Parameterisation of M.R. system performance : towards optimised measures of image quality

This thesis proposes optimal measures for the inter-system comparison of signal properties when assessing the imaging performance of Magnetic Resonance Imaging (MRI) scanners. MRI has become a popular clinical imaging modality and there are many manufacturers producing systems of various quality. It is essential, therefore, that the performance of each MRI system can be measured and compared. Five criteria have been identified as being of prime importance, namely, the signal-to-noise ratio (SNR), signal non-uniformity, resolution, system induced ghost artefacts and patient induced ghost artefacts. The research concentrated directly on the derivation of performance parameters from test object images. For each criterion a specific algorithm has been developed to obtain optimal parameters. For SNR, a method of evaluation has been derived that utilises the Wiener spectrum to distinguish between random and non-random noise in the MR image. The assessment of signal non-uniformity has been improved by applying statistical parameters. The Modulation Transfer Function has been used in the evaluation and comparison of resolution of MRI systems. Crosscorrelation techniques have enabled the complete automatic location and analysis of ghost artefacts in MR test object images. An autocorrelation technique has been created to compare the degree of respiratory motion artefact present in an MR image. All the techniques, wherever possible, have been optimised for speed and automated to eliminate operator dependency. The strength of this thesis lies in the fact that the data used is not simulated, it is actual data gathered with the full support of each manufacturer in the country of origin. This enables truly applicable comparison parameters to be derived. This is a prominent deficiency for workers who mathematically create images or who work with only one system. The success of the five parameterisations is demonstrated by performing an inter-system comparison of ten commercially available scanners.Open Acces

Multi-Isotope Multi-Pinhole SPECT Bildgebung in kleinen Labortieren: Experimentelle Messungen und Monte Carlo Simulationen

Single photon emission computed tomography (SPECT) in small laboratory animals has become an integral part of translational medicine. It enables non-invasive validation of drug targeting, safety and efficacy in living organisms, which is progressively gaining importance in pharmaceutical industry. The increasing demand for efficiency in pharmaceutical research could be addressed by novel multitracer study designs. Multi-isotope multi-pinhole sampling allows validation of multiple tracers in a single experiment and consolidation of consecutive research trials. Due to physical and technical limitations, however, image quality and quantification can be substantially reduced. Advanced corrective procedures are required to establish multi-isotope multi-pinhole SPECT as a reliable and quantitative imaging technique for widespread use. For this purpose, the present work aimed to investigate the technical capabilities and physical limitations of multi-isotope multi-pinhole SPECT imaging in small laboratory animals. Based on experimental measurements and Monte Carlo simulations, specific error sources have been identified and procedures for quantitative image correction have been developed. A Monte Carlo simulation model of a state-of-the art SPECT/CT system has been established to provide a generalized framework for in-silico optimization of imaging hardware, acquisition protocols and reconstruction algorithms. The findings of this work can be used to improve image quality and quantification of SPECT in-vivo data for multi-isotope applications. They guide through the laborious process of multi-isotope protocol optimization and support the 3R welfare initiative that aims to replace, reduce and refine animal experimentation.Die Einzelphotonen-Emissionscomputertomographie (SPECT) in kleinen Labortieren hat sich als wichtiger Bestandteil der translationalen Medizin etabliert. Sie ermöglicht die nicht-invasive Validierung der Zielgenauigkeit, Wirksamkeit und Sicherheit von Wirkstoffen in lebenden Organismen und gewinnt zunehmend an Bedeutung in der pharmazeutischen Industrie. Die Forderung nach mehr Effizienz in der pharmazeutischen Forschung könnte durch neuartige Multitracer-Studien adressiert werden. Die Multi-Isotopen Akquisition mit Multi-Pinhole Kollimatoren ermöglicht die Validierung mehrerer Tracer in einem einzelnen Experiment und die Konsolidierung konsekutiver Bildgebungsstudien. Aufgrund physikalischer und technischer Limitationen ist die Bildqualität und Quantifizierbarkeit bei diesem Verfahren jedoch häufig reduziert. Um die Multi-Isotopen SPECT als zuverlässige und quantitative Bildgebungsmethode für den breiten Einsatz zu etablieren sind komplexe Korrekturverfahren erforderlich. Ziel der vorliegenden Arbeit war daher, die technischen Möglichkeiten und physikalischen Limitationen der Multi-Isotopen SPECT-Bildgebung in kleinen Labortieren systematisch zu untersuchen. Mithilfe von experimentellen Messungen und Monte Carlo Simulationen wurden spezifische Fehlerquellen identifiziert und Verfahren zur quantitativen Bildkorrektur entwickelt. Zudem wurde das Monte-Carlo Modell eines neuartigen SPECT/CT-Systems etabliert, um eine Plattform für die in-silico Optimierung von Bildgebungshardware, Aufnahmeprotokollen und Rekonstruktionsalgorithmen zu schaffen. Die Ergebnisse dieser Arbeit können die Bildqualität und Quantifizierbarkeit von SPECT in-vivo Daten für Multi-Isotopen Anwendungen verbessern. Sie führen beispielhaft durch den Prozess der Multi-Isotopen Protokolloptimierung und unterstützen die 3R-Initiative mit dem Ziel, experimentelle Tierversuche zu vermeiden (Replace), zu vermindern (Reduce) und zu verbessern (Refine)

