Accuracy of implementing principles of fusion imaging in the follow up and surveillance of complex aneurysm repair.

Fusion imaging is standard for the endovascular treatment of complex aortic aneurysms, but its role in follow up has not been explored. A critical issue is renal function deterioration over time. Renal volume has been used as a marker of renal impairment; however, it is not reproducible and remains a complex and resource-intensive procedure. The aim of this study is to determine the accuracy of a fusion-based software to automatically calculate the renal volume changes during follow up. In this study, computerized tomography (CT) scans of 16 patients who underwent complex aortic endovascular repair were analysed. Preoperative, 1-month and 1-year follow-up CT scans have been analysed using a conventional approach of semi-automatic segmentation, and a second approach with automatic segmentation. For each kidney and at each time point the percentage of change in renal volume was calculated using both techniques. After review, volume assessment was feasible for all CT scans. For the left kidney, the intraclass correlation coefficient (ICC) was 0.794 and 0.877 at 1 month and 1 year, respectively. For the right side, the ICC was 0.817 at 1 month and 0.966 at 1 year. The automated technique reliably detected a decrease in renal volume for the eight patients with occluded renal arteries during follow up. This is the first report of a fusion-based algorithm to detect changes in renal volume during postoperative surveillance using an automated process. Using this technique, the standardized assessment of renal volume could be implemented with greater ease and reproducibility and serve as a warning of potential renal impairment.

Design and evaluation of an image-guidance system for robot-assisted radical prostatectomy.

UNLABELLED: WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: Systems for image guidance during laparoscopic surgery can be broadly defined as systems that enable the surgeon to refer to preoperatively gathered information during the procedure. For a laparoscopic system the preoperative information can be overlaid onto the laparoscopic video screen. Examples of surgical image-guidance systems and the results of early testing are not uncommon but the technical methodologies used vary widely as do the visualisation methods. This study reports our experience of using an image-guidance system on 13 patients. Furthermore, we use previously proposed methodology to form a development and evaluation framework specific to image-guided laparoscopic radical prostatectomy. Finally, we propose that if the system development process is properly designed, it should be possible to correlate system technical parameters with clinical outcomes. We present a possible plot for the key technical parameter of accuracy. Better understanding of this correlation should enable robust development and evaluation of surgical image-guidance systems to optimise patient outcomes. OBJECTIVE: To implement and test the feasibility of an image-guidance system for robot-assisted radical prostatectomy (RARP). Laparoscopic surgical outcomes may be improved through image guidance. However, to demonstrate improved outcomes rigorous evaluation techniques are required. Therefore we also present our work in establishing robust evaluation techniques. PATIENTS AND METHODS: Development work used three cadavers and an anatomy phantom. The system has been used on 13 patients. During surgery the surgeon can refer to the patient's magnetic resonance imaging (collected before the operation) overlaid on the endoscopic video image. The result of the overlay process was measured qualitatively by the surgeon with reference to the desired clinical outcomes. RESULTS: The use of the overlay system has not resulted in any measurable change in clinical outcomes. The surgeons found the system to be a useful tool for reference during surgery. A more rigorous evaluation method is proposed that will enable on-going development. CONCLUSION: Image guidance during RARP is feasible. We propose a series of measures that will improve further development and evaluation.

Feasibility and limitations of an automated 2D-3D rigid image registration system for complex endovascular aortic procedures.

PURPOSE: To examine the feasibility of an automated 2-dimensional (2D) to 3- dimensional (3D) image registration system to simplify the navigational challenges faced in complex endovascular aortic procedures. METHODS: An automated 2D-3D image registration system was used to overlay pre-acquired 3D computed tomography images onto fluoroscopy images taken during endovascular aneurysm repair. Errors between the 3D overlay and digital subtraction angiograms were measured and correlated with aortic neck angulation. A mean discrepancy < or =3 mm was considered clinically acceptable. RESULTS: There was a strong correlation between maximum neck angulation and maximum registration error (Pearson's r = 0.75). Aortas with a maximum neck angulation < or =30 degrees had a mean error of 2.5+/-1.2 mm, whereas aortas with neck angulation >30 degrees had a mean error of 6.2+/-2.5 mm (p<0.0001). CONCLUSION: The major source of registration errors is aortic deformation caused by the presence of the introducer and endovascular graft. Further work is required if this technology is to be routinely applied to severely angulated aortic anatomy.

