Three-dimensional guide-wire reconstruction from biplane image sequences for integrated display in 3-D vasculature

Topology observing 3D device reconstruction from continuous-sweep limited angle fluoroscopy

BACKGROUND

Minimally invasive procedures usually require navigating a microcatheter and guidewire through endoluminal structures such as blood vessels and airways to sites of the disease. For numerous clinical applications, two-dimensional (2D) fluoroscopy is the primary modality used for real-time image guidance during navigation. However, 2D imaging can pose challenges for navigation in complex structures. Real-time 3D visualization of devices within the anatomic context could provide considerable benefits for these procedures. Continuous-sweep limited angle (CLA) fluoroscopy has recently been proposed to provide a compromise between conventional rotational 3D acquisitions and real-time fluoroscopy.

PURPOSE

The purpose of this work was to develop and evaluate a noniterative 3D device reconstruction approach for CLA fluoroscopy acquisitions, which takes into account endoluminal topology to avoid impossible paths between disconnected branches.

METHODS

The algorithm relies on a static 3D roadmap (RM) of vessels or airways, which may be generated from conventional cone beam CT (CBCT) acquisitions prior to navigation. The RM is converted to a graph representation describing its topology. During catheter navigation, the device is segmented from the live 2D projection images using a deep learning approach from which the centerlines are extracted. Rays from the focal spot to detector pixels representing 2D device points are identified and intersections with the RM are computed. Based on the RM graph, a subset of line segments is selected as candidates to exclude device paths through disconnected branches of the RM. Depth localization for each point along the device is then performed by finding the point closest to the previous 3D reconstruction along the candidate segments. This process is repeated as the projection angle changes for each CLA image frame. The approach was evaluated in a phantom study in which a catheter and guidewire were navigated along five pathways within a complex vessel phantom. The result was compared to static cCBCT acquisitions of the device in the final position.

RESULTS

The average root mean squared 3D distance between CLA reconstruction and reference centerline was1.87 ± 0.30 $1.87 \pm 0.30$ mm. The Euclidean distance at the device tip was2.92 ± 2.35 $2.92 \pm 2.35$ mm. The correct pathway was identified during reconstruction in100 % $100\%$ of frames (n = 1475 $n=1475$ ). The percentage of 3D device points reconstructed inside the 3D roadmap was91.83 ± 2.52 % $91.83 \pm 2.52\%$ with an average distance of0.62 ± 0.30 $0.62 \pm 0.30$ mm between the device points outside the roadmap and the nearest point within the roadmap.

CONCLUSIONS

This study demonstrates the feasibility of reconstructing curvilinear devices such as catheters and guidewires during endoluminal procedures including intravascular and transbronchial interventions using a noniterative reconstruction approach for CLA fluoroscopy. This approach could improve device navigation in cases where the structure of vessels or airways is complex and includes overlapping branches.

Real-time 3D reconstruction of guidewires and stents using two update X-ray projections in a rotating imaging setup

BACKGROUND

Vascular diseases are often treated minimally invasively. The interventional material (stents, guidewires, etc.) used during such percutaneous interventions are visualized by some form of image guidance. Today, this image guidance is usually provided by 2D X-ray fluoroscopy, that is, a live 2D image. 3D X-ray fluoroscopy, that is, a live 3D image, could accelerate existing and enable new interventions. However, existing algorithms for the 3D reconstruction of interventional material require either too many X-ray projections and therefore dose, or are only capable of reconstructing single, curvilinear structures.

PURPOSE

Using only two new X-ray projections per 3D reconstruction, we aim to reconstruct more complex arrangements of interventional material than was previously possible.

METHODS

This is achieved by improving a previously presented deep learning-based reconstruction pipeline, which assumes that the X-ray images are acquired by a continuously rotating biplane system, in two ways: (a) separation of the reconstruction of different object types, (b) motion compensation using spatial transformer networks.