Methods for Improving MRI-Based Conductivity Mapping

The electrical properties - permittivity and conductivity - of a material describe how electromagnetic waves behave in that material. Electrical properties are frequency-dependent parameters and, for a liquid sample, are measured with a dielectric probe and a network analyzer. This measurement technique is not feasible in vivo, but methods have been developed to make these measurements using magnetic resonance imaging (MRI). This work focuses on measuring conductivity, or the ability to conduct electric current. Mapping the electrical properties within the human body can provide important information for MRI safety and diagnostic applications. First, the specific absorption rate (SAR) in an MRI scan is proportional to conductivity, and limited to minimize the risk of heating in a subject. Knowledge of subject-specific conductivity maps could lead to better, subject-specific SAR estimation. Second, several small studies in recent years have shown that conductivity is elevated in malignant tumors as compared to healthy tissue. There are open research questions regarding the correlation between conductivity and other diagnostic metrics. Both of these applications benefit from accurate conductivity maps. In this work we describe three different methods for improving the accuracy of conductivity maps. The first is a novel regularized, model-based approach which we refer to as the Inverse Laplacian method. The Inverse Laplacian method resulted in lower reconstruction bias and error due to noise in simulations than the conventional filtering method. The Inverse Laplacian method also produced conductivity maps closer to the measured values in a phantom and with reduced noise in the human brain, as compared to the filtering method. The second is a method for combining multi-coil MRI data for conductivity mapping, because the use of multi-coil receivers can drastically improve the SNR in conductivity maps. The noise in the combined phase data using the proposed method was slightly elevated as compared to the optimal combination method, but the conductivity uniformity in a uniform gel phantom was greater than that of the optimal combination method. Furthermore, by visual inspection, the human brain conductivity calculated from data combined using the proposed method had minimal bias and noise amplification. Finally, we present a method for mapping conductivity tensors, as opposed to scalar values, which provides an additional layer of information to conductivity maps. Our proposed mathematical framework yields accurate tensor quantities provided the object can rotate 90 degrees in any direction. However, restricting the object rotation to mimic the constraints on a human subject yields slightly inaccurate results. We also present a dictionary-based approach to tensor calculations to try to improve the tensor estimates using restricted rotations.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144027/1/kropella_1.pd

Quantitative Analysis of Three-Dimensional Cone-Beam Computed Tomography Using Image Quality Phantoms

In the clinical setting, weight-bearing static 2D radiographic imaging and supine 3D radiographic imaging modalities are used to evaluate radiographic changes such as, joint space narrowing, subchondral sclerosis, and osteophyte formation. These respective imaging modalities cannot distinguish between tissues with similar densities (2D imaging), and do not accurately represent functional joint loading (supine 3D imaging). Recent advances in cone-beam CT (CBCT) have allowed for scanner designs that can obtain weight-bearing 3D volumetric scans. The purpose of this thesis was to analyze, design, and implement advanced imaging techniques to quantify image quality parameters of reconstructed image volumes generated by a commercially-available CBCT scanner, and a novel ceiling-mounted CBCT scanner. In addition, imperfections during rotation of the novel ceiling-mounted CBCT scanner were characterized using a 3D printed calibration object with a modification to the single marker bead method, and prospective geometric calibration matrices

Comparison of reconstruction and acquisition choices for quantitative T2* maps and synthetic contrasts

Aim and scope: A Gradient Echo Plural Contrast Imaging technique (GEPCI) is a post-processing method, which can be used to obtain quantitative T2* values and generate multiple synthetic contrasts from a single acquisition. However, scan duration and image reconstruction from k-space data present challenges in a clinical workflow. This study aimed at optimizing image reconstruction and acquisition duration to facilitate a post-processing method for synthetic image contrast creation in clinical settings. Materials and methods: This study consists of tests using the American College of Radiology (ACR) image quality phantom, two healthy volunteers, four mild traumatic brain injury patients and four small vessel disease patients. The measurements were carried out on a 3.0 T scanner with multiple echo times. Reconstruction from k-space data and DICOM data with two different coil-channel combination modes were investigated. Partial Fourier techniques were tested to optimize the scanning time. Conclusions: Sum of squares coil-channel combination produced artifacts in phase images, but images created with adaptive combination were artifact-free. The voxel-wise median signed difference of T2* between the vendor's adaptive channel combination and k-space reconstruction modes was 2.9 +/- 0.7 ms for white matter and 4.5 +/- 0.6 ms for gray matter. Relative white matter/gray matter contrast of all synthetic images and contrast-to-noise ratio of synthetic T1-weighted images were almost equal between reconstruction modes. Our results indicate that synthetic contrasts can be generated from the vendor's DICOM data with the adaptive combination mode without affecting the quantitative T2* values or white matter/gray matter contrast.Peer reviewe

