Adaptive Cone-Beam Scan-Trajektorien für interventionelle Anwendungen

Adaptive Cone-Beam Scan-Trajektorien für interventionelle Anwendungen Die interventionelle Röntgenbildgebung stellt Ärzten während minimalinvasiven Eingriffen Informationen über die Patientenmorphologie bereit. Sie muss aber aufgrund der gewebeschädigenden Wirkung mit Bedacht eingesetzt werden. Derzeit können Ärzte nur zwischen dosisarmen Röntgenprojektionen ohne Tiefeninformation und strahlungsintensiven Cone-Beam- Computertomografien mit Tiefeninformation wählen. Viele medizinische Anwendungen wie Positionskontrollen erfordern zwar Tiefeninformation, aber keinen vollständigen 3D-Datensatz. Adaptive Scan-Trajektorien können diese Lücke schließen, indem sie Objekte gezielt unterabtasten und die relevanten Informationen so dosiseffizient in Erfahrung bringen. In dieser Arbeit wird eine Methode präsentiert, die eine Implementierung von neuen adaptiven Scan-Trajektorien an einem C-Bogen-System erlaubt. Am Beispiel einer Klasse von Scan-Trajektorien, der zirkulären Tomosynthese (ZT), wurde die Realisierbarkeit der Methode demonstriert. Streustrahlenmessungen ergaben, dass die ZT eine vorteilhaftere Streustrahlenverteilung als die klassischen 3D-Trajektorien aufweist. In kritischen Körperpartien wie oberer Torso und Gesicht, wurde eine geringere relative Dosis von 75% und 46% (ZT) als bei klassischen Trajektorien (100% und 63%) gemessen. Die Scan-Trajektorien wurden mit einer Kalibrierung kombiniert, die auch eine retrospektive Kalibrierung an beliebigen Positionen im Interventionsraum erlaubt. In Streßtests konnten die Positionen von Metallkugeln eines Evaluierungsphantoms mit einer mittleren Genauigkeit von (0,01 ± 0,08) mm und einer mittleren Radiusabweichung von (0,13 ± 0,07) mm bestimmt werden. Bei einer Voxelgröße von 0,48 mm sind die Abweichungen kleiner als die Messgenauigkeit des bildgebenden Systems. Die untersuchten Trajektorien verwenden nur ein Viertel bis ein Fünftel der Projektionen herkömmlicher 3D-Trajektorien. Die Unterabtastung des Objekts und die Dosiseinsparung verursachen Artefakte in den Bilddaten. Mithilfe eines vorwissenbasierten Ansatzes konnten diese Artefakte minimiert und die Bildqualität auf die eines konventionellen 3D-Datensatzes verbessert werden. Die Ergebnisse dieser Arbeit zeigen, dass adaptive Scan-Trajektorien die interventionelle Röntgenbildgebung um einen neuen Bildgebungsmodus erweitern können, der gegenüber derzeitigen Bildgebungsmodi relevante Bildinformationen bei reduzierter Dosis akquiriert

Spatial Resolution Analysis of a Variable Resolution X-ray Cone-beam Computed Tomography System

A new cone-beam computed tomography (CBCT) system is designed and implemented that can adaptively provide high resolution CT images for objects of different sizes. The new system, called Variable Resolution X-ray Cone-beam CT (VRX-CBCT) uses a CsI-based amorphous silicon flat panel detector (FPD) that can tilt about its horizontal (u) axis and vertical (v) axis independently. The detector angulation improves the spatial resolution of the CT images by changing the effective size of each detector cell. Two components of spatial resolution of the system, namely the transverse and axial modulation transfer functions (MTF), are analyzed in three different situations: (1) when the FPD is tilted only about its vertical axis (v), (2) when the FPD is tilted only about its horizontal axis (u), and (3) when the FPD is tilted isotropically about both its vertical and horizontal axes. Custom calibration and MTF phantoms were designed and used to calibrate and measure the spatial resolution of the system for each case described above. A new 3D reconstruction algorithm was developed and tested for the VRX-CBCT system, which combined with a novel 3D reconstruction algorithm, has improved the overall resolution of the system compared to an FDK-based algorithm

