Development of a Three-Dimensional Image-Guided Needle Positioning System for Small Animal Interventions

Conventional needle positioning techniques for small animal microinjections are fraught with issues of repeatability and targeting accuracy. To improve the outcomes of these interventions a small animal needle positioning system guided by micro-computed tomography (micro-CT) imaging was developed. A phantom was developed to calibrate the geometric accuracy of micro-CT scanners to a traceable standard of measurement. Use of the phantom ensures the geometric fidelity of micro-CT images for use in image-guided interventions or other demanding quantitative applications. The design of a robot is described which features a remote center of motion architecture and is compact enough to operate within a micro-CT bore. Methods to calibrate the robot and register it to a micro-CT scanner are introduced. The performance of the robot is characterized and a mean targeting accuracy of 149 ± 41 µm estimated. The robot is finally demonstrated by completing an in vivo biomedical application

New Mechatronic Systems for the Diagnosis and Treatment of Cancer

Both two dimensional (2D) and three dimensional (3D) imaging modalities are useful tools for viewing the internal anatomy. Three dimensional imaging techniques are required for accurate targeting of needles. This improves the efficiency and control over the intervention as the high temporal resolution of medical images can be used to validate the location of needle and target in real time. Relying on imaging alone, however, means the intervention is still operator dependent because of the difficulty of controlling the location of the needle within the image. The objective of this thesis is to improve the accuracy and repeatability of needle-based interventions over conventional techniques: both manual and automated techniques. This includes increasing the accuracy and repeatability of these procedures in order to minimize the invasiveness of the procedure. In this thesis, I propose that by combining the remote center of motion concept using spherical linkage components into a passive or semi-automated device, the physician will have a useful tracking and guidance system at their disposal in a package, which is less threatening than a robot to both the patient and physician. This design concept offers both the manipulative transparency of a freehand system, and tremor reduction through scaling currently offered in automated systems. In addressing each objective of this thesis, a number of novel mechanical designs incorporating an remote center of motion architecture with varying degrees of freedom have been presented. Each of these designs can be deployed in a variety of imaging modalities and clinical applications, ranging from preclinical to human interventions, with an accuracy of control in the millimeter to sub-millimeter range

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

Ultra-High Field Strength MR Image-Guided Robotic Needle Delivery Device for In-Bore Small Animal Interventions

Current methods of accurate soft tissue injections in small animals are prone to many sources of error. Although efforts have been made to improve the accuracy of needle deliveries, none of the efforts have provided accurate soft tissue references. An MR image-guided robot was designed to function inside the bore of a 9.4T MR scanner to accurately deliver needles to locations within the mouse brain. The robot was designed to have no noticeable negative effects on the image quality and was localized in the MR images through the use of an MR image visible fiducial. The robot was mechanically calibrated and subsequently validated in an image-guided phantom experiment, where the mean needle targeting accuracy and needle trajectory accuracy were calculated to be 178 ± 54µm and 0.27 ± 0.65º, respectively. Finally, the device successfully demonstrated an image-guided needle targeting procedure in situ

AUGMENTED REALITY AND INTRAOPERATIVE C-ARM CONE-BEAM COMPUTED TOMOGRAPHY FOR IMAGE-GUIDED ROBOTIC SURGERY

Minimally-invasive robotic-assisted surgery is a rapidly-growing alternative to traditionally open and laparoscopic procedures; nevertheless, challenges remain. Standard of care derives surgical strategies from preoperative volumetric data (i.e., computed tomography (CT) and magnetic resonance (MR) images) that benefit from the ability of multiple modalities to delineate different anatomical boundaries. However, preoperative images may not reflect a possibly highly deformed perioperative setup or intraoperative deformation. Additionally, in current clinical practice, the correspondence of preoperative plans to the surgical scene is conducted as a mental exercise; thus, the accuracy of this practice is highly dependent on the surgeon’s experience and therefore subject to inconsistencies. In order to address these fundamental limitations in minimally-invasive robotic surgery, this dissertation combines a high-end robotic C-arm imaging system and a modern robotic surgical platform as an integrated intraoperative image-guided system. We performed deformable registration of preoperative plans to a perioperative cone-beam computed tomography (CBCT), acquired after the patient is positioned for intervention. From the registered surgical plans, we overlaid critical information onto the primary intraoperative visual source, the robotic endoscope, by using augmented reality. Guidance afforded by this system not only uses augmented reality to fuse virtual medical information, but also provides tool localization and other dynamic intraoperative updated behavior in order to present enhanced depth feedback and information to the surgeon. These techniques in guided robotic surgery required a streamlined approach to creating intuitive and effective human-machine interferences, especially in visualization. Our software design principles create an inherently information-driven modular architecture incorporating robotics and intraoperative imaging through augmented reality. The system's performance is evaluated using phantoms and preclinical in-vivo experiments for multiple applications, including transoral robotic surgery, robot-assisted thoracic interventions, and cocheostomy for cochlear implantation. The resulting functionality, proposed architecture, and implemented methodologies can be further generalized to other C-arm-based image guidance for additional extensions in robotic surgery

Anniversary Paper: Evolution of ultrasound physics and the role of medical physicists and the AAPM and its journal in that evolution