Characterization and Compensation of Hysteretic Cardiac Respiratory Motion in Myocardial Perfusion Studies Through MRI Investigations

Respiratory motion causes artifacts and blurring of cardiac structures in reconstructed images of SPECT and PET cardiac studies. Hysteresis in respiratory motion causes the organs to move in distinct paths during inspiration and expiration. Current respiratory motion correction methods use a signal generated by tracking the motion of the abdomen during respiration to bin list- mode data as a function of the magnitude of this respiratory signal. They thereby fail to account for hysteretic motion. The goal of this research was to demonstrate the effects of hysteretic respiratory motion and the importance of its correction for different medical imaging techniques particularly SPECT and PET. This study describes a novel approach for detecting and correcting hysteresis in clinical SPECT and PET studies. From the combined use of MRI and a synchronized Visual Tracking System (VTS) in volunteers we developed hysteretic modeling using the Bouc-Wen model with inputs from measurements of both chest and abdomen respiratory motion. With the MRI determined heart motion as the truth in the volunteer studies we determined the Bouc Wen model could match the behavior over a range of hysteretic cycles. The proposed approach was validated through phantom simulations and applied to clinical SPECT studies

Single photon emission computed tomography: performance assessment, development and clinical applications

This is a general investigation of the SPECT imaging process. The primary aim is to determine the manner in which the SPECT studies should be performed in order to maximise the relevant clinical information given the characteristics and limitations of the particular gamma camera imaging system used. Thus the first part of this thesis is concerned with an assessment of the performance characteristics of the SPECT system itself. This involves the measurement of the fundamental planar imaging properties of the camera, their stability with rotation, the ability of the camera to rotate in a perfect circle and the accuracy of the transfer of the information from the camera to the computing system. Following this the performance of the SPECT system as a whole is optimised. This is achieved by examining the fundamental aspects of the SPECT imaging process and by optimising the selection of the parameters chosen for the acquisition and reconstruction of the data. As an aid to this a novel mathematical construct is introduced. By taking the logarithm of the power spectrum of the normalised projection profile data the relationship between the signal power and the noise power in the detected data can be visualised. From a theoretical consideration of the available options the Butterworth filter is chosen for use because it provides the best combination of spatial frequency transfer characteristics and flexibility. The flexibility of the Butterworth filter is an important feature because it means that the form of the actual function used in the reconstruction of a transaxial section can be chosen with regard to the relationship between the signal and the noise in the data. A novel method is developed to match the filter to the projection data. This consists of the construction of a mean angular power spectrum from the set of projection profiles required for the reconstruction of the particular transaxial section in question. From this the spatial frequency at which the the signal becomes dominated by the noise is identified. The value which the Butterworth filter should take at this point can then be determined with regard to the requirements of the particular clinical investigation to be performed. The filter matching procedure can be extended to two dimensions in a practical manner by operating on the projection data after it has been filtered in the y direction. The efficacy of several methods to correct for the effects of scatter, attenuation and camera non-uniformity are also investigated. Having developed the optimised methodology for the acquisition and reconstruction of the SPECT data the results which are obtained are applied in the investigation of some specific clinical problems. The assessment of intractable epilepsy using 99mTc-HMPAO is performed followed by the investigation of ischaemic heart disease using 99mTc-MIBI and finally, the diagnosis of avascular necrosis of the femoral head using 99mTc-MDP is studied. The SPECT studies described in this thesis make a significant contribution to patient management

Quantitative Statistical Methods for Image Quality Assessment

Quantitative measures of image quality and reliability are critical for both qualitative interpretation and quantitative analysis of medical images. While, in theory, it is possible to analyze reconstructed images by means of Monte Carlo simulations using a large number of noise realizations, the associated computational burden makes this approach impractical. Additionally, this approach is less meaningful in clinical scenarios, where multiple noise realizations are generally unavailable. The practical alternative is to compute closed-form analytical expressions for image quality measures. The objective of this paper is to review statistical analysis techniques that enable us to compute two key metrics: resolution (determined from the local impulse response) and covariance. The underlying methods include fixed-point approaches, which compute these metrics at a fixed point (the unique and stable solution) independent of the iterative algorithm employed, and iteration-based approaches, which yield results that are dependent on the algorithm, initialization, and number of iterations. We also explore extensions of some of these methods to a range of special contexts, including dynamic and motion-compensated image reconstruction. While most of the discussed techniques were developed for emission tomography, the general methods are extensible to other imaging modalities as well. In addition to enabling image characterization, these analysis techniques allow us to control and enhance imaging system performance. We review practical applications where performance improvement is achieved by applying these ideas to the contexts of both hardware (optimizing scanner design) and image reconstruction (designing regularization functions that produce uniform resolution or maximize task-specific figures of merit)