Recovery of respiratory motion and deformation of the liver using laparoscopic freehand 3D ultrasound system

Intraoperative Correction of Liver Deformation Using Sparse Surface and Vascular Features via Linearized Iterative Boundary Reconstruction

During image guided liver surgery, soft tissue deformation can cause considerable error when attempting to achieve accurate localization of the surgical anatomy through image-to-physical registration. In this paper, a linearized iterative boundary reconstruction technique is proposed to account for these deformations. The approach leverages a superposed formulation of boundary conditions to rapidly and accurately estimate the deformation applied to a preoperative model of the organ given sparse intraoperative data of surface and subsurface features. With this method, tracked intraoperative ultrasound (iUS) is investigated as a potential data source for augmenting registration accuracy beyond the capacity of conventional organ surface registration. In an expansive simulated dataset, features including vessel contours, vessel centerlines, and the posterior liver surface are extracted from iUS planes. Registration accuracy is compared across increasing data density to establish how iUS can be best employed to improve target registration error (TRE). From a baseline average TRE of 11.4 ± 2.2 mm using sparse surface data only, incorporating additional sparse features from three iUS planes improved average TRE to 6.4 ± 1.0 mm. Furthermore, increasing the sparse coverage to 16 tracked iUS planes improved average TRE to 3.9 ± 0.7 mm, exceeding the accuracy of registration based on complete surface data available with more cumbersome intraoperative CT without contrast. Additionally, the approach was applied to three clinical cases where on average error improved 67% over rigid registration and 56% over deformable surface registration when incorporating additional features from one independent tracked iUS plane.

Freehand 3-D Ultrasound Imaging: A Systematic Review

Two-dimensional ultrasound (US) imaging has been successfully used in clinical applications as a low-cost, portable and non-invasive image modality for more than three decades. Recent advances in computer science and technology illustrate the promise of the 3-D US modality as a medical imaging technique that is comparable to other prevalent modalities and that overcomes certain drawbacks of 2-D US. This systematic review covers freehand 3-D US imaging between 1970 and 2017, highlighting the current trends in research fields, the research methods, the main limitations, the leading researchers, standard assessment criteria and clinical applications. Freehand 3-D US systems are more prevalent in the academic environment, whereas in clinical applications and industrial research, most studies have focused on 3-D US transducers and improvement of hardware performance. This topic is still an interesting active area for researchers, and there remain many unsolved problems to be addressed.

Evaluation of model-based deformation correction in image-guided liver surgery via tracked intraoperative ultrasound

Soft-tissue deformation represents a significant error source in current surgical navigation systems used for open hepatic procedures. While numerous algorithms have been proposed to rectify the tissue deformation that is encountered during open liver surgery, clinical validation of the proposed methods has been limited to surface-based metrics, and subsurface validation has largely been performed via phantom experiments. The proposed method involves the analysis of two deformation-correction algorithms for open hepatic image-guided surgery systems via subsurface targets digitized with tracked intraoperative ultrasound (iUS). Intraoperative surface digitizations were acquired via a laser range scanner and an optically tracked stylus for the purposes of computing the physical-to-image space registration and for use in retrospective deformation-correction algorithms. Upon completion of surface digitization, the organ was interrogated with a tracked iUS transducer where the iUS images and corresponding tracked locations were recorded. Mean closest-point distances between the feature contours delineated in the iUS images and corresponding three-dimensional anatomical model generated from preoperative tomograms were computed to quantify the extent to which the deformation-correction algorithms improved registration accuracy. The results for six patients, including eight anatomical targets, indicate that deformation correction can facilitate reduction in target error of [Formula: see text].

