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

Atlas-based automated positioning of outer volume suppression slices in short-TE 3D MR spectroscopic imaging of the human brain

Spatial suppression of peripheral lipid-containing regions in volumetric MR spectroscopic imaging (MRSI) of the human brain requires placing large numbers of outer volume suppression (OVS) slices, which is time consuming, prone to operator error and may introduce subject-dependent variability in volume coverage. We developed a novel, computationally efficient atlas-based approach for automated positioning of up to 16 OVS slices and the MRSI slab. Standardized positions in MNI atlas space were established offline using a recently developed iterative optimization procedure. During the scanning session, positions in subject space were computed using affine transformation of standardized positions in MNI space. This atlas-based approach was characterized offline using MPRAGE data collected in 11 subjects. The method was further validated in 14 subjects on a clinical 3T scanner using 3D short TE (15-20ms) Proton-Echo-Planar-Spectroscopic-Imaging (PEPSI) in upper cerebrum. Comparison of manual and automatic placement using 8 OVS slices demonstrated consistent MRSI volume selection and comparable spectral quality with similar degree of lipid suppression and number of usable voxels. Automated positioning of 16 OVS slices enabled larger volume coverage, while maintaining similar spectral quality and lipid suppression. Atlas-based automatic prescription of short TE MRSI is expected to be advantageous for longitudinal and cross sectional studiesThis work was supported in part by the MIND Research Network (DOE Grant No. DE-FG02-99ER62764) and the University of New Mexico School of Medicine Brain and Behavioral Illness Signature Program.Publicad

Methodological consensus on clinical proton MRS of the brain: Review and recommendations

© 2019 International Society for Magnetic Resonance in Medicine Proton MRS (1H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use

Metabolic Profiling of IDH Mutation and Malignant Progression in Infiltrating Glioma.

Infiltrating low grade gliomas (LGGs) are heterogeneous in their behavior and the strategies used for clinical management are highly variable. A key factor in clinical decision-making is that patients with mutations in the isocitrate dehydrogenase 1 and 2 (IDH1/2) oncogenes are more likely to have a favorable outcome and be sensitive to treatment. Because of their relatively long overall median survival, more aggressive treatments are typically reserved for patients that have undergone malignant progression (MP) to an anaplastic glioma or secondary glioblastoma (GBM). In the current study, ex vivo metabolic profiles of image-guided tissue samples obtained from patients with newly diagnosed and recurrent LGG were investigated using proton high-resolution magic angle spinning spectroscopy (1H HR-MAS). Distinct spectral profiles were observed for lesions with IDH-mutated genotypes, between astrocytoma and oligodendroglioma histologies, as well as for tumors that had undergone MP. Levels of 2-hydroxyglutarate (2HG) were correlated with increased mitotic activity, axonal disruption, vascular neoplasia, and with several brain metabolites including the choline species, glutamate, glutathione, and GABA. The information obtained in this study may be used to develop strategies for in vivo characterization of infiltrative glioma, in order to improve disease stratification and to assist in monitoring response to therapy

Advanced parallel magnetic resonance imaging methods with applications to MR spectroscopic imaging

Parallel magnetic resonance imaging offers a framework for acceleration of conventional MRI encoding using an array of receiver coils with spatially-varying sensitivities. Novel encoding and reconstruction techniques for parallel MRI are investigated in this dissertation. The main goal is to improve the actual reconstruction methods and to develop new approaches for massively parallel MRI systems that take advantage of the higher information content provided by the large number of small receivers. A generalized forward model and inverse reconstruction with regularization for parallel MRI with arbitrary k-space sub-sampling is developed. Regularization methods using the singular value decomposition of the encoding matrix and pre-conditioning of the forward model are proposed to desensitize the solution from data noise and model errors. Variable density k-space sub-sampling is presented to improve the reconstruction with the common uniform sub-sampling. A novel method for massively parallel MRI systems named Superresolution Sensitivity Encoding (SURE-SENSE) is proposed where acceleration is performed by acquiring the low spatial resolution representation of the object being imaged and the stronger sensitivity variation from small receiver coils is used to perform intra-pixel reconstruction. SURE-SENSE compares favorably the performance of standard SENSE reconstruction for low spatial resolution imaging such as spectroscopic imaging. The methods developed in this dissertation are applied to Proton Echo Planar Spectroscopic Imaging (PEPSI) for metabolic imaging in human brain with high spatial and spectral resolution in clinically feasible acquisition times. The contributions presented in this dissertation are expected to provide methods that substantially enhance the utility of parallel MRI for clinical research and to offer a framework for fast MRSI of human brain with high spatial and spectral resolution

Automatic Placement of Outer Volume Suppression Slices in MR Spectroscopic Imaging of the Human Brain

