MR Shuffling: Accelerated Single-Scan Multi-Contrast Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is an attractive medical imaging modality as it is non-invasive and does not involve ionizing radiation. Routine clinical MRI exams obtain MR images corresponding to different soft tissue contrast by performing multiple scans. When two-dimensional (2D) imaging is used, these scans are often repeated in other scanning planes. As a result, the number of scans comprising an MRI exam leads to prohibitively long exam times as compared to other medical imaging modalities such as computed tomography. Many approaches have been designed to accelerate the MRI acquisition while maintaining diagnostic quality.One approach is to collect multiple measurements while the MRI signal is evolving due to relaxation. This enables a reduction in scan time, as fewer acquisition windows are needed to collect the same number of measurements. However, when the temporal aspect of the acquisition is left unmodeled, artifacts are likely to appear in the reconstruction. Most often, these artifacts manifest as image blurring. The effect depends on the acquisition parameters as well as the tissue relaxation itself, resulting in spatially varying blurring. The severity of the artifacts is directly related to the level of acceleration, and thus presents a tradeoff with scan time. The effect is amplified when imaging in three dimensions, severely limiting scan efficiency. Volumetric variants would be used if not for the blurring, as they are able to reconstruct images at isotropic resolution and support mutli-planar reformatting.Another established acceleration technique, called parallel imaging, takes advantage of spatially sensitive receive coil arrays to collect multiple MRI measurements in parallel. Thus, the acquisition is shortened, and the reconstruction uses the spatial sensitivity information to recover the image. More recently, methods have been developed that leverage image structure such as sparsity and low rank to reduce the required number of samples for a well-posed reconstruction. Compressed sensing and its low rank extensions use these concepts to acquire incoherent measurements below the Nyquist rate. These techniques are especially suited to MRI, as incoherent measurements can be easily achieved through pseudo-random under-sampling. As the mechanisms behind parallel imaging and compressed sensing are fundamentally different, they can be combined to achieve even higher acceleration.This dissertation proposes accelerated MRI acquisition and reconstruction techniques that account for the temporal dynamics of the MR signal. The methods build off of parallel imaging and compressed sensing to reduce scan time and flexibly model the temporal relaxation behavior. By randomly shuffling the sampling in the acquisition stage and imposing low rank constraints in the reconstruction stage, intrinsic physical parameters are modeled and their dynamics are recovered as multiple images of varying tissue contrast. Additionally, blurring artifacts are significantly reduced, as the temporal dynamics are accounted for in the reconstruction.This dissertation first introduces T2 Shuffling, a volumetric technique that reduces blurring and reconstructs multiple T2-weighted image contrasts from a single acquisition. The method is integrated into a clinical hospital environment and evaluated on patients. Next, this dissertation develops a fast and distributed reconstruction for T2 Shuffling that achieves clinically relevant processing time latency. Clinical validation results are shown comparing T2 Shuffling as a single-sequence alternative to conventional pediatric knee MRI. Based off the compelling results, a fast targeted knee MRI using T2 Shuffling is implemented, enabling same-day access to MRI at one-third the cost compared to the conventional exam. To date, over 2,400 T2 Shuffling patient scans have been performed.Continuing the theme of accelerated multi-contrast imaging, this dissertation extends the temporal signal model with T1-T2 Shuffling. Building off of T2 Shuffling, the new method additionally samples multiple points along the saturation recovery curve by varying the repetition time durations during the scan. Since the signal dynamics are governed by both T1 recovery and T2 relaxation, the reconstruction captures information about both intrinsic tissue parameters. As a result, multiple target synthetic contrast images are reconstructed, all from a single scan. Approaches for selecting the sequence parameters are provided, and the method is evaluated on in vivo brain imaging of a volunteer.Altogether, these methods comprise the theme of MR Shuffling, and may open new pathways toward fast clinical MRI

MRI-based radiomics: Quantifying the stability and reproducibility of tumour heterogeneity in vivo and in a 3D printed phantom

