Patient-specific catheter shaping for the minimally invasive closure of the left atrial appendage

Purpose

The minimally invasive closure of the left atrial appendage is a promising alternative to anticoagulation for stroke prevention in patients suffering from atrial fibrillation. One of the challenges of this procedure is the correct positioning and the coaxial alignment of the tip of the catheter sheath to the implant landing zone.

Method

In this paper, a novel preoperative planning system is proposed that allows patient-individual shaping of catheters to facilitate the correct positioning of the catheter sheath by offering a patient-specific catheter shape. Based on preoperative three-dimensional image data, anatomical points and the planned implant position are marked interactively and a patient-specific catheter shape is calculated if the standard catheter is not considered as suitable. An approach to calculate a catheter shape with four bends by maximization of the bending radii is presented. Shaping of the catheter is supported by a bending form that is automatically generated in the planning program and can be directly manufactured by using additive manufacturing methods.

Results

The feasibility of the planning and shaping of the catheter could be successfully shown using six data sets. The patient-specific catheters were tested in comparison with standard catheters by physicians on heart models. In four of the six tested models, the participating physicians rated the patient-individual catheters better than the standard catheter.

Conclusion

The novel approach for preoperatively planned and shaped patient-specific catheters designed for the minimally invasive closure of the left atrial appendage could be successfully implemented and a feasibility test showed promising results in anatomies that are difficult to access with the standard catheter.

     

Probe versus microscope: a comparison of different methods for image-to-patient registration

Purpose

Computer-aided navigation is widely used in ENT surgery. The position of a surgical instrument is shown in the CT/MR images of the patient and can thus be a good support for the surgeon. The accuracy is highly dependent on the registration done prior to surgery. A microscope and a probe can both be used for registration and navigation, depending on the surgical intervention. A navigation system typically only reports the fiducial registration error after paired-point registration. However, the target registration error (TRE)—a measurement for the accuracy in the surgical area—is much more relevant. The aim of this work was to compare the performance of a microscope relative to a conventional probe-based approach with different registration methods.

Methods

In this study, optical tracking was used to register a plastic skull to its preoperative CT images with paired-point registration. Anatomical landmarks and skin-affixed markers were used as fiducials and targets. With both microscope and probe, four different registration methods were evaluated based on their TREs at 10 targets. For half of the experiments, a surface registration and/or external fiducials were used additionally to paired-point registration to study their influence to accuracy.

Results

Overall, probe registration leads to a smaller TRE (\(1.69 \pm 0.74\,\hbox {mm}\)) than registration with a microscope (\(2.19 \pm 0.94\,\hbox {mm}\)). Additional surface registration does not result in better accuracy of navigation for microscope and probe. The lowest mean TRE for both pointers can be achieved with paired-point registration only and radiolucent markers.

Conclusion

Our experiments showed that a probe used for registration and navigation achieves lower TREs compared using a microscope. Neither additional surface registration nor additional fiducials on an external reference element are necessary for improved accuracy of navigated ENT surgery on a plastic skull.

     

Robust augmented reality guidance with fluorescent markers in laparoscopic surgery

Purpose

Laparoscopic interventions require the precise navigation of medical instruments through the patient’s body, while taking critical structures into account. Although numerous concepts have been proposed for displaying subsurface anatomical detail using augmented reality, clinical translation of these methods has suffered from a lack of robustness as well as from cumbersome integration into the clinical workflow. The purpose of this study was to investigate the feasibility of a new approach to intra-operative registration based on fluorescent markers.

Methods

The proposed approach to augmented reality visualization relies on metabolizable fluorescent markers that are attached to the target organ to guide a 2D/3D intra-operative registration algorithm. In an ex vivo porcine study, marker tracking performance is evaluated in the presence of smoke, blood, and tissue in the field of view of the endoscope.

