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

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

Improvements in the registration of multimodal medical imaging : application to intensity inhomogeneity and partial volume corrections

Alignment or registration of medical images has a relevant role on clinical diagnostic and treatment decisions as well as in research settings. With the advent of new technologies for multimodal imaging, robust registration of functional and anatomical information is still a challenge, particular in small-animal imaging given the lesser structural content of certain anatomical parts, such as the brain, than in humans. Besides, patient-dependent and acquisition artefacts affecting the images information content further complicate registration, as is the case of intensity inhomogeneities (IIH) showing in MRI and the partial volume effect (PVE) attached to PET imaging. Reference methods exist for accurate image registration but their performance is severely deteriorated in situations involving little images Overlap. While several approaches to IIH and PVE correction exist these methods still do not guarantee or rely on robust registration. This Thesis focuses on overcoming current limitations af registration to enable novel IIH and PVE correction methods.El registre d'imatges mèdiques té un paper rellevant en les decisions de diagnòstic i tractament clíniques així com en la recerca. Amb el desenvolupament de noves tecnologies d'imatge multimodal, el registre robust d'informació funcional i anatòmica és encara avui un repte, en particular, en imatge de petit animal amb un menor contingut estructural que en humans de certes parts anatòmiques com el cervell. A més, els artefactes induïts pel propi pacient i per la tècnica d'adquisició que afecten el contingut d'informació de les imatges complica encara més el procés de registre. És el cas de les inhomogeneïtats d'intensitat (IIH) que apareixen a les RM i de l'efecte de volum parcial (PVE) característic en PET. Tot i que existeixen mètodes de referència pel registre acurat d'imatges la seva eficàcia es veu greument minvada en casos de poc solapament entre les imatges. De la mateixa manera, també existeixen mètodes per la correcció d'IIH i de PVE però que no garanteixen o que requereixen un registre robust. Aquesta tesi es centra en superar aquestes limitacions sobre el registre per habilitar nous mètodes per la correcció d'IIH i de PVE

Quantitatively Imaging Chromosomes by Correlated Cryo-Fluorescence and Soft X-Ray Tomographies

AbstractSoft x-ray tomography (SXT) is increasingly being recognized as a valuable method for visualizing and quantifying the ultrastructure of cryopreserved cells. Here, we describe the combination of SXT with cryogenic confocal fluorescence tomography (CFT). This correlative approach allows the incorporation of molecular localization data, with isotropic precision, into high-resolution three-dimensional (3-D) SXT reconstructions of the cell. CFT data are acquired first using a cryogenically adapted confocal light microscope in which the specimen is coupled to a high numerical aperture objective lens by an immersion fluid. The specimen is then cryo-transferred to a soft x-ray microscope (SXM) for SXT data acquisition. Fiducial markers visible in both types of data act as common landmarks, enabling accurate coalignment of the two complementary tomographic reconstructions. We used this method to identify the inactive X chromosome (Xi) in female v-abl transformed thymic lymphoma cells by localizing enhanced green fluorescent protein-labeled macroH2A with CFT. The molecular localization data were used to guide segmentation of Xi in the SXT reconstructions, allowing characterization of the Xi topological arrangement in near-native state cells. Xi was seen to adopt a number of different topologies with no particular arrangement being dominant

Methods for interventional magnetic resonance imaging

This thesis has as its central aim to demonstrate, develop, discuss and promote new methods and technology for improving interventional low field magnetic resonance imaging. The work addresses problems related to accurate localization of minimally invasive surgical tools by describing novel devices and improvements to prior art techniques, such as optical tracking. In addition to instrument guidance, ablative treatment of liver tumours is discussed in connection with low field temperature measurement and the work describes suitable sequences for qualitative temperature imaging. For instrument localization, a method utilising ex vivo Overhauser enhancement of a catheter like structure was demonstrated. An enhancement factor of 10 was achieved, proving that a substantial signal gain is possible through the use of ex vivo-enhanced liquid. Similarly, a method for biopsy needle tip tracking was developed; where the position of the tip was tracked with a signal from a miniaturized electron spin resonance sample and gradient pulses. At an update rate of 10 samples per second, the accuracy was measured to be better than ±2 mm within a homogeneous sphere of 300 mm. Optical tracking methods concentrated on new indications of use for the developed optical tracking system and associated software: The system was applied to guide the needle 35 times into first sacral root foramina, with a success rate of 97%. It was also used in five bone biopsies, all of which were performed successfully, the samples allowed for a pathologic diagnosis, and the percutaneous procedures could be performed in less than 40 minutes. A new patient tracker device was developed for staged neurosurgical procedures and demonstrated with two patient cases. In the temperature measurement study, spin echo, gradient echo and completely balanced steady-state free precession sequences were optimized for maximal temperature sensitivity and the optimized sequences compared. The steady-state sequence seemed the most promising for the prediction of ablated volume in liver.reviewe