Echocardiography to magnetic resonance image registration for use in image-guided cardiac catheterization procedures.

We present a robust method to register three-dimensional echocardiography (echo) images to magnetic resonance images (MRI) based on anatomical features, which is designed to be used in the registration pipeline for overlaying MRI-derived roadmaps onto two-dimensional live x-ray images during cardiac catheterization procedures. The features used in image registration are the endocardial surface of the left ventricle and the centre line of the descending aorta. The MR-derived left ventricle surface is generated using a fully automated algorithm, and the echo-derived left ventricle surface is produced using a semi-automatic segmentation method provided by the QLab software (Philips Healthcare) that it is routinely used in clinical practice. We test our method on data from six volunteers and four patients. We validated registration accuracy using two methods: the first calculated a root mean square distance error using expert identified anatomical landmarks, and the second method used catheters as landmarks in two clinical electrophysiology procedures. Results show a mean error of 4.1 mm, which is acceptable for our clinical application, and no failed registrations were observed. In addition, our algorithm works on clinical data, is fast and only requires a small amount of manual input, and so it is applicable for use during cardiac catheterization procedures.

Postoperative calculation of acetabular cup position using 2-D-3-D registration.

A method to accurately measure the position and orientation of an acetabular cup implant from postoperative X-rays has been designed and validated. The method uses 2-D-3-D registration to align both the prosthesis and the preoperative computed tomography (CT) volume to the X-ray image. This allows the position of the implant to be calculated with respect to a CT-based surgical plan. Experiments have been carried out using ten sets of patient data. A conventional plain-film measurement technique was also investigated. A gold standard implant position and orientation was calculated using postoperative CT. Results show our method to be significantly more accurate than the plain-film method for calculating cup anteversion. Cup orientation and position could be measured to within a mean absolute error of 1.4 mm or degrees.

Registration of Multiview Echocardiography Sequences Using a Subspace Error Metric.

OBJECTIVE: 3-D +t echocardiography (3DtE) is widely employed for the assessment of left ventricular anatomy and function. However, the information derived from 3DtE images can be affected by the poor image quality and the limited field of view. Registration of multiview 3DtE sequences has been proposed to compound images from different acoustic windows, therefore improving both image quality and coverage. We propose a novel subspace error metric for an automatic and robust registration of multiview intrasubject 3DtE sequences. METHODS: The proposed metric employs linear dimensionality reduction to exploit the similarity in the temporal variation of multiview 3DtE sequences. The use of a low-dimensional subspace for the computation of the error metric reduces the influence of image artefacts and noise on the registration optimization, resulting in fast and robust registrations that do not require a starting estimate. RESULTS: The accuracy, robustness, and execution time of the proposed registration were thoroughly validated. Results on 48 pairwise multiview 3DtE registrations show the proposed error metric to outperform a state-of-the-art phase-based error metric, with improvements in median/75th percentile of the target registration error of 21%/31% and an improvement in mean execution time of 45%. CONCLUSION: The proposed subspace error metric outperforms sum-of-squared differences and phase-based error metrics for the registration of multiview 3DtE sequences in terms of accuracy, robustness, and execution time. SIGNIFICANCE: The use of the proposed subspace error metric has the potential to replace standard image error metrics for a robust and automatic registration of multiview 3DtE sequences.

Magnetic resonance imaging planning in children with complex congenital heart disease - A new approach.

