Surface registration for use in interactive, image-guided liver surgery

To Align Multimodal Lumbar Spine Images via Bending Energy Constrained Normalized Mutual Information

To align multimodal images is important for information fusion, clinical diagnosis, treatment planning, and delivery, while few methods have been dedicated to matching computerized tomography (CT) and magnetic resonance (MR) images of lumbar spine. This study proposes a coarse-to-fine registration framework to address this issue. Firstly, a pair of CT-MR images are rigidly aligned for global positioning. Then, a bending energy term is penalized into the normalized mutual information for the local deformation of soft tissues. In the end, the framework is validated on 40 pairs of CT-MR images from our in-house collection and 15 image pairs from the SpineWeb database. Experimental results show high overlapping ratio (in-house collection, vertebrae 0.97 ± 0.02, blood vessel 0.88 ± 0.07; SpineWeb, vertebrae 0.95 ± 0.03, blood vessel 0.93 ± 0.10) and low target registration error (in-house collection, ≤2.00 ± 0.62 mm; SpineWeb, ≤2.37 ± 0.76 mm) are achieved. The proposed framework concerns both the incompressibility of bone structures and the nonrigid deformation of soft tissues. It enables accurate CT-MR registration of lumbar spine images and facilitates image fusion, spine disease diagnosis, and interventional treatment delivery.

[Navigated liver surgery : Current state and importance in the future]

The preoperative computer-assisted resection planning is the basis for every navigation. Thanks to modern algorithms, the prerequisites have been created to carry out a virtual resection planning and a risk analysis. Thus, individual segment resections can be precisely planned in any conceivable combination. The transfer of planning information and resection suggestions to the operating theater is still problematic. The so-called stereotactic liver navigation supports the exact intraoperative implementation of the planned resection strategy and provides the surgeon with real-time three-dimensional information on resection margins and critical structures during the resection. This is made possible by a surgical navigation system that measures the position of surgical instruments and then presents them together with the preoperative surgical planning data. Although surgical navigation systems have been indispensable in neurosurgery and spinal surgery for many years, these procedures have not yet become established as standard in liver surgery. This is mainly due to the technical challenge of navigating a moving organ. As the liver is constantly moving and deforming during surgery due to respiration and surgical manipulation, the surgical navigation system must be able to measure these alterations in order to adapt the preoperative navigation data to the current situation. Despite these advances, further developments are required until navigated liver resection enters clinical routine; however, it is already clear that laparoscopic liver surgery and robotic surgery will benefit most from navigation technology.

Anthropomorphic liver phantom with flow for multimodal image-guided liver therapy research and training

Purpose

The objective of this study was to develop a multimodal, permanent liver phantom displaying functional vasculature and common pathologies, for teaching, training and equipment development in laparoscopic ultrasound and navigation.

Methods

Molten wax was injected simultaneously into the portal and hepatic veins of a human liver. Upon solidification of the wax, the surrounding liver tissue was dissolved, leaving a cast of the vessels. A connection was established between the two vascular trees by manually manipulating the wax. The cast was placed, along with different multimodal tumor models, in a liver shaped mold, which was subsequently filled with a polymer. After curing, the wax was melted and flushed out of the model, thereby establishing a system of interconnected channels, replicating the major vasculature of the original liver. Thus, a liquid can be circulated through the model in a way that closely mimics the natural blood flow.

Results

Both the tumor models, i.e., the metastatic tumors, hepatocellular carcinoma and benign cyst, and the vessels inside the liver model, were clearly visualized by all the three imaging modalities: CT, MR and ultrasound. Doppler ultrasound images of the vessels proved the blood flow functionality of the phantom.

Conclusion

By a two-step casting procedure, we produced a multimodal liver phantom, with open vascular channels, and tumor models, that is the next best thing to practicing imaging and guidance procedures in animals or humans. The technique is in principle applicable to any organ of the body.

Intraoperative on-the-fly organ-mosaicking for laparoscopic surgery

The goal of computer-assisted surgery is to provide the surgeon with guidance during an intervention, e.g., using augmented reality. To display preoperative data, soft tissue deformations that occur during surgery have to be taken into consideration. Laparoscopic sensors, such as stereo endoscopes, can be used to create a three-dimensional reconstruction of stereo frames for registration. Due to the small field of view and the homogeneous structure of tissue, reconstructing just one frame, in general, will not provide enough detail to register preoperative data, since every frame only contains a part of an organ surface. A correct assignment to the preoperative model is possible only if the patch geometry can be unambiguously matched to a part of the preoperative surface. We propose and evaluate a system that combines multiple smaller reconstructions from different viewpoints to segment and reconstruct a large model of an organ. Using graphics processing unit-based methods, we achieved four frames per second. We evaluated the system with in silico, phantom, ex vivo, and in vivo (porcine) data, using different methods for estimating the camera pose (optical tracking, iterative closest point, and a combination). The results indicate that the proposed method is promising for on-the-fly organ reconstruction and registration.

