Comparing Measured and Theoretical Target Registration Error of an Optical Tracking System

The goal of this thesis is to experimentally measure the accuracy of an optical tracking system used in commercial surgical navigation systems. We measure accuracy by constructing a mechanism that allows a tracked target to move with spherical motion (i.e., there exists a single point on the mechanism—the center of the sphere—that does not change position when the tracked target is moved). We imagine that the center of the sphere is the tip of a surgical tool rigidly attached to the tracked target. The location of the tool tip cannot be measured directly by the tracking system (because it is impossible to attach a tracking marker to the tool tip) and must be calculated using the measured location and orientation of the tracking target. Any measurement error in the tracking system will cause the calculated position of the tool tip to change as the target is moved; the spread of the calculated tool tip positions is a measurement of tracking error called the target registration error (TRE). The observed TRE will be compared to an analytic model of TRE to assess the predictions of the analytic model

High-contrast imaging in the Hyades with snapshot LOCI

To image faint substellar companions obscured by the stellar halo and speckles, scattered light from the bright primary star must be removed in hardware or software. We apply the "locally-optimized combination of images" (LOCI) algorithm to 1-minute Keck Observatory snapshots of GKM dwarfs in the Hyades using source diversity to determine the most likely PSF. We obtain a mean contrast of 10^{-2} at 0.01", 10^{-4} at <1", and 10^{-5} at 5". New brown dwarf and low-mass stellar companions to Hyades primaries are found in a third of the 84 targeted systems. This campaign shows the efficacy of LOCI on snapshot imaging as well as on bright wide binaries with off-axis LOCI, reaching contrasts sufficient for imaging 625-Myr late-L/early-T dwarfs purely in post-processing.Comment: 12 pages, 12 figures, to appear in SPIE Astronomy 2012, paper 8447-16

Current Accuracy of Augmented Reality Neuronavigation Systems: Systematic Review and Meta-Analysis

BACKGROUND Augmented reality neuronavigation (ARN) systems can overlay three-dimensional anatomy and pathology without the need for a two-dimensional external monitor. Accuracy is crucial for their clinical applicability. We performed a systematic review regarding the reported accuracy of ARN systems and compared them with the accuracy of conventional infrared neuronavigation (CIN). OBJECTIVE Explore the current navigation accuracy of ARN systems and compare them with CIN. METHODS Pubmed and Embase were searched for ARN and CIN systems. For ARN: type of system, method of patient-to-image registration, accuracy method and accuracy of the system was noted. For CIN: navigation accuracy, expressed as target registration error (TRE), was noted. A meta-analysis was performed comparing the TRE of ARN and CIN systems. RESULTS 35 studies were included, 12 for ARN and 23 for CIN. ARN systems were divided into head-mounted display and heads-up display. In ARN, four methods were encountered for patient-to-image registration, of which point-pair matching was the one most frequently used. Five methods for assessing accuracy were described. 94 TRE measurements of ARN systems were compared with 9058 TRE measurements of CIN systems. Mean TRE was 2.5 mm (CI 95% 0.7 - 4.4) for ARN systems and 2.6 mm (CI 95% 2.1 - 3.1) for CIN systems. CONCLUSIONS In ARN, there seems to be lack of agreement regarding the best method to assess accuracy. Nevertheless, ARN systems seem able to achieve an accuracy comparable with CIN systems. Future studies should be prospective and compare TREs which should be measured in a standardized fashion

On uncertainty propagation in image-guided renal navigation: Exploring uncertainty reduction techniques through simulation and in vitro phantom evaluation