OBJECTIVES: To compare a standard sequential 2D Planning Method (2D-PM) with a 3D offline Planning Method (3D-PM) based on 3D contrast-enhanced magnetic resonance angiography (CE-MRA) in children with congenital heart disease (CHD). DESIGN: In 14 children with complex CHD (mean: 2.6 years, range: 3 months to 7.6 years), axial and coronal cuts were obtained with single slice spin echo sequences to get the final double oblique longitudinal cut of the targeted anatomical structure (2D-PM, n = 31). On a separate workstation, similar maximal intensity projection (MIP) images were generated offline from a 3D CE-MRA. MIP images were localizers for repeated targeted imaging using the previous spin echo sequence (3D-PM). Finally, image coverage, spatial orientation and acquisition time were compared for 2D-PM and 3D-PM. MAIN OUTCOME MEASURES: 2D-PM and 3D-PM images were similar: both perfectly covered the selected anatomic regions and no spatial differences were found (p>0.05). The mean time for creation of the final imaging plane was 241 ± 31 s (2D-PM) compared to 71 ± 18 s (3D-PM) (p<0.05). CONCLUSIONS: 3D-PM shows similar results compared to 2D-PM, but allows faster and offline planning thereby reducing the scan time significantly. As newly developed high-resolution 3D datasets can also be used further improvement of this technology is expected.

Self-calibrating 3D-ultrasound-based bone registration for minimally invasive orthopedic surgery.

Intraoperative freehand three-dimensional (3-D) ultrasound (3D-US) has been proposed as a noninvasive method for registering bones to a preoperative computed tomography image or computer-generated bone model during computer-aided orthopedic surgery (CAOS). In this technique, an US probe is tracked by a 3-D position sensor and acts as a percutaneous device for localizing the bone surface. However, variations in the acoustic properties of soft tissue, such as the average speed of sound, can introduce significant errors in the bone depth estimated from US images, which limits registration accuracy. We describe a new self-calibrating approach to US-based bone registration that addresses this problem, and demonstrate its application within a standard registration scheme. Using realistic US image data acquired from 6 femurs and 3 pelves of intact human cadavers, and accurate Gold Standard registration transformations calculated using bone-implanted fiducial markers, we show that self-calibrating registration is significantly more accurate than a standard method, yielding an average root mean squared target registration error of 1.6 mm. We conclude that self-calibrating registration results in significant improvements in registration accuracy for CAOS applications over conventional approaches where calibration parameters of the 3D-US system remain fixed to values determined using a preoperative phantom-based calibration.

Regional Differences in End-Diastolic Volumes between 3D Echo and CMR in HLHS Patients.

Ultrasound is commonly thought to underestimate ventricular volumes compared to magnetic resonance imaging (MRI), although the reason for this and the spatial distribution of the volume difference is not well understood. In this paper, we use landmark-based image registration to spatially align MRI and ultrasound images from patients with hypoplastic left heart syndrome and carry out a qualitative and quantitative spatial comparison of manual segmentations of the ventricular volume obtained from the respective modalities. In our experiments, we have found a trend showing volumes estimated from ultrasound to be smaller than those obtained from MRI (by approximately up to 20 ml), and that important contributors to this difference are the presence of artifacts such as shadows in the echo images and the different criteria to include or exclude image features as part of the ventricular volume.

Alignment of sparse freehand 3-D ultrasound with preoperative images of the liver using models of respiratory motion and deformation.