RESULTS

Our pipeline achieves submillimeter accuracy on measured data of a stent and two guidewires inside an anthropomorphic phantom with respiratory motion. In an ablation study, we find that the aforementioned algorithmic changes improve our two figures of merit by 75 % (1.76 mm → 0.44 mm) and 59 % (1.15 mm → 0.47 mm) respectively. A comparison of our measured dose area product (DAP) rate to DAP rates of 2D fluoroscopy indicates a roughly similar dose burden.

CONCLUSIONS

This dose efficiency combined with the ability to reconstruct complex arrangements of interventional material makes the presented algorithm a promising candidate to enable 3D fluoroscopy.

3D localization from 2D X-ray projection

PURPOSE

Most cardiology procedures are guided using X-ray (XR) fluoroscopy. However, the projective nature of the XR fluoroscopy does not allow for true depth perception as required for safe and efficient intervention guidance in structural heart diseases. For improving guidance, different methods have been proposed often being radiation-intensive, time-consuming, or expensive. We propose a simple 3D localization method based on a single monoplane XR projection using a co-registered centerline model.

METHODS

The method is based on 3D anatomic surface models and corresponding centerlines generated from preprocedural imaging. After initial co-registration, 2D working points identified in monoplane XR projections are localized in 3D by minimizing the angle between the projection lines of the centerline points and the working points. The accuracy and reliability of the located 3D positions were assessed in 3D using phantom data and in patient data projected to 2D obtained during placement of embolic protection system in interventional procedures.

RESULTS

With the proposed methods, 2D working points identified in monoplane XR could be successfully located in the 3D phantom and in the patient-specific 3D anatomy. Accuracy in the phantom (3D) resulted in 1.6 mm (± 0.8 mm) on average, and 2.7 mm (± 1.3 mm) on average in the patient data (2D).

CONCLUSION

The use of co-registered centerline models allows reliable and accurate 3D localization of devices from a single monoplane XR projection during placement of the embolic protection system in TAVR. The extension to different vascular interventions and combination with automatic methods for device detection and registration might be promising.

Shape Reconstruction Processes for Interventional Application Devices: State of the Art, Progress, and Future Directions

Soft and continuum robots are transforming medical interventions thanks to their flexibility, miniaturization, and multidirectional movement abilities. Although flexibility enables reaching targets in unstructured and dynamic environments, it also creates challenges for control, especially due to interactions with the anatomy. Thus, in recent years lots of efforts have been devoted for the development of shape reconstruction methods, with the advancement of different kinematic models, sensors, and imaging techniques. These methods can increase the performance of the control action as well as provide the tip position of robotic manipulators relative to the anatomy. Each method, however, has its advantages and disadvantages and can be worthwhile in different situations. For example, electromagnetic (EM) and Fiber Bragg Grating (FBG) sensor-based shape reconstruction methods can be used in small-scale robots due to their advantages thanks to miniaturization, fast response, and high sensitivity. Yet, the problem of electromagnetic interference in the case of EM sensors, and poor response to high strains in the case of FBG sensors need to be considered. To help the reader make a suitable choice, this paper presents a review of recent progress on shape reconstruction methods, based on a systematic literature search, excluding pure kinematic models. Methods are classified into two categories. First, sensor-based techniques are presented that discuss the use of various sensors such as FBG, EM, and passive stretchable sensors for reconstructing the shape of the robots. Second, imaging-based methods are discussed that utilize images from different imaging systems such as fluoroscopy, endoscopy cameras, and ultrasound for the shape reconstruction process. The applicability, benefits, and limitations of each method are discussed. Finally, the paper draws some future promising directions for the enhancement of the shape reconstruction methods by discussing open questions and alternative methods.

Deep learning-based reconstruction of interventional tools and devices from four X-ray projections for tomographic interventional guidance

PURPOSE

Image guidance for minimally invasive interventions is usually performed by acquiring fluoroscopic images using a monoplanar or a biplanar C-arm system. However, the projective data provide only limited information about the spatial structure and position of interventional tools and devices such as stents, guide wires, or coils. In this work, we propose a deep learning-based pipeline for real-time tomographic (four-dimensional [4D]) interventional guidance at conventional dose levels.