Results

In contrast to state-of-the-art needle-shaped fiducial markers, the fluorescent markers can be reliably tracked when occluded by smoke, blood or tissue. This makes the new 2D/3D intra-operative registration approach considerably more robust than state-of-the-art marker-based methods.

Conclusion

As the concept can be smoothly integrated into the clinical workflow, its potential for application in clinical laparoscopy is high.

     

A clinically applicable laser-based image-guided system for laparoscopic liver procedures

Purpose

Laser range scanners (LRS) allow performing a surface scan without physical contact with the organ, yielding higher registration accuracy for image-guided surgery (IGS) systems. However, the use of LRS-based registration in laparoscopic liver surgery is still limited because current solutions are composed of expensive and bulky equipment which can hardly be integrated in a surgical scenario.

Methods

In this work, we present a novel LRS-based IGS system for laparoscopic liver procedures. A triangulation process is formulated to compute the 3D coordinates of laser points by using the existing IGS system tracking devices. This allows the use of a compact and cost-effective LRS and therefore facilitates the integration into the laparoscopic setup. The 3D laser points are then reconstructed into a surface to register to the preoperative liver model using a multi-level registration process.

Results

Experimental results show that the proposed system provides submillimeter scanning precision and accuracy comparable to those reported in the literature. Further quantitative analysis shows that the proposed system is able to achieve a patient-to-image registration accuracy, described as target registration error, of \(3.2\pm 0.57\,\hbox {mm}\).

Conclusions

We believe that the presented approach will lead to a faster integration of LRS-based registration techniques in the surgical environment. Further studies will focus on optimizing scanning time and on the respiratory motion compensation.

     

The interactive electrode localization utility: software for automatic sorting and labeling of intracranial subdural electrodes

Purpose

Existing methods for sorting, labeling, registering, and across-subject localization of electrodes in intracranial encephalography (iEEG) may involve laborious work requiring manual inspection of radiological images.

Methods

We describe a new open-source software package, the interactive electrode localization utility which presents a full pipeline for the registration, localization, and labeling of iEEG electrodes from CT and MR images. In addition, we describe a method to automatically sort and label electrodes from subdural grids of known geometry.

Results

We validated our software against manual inspection methods in twelve subjects undergoing iEEG for medically intractable epilepsy. Our algorithm for sorting and labeling performed correct identification on 96% of the electrodes.

Conclusions

The sorting and labeling methods we describe offer nearly perfect performance and the software package we have distributed may simplify the process of registering, sorting, labeling, and localizing subdural iEEG grid electrodes by manual inspection.

     

Guided ultrasound calibration: where,how, and how many calibration fiducials

Purpose

Many image-guided interventions rely on tracked ultrasound where the transducer is augmented with a tracking device. The relationship between the ultrasound image coordinate system and the tracking sensor must be determined accurately via probe calibration. We introduce a novel calibration framework guided by the prediction of target registration error (TRE): Between successive measurements of the calibration phantom, our framework guides the user in choosing the pose of the calibration phantom by optimizing TRE.

Methods

We introduced an oriented line calibration phantom and modeled the ultrasound calibration process as a point-to-line registration problem. We then derived a spatial stiffness model of point-to-line registration for estimating TRE magnitude at any target. Assuming isotropic, identical localization error, we used the model to estimate TRE for each pixel using the current calibration estimate. We then searched through the calibration tool space to find the pose for the next fiducial which maximally minimized TRE.

Results

Both simulation and experimental results suggested that TRE decreases monotonically, reaching an asymptote when a sufficient number of measurements (typically around 12) are made. Independent point reconstruction accuracy assessment showed sub-millimeter accuracy of the calibration framework.

Conclusion

We have introduced the first TRE-guided ultrasound calibration framework. Using a hollow straw as an oriented line phantom, we virtually constructed a rigid lines phantom and modeled the calibration process as a point-to-line registration. Highly accurate calibration was achieved with minimal measurements by using a spatial stiffness model of TRE to strategically choose the pose of the calibration phantom between successive measurements.