We present a method for alignment of an interventional plan to optically tracked two-dimensional intraoperative ultrasound (US) images of the liver. Our clinical motivation is to enable the accurate transfer of information from three-dimensional preoperative imaging modalities [magnetic resonance (MR) or computed tomography (CT)] to intraoperative US to aid needle placement for thermal ablation of liver metastases. An initial rigid registration to intraoperative coordinates is obtained using a set of US images acquired at maximum exhalation. A preprocessing step is applied to both the preoperative images and the US images to produce evidence of corresponding structures. This yields two sets of images representing classification of regions as vessels. The registration then proceeds using these images. The preoperative images and plan are then warped to correspond to a single US slice acquired at an unknown point in the breathing cycle where the liver is likely to have moved and deformed relative to the preoperative image. Alignment is constrained using a patient-specific model of breathing motion and deformation. Target registration error is estimated by carrying out simulation experiments using resliced MR volumes to simulate real US and comparing the registration results to a "bronze-standard" registration performed on the full MR volume. Finally, the system is tested using real US and verified using visual inspection.

Standardized evaluation methodology for 2-D-3-D registration.

In the past few years, a number of two-dimensional (2-D) to three-dimensional (3-D) (2-D-3-D) registration algorithms have been introduced. However, these methods have been developed and evaluated for specific applications, and have not been directly compared. Understanding and evaluating their performance is therefore an open and important issue. To address this challenge we introduce a standardized evaluation methodology, which can be used for all types of 2-D-3-D registration methods and for different applications and anatomies. Our evaluation methodology uses the calibrated geometry of a 3-D rotational X-ray (3DRX) imaging system (Philips Medical Systems, Best, The Netherlands) in combination with image-based 3-D-3-D registration for attaining a highly accurate gold standard for 2-D X-ray to 3-D MR/CT/3DRX registration. Furthermore, we propose standardized starting positions and failure criteria to allow future researchers to directly compare their methods. As an illustration, the proposed methodology has been used to evaluate the performance of two 2-D-3-D registration techniques, viz. a gradient-based and an intensity-based method, for images of the spine. The data and gold standard transformations are available on the internet (http://www.isi.uu.nl/Research/Databases/).

Fully automated 2D-3D registration and verification.

Clinical application of 2D-3D registration technology often requires a significant amount of human interaction during initialisation and result verification. This is one of the main barriers to more widespread clinical use of this technology. We propose novel techniques for automated initial pose estimation of the 3D data and verification of the registration result, and show how these techniques can be combined to enable fully automated 2D-3D registration, particularly in the case of a vertebra based system. The initialisation method is based on preoperative computation of 2D templates over a wide range of 3D poses. These templates are used to apply the Generalised Hough Transform to the intraoperative 2D image and the sought 3D pose is selected with the combined use of the generated accumulator arrays and a Gradient Difference Similarity Measure. On the verification side, two algorithms are proposed: one using normalised features based on the similarity value and the other based on the pose agreement between multiple vertebra based registrations. The proposed methods are employed here for CT to fluoroscopy registration and are trained and tested with data from 31 clinical procedures with 417 low dose, i.e. low quality, high noise interventional fluoroscopy images. When similarity value based verification is used, the fully automated system achieves a 95.73% correct registration rate, whereas a no registration result is produced for the remaining 4.27% of cases (i.e. incorrect registration rate is 0%). The system also automatically detects input images outside its operating range.

Interventional digital tomosynthesis from a standard fluoroscopy system using 2D-3D registration.

Interventional fluoroscopy provides guidance in a variety of minimally invasive procedures. However, three-dimensional (3D) clinically relevant information is projected onto a two-dimensional (2D) image which can make image interpretation difficult. Moreover, vasculature visualisation requires the use of iodinated contrast media which is nephrotoxic and is the primary cause of renal complications. In this article, we demonstrate how digital tomosynthesis slices can be produced on standard fluoroscopy equipment by registering the preoperative CT volume and the intraoperative fluoroscopy images using 2D-3D image registration. The proposed method automatically reconstructs patient-anatomy-specific slices and removes clutter resulting from bony anatomy. Such slices could provide additional intraoperative information which cannot be provided by the preoperative CT volume alone, such as the deformed aorta position offering improved guidance precision. Image acquisition would fit with interventional clinical work-flow and would not require a high X-ray dose. Experiments are carried out using one phantom and four clinical datasets. Phantom results showed a 3351% contrast-to-noise improvement compared to standard fluoroscopy. Patient results showed our method enabled visualization of clinically relevant features: outline of the aorta, the aortic bifurcation and some aortic calcifications.