METHODS

Our pipeline is comprised of two steps. In the first one, interventional tools are extracted from four cone-beam CT projections using a deep convolutional neural network. These projections are then Feldkamp reconstructed and fed into a second network, which is trained to segment the interventional tools and devices in this highly undersampled reconstruction. Both networks are trained using simulated CT data and evaluated on both simulated data and C-arm cone-beam CT measurements of stents, coils, and guide wires.

RESULTS

The pipeline is capable of reconstructing interventional tools from only four X-ray projections without the need for a patient prior. At an isotropic voxel size of 100 μ m , our methods achieve a precision/recall within a 100 μ m environment of the ground truth of 93%/98%, 90%/71%, and 93%/76% for guide wires, stents, and coils, respectively.

CONCLUSIONS

A deep learning-based approach for 4D interventional guidance is able to overcome the drawbacks of today's interventional guidance by providing full spatiotemporal (4D) information about the interventional tools at dose levels comparable to conventional fluoroscopy.

Laser-Generated Leaky Acoustic Wave Imaging for Interventional Guidewire Guidance

Ultrasound (US) is widely used to visualize both tissue and the positions of surgical instruments in real time during surgery. Previously we proposed a new method to exploit US imaging and laser-generated leaky acoustic waves (LAWs) for needle visualization. Although successful, that method only detects the position of a needle tip, with the location of the entire needle deduced from knowing that the needle is straight. The purpose of the current study was to develop a beamforming-based method for the direct visualization of objects. The approach can be applied to objects with arbitrary shapes, such as the guidewires that are commonly used in interventional guidance. With this method, illumination by a short laser pulse generates photoacoustic waves at the top of the guidewire that propagate down its metal surface. These waves then leak into the surrounding tissue, which can be detected by a US array transducer. The time of flight consists of two parts: 1) the propagation time of the guided waves on the guidewire and 2) the propagation time of the US that leaks into the tissue. In principle, an image of the guidewire can be formed based on array beamforming by taking the propagation time on the metal into consideration. Furthermore, we introduced directional filtering and a matched filter to compress the dispersion signal associated with long propagation times. The results showed that guidewires could be detected at depths of at least 70 mm. The maximum detectable angle was 56.3°. LAW imaging with a 1268-mm-long guidewire was also demonstrated. The proposed method has considerable potential in new clinical applications.

Constrained stochastic state estimation of deformable 1D objects: Application to single-view 3D reconstruction of catheters with radio-opaque markers

Minimally invasive fluoroscopy-based procedures are the gold standard for diagnosis and treatment of various pathologies of the cardiovascular system. This kind of procedures imply for the clinicians to infer the 3D shape of the device from 2D images, which is known to be an ill-posed problem. In this paper we present a method to reconstruct the 3D shape of the interventional device, with the aim of improving the navigation. The method combines a physics-based simulation with non-linear Bayesian filter. Whereas the physics-based model provides a prediction of the shape of the device navigating within the blood vessels (taking into account non-linear interactions between the catheter and the surrounding anatomy), an Unscented Kalman Filter is used to correct the navigation model using 2D image features as external observations. The proposed framework has been evaluated on both synthetic and real data, under different model parameterizations, filter parameters tuning and external observations data-sets. Comparing the reconstructed 3D shape with a known ground truth, for the synthetic data-set, we obtained average values for 3D Hausdorff Distance of 0.81±0.53mm, for the 3D mean distance at the segment of 0.37±0.17mm and an average 3D tip error of 0.24±0.13mm. For the real data-set,we obtained an average 3D Hausdorff distance of 1.74±0.77mm, a average 3D mean distance at the distal segment of 0.91±0.14mm, an average 3D error on the tip of 0.53±0.09mm. These results show the ability of our method to retrieve the 3D shape of the device, under a variety of filter parameterizations and challenging conditions: uncertainties on model parameterization, ambiguous views and non-linear complex phenomena such as stick and slip motions.