Persistent and automatic intraoperative 3D digitization of surfaces under dynamic magnifications of an operating microscope

One of the major challenges impeding advancement in image-guided surgical (IGS) systems is the soft-tissue deformation during surgical procedures. These deformations reduce the utility of the patient's preoperative images and may produce inaccuracies in the application of preoperative surgical plans. Solutions to compensate for the tissue deformations include the acquisition of intraoperative tomographic images of the whole organ for direct displacement measurement and techniques that combines intraoperative organ surface measurements with computational biomechanical models to predict subsurface displacements. The later solution has the advantage of being less expensive and amenable to surgical workflow. Several modalities such as textured laser scanners, conoscopic holography, and stereo-pair cameras have been proposed for the intraoperative 3D estimation of organ surfaces to drive patient-specific biomechanical models for the intraoperative update of preoperative images. Though each modality has its respective advantages and disadvantages, stereo-pair camera approaches used within a standard operating microscope is the focus of this article. A new method that permits the automatic and near real-time estimation of 3D surfaces (at 1 Hz) under varying magnifications of the operating microscope is proposed. This method has been evaluated on a CAD phantom object and on full-length neurosurgery video sequences (∼1 h) acquired intraoperatively by the proposed stereovision system. To the best of our knowledge, this type of validation study on full-length brain tumor surgery videos has not been done before. The method for estimating the unknown magnification factor of the operating microscope achieves accuracy within 0.02 of the theoretical value on a CAD phantom and within 0.06 on 4 clinical videos of the entire brain tumor surgery. When compared to a laser range scanner, the proposed method for reconstructing 3D surfaces intraoperatively achieves root mean square errors (surface-to-surface distance) in the 0.28-0.81 mm range on the phantom object and in the 0.54-1.35 mm range on 4 clinical cases. The digitization accuracy of the presented stereovision methods indicate that the operating microscope can be used to deliver the persistent intraoperative input required by computational biomechanical models to update the patient's preoperative images and facilitate active surgical guidance.

Real-time 3D image reconstruction guidance in liver resection surgery

BACKGROUND

Minimally invasive surgery represents one of the main evolutions of surgical techniques. However, minimally invasive surgery adds difficulty that can be reduced through computer technology.

METHODS

From a patient's medical image [US, computed tomography (CT) or MRI], we have developed an Augmented Reality (AR) system that increases the surgeon's intraoperative vision by providing a virtual transparency of the patient. AR is based on two major processes: 3D modeling and visualization of anatomical or pathological structures appearing in the medical image, and the registration of this visualization onto the real patient. We have thus developed a new online service, named Visible Patient, providing efficient 3D modeling of patients. We have then developed several 3D visualization and surgical planning software tools to combine direct volume rendering and surface rendering. Finally, we have developed two registration techniques, one interactive and one automatic providing intraoperative augmented reality view.

RESULTS

From January 2009 to June 2013, 769 clinical cases have been modeled by the Visible Patient service. Moreover, three clinical validations have been realized demonstrating the accuracy of 3D models and their great benefit, potentially increasing surgical eligibility in liver surgery (20% of cases). From these 3D models, more than 50 interactive AR-assisted surgical procedures have been realized illustrating the potential clinical benefit of such assistance to gain safety, but also current limits that automatic augmented reality will overcome.

CONCLUSIONS

Virtual patient modeling should be mandatory for certain interventions that have now to be defined, such as liver surgery. Augmented reality is clearly the next step of the new surgical instrumentation but remains currently limited due to the complexity of organ deformations during surgery. Intraoperative medical imaging used in new generation of automated augmented reality should solve this issue thanks to the development of Hybrid OR.