Spatial suppression of peripheral regions (outer volume suppression) is used in MR spectroscopic imaging to reduce contamination from strong lipid and water signals. The manual placement of outer volume suppression slices requires significant operator interaction, which is time consuming and introduces variability in volume coverage. Placing a large number of outer volume saturation bands for volumetric MR spectroscopic imaging studies is particularly challenging and time consuming and becomes unmanageable as the number of suppression bands increases. In this study, a method is presented that automatically segments a high-resolution MR image in order to identify the peripheral lipid-containing regions. This method computes an optimized placement of suppression bands in three dimensions and is based on the maximization of a criterion function. This criterion function maximizes coverage of peripheral lipid-containing areas and minimizes suppression of cortical brain regions and regions outside of the head. Computer simulation demonstrates automatic placement of 16 suppression slices to form a convex hull that covers peripheral lipid-containing regions above the base of the brain. In vivo metabolite mapping obtained with short echo time proton-echo-planar spectroscopic imaging shows that the automatic method yields a placement of suppression slices that is very similar to that of a skilled human operator in terms of lipid suppression and usable brain voxels.Publicad

In-Vivo Three Dimensional Proton Hadamard Spectroscopic Imaging in the Human Brain

Magnetic resonance spectroscopic imaging (MRSI) is a useful tool for obtaining information on the biochemical processes underlying various pathologies. A widely used multi-voxel localization method is chemical shift imaging (CSI) which uses gradients for phase encoding. Although simple to implement, low in specific absorption rate (SAR) and immune to chemical shift displacement (CSD), it also suffers from some well known drawbacks caused by its sinc-shaped point spread function (PSF). This results in loss of both signal-to-noise ratio (SNR) as well as localization, an effect that is exacerbated at low resolutions. In contrast, an alternative localization method, Hadamard spectroscopic imaging (HSI) benefits from a theoretically ideal PSF and consequently does not suffer from these drawbacks. In this work we exploit the theoretically ideal PSF of HSI encoding to develop a novel three dimensional (3D) multi-voxel MR localization method based on transverse HSI (T-HSI). The advantages of T HSI are that unlike gradient phase-encoding: (i) the volume of interest (VOI) does not need to be smaller than the field-of-view to prevent aliasing; (ii) the number of partitions in each direction can be small, 8, 4 or even 2 at no cost in PSF; (iii) the VOI does not have to be contiguous; and (iv) the voxel profile depends on the available B1 and pulse synthesis paradigm and can therefore, at least theoretically, approach "ideal" "1" inside and "0" elsewhere. Clinical utility of the new method is shown by spectra obtained from the brain of a healthy volunteer. The benefits of T-HSI are demonstrated by a quantitative comparison to CSI of the SNR and localization in a phantom in both one and three dimensions at clinical resolutions. A novel matrix formalism is used to quantify the impact of non-ideal flip angles on T-HSI. The superior PSF of T-HSI is then used to demonstrate the feasibility of scanning regions near or on the skull while limiting the impact of lipid contamination and obtaining quantifiable spectra. A comparison to spectra obtained using CSI is shown for a healthy volunteer. The new method is also used in a clinical pathology: to scan multiple sclerosis (MS) lesions occurring near the skull. To maintain the benefits provided by the PSF of HSI at higher fields, despite its susceptibility to CSD, a additional hybrid sequence is also developed that limits both the SAR and the CSD, regardless of the size of the VOI. A comparison to CSI in a phantom and in-vivo is carried out and spectra obtained from the brain of a healthy volunteer at 3T are shown. Finally, future research avenues involving extension of this research to ultra high fields (7T) are discussed and possible clinical uses are described

Implementation of 3 T Lactate-Edited 3D 1H MR Spectroscopic Imaging with Flyback Echo-Planar Readout for Gliomas Patients

The purpose of this study was to implement a new lactate-edited 3D 1H magnetic resonance spectroscopic imaging (MRSI) sequence at 3 T and demonstrate the feasibility of using this sequence for measuring lactate in patients with gliomas. A 3D PRESS MRSI sequence incorporating shortened, high bandwidth 180° pulses, new dual BASING lactate-editing pulses, high bandwidth very selective suppression (VSS) pulses and a flyback echo-planar readout was implemented at 3 T. Over-prescription factor of PRESS voxels was optimized using phantom to minimize chemical shift artifacts. The lactate-edited flyback sequence was compared with lactate-edited MRSI using conventional elliptical k-space sampling in a phantom and volunteers, and then applied to patients with gliomas. The results demonstrated the feasibility of detecting lactate within a short scan time of 9.5 min in both phantoms and patients. Over-prescription of voxels gave less chemical shift artifacts allowing detection of lactate on the majority of the selected volume. The normalized SNR of brain metabolites using the flyback encoding were comparable to the SNR of brain metabolites using conventional phase encoding MRSI. The specialized lactate-edited 3D MRSI sequence was able to detect lactate in brain tumor patients at 3 T. The implementation of this technique means that brain lactate can be evaluated in a routine clinical setting to study its potential as a marker for prognosis and response to therapy