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 [Formula: see text].

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.

Image-Guided Abdominal Surgery and Therapy Delivery

Image-Guided Surgery has become the standard of care in intracranial neurosurgery providing more exact resections while minimizing damage to healthy tissue. Moving that process to abdominal organs presents additional challenges in the form of image segmentation, image to physical space registration, organ motion and deformation. In this paper, we present methodologies and results for addressing these challenges in two specific organs: the liver and the kidney.

Organ surface deformation measurement and analysis in open hepatic surgery: method and preliminary results from 12 clinical cases

The incidence of soft tissue deformation has been well documented in neurosurgical procedures and is known to compromise the spatial accuracy of image-guided surgery systems.Within the context of image-guided liver surgery (IGLS), no detailed method to study and analyze the observed organ shape change between preoperative imaging and the intra-operative presentation has been developed. Contrary to the studies of deformation in neurosurgical procedures, the majority of deformation in IGLS is imposed prior to resection and due to laparotomy and mobilization. As such, methods of analyzing the organ shape change must be developed to use the intra-operative data (e.g. laser range scan (LRS) surfaces) acquired with the organ in its fully deformed shape. To achieve this end we use a signed closest point distance deformation metric computed after rigid alignment of the intra-operative LRS data with organ surfaces generated from the preoperative tomograms. The rigid alignment between the intra-operative LRS surfaces and pre-operative image data was computed with a feature weighted surface registration algorithm. In order to compare the deformation metrics across patients, an inter-patient non-rigid registration of the pre-operative CT images was performed. Given the inter-patient liver registrations, an analysis was performed to determine the potential similarities in the distribution of measured deformation between patients for which similar procedures had been performed. The results of the deformation measurement and analysis indicates the potential for soft tissue deformation to compromise surgical guidance information and suggests a similarity in imposed deformation among similar procedure types.

Model-updated image-guided liver surgery: preliminary results using surface characterization

The current protocol for image guidance in open abdominal liver tumor removal surgeries involves a rigid registration between the patient's operating room space and the pre-operative diagnostic image-space. Systematic studies have shown that the liver can deform up to 2 cm during surgeries in a non-rigid fashion thereby compromising the accuracy of these surgical navigation systems. Compensating for intra-operative deformations using mathematical models has shown promising results. In this work, we follow up the initial rigid registration with a computational approach that is geared towards minimizing the residual closest point distances between the un-deformed pre-operative surface and the rigidly registered intra-operative surface. We also use a surface Laplacian equation based filter that generates a realistic deformation field. Preliminary validation of the proposed computational framework was performed using phantom experiments and clinical trials. The proposed framework improved the rigid registration errors for the phantom experiments on average by 43%, and 74% using partial and full surface data, respectively. With respect to clinical data, it improved the closest point residual error associated with rigid registration by 54% on average for the clinical cases. These results are highly encouraging and suggest that computational models can be used to increase the accuracy of image-guided open abdominal liver tumor removal surgeries.

Robust surface registration using salient anatomical features for image-guided liver surgery: algorithm and validation

A successful surface-based image-to-physical space registration in image-guided liver surgery (IGLS) is critical to provide reliable guidance information to surgeons and pertinent surface displacement data for use in deformation correction algorithms. The current protocol used to perform the image-to-physical space registration involves an initial pose estimation provided by a point based registration of anatomical landmarks identifiable in both the preoperative tomograms and the intraoperative presentation. The surface based registration is then performed via a traditional iterative closest point (ICP) algorithm between the preoperative liver surface, segmented from the tomographic image set, and an intraoperatively acquired point cloud of the liver surface provided by a laser range scanner. Using this more conventional method, the registration accuracy can be compromised by poor initial pose estimation as well as tissue deformation due to the laparotomy and liver mobilization performed prior to tumor resection. In order to increase the robustness of the current surface-based registration method used in IGLS, we propose the incorporation of salient anatomical features, identifiable in both the preoperative image sets and intraoperative liver surface data, to aid in the initial pose estimation and play a more significant role in the surface-based registration via a novel weighting scheme. Examples of such salient anatomical features are the falciform groove region as well as the inferior ridge of the liver surface. In order to validate the proposed weighted patch registration method, the alignment results provided by the proposed algorithm using both single and multiple patch regions were compared with the traditional ICP method using six clinical datasets. Robustness studies were also performed using both phantom and clinical data to compare the resulting registrations provided by the proposed algorithm and the traditional method under conditions of varying initial pose. The results provided by the robustness trials and clinical registration comparisons suggest that the proposed weighted patch registration algorithm provides a more robust method with which to perform the image-to-physical space registration in IGLS. Furthermore, the implementation of the proposed algorithm during surgical procedures does not impose significant increases in computation or data acquisition times.

Feasibility of navigated resection of liver tumors using multiplanar visualization of intraoperative 3-dimensional ultrasound data

BACKGROUND

Intraoperative ultrasound is widely used in liver surgery, but primarily for diagnostic purposes. We have developed and evaluated a system for navigated liver resections using on intraoperatively acquired 3-dimensional (3D) ultrasound data.