     

Time-of-flight-assisted Kinect camera-based people detection for intuitive human robot cooperation in the surgical operating room

Background

Scene supervision is a major tool to make medical robots safer and more intuitive. The paper shows an approach to efficiently use 3D cameras within the surgical operating room to enable for safe human robot interaction and action perception. Additionally the presented approach aims to make 3D camera-based scene supervision more reliable and accurate.

Methods

A camera system composed of multiple Kinect and time-of-flight cameras has been designed, implemented and calibrated. Calibration and object detection as well as people tracking methods have been designed and evaluated.

Results

The camera system shows a good registration accuracy of 0.05 m. The tracking of humans is reliable and accurate and has been evaluated in an experimental setup using operating clothing. The robot detection shows an error of around 0.04 m.

Conclusions

The robustness and accuracy of the approach allow for an integration into modern operating room. The data output can be used directly for situation and workflow detection as well as collision avoidance.

     

Accuracy analysis in MRI-guided robotic prostate biopsy

Purpose

To assess retrospectively the clinical accuracy of an magnetic resonance imaging-guided robotic prostate biopsy system that has been used in the US National Cancer Institute for over 6 years.

Methods

Series of 2D transverse volumetric MR image slices of the prostate both pre (high-resolution T2-weighted)- and post (low-resolution)- needle insertions were used to evaluate biopsy accuracy. A three-stage registration algorithm consisting of an initial two-step rigid registration followed by a B-spline deformable alignment was developed to capture prostate motion during biopsy. The target displacement (distance between planned and actual biopsy target), needle placement error (distance from planned biopsy target to needle trajectory), and biopsy error (distance from actual biopsy target to needle trajectory) were calculated as accuracy assessment.

Results

A total of 90 biopsies from 24 patients were studied. The registrations were validated by checking prostate contour alignment using image overlay, and the results were accurate to within 2 mm. The mean target displacement, needle placement error, and clinical biopsy error were 5.2, 2.5, and 4.3 mm, respectively.

Conclusion

The biopsy error reported suggests that quantitative imaging techniques for prostate registration and motion compensation may improve prostate biopsy targeting accuracy.

     

Context region discovery for automatic motion compensation in fluoroscopy

Purpose

Image-based tracking for motion compensation is an important topic in image-guided interventions, as it enables physicians to operate in a less complex space. In this paper, we propose an automatic motion compensation scheme to boost image guidence power in transcatheter aortic valve implantation (TAVI).

Methods

The proposed tracking algorithm automatically discovers reliable regions that correlate strongly with the target. These discovered regions can assist to estimate target motion under severe occlusion, even if target tracker fails.

Results

We evaluate the proposed method for pigtail tracking during TAVI. We obtain significant improvement (12 %) over the baseline in a clinical dataset. Calcification regions are automatically discovered during tracking, which would aid TAVI processes.

Conclusion

In this work, we open a new paradigm to provide dynamic real-time guidance for TAVI without user interventions, specially in case of severe occlusion where conventional tracking methods are challenged.

     

Preliminary study on magnetic tracking-based planar shape sensing and navigation for flexible surgical robots in transoral surgery: methods and phantom experiments

Purpose

Flexible surgical robot can work in confined and complex environments, which makes it a good option for minimally invasive surgery. In order to utilize flexible manipulators in complicated and constrained surgical environments, it is of great significance to monitor the position and shape of the curvilinear manipulator in real time during the procedures. In this paper, we propose a magnetic tracking-based planar shape sensing and navigation system for flexible surgical robots in the transoral surgery. The system can provide the real-time tip position and shape information of the robot during the operation.

Methods

We use wire-driven flexible robot to serve as the manipulator. It has three degrees of freedom. A permanent magnet is mounted at the distal end of the robot. Its magnetic field can be sensed with a magnetic sensor array. Therefore, position and orientation of the tip can be estimated utilizing a tracking method. A shape sensing algorithm is then carried out to estimate the real-time shape based on the tip pose. With the tip pose and shape display in the 3D reconstructed CT model, navigation can be achieved.