STATIONARY DIGITAL TOMOSYNTHESIS: IMPLEMENTATION, CHARACTERIZATION, AND IMAGE PROCESSING TECHNIQUES

The use of carbon nanotube cathodes for x-ray generation was pioneered and perfected by our team in the Applied Nanotechnology Laboratory at the University of North Carolina at Chapel Hill. Over the past decade, carbon nanotube (CNT) field emission x-ray source technology has matured and translated into multiple pre-clinical and clinical devices. One of the most prominent implementations of CNT x-ray technology is a limited angle tomography method called tomosynthesis, which is rapidly emerging in clinical radiography. The purpose of this project is two-fold, to develop and characterize to the latest iteration, stationary intraoral tomosynthesis, and develop a low-dose, effective scatter reduction technique for breast and chest tomosynthesis. The first portion of this project was to develop and evaluate a new quasi-3D imaging modality for dental imaging. My work consists of experiments which dictated the design parameters and subsequent system evaluation of the dedicated s-IOT clinical prototype system currently installed in the UNC Department of Oral and Maxillofacial Radiology clinic in the School of Dentistry. Experiments were performed in our lab to determine optimal source array geometry and system configuration. The system was fabricated by our commercial partner then housed in our research lab where I performed initial characterization and assisted with software development. After installation in the SOD, I performed additional system characterization, including source output validation, dosimetry, and quantification of resolution. The system components and software were refined through a rapid feedback loop with the engineers involved. Four pre-clinical imaging studies have been performed in collaboration with several dentists using phantoms, extracted teeth, and cadaveric dentition. I have generated an operating manual and trained four dental radiologists in the use of the s-IOT device. The system has now been vetted and is ready for patient use. The second portion of this project consists of hardware development and implementation of an image processing technique for scatter correction. The primary sampling scatter correction (PSSC) is a beam pass technique to measure the primary transmission through the patient and calculate the scatter profile for subtraction. Though developed for breast and chest tomosynthesis, utilization in mammography and chest radiography are also demonstrated in this project. This dissertation is composed of five chapters. Chapters one and two provide the basics of x-ray generation and a brief history of the evolution of carbon nanotube x-ray source technology in our lab at UNC. Chapter three focuses on stationary intraoral tomosynthesis. The first section provides background information on dental radiology and project motivation. Sections 3.2 and 3.3 detail my work in benchtop feasibility and optimization studies, as well as characterization and evaluation of the clinical prototype. Chapter four introduces scatter in imaging, providing motivation for my work on primary sampling scatter correction (PSSC) image processing method, detailed in chapter five.Doctor of Philosoph

Robotic Ultrasound Tomography and Collaborative Control

Ultrasound computed tomography (USCT) offers quantitative anatomical tissue characterization for cancer detection, and has shown similar diagnostic power to MRI on ex vivo prostate tissue. While most USCT research and commercial development has focused on submerging target anatomy in a transducer-lined cylindrical water-tank, this approach is not practical for imaging deep anatomy like the prostate and an alternative acquisition system using aligned abdominal and endolumenal ultrasound probes is required. This work outlines a clinical workflow, calibration scheme, and motion framework for an innovative dual-robotic USCT acquisition system specific to in vivo prostate imaging – one arm wielding a linear abdominal probe, the other wielding a linear transrectal ultrasound (TRUS) probe. After a three-way calibration, the robotic system works to autonomously keep the abdominal probe collinear with the physician-rotated TRUS probe using a hybrid force-position convex contour tracking scheme, while impedance control enforces its gentle contact with the patient’s pubic region for capturing the transmission ultrasound slices needed for limited-angle tomographic reconstruction. TRUS rotation was induced by joystick control for precision during testing, however collaborative control via admittance control of hand forces presents a useful workflow option to the physician. An improved robot admittance control algorithm for transparent collaborative control utilizing Kalman filtering was developed and verified to smooth robot hand guidance. Such an improvement additionally has important implications for generally alleviating ultrasonographer musculoskeletal strain through cooperatively controlled robots. The ultimate dual-robotic USCT system proved repeatable and sufficiently accurate for tomography based on pelvic phantom testing. Future steps in system verification and validation are discussed, as is incorporation into feasibility studies to test the potential and utility of the system for future prostate malignancy diagnosis and staging in vivo