4D Blood Flow Reconstruction Over the Entire Ventricle From Wall Motion and Blood Velocity Derived From Ultrasound Data.

We demonstrate a new method to recover 4D blood flow over the entire ventricle from partial blood velocity measurements using multiple 3D+t colour Doppler images and ventricular wall motion estimated using 3D+t BMode images. We apply our approach to realistic simulated data to ascertain the ability of the method to deal with incomplete data, as typically happens in clinical practice. Experiments using synthetic data show that the use of wall motion improves velocity reconstruction, shows more accurate flow patterns and improves mean accuracy particularly when coverage of the ventricle is poor. The method was applied to patient data from 6 congenital cases, producing results consistent with the simulations. The use of wall motion produced more plausible flow patterns and reduced the reconstruction error in all patients.

Intensity-based 2-D-3-D registration of cerebral angiograms.

We propose a new method for aligning three-dimensional (3-D) magnetic resonance angiography (MRA) with 2-D X-ray digital subtraction angiograms (DSA). Our method is developed from our algorithm to register computed tomography volumes to X-ray images based on intensity matching of digitally reconstructed radiographs (DRRs). To make the DSA and DRR more similar, we transform the MRA images to images of the vasculature and set to zero the contralateral side of the MRA to that imaged with DSA. We initialize the search for a match on a user defined circular region of interest. We have tested six similarity measures using both unsegmented MRA and three segmentation variants of the MRA. Registrations were carried out on images of a physical neuro-vascular phantom and images obtained during four neuro-vascular interventions. The most accurate and robust registrations were obtained using the pattern intensity, gradient difference, and gradient correlation similarity measures, when used in conjunction with the most sophisticated MRA segmentations. Using these measures, 95% of the phantom start positions and 82% of the clinical start positions were successfully registered. The lowest root mean square reprojection errors were 1.3 mm (standard deviation 0.6) for the phantom and 1.5 mm (standard deviation 0.9) for the clinical data sets. Finally, we present a novel method for the comparison of similarity measure performance using a technique borrowed from receiver operator characteristic analysis.

Personalising population-based respiratory motion models of the heart using neighbourhood approximation based on learnt anatomical features.

Respiratory motion models have been proposed for the estimation and compensation of respiratory motion during image acquisition and image-guided interventions on organs in the chest and abdomen. However, such techniques are not commonly used in the clinic. Subject-specific motion models require a dynamic calibration scan that interrupts the clinical workflow and is often impractical to acquire, while population-based motion models are not as accurate as subject-specific motion models. To address this lack of accuracy, we propose a novel personalisation framework for population-based respiratory motion models and demonstrate its application to respiratory motion of the heart. The proposed method selects a subset of the population sample which is more likely to represent the cardiac respiratory motion of an unseen subject, thus providing a more accurate motion model. The selection is based only on anatomical features of the heart extracted from a static image. The features used are learnt using a neighbourhood approximation technique from a set of training datasets for which respiratory motion estimates are available. Results on a population sample of 28 adult healthy volunteers show average improvements in estimation accuracy of 20% compared to a standard population-based motion model, with an average value for the 50th and 95th quantiles of the estimation error of 1.6mm and 4.7 mm respectively. Furthermore, the anatomical features of the heart most strongly correlated to respiratory motion are investigated for the first time, showing the features on the apex in proximity to the diaphragm and the rib cage, on the left ventricle and interventricular septum to be good predictors of the similarity in cardiac respiratory motion.

Retrospective Rigid Motion Correction in k-Space for Segmented Radial MRI.