Results

Using the proposed system, we carried out planar navigation experiments on a skull phantom to touch three different target positions under the navigation of the skull display interface. During the experiments, the real-time shape has been well monitored and distance errors between the robot tip and the targets in the skull have been recorded. The mean navigation error is \(2.07\pm 0.71\) mm, while the maximum error is 3.2 mm.

Conclusion

The proposed method provides the advantages that no sensors are needed to mount on the robot and no line-of-sight problem. Experimental results verified the feasibility of the proposed method.

     

Fiducial-based registration with a touchable region model

Purpose

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

Methods

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

Results

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

Conclusions

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

     

Deformable registration of preoperative MR,pre-resection ultrasound,and post-resection ultrasound images of neurosurgery

Purpose

Sites that use ultrasound (US) in image-guided neurosurgery (IGNS) of brain tumors generally have three sets of imaging data: preoperative magnetic resonance (MR) image, pre-resection US, and post-resection US. The MR image is usually acquired days before the surgery, the pre-resection US is obtained after the craniotomy but before the resection, and finally, the post-resection US scan is performed after the resection of the tumor. The craniotomy and tumor resection both cause brain deformation, which significantly reduces the accuracy of the MR–US alignment.

Method

Three unknown transformations exist between the three sets of imaging data: MR to pre-resection US, pre- to post-resection US, and MR to post-resection US. We use two algorithms that we have recently developed to perform the first two registrations (i.e., MR to pre-resection US and pre- to post-resection US). Regarding the third registration (MR to post-resection US), we evaluate three strategies. The first method performs a registration between the MR and pre-resection US, and another registration between the pre- and post-resection US. It then composes the two transformations to register MR and post-resection US; we call this method compositional registration. The second method ignores the pre-resection US and directly registers the MR and post-resection US; we refer to this method as direct registration. The third method is a combination of the first and second: it uses the solution of the compositional registration as an initial solution for the direct registration method. We call this method group-wise registration.

Results

We use data from 13 patients provided in the MNI BITE database for all of our analysis. Registration of MR and pre-resection US reduces the average of the mean target registration error (mTRE) from 4.1 to 2.4 mm. Registration of pre- and post-resection US reduces the average mTRE from 3.7 to 1.5 mm. Regarding the registration of MR and post-resection US, all three strategies reduce the mTRE. The initial average mTRE is 5.9 mm, which reduces to 3.3 mm with the compositional method, 2.9 mm with the direct technique, and 2.8 mm with the group-wise method.

Conclusion

Deformable registration of MR and pre- and post-resection US images significantly improves their alignment. Among the three methods proposed for registering the MR to post-resection US, the group-wise method gives the lowest TRE values. Since the running time of all registration algorithms is less than 2 min on one core of a CPU, they can be integrated into IGNS systems for interactive use during surgery.

     

Fully automated MR liver volumetry using watershed segmentation coupled with active contouring

Purpose

Our purpose is to develop a fully automated scheme for liver volume measurement in abdominal MR images, without requiring any user input or interaction.

Methods

The proposed scheme is fully automatic for liver volumetry from 3D abdominal MR images, and it consists of three main stages: preprocessing, rough liver shape generation, and liver extraction. The preprocessing stage reduced noise and enhanced the liver boundaries in 3D abdominal MR images. The rough liver shape was revealed fully automatically by using the watershed segmentation, thresholding transform, morphological operations, and statistical properties of the liver. An active contour model was applied to refine the rough liver shape to precisely obtain the liver boundaries. The liver volumes calculated by the proposed scheme were compared to the “gold standard” references which were estimated by an expert abdominal radiologist.

Results

The liver volumes computed by using our developed scheme excellently agreed (Intra-class correlation coefficient was 0.94) with the “gold standard” manual volumes by the radiologist in the evaluation with 27 cases from multiple medical centers. The running time was 8.4 min per case on average.