Simultaneous reconstruction of multiple stiff wires from a single X-ray projection for endovascular aortic repair

PURPOSE

Endovascular repair of aortic aneurysms (EVAR) can be supported by fusing pre- and intraoperative data to allow for improved navigation and to reduce the amount of contrast agent needed during the intervention. However, stiff wires and delivery devices can deform the vasculature severely, which reduces the accuracy of the fusion. Knowledge about the 3D position of the inserted instruments can help to transfer these deformations to the preoperative information.

METHOD

We propose a method to simultaneously reconstruct the stiff wires in both iliac arteries based on only a single monoplane acquisition, thereby avoiding interference with the clinical workflow. In the available X-ray projection, the 2D course of the wire is extracted. Then, a virtual second view of each wire orthogonal to the real projection is estimated using the preoperative vessel anatomy from a computed tomography angiography as prior information. Based on the real and virtual 2D wire courses, the wires can then be reconstructed in 3D using epipolar geometry.

RESULTS

We achieve a mean modified Hausdorff distance of 4.2 mm between the estimated 3D position and the true wire course for the contralateral side and 4.5 mm for the ipsilateral side.

CONCLUSION

The accuracy and speed of the proposed method allow for use in an intraoperative setting of deformation correction for EVAR.

A dynamic model-based approach to motion and deformation tracking of prosthetic valves from biplane x-ray images

PURPOSE

Transcatheter aortic valve replacement (TAVR) is a minimally invasive procedure in which a prosthetic heart valve is placed and expanded within a defective aortic valve. The device placement is commonly performed using two-dimensional (2D) fluoroscopic imaging. Within this work, we propose a novel technique to track the motion and deformation of the prosthetic valve in three dimensions based on biplane fluoroscopic image sequences.

METHODS

The tracking approach uses a parameterized point cloud model of the valve stent which can undergo rigid three-dimensional (3D) transformation and different modes of expansion. Rigid elements of the model are individually rotated and translated in three dimensions to approximate the motions of the stent. Tracking is performed using an iterative 2D-3D registration procedure which estimates the model parameters by minimizing the mean-squared image values at the positions of the forward-projected model points. Additionally, an initialization technique is proposed, which locates clusters of salient features to determine the initial position and orientation of the model.

RESULTS

The proposed algorithms were evaluated based on simulations using a digital 4D CT phantom as well as experimentally acquired images of a prosthetic valve inside a chest phantom with anatomical background features. The target registration error was 0.12 ± 0.04 mm in the simulations and 0.64 ± 0.09 mm in the experimental data.

CONCLUSIONS

The proposed algorithm could be used to generate 3D visualization of the prosthetic valve from two projections. In combination with soft-tissue sensitive-imaging techniques like transesophageal echocardiography, this technique could enable 3D image guidance during TAVR procedures.

4D interventional device reconstruction from biplane fluoroscopy

PURPOSE

Biplane angiography systems provide time resolved 2D fluoroscopic images from two different angles, which can be used for the positioning of interventional devices such as guidewires and catheters. The purpose of this work is to provide a novel algorithm framework, which allows the 3D reconstruction of these curvilinear devices from the 2D projection images for each time frame. This would allow creating virtual projection images from arbitrary view angles without changing the position of the gantries, as well as virtual endoscopic 3D renderings.

METHODS

The first frame of each time sequence is registered to and subtracted from the following frame using an elastic grid registration technique. The images are then preprocessed by a noise reduction algorithm using directional adaptive filter kernels and a ridgeness filter that emphasizes curvilinear structures. A threshold based segmentation of the device is then performed, followed by a flux driven topology preserving thinning algorithm to extract the segments of the device centerline. The exact device path is determined using Dijkstra's algorithm to minimize the curvature and distance between adjacent segments as well as the difference to the device path of the previous frame. The 3D device centerline is then reconstructed using epipolar geometry.

RESULTS

The accuracy of the reconstruction was measured in a vascular head phantom as well as in a cadaver head and a canine study. The device reconstructions are compared to rotational 3D acquisitions. In the phantom experiments, an average device tip accuracy of 0.35 ± 0.09 mm, a Hausdorff distance of 0.65 ± 0.32 mm, and a mean device distance of 0.54 ± 0.33 mm were achieved. In the cadaver head and canine experiments, the device tip was reconstructed with an average accuracy of 0.26 ± 0.20 mm, a Hausdorff distance of 0.62 ± 0.08 mm, and a mean device distance of 0.41 ± 0.08 mm. Additionally, retrospective reconstruction results of real patient data are presented.