A Mechanics-Based Nonrigid Registration Method for Liver Surgery Using Sparse Intraoperative Data

In open abdominal image-guided liver surgery, sparse measurements of the organ surface can be taken intraoperatively via a laser-range scanning device or a tracked stylus with relatively little impact on surgical workflow. We propose a novel nonrigid registration method which uses sparse surface data to reconstruct a mapping between the preoperative CT volume and the intraoperative patient space. The mapping is generated using a tissue mechanics model subject to boundary conditions consistent with surgical supportive packing during liver resection therapy. Our approach iteratively chooses parameters which define these boundary conditions such that the deformed tissue model best fits the intraoperative surface data. Using two liver phantoms, we gathered a total of five deformation datasets with conditions comparable to open surgery. The proposed nonrigid method achieved a mean target registration error (TRE) of 3.3 mm for targets dispersed throughout the phantom volume, using a limited region of surface data to drive the nonrigid registration algorithm, while rigid registration resulted in a mean TRE of 9.5 mm. In addition, we studied the effect of surface data extent, the inclusion of subsurface data, the trade-offs of using a nonlinear tissue model, robustness to rigid misalignments, and the feasibility in five clinical datasets.

GPU based real-time surgical navigation system with three-dimensional ultrasound imaging for water-filled laparo-endoscope surgery

Presently, a variety of navigation systems are employed in clinical treatments involving neurosurgery, ENT, orthopedic, and head and neck surgery. An ultrasound diagnostic system is used as the navigation system for movable and deformable organs in the abdomen or chest. In this study, we developed a real-time updated 3D ultrasound navigation system that facilitates the high-speed transfer of image data and GPGPU processing for fetal surgery and water-filled laparo-endoscopic surgery (WAFLES). Experimental results showed that our system was able to update every 62 ms. Further, in vivo experimental results showed the ability of our system to guide a surgeon to a target organ during WAFLES in a case where the endoscopic view experienced problems.

Positioning error evaluation of GPU-based 3D ultrasound surgical navigation system for moving targets by using optical tracking system

PURPOSE

A near real-time three-dimensional (3D) ultrasound navigation system has been developed for guiding surgery involving internal organs that move and change shape (e.g., abdominal surgery, fetal surgery). In practical applications, significant errors arise between the actual navigation-image positions depending on the time delay of the system. Therefore, the positioning error of the system relative to the target velocity was evaluated.

METHODS

We developed a method for evaluating the positioning error of a graphics processing unit-based 3D ultrasound surgical navigation system (with an optical tracking system) for moving targets. The effectiveness of this system was quantitatively evaluated in terms of its image processing runtime, target registration error (TRE), and positioning error for a moving target. The positioning error was evaluated for a phantom (with an optical tracking marker) moving at speeds of 5-25 mm/s, and the navigation target was the center point of the phantom. The imaging range of the volume data was set to the maximum angle and range of the ultrasound diagnostic system (update rate: 4 Hz).

RESULTS

The image processing runtime was 27.43 ± 4.80 ms, and the TRE was 1.50 ± 0.28 mm. The positioning error was 4.24 ± 0.12 mm for a target moving at a speed of 10 mm/s and 5.36 ± 0.10 mm for one moving at 15 mm/s.

CONCLUSION

The effectiveness of an ultrasound navigation system was quantitatively evaluated by using the positioning error for a moving target. This navigation system demonstrated high calculation speed and positioning accuracy for a moving target. Therefore, it is suitable to guide the surgery of abdominal internal organs (e.g., in fetal and abdominal surgeries) that move or change shape during breathing and surgical approaches.

Real time image-based tracking of 4D ultrasound data

We propose a methodology to perform real time image-based tracking on streaming 4D ultrasound data, using image registration to deduce the positioning of each ultrasound frame in a global coordinate system. Our method provides an alternative approach to traditional external tracking devices used for tracking probe movements. We compare the performance of our method against magnetic tracking on phantom and liver data, and show that our method is able to provide results in agreement with magnetic tracking.