Conclusions

We developed a fully automated liver volumetry scheme in MR, which does not require any interaction by users. It was evaluated with cases from multiple medical centers. The liver volumetry performance of our developed system was comparable to that of the gold standard manual volumetry, and it saved radiologists’ time for manual liver volumetry of 24.7 min per case.

     

Real-time microrobot posture recognition via biplane X-ray imaging system for external electromagnetic actuation

Purpose

As a promising intravascular therapeutic approach for autonomous catheterization, especially for thrombosis treatment, a microrobot or robotic catheter driven by an external electromagnetic actuation system has been recently investigated. However, the three-dimensional (3D) real-time position and orientation tracking of the microrobot remains a challenge for precise feedback control in clinical applications owing to the micro-size of the microrobot geometry in vessels, along with bifurcation and vulnerability. Therefore, in this paper, we propose a 3D posture recognition method for the unmanned microrobotic surgery driven by an external electromagnetic actuator system.

Methods

We propose a real-time position and spatial orientation tracking method for a millimeter-sized intravascular object or microrobot using a principal component analysis algorithm and an X-ray reconstruction. The suggested algorithm was implemented to an actual controllable wireless microrobot system composed of a bullet-shaped object, a biplane X-ray imaging device, and an electromagnetic actuation system. Numerical computations and experiments were conducted for the performance verification.

Results

The experimental results showed a good performance of the implemented system with tracking errors less than 0.4 mm in position and 2° in orientation. The proposed tracking technique accomplished a fast processing time, ~?0.125 ms/frame, and high-precision recognition of the micro-sized object.

Conclusions

Since the suggested method does not require pre-information of the object geometry in the human body for its 3D shape and position recognition, it could be applied to various elliptical shapes of the microrobot system with computation time efficacy and recognition accuracy. Hence, the method can be used for therapeutic millimeter- or micron-sized manipulator recognition in vascular, as well as implanted objects in the human body.

     

Learning-based endovascular navigation through the use of non-rigid registration for collaborative robotic catheterization

Purpose

Endovascular intervention is limited by two-dimensional intraoperative imaging and prolonged procedure times in the presence of complex anatomies. Robotic catheter technology could offer benefits such as reduced radiation exposure to the clinician and improved intravascular navigation. Incorporating three-dimensional preoperative imaging into a semiautonomous robotic catheterization platform has the potential for safer and more precise navigation. This paper discusses a semiautonomous robotic catheter platform based on previous work (Rafii-Tari et al., in: MICCAI2013, pp 369–377. https://doi.org/10.1007/978-3-642-40763-5_46, 2013) by proposing a method to address anatomical variability among aortic arches. It incorporates anatomical information in the process of catheter trajectories optimization, hence can adapt to the scale and orientation differences among patient-specific anatomies.

Methods

Statistical modeling is implemented to encode the catheter motions of both proximal and distal sites based on cannulation data obtained from a single phantom by an expert operator. Non-rigid registration is applied to obtain a warping function to map catheter tip trajectories into other anatomically similar but shape/scale/orientation different models. The remapped trajectories were used to generate robot trajectories to conduct a collaborative cannulation task under flow simulations. Cross-validations were performed to test the performance of the non-rigid registration. Success rates of the cannulation task executed by the robotic platform were measured. The quality of the catheterization was also assessed using performance metrics for manual and robotic approaches. Furthermore, the contact forces between the instruments and the phantoms were measured and compared for both approaches.

Results

The success rate for semiautomatic cannulation is 98.1% under dry simulation and 94.4% under continuous flow simulation. The proposed robotic approach achieved smoother catheter paths than manual approach. The mean contact forces have been reduced by 33.3% with the robotic approach, and 70.6% less STDEV forces were observed with the robot.

Conclusions

This work provides insights into catheter task planning and an improved design of hands-on ergonomic catheter navigation robots.

