Load-Independent And Regional Measures Of Cardiac Function Via Real-Time Mri

LOAD-INDEPENDENT AND REGIONAL MEASURES OF CARDIAC FUNCTION VIA REAL-TIME MRI Francisco Jose Contijoch Robert C Gorman, MD Expansion of infarcted tissue during left ventricular (LV) remodeling after a myocardial infarction is associated with poor long-term prognosis. Several interventions have been developed to limit infarct expansion by modifying the material properties of the infarcted or surrounding borderzone tissue. Measures of myocardial function and material properties can be obtained non-invasively via imaging. However, these measures are sensitive to variations in loading conditions and acquisition of load-independent measures have been limited by surgically invasive procedures and limited spatial resolution. In this dissertation, a real-time magnetic resonance imaging (MRI) technique was validated in clinical patients and instrumented animals, several technical improvements in MRI acquisition and reconstruction were presented for improved imaging resolution, load-independent measures were obtained in animal studies via non-invasive imaging, and regional variations in function were measured in both na�ve and post-infarction animals. Specifically, a golden-angle radial MRI acquisition with non-Cartesian SENSE-based reconstruction with an exposure time less than 95 ms and a frame rate above 89 fps allows for accurate estimation of LV slice volume in clinical patients and instrumented animals. Two technical developments were pursued to improve image quality and spatial resolution. First, the slice volume obtained can be used as a self-navigator signal to generate retrospectively-gated, high-resolution datasets of multiple beat morphologies. Second, cross-correlation of the ECG with previously observed values resulted in accurate interpretation of cardiac phase in patients with arrhythmias and allowed for multi-shot imaging of dynamic scenarios. Synchronizing the measured LV slice volume with an LV pressure signal allowed for pressure-volume loops and corresponding load-independent measures of function to be obtained in instrumented animals. Acquiring LV slice volume at multiple slice locations revealed regional differences in contractile function. Motion-tracking of the myocardium during real-time imaging allowed for differences in contractile function between normal, borderzone, and infarcted myocardium to be measured. Lastly, application of real-time imaging to patients with arrhythmias revealed the variable impact of ectopic beats on global hemodynamic function, depending on frequency and ectopic pattern. This work established the feasibility of obtaining load-independent measures of function via real-time MRI and illustrated regional variations in cardiac function

Investigation of Personalised Post-Reconstruction Positron Range Correction in 68Ga Positron Emission Tomography Imaging

Positron range limits the spatial resolution of Positron Emission Tomography, reducing image quality and accuracy. This thesis investigated factors affecting the magnitude of positron range, developed a personalised approach to range correction, and demonstrated the approach using simulated, phantom and patient data. The Geant4 Application for Emission Tomography software was utilised to model positron range when emitted by radionuclides, namely 18F and 68Ga, in water, bone and lung. The impact of range blurring in lungs was found to be ten times larger than in bone and four times larger than in water or soft tissue, regardless of the positron energy. Range effects occurring with different isotopes (18F and 68Ga) were evaluated across measurement and reconstructed spatial resolutions. It was found that range correction was not necessary when using 18F for voxel sizes larger than 4 mm. In contrast, range correction was required for images generated using 68Ga, particularly within or adjacent to the lung. An iterative, post-reconstruction range correction method was developed which relied only on the measured data. The correction method was validated in both simulation and phantom studies. Image quality and quantification accuracy of corrected images was shown to be superior when imaging with 68Ga. Importantly, the range correction suppressed and controlled image noise at high iteration numbers. Finally, in a patient study, image noise in regions of uniform uptake was significantly increased by ~2% (p<0.05), yet mean standardised uptake values remained unchanged after correction, showing the same uptake for normal radionuclide distributions. The lesion contrast and maximum uptake values were improved by 20% and 45%, respectively with statistical significance (p<0.05). Although these promising results show that the proposed method of range correction can be generalised to reconstructed images regardless of measurement system, acquisition parameters and radionuclides used, further research is warranted to improve the method, particularly with respect to removing or reducing the artefacts which were shown to impacted reader preference

Digital radiography: image acquisition and scattering reduction in x-ray imaging.

Since the discovery of the X-rays in 1895, their use in both medical and industrial imaging applications has gained increasing importance. As a consequence, X-ray imaging devices have evolved and adapted to the needs of individual applications, leading to the appearance of digital image capture devices. Digital technologies introduced the possibility of separating the image acquisition and image processing steps, allowing their individual optimization. This thesis explores both areas, by seeking the improvement in the design of the new family of Varex Imaging CMOS X-ray detectors and by developing a method to reduce the scatter contribution in mammography examinations using image post-processing techniques. During the CMOS X-ray detector product design phase, it is crucial to detect any short- comings that the detector might present. Image characterization techniques are a very efficient method for finding these possible detector features. This first part of the thesis focused in taking these well-known test methods and adapt and optimize them, so they could act as a red flag indicating when something needed to be investigated. The methods chosen in this study have proven to be very effective in finding detector short- comings and the designs have been optimised in accordance with the results obtained. With the aid of the developed imaging characterization tests, new sensor designs have been successfully integrated into a detector, resulting in the recent release into the market of a new family of Varex Imaging CMOS X-ray detectors. The second part of the thesis focuses in X-ray mammography applications, the gold standard technique in breast cancer screening programmes. Scattered radiation degrades the quality of the image and complicates the diagnosis process. Anti-scatter grids, the main scattering reduction technique, are not a perfect solution. This study is concerned with the use of image post-processing to reduce the scatter contribution in the image, by convolving the output image with kernels obtained from simplified Monte Carlo simulations. The proposed semi-empirical approach uses three thickness-dependant symmetric kernels to accurately estimate the environment contribution to the breast, which has been found to be of key importance in the correction of the breast-edge area. When using a single breast thickness-dependant kernel to convolve the image, the post-processing technique can over-estimate the scattering up to 60%. The method presented in this study reduces the uncertainty to a 4-10% range for a 35 to 70 mm breast thickness range, making it a very efficient scatter modelling technique. The method has been successfully proven against full Monte Carlo simulations and mammography phantoms, where it shows clear improvements in terms of the contrast to noise ratio and variance ratio when the performance is compared against images acquired with anti-scatter grids

Techniques for enhancing digital images

The images obtain from either research studies or optical instruments are often corrupted with noise. Image denoising involves the manipulation of image data to produce a visually high quality image. This thesis reviews the existing denoising algorithms and the filtering approaches available for enhancing images and/or data transmission. Spatial-domain and Transform-domain digital image filtering algorithms have been used in the past to suppress different noise models. The different noise models can be either additive or multiplicative. Selection of the denoising algorithm is application dependent. It is necessary to have knowledge about the noise present in the image so as to select the appropriated denoising algorithm. Noise models may include Gaussian noise, Salt and Pepper noise, Speckle noise and Brownian noise. The Wavelet Transform is similar to the Fourier transform with a completely different merit function. The main difference between Wavelet transform and Fourier transform is that, in the Wavelet Transform, Wavelets are localized in both time and frequency. In the standard Fourier Transform, Wavelets are only localized in frequency. Wavelet analysis consists of breaking up the signal into shifted and scales versions of the original (or mother) Wavelet. The Wiener Filter (mean squared estimation error) finds implementations as a LMS filter (least mean squares), RLS filter (recursive least squares), or Kalman filter. Quantitative measure (metrics) of the comparison of the denoising algorithms is provided by calculating the Peak Signal to Noise Ratio (PSNR), the Mean Square Error (MSE) value and the Mean Absolute Error (MAE) evaluation factors. A combination of metrics including the PSNR, MSE, and MAE are often required to clearly assess the model performance