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134810/1/mp2048.pd

Multimodal and multiscale imaging of the human placental vasculature

Minimally invasive fetal interventions, such as those used for therapy of twin-to- twin transfusion syndrome (TTTS), require accurate image guidance to optimise patient outcomes. Photoacoustic imaging can provide molecular contrast based on the optical absorption of the haemoglobin, and in this dissertation, it was proposed as a novel technique to image the human placental vasculature. Normal term and in utero TTTS treated placentas were imaged post-partum using two novel photoacoustic imaging systems. With PA imaging, vasculature was resolved to a depth of approximately 7 mm from the chorionic placental surface; the photocoagulated tissue provided a negative contrast and the ablation depth of the scar was visualised. Complementary imaging of the placental vasculature in a microscopic size scale was performed with a handheld incident dark field illumination video microscope in fresh and formalin-fixed term placentas. Real time visualisation of the villus tree down to the terminal villi level was achieved without any contrast injection or extensive tissue preparation. Additionally, the novel application of photoacoustic imaging to guide minimally invasive fetal interventions motivated the development of tissue-mimicking placental phantoms for bench-top system validation and for clinical training. Ideally, phantoms for this modality comprise materials with optical and acoustic properties that can be precisely and independently controlled, which are stable over time, and which are non-toxic and low-cost. Gel wax was proposed as a novel tissue-mimicking material (TMM) that satisfies these criteria, and that it can be used to represent various soft tissues and fabricate heterogeneous phantoms with structures based on patient-specific anatomy. This dissertation sets the stage for the development of miniaturised photoacoustic imaging probes for intraoperative guidance, and new methods of understanding the placental vascular anatomy in health and disease. Gel wax has strong potential to become a next generation TMM for evaluation, and standardisation of imaging systems, and for clinical training

Investigation of Subchondral Bone Abnormalities associated with Osteoarthritis using Image-Based Biomechanics

Osteoarthritis (OA) is degenerative disease caused by a mechanical failure of bone and cartilage. Common risk factors for developing OA include: being over-weight, female, having joint malalignment, or a history of prior joint injury. Post-traumatic OA is extremely common in the knee as individuals frequently suffer injuries to structures that provide stability to the joint. To enhance our understanding about OA, animal models are employed where the injury can be and monitored in a controlled environment. When used in conjunction with pre-clinical imaging techniques the longitudinal degradation of bone and cartilage can be quantitatively monitored in vivo. Recent evidence has identified cystic lesions within the subchondral bone as the possible source of painful symptoms and accelerated disease progression, but little is known about their etiology. The purpose of this thesis was to improve knowledge regarding the mechanism that causes subchondral cysts. OA was induced in the rodent knee via surgery, and the pathological changes were quantified with micro-CT and MRI. The composition of the cysts was correlated with end-stage histology. Thus, an accurate definition of OA bone cysts was achieved. To assess the effect of cysts in human bone, a study was conducted using a patient data set restrospectively. Using finite element (FE) analysis, higher stress values were found within bone surrounding cysts. Therefore, the probable mechanism of cyst expansion, stress induced resorption, was identified. Finally, the FE models of the bones were combined with soft tissue structures – from a co-registered MRI – to produce comprehensive patient-specific models of the knee

Exploiting Temporal Image Information in Minimally Invasive Surgery

Minimally invasive procedures rely on medical imaging instead of the surgeons direct vision. While preoperative images can be used for surgical planning and navigation, once the surgeon arrives at the target site real-time intraoperative imaging is needed. However, acquiring and interpreting these images can be challenging and much of the rich temporal information present in these images is not visible. The goal of this thesis is to improve image guidance for minimally invasive surgery in two main areas. First, by showing how high-quality ultrasound video can be obtained by integrating an ultrasound transducer directly into delivery devices for beating heart valve surgery. Secondly, by extracting hidden temporal information through video processing methods to help the surgeon localize important anatomical structures. Prototypes of delivery tools, with integrated ultrasound imaging, were developed for both transcatheter aortic valve implantation and mitral valve repair. These tools provided an on-site view that shows the tool-tissue interactions during valve repair. Additionally, augmented reality environments were used to add more anatomical context that aids in navigation and in interpreting the on-site video. Other procedures can be improved by extracting hidden temporal information from the intraoperative video. In ultrasound guided epidural injections, dural pulsation provides a cue in finding a clear trajectory to the epidural space. By processing the video using extended Kalman filtering, subtle pulsations were automatically detected and visualized in real-time. A statistical framework for analyzing periodicity was developed based on dynamic linear modelling. In addition to detecting dural pulsation in lumbar spine ultrasound, this approach was used to image tissue perfusion in natural video and generate ventilation maps from free-breathing magnetic resonance imaging. A second statistical method, based on spectral analysis of pixel intensity values, allowed blood flow to be detected directly from high-frequency B-mode ultrasound video. Finally, pulsatile cues in endoscopic video were enhanced through Eulerian video magnification to help localize critical vasculature. This approach shows particular promise in identifying the basilar artery in endoscopic third ventriculostomy and the prostatic artery in nerve-sparing prostatectomy. A real-time implementation was developed which processed full-resolution stereoscopic video on the da Vinci Surgical System