METHODS

Navigation technique based on 3D ultrasound and an optical tracking system. Accuracy of the system was validated experimentally in a tumor model. Subsequently, clinical application was evaluated in 54 patients for resection of central liver tumors. Clinical feasibility and accuracy of the navigation technique were assessed with respect to practicability, adequacy of visualization, and precision of navigated resection (free margin).

RESULTS

Evaluation of the system in the tumor model showed a significant increase of the accuracy of navigated resections compared with conventional resection (P < 0.05). Clinical application of 3D ultrasound-based navigation was feasible in 52 of 54 patients. Sufficient visualization was obtained with 2 orthogonal section planes. This navigation strategy provided complete anatomic orientation and accurate position control of surgical instruments. Mean histologic resection margin was 9 mm with a maximum deviation of 8 mm from the planned virtual resection margins.

CONCLUSIONS

Optoelectronic navigation with section mode visualization in 2 orthogonal planes does sufficiently display intraoperative 3D data and enables accurate ultrasound-based navigation of liver resections.

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.

An Augmented Reality System for MR Image–guided Needle Biopsy: Initial Results in a Swine Model

PURPOSE

To evaluate an augmented reality (AR) system in combination with a 1.5-T closed-bore magnetic resonance (MR) imager as a navigation tool for needle biopsies.

MATERIALS AND METHODS

The experimental protocol had institutional animal care and use committee approval. Seventy biopsies were performed in phantoms by using 20 tube targets, each with a diameter of 6 mm, and 50 virtual targets. The position of the needle tip in AR and MR space was compared in multiple imaging planes, and virtual and real needle tip localization errors were calculated. Ten AR-guided biopsies were performed in three pigs, and the duration of each procedure was determined. After successful puncture, the distance to the target was measured on MR images. The confidence limits for the achieved in-plane hit rate and for lateral deviation were calculated. A repeated measures analysis of variance was used to determine whether the placement error in a particular dimension (x, y, or z) differed from the others.

RESULTS

For the 50 virtual targets, a mean error of 1.1 mm +/- 0.5 (standard deviation) was calculated. A repeated measures analysis of variance indicated no statistically significant difference (P > .99) in the errors in any particular orientation. For the real targets, all punctures were inside the 6-mm-diameter tube in the transverse plane. The needle depth was within the target plane in 11 biopsy procedures; the mean distance to the center of the target was 2.55 mm (95% confidence interval: 1.77 mm, 3.34 mm). For nine biopsy procedures, the needle tip was outside the target plane, with a mean distance to the edge of the target plane of 1.5 mm (range, 0.07-3.46 mm). In the animal experiments, the puncture was successful in all 10 cases, with a mean target-needle distance of 9.6 mm +/- 4.85. The average procedure time was 18 minutes per puncture.

CONCLUSION

Biopsy procedures performed with a combination of a closed-bore MR system and an AR system are feasible and accurate.

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.

The process and development of image-guided procedures

Medical imaging has been used primarily for diagnosis. In the past 15 years there has been an emergence of the use of images for the guidance of therapy. This process requires three-dimensional localization devices, the ability to register medical images to physical space, and the ability to display position and trajectory on those images. This paper examines the development and state of the art in those processes.

Registration of physical space to laparoscopic image space for use in minimally invasive hepatic surgery

While laparoscopes are used for numerous minimally invasive (MI) procedures, MI liver resection and ablative surgery is infrequently performed. The paucity of cases is due to the restriction of the field of view by the laparoscope and the difficulty in determining tumor location and margins under video guidance. By merging MI surgery with interactive, image-guided surgery (IIGS), we hope to overcome localization difficulties present in laparoscopic liver procedures. One key component of any IIGS system is the development of accurate registration techniques to map image space to physical or patient space. This manuscript focuses on the accuracy and analysis of the direct linear transformation (DLT) method to register physical space with laparoscopic image space on both distorted and distortion-corrected video images. Experiments were conducted on a liver-sized plastic phantom affixed with 20 markers at various depths. After localizing the points in both physical and laparoscopic image space, registration accuracy was assessed for different combinations and numbers of control points (n) to determine the quantity necessary to develop a robust registration matrix. For n = 11, average target registration error (TRE) was 0.70 +/- 0.20 mm. We also studied the effects of distortion correction on registration accuracy. For the particular distortion correction method and laparoscope used in our experiments, there was no statistical significance between physical to image registration error for distorted and corrected images. In cases where a minimum number of control points (n = 6) are acquired, the DLT is often not stable and the mathematical process can lead to high TRE values. Mathematical filters developed through the analysis of the DLT were used to prospectively eliminate outlier cases where the TRE was high. For n = 6, prefilter average TRE was 17.4 +/- 153 mm for all trials; when the filters were applied, average TRE decreased to 1.64 +/- 1.10 mm for the remaining trials.