Compressed Sensing Accelerated Magnetic Resonance Spectroscopic Imaging

abstract: Magnetic resonance spectroscopic imaging (MRSI) is a valuable technique for assessing the in vivo spatial profiles of metabolites like N-acetylaspartate (NAA), creatine, choline, and lactate. Changes in metabolite concentrations can help identify tissue heterogeneity, providing prognostic and diagnostic information to the clinician. The increased uptake of glucose by solid tumors as compared to normal tissues and its conversion to lactate can be exploited for tumor diagnostics, anti-cancer therapy, and in the detection of metastasis. Lactate levels in cancer cells are suggestive of altered metabolism, tumor recurrence, and poor outcome. A dedicated technique like MRSI could contribute to an improved assessment of metabolic abnormalities in the clinical setting, and introduce the possibility of employing non-invasive lactate imaging as a powerful prognostic marker. However, the long acquisition time in MRSI is a deterrent to its inclusion in clinical protocols due to associated costs, patient discomfort (especially in pediatric patients under anesthesia), and higher susceptibility to motion artifacts. Acceleration strategies like compressed sensing (CS) permit faithful reconstructions even when the k-space is undersampled well below the Nyquist limit. CS is apt for MRSI as spectroscopic data are inherently sparse in multiple dimensions of space and frequency in an appropriate transform domain, for e.g. the wavelet domain. The objective of this research was three-fold: firstly on the preclinical front, to prospectively speed-up spectrally-edited MRSI using CS for rapid mapping of lactate and capture associated changes in response to therapy. Secondly, to retrospectively evaluate CS-MRSI in pediatric patients scanned for various brain-related concerns. Thirdly, to implement prospective CS-MRSI acquisitions on a clinical magnetic resonance imaging (MRI) scanner for fast spectroscopic imaging studies. Both phantom and in vivo results demonstrated a reduction in the scan time by up to 80%, with the accelerated CS-MRSI reconstructions maintaining high spectral fidelity and statistically insignificant errors as compared to the fully sampled reference dataset. Optimization of CS parameters involved identifying an optimal sampling mask for CS-MRSI at each acceleration factor. It is envisioned that time-efficient MRSI realized with optimized CS acceleration would facilitate the clinical acceptance of routine MRSI exams for a quantitative mapping of important biomarkers.Dissertation/ThesisDoctoral Dissertation Bioengineering 201

Accelerated Imaging Techniques for Chemical Shift Magnetic Resonance Imaging

Chemical shift imaging is a method for the separation two or more chemical species. The cost of chemical shift encoding is increased acquisition time as multiple acquisitions are acquired at different echo times. Image acceleration techniques, typically parallel imaging, are often used to improve the spatial coverage and resolution. This thesis describes a new technique for estimating the signal to noise ratio for parallel imaging reconstructions and proposes new image reconstructions for accelerated chemical shift imaging using compressed sensing and/or parallel imaging for two applications: water-fat separation and metabolic imaging of hyperpolarized [1-13C] pyruvate. Spatially varying noise in parallel imaging reconstructions makes measurements of the signal to noise ratio, a commonly used metric for image for image quality, difficult. Existing approaches have limitations such as they are not applicable to all reconstructions, require significant computation time, or rely on repeated image acquisitions. A SNR estimation technique is proposed that does not exhibit these limitations. Water-fat imaging of highly undersampled datasets from the liver, calf, knee, and abdominal cavity are demonstrated using a customized IDEAL-SPGR pulse sequence and an integrated compressed sensing, parallel imaging, water-fat reconstruction. This method is shown to offer comparable image quality relative to fully sampled reference images for a range of acceleration factors. At high acceleration factors, this technique is shown to offer improved image quality when compared to the current standard of parallel imaging. Accelerated chemical shift imaging was demonstrated for metabolic of hyperpolarized [1-13C] pyruvate. Pyruvate, lactate, alanine, and bicarbonate images were reconstructed from undersampled datasets. Phantoms were used to validate this technique while retrospectively and prospectively accelerated 3D in vivo datasets were used to demonstrate. Alternatively, acceleration was also achieved through the use of a high performance magnetic field gradient set. This thesis addresses the inherently slow acquisition times of chemical shift imaging by examining the role compressed sensing and parallel imaging can be play in chemical shift imaging. An approach to SNR assessment for parallel imaging reconstruction is proposed and approaches to accelerated chemical shift imaging are described for applications in water-fat imaging and metabolic imaging of hyperpolarized [1-13C] pyruvate

Single shot three-dimensional pulse sequence for hyperpolarized 13 C MRI.

PURPOSE: Metabolic imaging with hyperpolarized 13 C-labeled cell substrates is a promising technique for imaging tissue metabolism in vivo. However, the transient nature of the hyperpolarization, and its depletion following excitation, limits the imaging time and the number of excitation pulses that can be used. We describe here a single-shot three-dimensional (3D) imaging sequence and demonstrate its capability to generate 13 C MR images in tumor-bearing mice injected with hyperpolarized [1-13 C]pyruvate. METHODS: The pulse sequence acquires a stack-of-spirals at two spin echoes after a single excitation pulse and encodes the kz-dimension in an interleaved manner to enhance robustness to B0 inhomogeneity. Spectral-spatial pulses are used to acquire dynamic 3D images from selected hyperpolarized 13 C-labeled metabolites. RESULTS: A nominal spatial/temporal resolution of 1.25 × 1.25 × 2.5 mm3  × 2 s was achieved in tumor images of hyperpolarized [1-13 C]pyruvate and [1-13 C]lactate acquired in vivo. Higher resolution in the z-direction, with a different k-space trajectory, was demonstrated in measurements on a thermally polarized [1-13 C]lactate phantom. CONCLUSION: The pulse sequence is capable of imaging hyperpolarized 13 C-labeled substrates at relatively high spatial and temporal resolutions and is robust to moderate system imperfections. Magn Reson Med 77:740-752, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.The work was supported by a Cancer Research UK Programme grant (17242) to KMB and by the CRUK-EPSRC Imaging Centre in Cambridge and Manchester (16465). JW was also supported, in part, by a grant from the Danish Strategic Research Council (LIFE-DNP: Hyperpolarized magnetic resonance for in vivo quantification of lipid, sugar and amino acid metabolism in lifestyle related diseases).This is the final version of the article. It first appeared from Wiley via https://doi.org/10.1002/mrm.2616