CONCLUSIONS

The presented algorithm is a novel approach for the time resolved 3D reconstruction of interventional devices from biplane fluoroscopic images, thus allowing the creation of virtual projection images from arbitrary view angles as well as virtual endoscopic 3D renderings. Availability of this technique would enhance the ability to accurately position devices in minimally invasive endovascular procedures.

Electrophysiology Catheter Detection and Reconstruction From Two Views in Fluoroscopic Images

Electrophysiology (EP) studies and catheter ablation have become important treatment options for several types of cardiac arrhythmias. We present a novel image-based approach for automatic detection and 3-D reconstruction of EP catheters where the physician marks the catheter to be reconstructed by a single click in each image. The result can be used to provide 3-D information for enhanced navigation throughout EP procedures. Our approach involves two X-ray projections acquired from different angles, and it is based on two steps: First, we detect the catheter in each view after manual initialization using a graph-search method. Then, the detection results are used to reconstruct a full 3-D model of the catheter based on automatically determined point pairs for triangulation. An evaluation on 176 different clinical fluoroscopic images yielded a detection rate of 83.4%. For measuring the error, we used the coupling distance which is a more accurate quality measure than the average point-wise distance to a reference. For successful outcomes, the 2-D detection error was 1.7 mm ±1.2 mm. Using successfully detected catheters for reconstruction, we obtained a reconstruction error of 1.8 mm ±1.1 mm on phantom data. On clinical data, our method yielded a reconstruction error of 2.2 mm ±2.2 mm.

Automatic 3D reconstruction of electrophysiology catheters from two-view monoplane C-arm image sequences

PURPOSE

Catheter guidance is a vital task for the success of electrophysiology interventions. It is usually provided through fluoroscopic images that are taken intra-operatively. The cardiologists, who are typically equipped with C-arm systems, scan the patient from multiple views rotating the fluoroscope around one of its axes. The resulting sequences allow the cardiologists to build a mental model of the 3D position of the catheters and interest points from the multiple views.

METHOD

We describe and compare different 3D catheter reconstruction strategies and ultimately propose a novel and robust method for the automatic reconstruction of 3D catheters in non-synchronized fluoroscopic sequences. This approach does not purely rely on triangulation but incorporates prior knowledge about the catheters. In conjunction with an automatic detection method, we demonstrate the performance of our method compared to ground truth annotations.

RESULTS

In our experiments that include 20 biplane datasets, we achieve an average reprojection error of 0.43 mm and an average reconstruction error of 0.67 mm compared to gold standard annotation.

CONCLUSIONS

In clinical practice, catheters suffer from complex motion due to the combined effect of heartbeat and respiratory motion. As a result, any 3D reconstruction algorithm via triangulation is imprecise. We have proposed a new method that is fully automatic and highly accurate to reconstruct catheters in three dimensions.

Automatic detection of selective arterial devices for advanced visualization during abdominal aortic aneurysm endovascular repair

Here we address the automatic segmentation of endovascular devices used in the endovascular repair (EVAR) of abdominal aortic aneurysms (AAA) that deform vascular tissues. Using this approach, the vascular structure is automatically reshaped solving the issue of misregistration observed on 2D/3D image fusion for EVAR guidance. The endovascular devices we considered are the graduated pigtail catheter (PC) used for contrast injection and the stent-graft delivery device (DD). The segmentation of the DD was enhanced using an asymmetric Frangi filter. The segmented geometries were then analysed using their specific features to remove artefacts. The radiopaque markers of the PC were enhanced using a fusion of Hessian and newly introduced gradient norm shift filters. Extensive experiments were performed using a database of images taken during 28 AAA-EVAR interventions. This dataset was divided into two parts: the first half was used to optimize parameters and the second to compile performances using optimal values obtained. The radiopaque markers of the PC were detected with a sensitivity of 88.3% and a positive predictive value (PPV) of 96%. The PC can therefore be positioned with a majority of its markers localized while the artefacts were all located inside the vessel lumen. The major parts of the DD, the dilatator tip and the pusher surfaces, were detected accurately with a sensitivity of 85.9% and a PPV of 88.7%. The less visible part of the DD, the stent enclosed within the sheath, was segmented with a sensitivity of 63.4% because the radiopacity of this region is low and uneven. The centreline of the DD in this stent region was alternatively traced within a 0.74 mm mean error. The automatic segmentation of endovascular devices during EVAR is feasible and accurate; it could be useful to perform elastic registration of the vascular lumen during endovascular repair.