Motion occurring during magnetic resonance imaging acquisition is a major factor of image quality degradation. Self-navigation can help reduce artefacts by estimating motion from the acquired data to enable motion correction. Popular self-navigation techniques rely on the availability of a fully-sampled motion-free reference to register the motion corrupted data with. In the proposed technique, rigid motion parameters are derived using the inherent correlation between radial segments in k-space. The registration is performed exclusively in k-space using the Phase Correlation Method, a popular registration technique in computer vision. Robust and accurate registration has been carried out from radial segments composed of as few as 32 profiles. Successful self-navigation has been performed on 2-D dynamic brain scans corrupted with continuous motion for six volunteers. Retrospective motion correction using the derived self-navigation parameters resulted in significant improvement of image quality compared to the conventional sliding window. This work also demonstrates the benefits of using a bit-reversed ordering scheme to limit undesirable effects specific to retrospective motion correction on radial trajectories. This method provides a fast and efficient mean of measuring rigid motion directly in k-space from dynamic radial data under continuous motion.

Increasing the automation of a 2D-3D registration system.

Routine clinical use of 2D-3D registration algorithms for Image Guided Surgery remains limited. A key aspect for routine clinical use of this technology is its degree of automation, i.e., the amount of necessary knowledgeable interaction between the clinicians and the registration system. Current image-based registration approaches usually require knowledgeable manual interaction during two stages: for initial pose estimation and for verification of produced results. We propose four novel techniques, particularly suited to vertebra-based registration systems, which can significantly automate both of the above stages. Two of these techniques are based upon the intraoperative "insertion" of a virtual fiducial marker into the preoperative data. The remaining two techniques use the final registration similarity value between multiple CT vertebrae and a single fluoroscopy vertebra. The proposed methods were evaluated with data from 31 operations (31 CT scans, 419 fluoroscopy images). Results show these methods can remove the need for manual vertebra identification during initial pose estimation, and were also very effective for result verification, producing a combined true positive rate of 100% and false positive rate equal to zero. This large decrease in required knowledgeable interaction is an important contribution aiming to enable more widespread use of 2D-3D registration technology.

Improved modelling of tool tracking errors by modelling dependent marker errors.

Accurate understanding of equipment tracking error is essential for decision making in image guided surgery. For tools tracked using markers attached to a rigid body, existing error estimation methods use the assumption that the individual marker errors are independent random variables. This assumption is not valid for all tracking systems. This paper presents a method to estimate a more accurate tracking error function, consisting of a systematic and random component. The proposed method does not require detailed knowledge of the tracking system physics. Results from a pointer calibration are used to demonstrate that the proposed method provides a better match to observed results than the existing state of the art. A simulation of the pointer calibration process is then used to show that existing methods can underestimate the pointer calibration error by a factor of two. A further simulation of laparoscopic camera tracking is used to show that existing methods cannot model important variations in system performance due to the angular arrangement of the tracking markers. By arranging the markers such that the systematic errors are nearly identical for all markers, the rotational component of the tracking error can be reduced, resulting in a significant reduction in target tracking errors.

Interventional digital tomosynthesis from a standard fluoroscopy system using 2D-3D registration.

Fluoroscopy is the mainstay of interventional radiology. However, the images are 2D and visualisation of vasculature requires nephrotoxic contrast. Cone-beam computed tomography is often available, but involves large radiation dose and interruption to clinical workflow. We propose the use of 2D-3D image registration to allow digital tomosynthesis (DTS) slices to be produced using standard fluoroscopy equipment. Our method automatically produces patient-anatomy-specific slices and removes clutter resulting from bones. Such slices could provide additional intraoperative information, offering improved guidance precision. Image acquisition would fit with interventional clinical workflow and would not require a high x-ray dose. Phantom results showed a 1133% contrast-to-noise improvement compared to standard fluoroscopy. Patient results showed our method enabled visualisation of clinically relevant features: outline of the aorta, the aortic bifurcation and some aortic calcifications.