Magnetic resonance imaging (MRI) is a key component in the oncology workflow. Radiomics analysis is a new approach that uses standard of care (SOC) magnetic resonance (MR) images to non-invasively characterise tumour heterogeneity. For radiomics to be reliable, the imaging features measured must be stable and reproducible. This thesis aims to quantify the stability and reproducibility of MRI-based radiomics in vivo and in a 3D printed phantom. Chapter 4 explores the feasibility of constructing a 3D printed phantom using an MRI visible material (‘red resin’). The study shows that the material used to construct an anthropomorphic skull phantom mimicked human cortical bone with a T2* of 411 ± 19 µs. The phantom material provided sufficient signal for tissue segmentation however was only visible with an ultrashort echo time sequence, not commonly used in SOC imaging. Chapter 5 investigates a high temperature resin (‘white resin’) where a texture object was developed for analysis. The ‘white resin’ was visible using SOC sequences. The interscanner repeatability measurements of the texture phantom demonstrated high reproducibility with 76% of texture features having an ICC > 0.9. In chapter 6, further texture and shape objects were developed and employed in a multi-centre study assessing inter and intrascanner variation of MRI-based radiomics. The phantom was stable over a period of 12 months, with a T1 and T2 of 150.7 ± 6.7 ms and 56.1 ± 3.9 ms, respectively. The study also found that histogram features were more stable (ICC > 0.8 for 67%) compared to texture (ICC > 0.8 for 58%) and shape texture (ICC > 0.8 for 0%) across the 8 scanners. In chapter 7, phantom measurements found that radiomics features were more sensitive to changes of image resolution and noise. The in vivo test-retest component of chapter 7 detected many unstable features not suitable for use in a radiomics prognostic model. In chapter 8, of the 83 features computed only 19 features had significant changes between the baseline, mid and post radiation treatment and may be informative to assess rectal cancer treatment response. When considering using radiomics analysis for SOC MRI scans, caution must be taken to ensure imaging protocols, imaging equipment including scanners and coils are consistent to improve intra and inter-institutional feature robustness. This can be achieved with regular quality assurance (QA) of imaging protocols using a suitable phantom and appropriate feature selection using phantom and in vivo datasets

Atherosclerotic Plaque Characterization in Humans with Acoustic Radiation Force Impulse (ARFI) Imaging

Cardio- and cerebrovascular diseases (CVD) are among the leading causes of death and disability in the United States. A vast majority of heart attacks and strokes are linked to atherosclerosis; a condition characterized by inflammation and plaque accumulation in the arterial wall that can rupture and propagate an acute thrombotic event. Identification of plaques that are vulnerable to rupture is paramount to the prevention of heart attacks and strokes, but a noninvasive plaque characterization imaging technology that is cost-effective, safe, and accurate has remained elusive. The goal of this dissertation is to evaluate whether acoustic radiation force impulse (ARFI) imaging, an ultrasound-based elastography technique, can noninvasively characterize plaque components and identify features that have been shown to correlate with plaque vulnerability. Data are presented from preclinical studies, done in a porcine model of atherosclerosis, and clinical studies, performed in patients undergoing carotid endarterectomy (CEA), to demonstrate the sensitivity and specificity of ARFI for various plaque components. Additionally, the ability of ARFI to measure fibrous cap thickness is assessed with finite element method (FEM) modelling, and the limits of ARFI fibrous cap resolution are analyzed. Lastly, advanced ARFI-based plaque imaging methods are explored, including intravascular ARFI for coronary plaque characterization. Overall, these studies demonstrate that ARFI can delineate features consistent with vulnerable plaque in a clinical imaging context and suggest that ARFI has the potential to improve the current state of the art in atherosclerosis diagnostics.Doctor of Philosoph

Quantitative methods in high field MRI

The increased signal-to-noise ratio available at high magnetic field makes possible the acquisition of clinically useful MR images either at higher resolution or for quantitative methods. The work in this thesis is focused on the development of quantitative imaging methods used to overcome difficulties due to high field MRI systems (> 3T). The protocols developed and presented here have been tested on various studies aiming at discriminating tissues based on their NMR properties. The quantities of interest in this thesis are the longitudinal relaxation time T1, as well as the magnetization transfer process, particularly the chemical exchange phenomenon involving amide protons which is highlighted particularly well at 7T under specific conditions. Both quantities (T1 and amide proton transfer) are related to the underlying structure of the tissues in-vivo, especially inside the white matter of the brain. While a standard weighted image at high resolution can provide indices of the extent of the pathology, a robust measure of the NMR properties of brain tissues can detect earlier abnormalities. A method based on a 3D Turbo FLASH readout and measuring reliably the T1 in-vivo for clinical studies at 7T is first presented. The other major part of this thesis presents magnetization transfer and chemical exchange phenomena. First a quantitative method is investigated at 7T, leading to a new model for exchange as well as contrast optimization possibility for imaging. Results using those methods are presented and applied in clinical setting, the main focus being to image reliably the brain of both healthy subjects and Multiple Sclerosis patients to look at myelin structures