Noise reduction for curve-linear structures in real time fluoroscopy applications using directional binary masks

PURPOSE

Recent efforts in the reconstruction of interventional devices from two distinct views require the segmentation of the object in both fluoroscopic images. Noise might decrease the quality of the segmentation and cause artifacts in the reconstruction. The noise level depends on the x-ray dose the patient is exposed to. The proposed algorithm reduces the noise and enhances the separability of curvilinear devices in background subtracted fluoroscopic images to allow a more accurate segmentation.

METHODS

The algorithm uses a set of binary masks to estimate a line conformity measure that determines the best direction for a directional filter kernel. If the calculated value exceeds a certain threshold, the directional kernel is used to obtain the filtered value. Otherwise, an isotropic filter kernel is used.

RESULTS

The evaluation was performed on a set of 36 fluoroscopic images using a vascular head phantom with three different guidewires and nine different x-ray dosages from 6 nGy/pulse to 45 nGy/pulse as well as a clinical data set containing ten images. Compared with wavelet shrinkage and the bilateral filter, the proposed algorithm increased the average contrast to noise ratio by at least 17.8% for the phantom and 68.9% for the clinical images. The accuracy of the device segmentation was improved on average by at least 17.3% and 14.0%, respectively.

CONCLUSIONS

The proposed algorithm was able to significantly reduce the amount of noise in the images and therefore increase the quality of the device segmentations compared to both the bilateral filter and the wavelet thresholding approach for all acquired noise levels using rotating directional filter kernels near line structures and isotropic kernels for the background. The application of the proposed algorithm for the 3D reconstruction of curvilinear devices from two views would allow a more accurate reconstruction of the device.

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.

Vessel target location estimation during the TIPS procedure

Creation of a transjugular intrahepatic portosystemic shunt (TIPS) requires passage of a needle toward a moving target that is only seen transiently by X-ray prior to needle passage. Intraoperative, 3D target localization would facilitate target access and improve the safety of the procedure. The clinical assumption is that patients undergoing the TIPS procedure possess rigid, cirrhotic livers that undergo only intraoperative translation without significant deformation or rotation. Based upon this assumption, we hypothesize that the position of any unseen, 3D target point within the liver can be determined intraoperatively by precalculation of the relative positions of the target point to a different 3D point that can be tracked intraoperatively. This paper examines this hypothesis using intraoperatively acquired, biplane, X-ray images of seven patients. In six, we tracked the effects of cardiac and respiratory motion, and in three the effects of needle pressure. Methods involved reconstruction of 3D vessel bifurcation and other trackable intrahepatic points from biplane angiograms, measurement of liver deformation by examining changing distances between these 3D points over time, and comparison of expected to actual displacements of these points with respect to a fixed reference point in the liver. We conclude that, for the rigid livers associated with patients undergoing TIPS, that there is less intraoperative deformation than previously reported by other groups addressing healthy liver deformation, and that the location of an unseen target can be predicted within 3mm accuracy.