Image-Guided Robotic Dental Implantation With Natural-Root-Formed Implants

Dental implantation is now recognized as the standard of the care for tooth replacement. Although many studies show high short term survival rates greater than 95%, long term studies (\u3e 5 years) have shown success rates as low as 41.9%. Reasons affecting the long term success rates might include surgical factors such as limited accuracy of implant placement, lack of spacing controls, and overheating during the placement. In this dissertation, a comprehensive solution for improving the outcome of current dental implantation is presented, which includes computer-aided preoperative planning for better visualization of patient-specific information and automated robotic site-preparation for superior placement and orientation accuracy. Surgical planning is generated using patient-specific three-dimensional (3D) models which are reconstructed from Cone-beam CT images. An innovative image-guided robotic site-preparation system for implants insertion is designed and implemented. The preoperative plan of the implant insertion is transferred into intra-operative operations of the robot using a two-step registration procedure with the help of a Coordinate Measurement Machine (CMM). The natural-root implants mimic the root structure of natural teeth and were proved by Finite Element Method (FEM) to provide superior stress distribution than current cylinder-shape implants. However, due to their complicated geometry, manual site-preparation for these implants cannot be accomplished. Our innovative image-guided robotic implantation system provides the possibility of using this advanced type of implant. Phantom experiments with patient-specific jaw models were performed to evaluate the accuracy of positioning and orientation. Fiducial Registration Error (FRE) values less than 0.20 mm and final Target Registration Error (TRE) values after the two-step registration of 0.36±0.13 mm (N=5) were achieved. Orientation error was 1.99±1.27° (N=14). Robotic milling of the natural-root implant shape with single- and double-root was also tested, and the results proved that their complicated volumes can be removed as designed by the robot. The milling time for single- and double-root shape was 177 s and 1522 s, respectively

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

Augmented Image-Guidance for Transcatheter Aortic Valve Implantation

The introduction of transcatheter aortic valve implantation (TAVI), an innovative stent-based technique for delivery of a bioprosthetic valve, has resulted in a paradigm shift in treatment options for elderly patients with aortic stenosis. While there have been major advancements in valve design and access routes, TAVI still relies largely on single-plane fluoroscopy for intraoperative navigation and guidance, which provides only gross imaging of anatomical structures. Inadequate imaging leading to suboptimal valve positioning contributes to many of the early complications experienced by TAVI patients, including valve embolism, coronary ostia obstruction, paravalvular leak, heart block, and secondary nephrotoxicity from contrast use. A potential method of providing improved image-guidance for TAVI is to combine the information derived from intra-operative fluoroscopy and TEE with pre-operative CT data. This would allow the 3D anatomy of the aortic root to be visualized along with real-time information about valve and prosthesis motion. The combined information can be visualized as a `merged\u27 image where the different imaging modalities are overlaid upon each other, or as an `augmented\u27 image, where the location of key target features identified on one image are displayed on a different imaging modality. This research develops image registration techniques to bring fluoroscopy, TEE, and CT models into a common coordinate frame with an image processing workflow that is compatible with the TAVI procedure. The techniques are designed to be fast enough to allow for real-time image fusion and visualization during the procedure, with an intra-procedural set-up requiring only a few minutes. TEE to fluoroscopy registration was achieved using a single-perspective TEE probe pose estimation technique. The alignment of CT and TEE images was achieved using custom-designed algorithms to extract aortic root contours from XPlane TEE images, and matching the shape of these contours to a CT-derived surface model. Registration accuracy was assessed on porcine and human images by identifying targets (such as guidewires or coronary ostia) on the different imaging modalities and measuring the correspondence of these targets after registration. The merged images demonstrated good visual alignment of aortic root structures, and quantitative assessment measured an accuracy of less than 1.5mm error for TEE-fluoroscopy registration and less than 6mm error for CT-TEE registration. These results suggest that the image processing techniques presented have potential for development into a clinical tool to guide TAVI. Such a tool could potentially reduce TAVI complications, reducing morbidity and mortality and allowing for a safer procedure