Image-guided interventions (IGIs) entail the use of imaging to augment or replace direct vision during therapeutic interventions, with the overall goal is to provide effective treatment in a less invasive manner, as an alternative to traditional open surgery, while reducing patient trauma and shortening the recovery time post-procedure. IGIs rely on pre-operative images, surgical tracking and localization systems, and intra-operative images to provide correct views of the surgical scene. Pre-operative images are used to generate patient-specific anatomical models that are then registered to the patient using the surgical tracking system, and often complemented with real-time, intra-operative images. IGI systems are subject to uncertainty from several sources, including surgical instrument tracking / localization uncertainty, model-to-patient registration uncertainty, user-induced navigation uncertainty, as well as the uncertainty associated with the calibration of various surgical instruments and intra-operative imaging devices (i.e., laparoscopic camera) instrumented with surgical tracking sensors. All these uncertainties impact the overall targeting accuracy, which represents the error associated with the navigation of a surgical instrument to a specific target to be treated under image guidance provided by the IGI system. Therefore, understanding the overall uncertainty of an IGI system is paramount to the overall outcome of the intervention, as procedure success entails achieving certain accuracy tolerances specific to individual procedures. This work has focused on studying the navigation uncertainty, along with techniques to reduce uncertainty, for an IGI platform dedicated to image-guided renal interventions. We constructed life-size replica patient-specific kidney models from pre-operative images using 3D printing and tissue emulating materials and conducted experiments to characterize the uncertainty of both optical and electromagnetic surgical tracking systems, the uncertainty associated with the virtual model-to-physical phantom registration, as well as the uncertainty associated with live augmented reality (AR) views of the surgical scene achieved by enhancing the pre-procedural model and tracked surgical instrument views with live video views acquires using a camera tracked in real time. To better understand the effects of the tracked instrument calibration, registration fiducial configuration, and tracked camera calibration on the overall navigation uncertainty, we conducted Monte Carlo simulations that enabled us to identify optimal configurations that were subsequently validated experimentally using patient-specific phantoms in the laboratory. To mitigate the inherent accuracy limitations associated with the pre-procedural model-to-patient registration and their effect on the overall navigation, we also demonstrated the use of tracked video imaging to update the registration, enabling us to restore targeting accuracy to within its acceptable range. Lastly, we conducted several validation experiments using patient-specific kidney emulating phantoms using post-procedure CT imaging as reference ground truth to assess the accuracy of AR-guided navigation in the context of in vitro renal interventions. This work helped find answers to key questions about uncertainty propagation in image-guided renal interventions and led to the development of key techniques and tools to help reduce optimize the overall navigation / targeting uncertainty

Ultrasound-Guided Mechatronic System for Targeted Delivery of Cell-Based Cancer Vaccine Immunotherapy in Preclinical Models

Injection of dendritic cell (DC) vaccines into lymph nodes (LN) is a promising strategy for eliciting immune responses against cancer, but these injections in mouse cancer models are challenging due to the small target scale (~ 1 mm × 2 mm). Direct manual intranodal injection is difficult and can cause architectural damage to the LN, potentially disrupting crucial interactions between DC and T cells. Therefore, a second-generation ultrasound-guided mechatronic device has been developed to perform this intervention. A targeting accuracy of \u3c 500 μm will enable targeted delivery of the DCs specifically to a LN subcapsular space. The device was redesigned from its original CT-guided edition, which used a remote centre of motion architecture, to be easily integrated onto a commercially available VisualSonics imaging rail system. Subtle modifications were made to ensure simple workflow that allows for live-animal interventions that fall within the knockout periods stated in study protocols. Several calibration and registration techniques were developed in order to achieve an overall targeting accuracy appropriate for the intended application. A variety of methods to quantify the positioning accuracy of the device were investigated. The method chosen involved validating a guided injection into a tissue-mimicking phantom using ultrasound imaging post-operatively to localize the end-point position of the needle tip in the track left behind by the needle. Ultrasound-guided injections into a tissue-mimicking phantom revealed a targeting accuracy of 285 ± 94 μm for the developed robot compared to 508 ± 166 μm for a commercial-available manually-actuated injection device from VisuailSonics. The utility of the robot was also demonstrated by performing in vivo injections into the lymph nodes of mice

Estimating Target Vessel Location on Robot-Assisted CABG using Feature-based CT to US Registration

Although robot-assisted coronary artery bypass grafting (RA-CABG) has gained more acceptance worldwide, its success still depends on the surgeon’s experience and expertise, and the conversion rate to full sternotomy is in the order of 15%—25%. One of the reasons for conversion is poor pre-operative planning, which is based solely on pre-operative computed tomography (CT) images. This thesis proposes a technique to estimate the global peri-operative displacement of the heart and to predict the intra-operative target vessel location. The technique has been validated via both an in vitro and a clinical study, and predicted the position of the peri-operative target vessel location with ~ 3.5 mm RMS accuracy in the in vitro study while it yielded ~ 5.0 mm accuracy for the clinical validation. As the desired clinical accuracy imposed by this procedure is on the order of one intercostal space (10 - 15 mm), our technique suits the clinical requirements. It is therefore believed that this technique has the potential to improve the pre-operative planning by updating peri-operative migration patterns of the heart and, consequently, will lead to reduced conversion to conventional open thoracic procedures

Target localization of 3D versus 4D cone beam computed tomography in lipiodol-guided stereotactic radiotherapy of hepatocellular carcinomas

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