An algorithm for tracking microcatheters in fluoroscopy

Currently, a large number of endovascular interventions are performed for treatment of intracranial aneurysms. For these treatments, correct positioning of microcatheter tips, microguide wire tips, or coils is essential. Techniques to detect such devices may facilitate endovascular interventions. In this paper, we describe an algorithm for tracking of microcatheter tips during fluoroscopically guided neuroendovascular interventions. A sequence of fluoroscopic images (1,024 x 1,024 x 12 bits) was acquired using a C-arm angiography system as a microcatheter was passed through a carotid phantom which was on top of a head phantom. The carotid phantom was a silicone cylinder containing a simulated vessel with the shape and curvatures of the internal carotid artery. The head phantom consisted of a human skull and tissue-equivalent material. To detect the microcatheter in a given fluoroscopic frame, a background image consisting of an average of the four previous frames is subtracted from the current frame, the resulting image is filtered using a matched filter, and the position of maximum intensity in the filtered image is taken as the catheter tip position in the current frame. The distance between the tracked position and the correct position (error distance) was measured in each of the fluoroscopic images. The mean and standard deviation of the error distance values were 0.277 mm (1.59 pixels) and 0.26 mm (1.5 pixels), respectively. The error distance was less than 3 pixels in the 93.0% frames. Although the algorithm intermittently failed to correctly detect the catheter, the algorithm recovered the catheter in subsequent frames.

Microcatheter tip enhancement in fluoroscopy: a comparison of techniques

We compared three techniques for enhancement of microcatheter tips in fluoroscopic images: conventional subtraction technique (CST); averaged image subtraction technique (AIST), which we have developed; and double average filtering (DAF) technique, which uses nonlinear background estimates. A pulsed fluoroscopic image sequence was obtained as a microcatheter was passed through a carotid phantom that was on top of a head phantom. The carotid phantom was a silicone cylinder containing a simulated vessel with the shape and curvatures of the internal carotid artery. The three techniques were applied to the images of the sequence, then the catheter tip was manually identified in each image, and 100 x 100 pixel images, centered at the indicated microcatheter tip positions, were extracted for the evaluations. The signal-to-noise ratio (SNR) was calculated in each of the extracted images from which the mean value of the SNR and its standard deviation (SD) were calculated for each technique. The mean values and the standard deviations were 4.36 (SD 3.40) for CST, 6.34 (SD 3.62) for AIST, and 3.55 (SD 1.27) for DAF. AIST had a higher SNR compared to CST in almost all frames. Although DAF yielded the smallest mean SNR value, it yielded the best SNR in those frames in which the microcatheter tip did not move between frames. We conclude that AIST provides the best SNR for a moving microcatheter tip and that DAF is optimal for a temporarily stationary microcatheter tip.

Image-guidance for surgical procedures

Contemporary imaging modalities can now provide the surgeon with high quality three- and four-dimensional images depicting not only normal anatomy and pathology, but also vascularity and function. A key component of image-guided surgery (IGS) is the ability to register multi-modal pre-operative images to each other and to the patient. The other important component of IGS is the ability to track instruments in real time during the procedure and to display them as part of a realistic model of the operative volume. Stereoscopic, virtual- and augmented-reality techniques have been implemented to enhance the visualization and guidance process. For the most part, IGS relies on the assumption that the pre-operatively acquired images used to guide the surgery accurately represent the morphology of the tissue during the procedure. This assumption may not necessarily be valid, and so intra-operative real-time imaging using interventional MRI, ultrasound, video and electrophysiological recordings are often employed to ameliorate this situation. Although IGS is now in extensive routine clinical use in neurosurgery and is gaining ground in other surgical disciplines, there remain many drawbacks that must be overcome before it can be employed in more general minimally-invasive procedures. This review overviews the roots of IGS in neurosurgery, provides examples of its use outside the brain, discusses the infrastructure required for successful implementation of IGS approaches and outlines the challenges that must be overcome for IGS to advance further.