Navigated laparoscopic ultrasound in abdominal soft tissue surgery: technological overview and perspectives

PURPOSE

Two-dimensinal laparoscopic ultrasound (LUS) is commonly used for many laparoscopic procedures, but 3D LUS and navigation technology are not conventional tools in the clinic. Navigated LUS can help the user understand and interpret the ultrasound images in relation to the laparoscopic view and preoperative images. When combined with information from MRI or CT, navigated LUS has the potential to provide information about anatomic shifts during the procedure. In this paper, we present an overview of the ongoing technological research and development related to LUS combined with navigation technology, The purpose of this overview is threefold: (1) an introduction for those new to the field of navigated LUS; (2) an overview for those working in the field and; and (3) as a reference for those searching for literature on technological developments related to navigation in ultrasound-guided laparoscopic surgery.

METHODS

Databases were searched to identify relevant publications from the last 10 years.

RESULTS

We were able to identify 18 key papers in the area of navigated LUS for the abdomen, originating from about 10-11 groups. We present the literature overview, including descriptions of our own experience in the field, and a discussion of the important clinical and technological aspects related to navigated LUS.

CONCLUSIONS

LUS integrated with miniaturized tracking technology is likely to play an important role in guiding future laparoscopic surgery.

Augmented reality in laparoscopic surgical oncology

Minimally invasive surgery represents one of the main evolutions of surgical techniques aimed at providing a greater benefit to the patient. However, minimally invasive surgery increases the operative difficulty since the depth perception is usually dramatically reduced, the field of view is limited and the sense of touch is transmitted by an instrument. However, these drawbacks can currently be reduced by computer technology guiding the surgical gesture. Indeed, from a patient's medical image (US, CT or MRI), Augmented Reality (AR) can increase the surgeon's intra-operative vision by providing a virtual transparency of the patient. AR is based on two main processes: the 3D visualization of the anatomical or pathological structures appearing in the medical image, and the registration of this visualization on the real patient. 3D visualization can be performed directly from the medical image without the need for a pre-processing step thanks to volume rendering. But better results are obtained with surface rendering after organ and pathology delineations and 3D modelling. Registration can be performed interactively or automatically. Several interactive systems have been developed and applied to humans, demonstrating the benefit of AR in surgical oncology. It also shows the current limited interactivity due to soft organ movements and interaction between surgeon instruments and organs. If the current automatic AR systems show the feasibility of such system, it is still relying on specific and expensive equipment which is not available in clinical routine. Moreover, they are not robust enough due to the high complexity of developing a real-time registration taking organ deformation and human movement into account. However, the latest results of automatic AR systems are extremely encouraging and show that it will become a standard requirement for future computer-assisted surgical oncology. In this article, we will explain the concept of AR and its principles. Then, we will review the existing interactive and automatic AR systems in digestive surgical oncology, highlighting their benefits and limitations. Finally, we will discuss the future evolutions and the issues that still have to be tackled so that this technology can be seamlessly integrated in the operating room.

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.

Integrated MR-laparoscopy system with respiratory synchronization for minimally invasive liver surgery

PURPOSE

The laparoscope has been invaluable in minimally invasive surgery, but provides only a surface view of target tissue; therefore it is lacking internal tissue information. In combination with the laparoscope for visualizing the cross-sectional view of the tissue, MRI is superior to ultrasonography or X-ray CT, because of its high soft-tissue contrast, arbitrary slice orientation and lack of radiation properties. Thus, we propose an integrated MR-laparoscopy system with a respiratory-synchronized navigation.

METHODS

A transmit/receive RF coil for localized MR imaging with a 0.5 T open-MRI was mounted onto the tip of an MR-compatible laparoscope. The signal detection of the coil was examined with an excised porcine liver sample, an agar phantom and the abdominal wall of a healthy volunteer. A real-time navigation system to compensate for respiratory motion was developed, and examined with a healthy volunteer.

RESULTS

The SNRs of the local MR images were 112, 62, and 62 in the liver sample, phantom, and volunteer. The navigation system successfully displayed the scope view, scope location and orientation, and MR images with respiratory-synchronized real time operation.

CONCLUSIONS

The MR-imaging and synchronization function of the proposed system seemed to be helpful for laparoscopic surgery.