Development of pulse sequences for hyperpolarized 13C magnetic resonance spectroscopic imaging of tumour metabolism

Metabolic imaging with hyperpolarized 13C-labeled cell substrates is a promising technique for imaging tissue metabolism in vivo. However, the transient nature of the hyperpolarization - and its depletion following excitation - limits the imaging time and the number of excitation pulses that can be used. A single-shot 3D imaging sequence has been developed and it is shown in this thesis to generate 13C MR images in tumour-bearing mice injected with hyperpolarized [1-13C]pyruvate. The pulse sequence acquires a stack-of-spirals at two spin echoes after a single excitation pulse and encodes the kz-dimension in an interleaved manner to enhance robustness to B0 inhomogeneity. Spectral-spatial pulses are used to acquire dynamic 3D images from selected hyperpolarized 13C-labeled metabolites. A nominal spatial/temporal resolution of 1.25 x 1.25 x 2.5 $mm^3$ x 2 s was achieved in tumour images of hyperpolarized [1-13C]pyruvate and [1-13C]lactate acquired in vivo. An advanced sequence is also described in this thesis in a later study to acquire higher resolution images with isotropic voxels (1.25 x 1.25 x 1.25 $mm^3$) at no cost of temporal resolution. EPI is a sequence widely used in hyperpolarized 13C MRI because images can be acquired rapidly with limited RF exposure. However, EPI suffers from Nyquist ghosting, which is normally corrected for by acquiring a reference scan. In this thesis a workflow for hyperpolarized 13C EPI is proposed that requires no reference scan and, therefore, that does not sacrifice a time point in the dynamic monitoring of tissue metabolism. To date, most of the hyperpolarized MRI on metabolism are based on 13C imaging, while 1H is a better imaging target for its 4 times higher gyromagnetic ratio and hence 16 times signal. In this thesis the world’s first dynamic 1H imaging in vivo of hyperpolarized [1-13C]lactate is presented, via a novel double-dual-spin-echo INEPT sequence that transfers the hyperpolarization from 13C to 1H, achieving a spatial resolution of 1.25 x 1.25 $mm^2$

Reduction of acquisition time using partition of the signal decay in spectroscopic imaging technique (RAPID-SI)

To overcome long acquisition times of Chemical Shift Imaging (CSI), a new Magnetic Resonance Spectroscopic Imaging (MRSI) technique called Reduction of Acquisition time by Partition of the signal Decay in Spectroscopic Imaging (RAPID-SI) using blipped phase encoding gradients inserted during signal acquisition was developed. To validate the results using RAPID-SI and to demonstrate its usefulness in terms of acquisition time and data quantification; simulations, phantom and in vivo studies were conducted, and the results were compared to standard CSI. The method was based upon the partition of a magnetic resonance spectroscopy (MRS) signal into sequential sub-signals encoded using blipped phase encoding gradients inserted during signal acquisition at a constant time interval. The RAPID-SI technique was implemented on a clinical 3 T Siemens scanner to demonstrate its clinical utility. Acceleration of data collection was performed by inserting R (R= acceleration factor) blipped gradients along a given spatial direction during data acquisition. Compared to CSI, RAPID-SI reduced acquisition time by the acceleration factor R. For example, a 2D 16x16 data set acquired in about 17 min with CSI, was reduced to approximately 2 min with the RAPID-SI (R= 8). While the SNR of the acquired RAPID-SI signal was lower compared to CSI by approximately the factor root R, it can be improved after data pre-processing and reconstruction. Compared to CSI, RAPID-SI reduces acquisition time, while preserving metabolites information. Furthermore, the method is flexible and could be combined with other acceleration methods such as Parallel Imaging

Emerging Techniques in Breast MRI

As indicated throughout this chapter, there is a constant effort to move to more sensitive, specific, and quantitative methods for characterizing breast tissue via magnetic resonance imaging (MRI). In the present chapter, we focus on six emerging techniques that seek to quantitatively interrogate the physiological and biochemical properties of the breast. At the physiological scale, we present an overview of ultrafast dynamic contrast-enhanced MRI and magnetic resonance elastography which provide remarkable insights into the vascular and mechanical properties of tissue, respectively. Moving to the biochemical scale, magnetization transfer, chemical exchange saturation transfer, and spectroscopy (both “conventional” and hyperpolarized) methods all provide unique, noninvasive, insights into tumor metabolism. Given the breadth and depth of information that can be obtained in a single MRI session, methods of data synthesis and interpretation must also be developed. Thus, we conclude the chapter with an introduction to two very different, though complementary, methods of data analysis: (1) radiomics and habitat imaging, and (2) mechanism-based mathematical modeling