3D registration of x-ray images to CBCT, regardless of the similarity measure used.

Registration of 2D x-ray images to 3D MRI by generating pseudo-CT data

Spatial and soft tissue information provided by magnetic resonance imaging can be very valuable during image-guided procedures, where usually only real-time two-dimensional (2D) x-ray images are available. Registration of 2D x-ray images to three-dimensional (3D) magnetic resonance imaging (MRI) data, acquired prior to the procedure, can provide optimal information to guide the procedure. However, registering x-ray images to MRI data is not a trivial task because of their fundamental difference in tissue contrast. This paper presents a technique that generates pseudo-computed tomography (CT) data from multi-spectral MRI acquisitions which is sufficiently similar to real CT data to enable registration of x-ray to MRI with comparable accuracy as registration of x-ray to CT. The method is based on a k-nearest-neighbors (kNN)-regression strategy which labels voxels of MRI data with CT Hounsfield Units. The regression method uses multi-spectral MRI intensities and intensity gradients as features to discriminate between various tissue types. The efficacy of using pseudo-CT data for registration of x-ray to MRI was tested on ex vivo animal data. 2D-3D registration experiments using CT and pseudo-CT data of multiple subjects were performed with a commonly used 2D-3D registration algorithm. On average, the median target registration error for registration of two x-ray images to MRI data was approximately 1 mm larger than for x-ray to CT registration. The authors have shown that pseudo-CT data generated from multi-spectral MRI facilitate registration of MRI to x-ray images. From the experiments it could be concluded that the accuracy achieved was comparable to that of registering x-ray images to CT data.

3D multimodality roadmapping in neuroangiography

In this paper we describe a novel approach to using morphological datasets (such as CT or MR) in the minimally invasive image guidance of intra-arterial and intra-venous endovascular devices in neuroangiography interventions. Minimally invasive X-ray angiography procedures rely on the navigation of endovascular devices, such as guide wires and catheters, through human vessels, using C-arm fluoroscopy. While the bone structure may be visible, and the injection of iodine contrast medium allows to guide endovascular devices through the vasculature, the soft-tissue structures remain invisible in the fluoroscopic images. We intend to present a method for the combined visualization of morphological data, a 3D rotational angiography (3DRA) reconstruction and the live fluoroscopy data stream in a single image. The combination of the fluoroscopic image with the 3DRA vessel tree offers the advantage that endovascular devices can be located with respect to the vasculature, without additional contrast injection, while the position of the C-arm geometry can be altered freely. The additional visualization of the morphological data, adds contextual information to the position of endovascular devices. This article addresses the clinical applications, the real-time aspects of the registration algorithms and fast fused visualization of the proposed method.

Surgical Navigation Technology Based on Augmented Reality and Integrated 3D Intraoperative Imaging: A Spine Cadaveric Feasibility and Accuracy Study.

Study Design. A cadaveric laboratory study. Objective. The aim of this study was to assess the feasibility and accuracy of thoracic pedicle screw placement using augmented reality surgical navigation (ARSN). Summary of Background Data. Recent advances in spinal navigation have shown improved accuracy in lumbosacral pedicle screw placement but limited benefits in the thoracic spine. 3D intraoperative imaging and instrument navigation may allow improved accuracy in pedicle screw placement, without the use of x-ray fluoroscopy, and thus opens the route to image-guided minimally invasive therapy in the thoracic spine. Methods. ARSN encompasses a surgical table, a motorized flat detector C-arm with intraoperative 2D/3D capabilities, integrated optical cameras for augmented reality navigation, and noninvasive patient motion tracking. Two neurosurgeons placed 94 pedicle screws in the thoracic spine of four cadavers using ARSN on one side of the spine (47 screws) and free-hand technique on the contralateral side. X-ray fluoroscopy was not used for either technique. Four independent reviewers assessed the postoperative scans, using the Gertzbein grading. Morphometric measurements of the pedicles axial and sagittal widths and angles, as well as the vertebrae axial and sagittal rotations were performed to identify risk factors for breaches. Results. ARSN was feasible and superior to free-hand technique with respect to overall accuracy (85% vs. 64%, P < 0.05), specifically significant increases of perfectly placed screws (51% vs. 30%, P < 0.05) and reductions in breaches beyond 4 mm (2% vs. 25%, P < 0.05). All morphometric dimensions, except for vertebral body axial rotation, were risk factors for larger breaches when performed with the free-hand method. Conclusion. ARSN without fluoroscopy was feasible and demonstrated higher accuracy than free-hand technique for thoracic pedicle screw placement. Level of Evidence: N/A

Real-time integration of 3-D multimodality data in interventional neuroangiography

We describe a novel approach to using soft-tissue data sets, such as computer tomography on magnetic resonance, in the minimally invasive image guidance of intra-arterial and intravenous endovascular devices in neuroangiography interventions. Minimally invasive x-ray angiography procedures rely on the navigation of en- dovascular devices, such as guide wires and catheters, through hu- man vessels, using C-arm fluoroscopy. Although the bone structure may be visible and the injection of iodine contrast medium allows one to guide endovascular devices through the vasculature, the soft-tissue structures remain invisible in the fluoroscopic images. We intend to present a method for the combined visualization of soft-tissue data, a 3-D rotational angiography (3-DRA) reconstruc- tion, and the live fluoroscopy data stream in a single fused image. Combining the fluoroscopic image with the 3-DRA vessel tree offers the advantage that endovascular devices can be located within the vasculature without additional contrast injection, while the position of the C-arm geometry can be altered freely. The additional visualiza- tion of the soft-tissue data adds contextual information to the posi- tion of endovascular devices. We address the clinical applications, the real-time aspects of the registration algorithms, and fast-fused visualization of the proposed method.

Real-time 3D position reconstruction of guidewire for monoplane X-ray

We present a novel real-time method for the 3D reconstruction of the guidewire using a monoplane X-ray. The method consists of two steps: (1) the backprojection step to reconstruct a 3D surface that contains the guidewire and (2) the optimization step to select a curve on the surface that is the best match under the pre-specified constraints. The proposed method utilizes a priori knowledge in the form of a volume that indicates positions of the blood vessels and thus restricts the reconstruction. The reconstruction precision is limited by the local thickness of the vessels. The method is quantitatively evaluated on five phantom datasets and qualitatively on two patient datasets. For the phantom datasets the average reconstruction error is resolution limited to 1-2 voxels and is biased in the depth direction. The worst-case reconstruction error for any point, including the guidewire tip, is not larger than the local vessel thickness. A visual inspection of results for the patient datasets shows the guidewire is always placed in the proper vessel and is aligned with the 2D image, which is sufficient for the guidewire navigation. The developed implementation achieves the processing speed of 12 fps using Core™i7 CPU 920 at 2.67 GHz.