Tracking technique of a micro guide wire in sequential fluorograms

In this paper, we propose a tracking technique for a micro guide wire in a sequence of fluorograms. A technique in which the region-growing technique was embedded was developed. It gives the center line of a micro guide wire. A sequence of 1,024 x 1,024 x 16 bit fluorograms (111 frames) with a carotid phantom and head phantom was obtained with a CAS-8000V (Toshiba America Medical Systems, Inc., CA, USA) C-arm angiography system and a Hi-Torque Standard micro guide wire (Advanced Cardiovascular Systems, Inc., CA, USA). To evaluate the technique, we manually traced the guide wire in each sequence frame three times, and a "true" single-width micro guide wire was created from them. The number of pixels on the true guide wire and inside the two-pixel tolerance of the center line was counted in each fluorogram, and the percentage of that count based on the number of all pixels on the true guide wire was calculated as true positive (TP). In addition, the number of pixels on the center line and outside the two-pixel tolerance of the true guide wire was counted in each frame as false positive (FP). The tracking technique has a mean TP of 94.8% and a mean FP of 5.1 pixels/frame. Several frames have low TP and high FP, but the technique could continue to track the micro guide wire until the end of the sequence. We therefore concluded that we had developed an accurate automatic tracking technique for micro guide wires in fluoroscopic sequences.

A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use

Two-dimensional (2-D)-to-three-dimensional (3-D) registration can improve visualization which may aid minimally invasive neurointerventions. Using clinical and phantom studies, two state-of-the-art approaches to rigid registration are compared quantitatively: an intensity-based algorithm using the gradient difference similarity measure; and an iterative closest point (ICP)-based algorithm. The gradient difference approach was found to be more accurate, with an average registration accuracy of 1.7 mm for clinical data, compared to the ICP-based algorithm with an average accuracy of 2.8 mm. In phantom studies, the ICP-based algorithm proved more reliable, but with more complicated clinical data, the gradient difference algorithm was more robust. Average computation time for the ICP-based algorithm was 20 s per registration, compared with 14 min and 50 s for the gradient difference algorithm.

Guide wire reconstruction and visualization in 3DRA using monoplane fluoroscopic imaging

A method has been developed that, based on the guide wire position in monoplane fluoroscopic images, visualizes the approximate guide wire position in the three-dimensional (3-D) vasculature, that is obtained prior to the intervention with 3-D rotational X-ray angiography (3DRA). The method assumes the position of the guide wire in the fluoroscopic images is known. A two-dimensional feature image is determined from the 3DRA data. In this feature image, the guide wire position is determined in a two-step approach: a mincost algorithm is used to determine a suitable position for the guide wire, and subsequently a snake optimization technique is applied to move the guide wire to a better position. The resulting guide wire can then be visualized in 3-D in combination with the 3DRA dataset. The reconstruction accuracy of the method has been evaluated using a 3DRA image of a vascular phantom filled with contrast, and monoplane fluoroscopic images of the same phantom without contrast and with a guide wire inserted. The evaluation has been performed for different projection angles, and with different parameters for the method. The final result does not appear to be very sensitive to the parameters of the method. The average mean error of the estimated 3-D guide wire position is 1.5 mm, and the average tip distance is 2.3 mm. The effect of inaccurate C-arm geometry information is also investigated. Small errors in geometry information (up to 1 degrees) will slightly decrease the 3-D reconstruction accuracies, with an error of at most 1 mm. The feasibility of this approach on clinical data is demonstrated.

Motion compensation for interventional navigation on 3D static roadmaps based on an affine model and gating

Current cardiac interventions are performed under 2D fluoroscopy, which comes along with well-known burdens to patients and physicians, such as x-ray exposure and the use of contrast agent. Furthermore, the navigation on complex structures such as the coronaries is complicated by the use of 2D images in which the catheter position is only visible while the contrast agent is introduced. In this work, a new method is presented, which circumvents these drawbacks and enables the cardiac interventional navigation on motion-compensated 3D static roadmaps. For this, the catheter position is continuously reconstructed within a previously acquired 3D roadmap of the coronaries. The motion compensation makes use of an affine motion model for compensating the respiratory motion and compensates the motion due to cardiac contraction by gating the catheter position. In this process, only those positions which have been acquired during the rest phase of the heart are used for the reconstruction. The method necessitates the measurement of the catheter position, which is done by using a magnetic tracking system. Nevertheless, other techniques, such as image-based catheter tracking, can be applied. This motion compensation has been tested on a dynamic heart phantom. The evaluation shows that the algorithm can reconstruct the catheter position on the 3D static roadmap precisely with a residual motion of 1.0 mm and less.