     

Magnetic resonance imaging compatible remote catheter navigation system with 3 degrees of freedom

Purpose

To facilitate MRI-guided catheterization procedures, we present an MRI-compatible remote catheter navigation system that allows remote navigation of steerable catheters with 3 degrees of freedom.

Methods

The system consists of a user interface (master), a robot (slave), and an ultrasonic motor control servomechanism. The interventionalist applies conventional motions (axial, radial and plunger manipulations) on an input catheter in the master unit; this user input is measured and used by the servomechanism to control a compact catheter manipulating robot, such that it replicates the interventionalist’s input motion on the patient catheter. The performance of the system was evaluated in terms of MRI compatibility (SNR and artifact), feasibility of remote navigation under real-time MRI guidance, and motion replication accuracy.

Results

Real-time MRI experiments demonstrated that catheter was successfully navigated remotely to desired target references in all 3 degrees of freedom. The system had an absolute value error of \({<}\)1 mm in axial catheter motion replication over 30 mm of travel and \(3^{\circ } \pm 2^{\circ }\) for radial catheter motion replication over \(180^{\circ }\). The worst case SNR drop was observed to be \({<}\)3 %; the robot did not introduce any artifacts in the MR images.

Conclusion

An MRI-compatible compact remote catheter navigation system has been developed that allows remote navigation of steerable catheters with 3 degrees of freedom. The proposed system allows for safe and accurate remote catheter navigation, within conventional closed-bore scanners, without degrading MR image quality.

     

Fluoroscopy-based tracking of femoral kinematics with statistical shape models

Purpose

Precise knee kinematics assessment helps to diagnose knee pathologies and to improve the design of customized prosthetic components. The first step in identifying knee kinematics is to assess the femoral motion in the anatomical frame. However, no work has been done on pathological femurs, whose shape can be highly different from healthy ones.

Methods

We propose a new femoral tracking technique based on statistical shape models and two calibrated fluoroscopic images, taken at different flexion–extension angles. The cost function optimization is based on genetic algorithms, to avoid local minima. The proposed approach was evaluated on 3 sets of digitally reconstructed radiographic images of osteoarthritic patients.

Results

It is found that using the estimated shape, rather than that calculated from CT, significantly reduces the pose accuracy, but still has reasonably good results (angle errors around 2\(^\circ \), translation around 1.5 mm).

     

Validation of automated ultrasound-CT registration of vertebrae

Purpose

Image-guided spine surgery requires registration of the patient anatomy and preoperative computed tomography (CT) images. A technique for intraoperative ultrasound image registration to preoperative CT scans was developed and tested. Validation of the ultrasound-CT registration technique was performed using porcine cadavers.

Methods

An ultrasound-CT registration technique was evaluated using 18 thoracic and lumbar vertebrae of 3 porcine cadavers with 10 different sweep patterns for ultrasound acquisition. For each sweep pattern at each vertebra, 100 randomly simulated initial misalignments were introduced. Each misalignment was registered. The resulting registration transformations were compared to gold standard registrations based on implanted fiducials to assess accuracy and robustness of the technique.

Results

The orthogonal-sweep acquisition was found to perform best and yielded a registration accuracy of 1.65 mm across all vertebrae on all porcine cadavers, where 82.5% of the registrations resulted in target registration errors below the 2 mm threshold recommended by a joint report from the experts in the field. In addition, we found that registration accuracy varies by the sweep pattern and vertebral level, but neighboring vertebrae tend to result in statistically similar accuracy. Ultrasound-CT registration took an average of 2.5 min to run, and the total registration time per vertebra (also including time for ultrasound acquisition and reconstruction) is approximately 8 min.

Conclusions

A previously described ultrasound-CT registration technique yields clinically acceptable accuracy and robustness on multiple vertebrae across multiple porcine cadavers. The total registration time is shorter than that of surface point-based manual registration.