Development and Validation of Mechatronic Systems for Image-Guided Needle Interventions and Point-of-Care Breast Cancer Screening with Ultrasound (2D and 3D) and Positron Emission Mammography

The successful intervention of breast cancer relies on effective early detection and definitive diagnosis. While conventional screening mammography has substantially reduced breast cancer-related mortalities, substantial challenges persist in women with dense breasts. Additionally, complex interrelated risk factors and healthcare disparities contribute to breast cancer-related inequities, which restrict accessibility, impose cost constraints, and reduce inclusivity to high-quality healthcare. These limitations predominantly stem from the inadequate sensitivity and clinical utility of currently available approaches in increased-risk populations, including those with dense breasts, underserved and vulnerable populations. This PhD dissertation aims to describe the development and validation of alternative, cost-effective, robust, and high-resolution systems for point-of-care (POC) breast cancer screening and image-guided needle interventions. Specifically, 2D and 3D ultrasound (US) and positron emission mammography (PEM) were employed to improve detection, independent of breast density, in conjunction with mechatronic and automated approaches for accurate image acquisition and precise interventional workflow. First, a mechatronic guidance system for US-guided biopsy under high-resolution PEM localization was developed to improve spatial sampling of early-stage breast cancers. Validation and phantom studies showed accurate needle positioning and 3D spatial sampling under simulated PEM localization. Subsequently, a whole-breast spatially-tracked 3DUS system for point-of-care screening was developed, optimized, and validated within a clinically-relevant workspace and healthy volunteer studies. To improve robust image acquisition and adaptability to diverse patient populations, an alternative, cost-effective, portable, and patient-dedicated 3D automated breast (AB) US system for point-of-care screening was developed. Validation showed accurate geometric reconstruction, feasible clinical workflow, and proof-of-concept utility across healthy volunteers and acquisition conditions. Lastly, an orthogonal acquisition and 3D complementary breast (CB) US generation approach were described and experimentally validated to improve spatial resolution uniformity by recovering poor out-of-plane resolution. These systems developed and described throughout this dissertation show promise as alternative, cost-effective, robust, and high-resolution approaches for improving early detection and definitive diagnosis. Consequently, these contributions may advance breast cancer-related equities and improve outcomes in increased-risk populations and limited-resource settings

Geometrical Calibration and Filter Optimization for Cone-Beam Computed Tomography

This thesis will discuss the requirements of a software library for tomography and will derive a framework which can be used to realize various applications in cone-beam computed tomography (CBCT). The presented framework is self-contained and is realized using the MATLAB environment in combination with native low-level technologies (C/C++ and CUDA) to improve its computational performance, while providing accessibility and extendability through to use of a scripting language environment. On top of this framework, the realization of Katsevich’s algorithm on multicore hardware will be explained and the resulting implementation will be compared to the Feldkamp, Davis and Kress (FDK) algorithm. It will also be shown that this helical reconstruction method has the potential to reduce the measurement uncertainty. However, misalignment artifacts appear more severe in the helical reconstructions from real data than in the circular ones. Especially for helical CBCT (H-CBCT), this fact suggests that a precise calibration of the computed tomography (CT) system is inevitable. As a consequence, a self-calibration method will be designed that is able to estimate the misalignment parameters from the cone-beam projection data without the need of any additional measurements. The presented method employs a multi-resolution 2D-3D registration technique and a novel volume update scheme in combination with a stochastic reprojection strategy to achieve a reasonable runtime performance. The presented results will show that this method reaches sub-voxel accuracy and can compete with current state-of-the-art online- and offline-calibration approaches. Additionally, for the construction of filters in the area of limited-angle tomography a general scheme which uses the Approximate Inverse (AI) to compute an optimized set of 2D angle-dependent projection filters will be derived. Optimal sets of filters are then precomputed for two angular range setups and will be reused to perform various evaluations on multiple datasets with a filtered backprojection (FBP)-type method. This approach will be compared to the standard FDK algorithm and to the simultaneous iterative reconstruction technique (SIRT). The results of the study show that the introduced filter optimization produces results comparable to those of SIRT with respect to the reduction of reconstruction artifacts, whereby its runtime is comparable to that of the FDK algorithm