MRS) And Spectroscopic Imaging Research Articles

B0 shimming for in vivo magnetic resonance spectroscopy: Experts' consensus recommendations.

Magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) allow the chemical analysis of physiological processes in vivo and provide powerful tools in the life sciences and for clinical diagnostics. Excellent homogeneity of the static B0 magnetic field over the object of interest is essential for achieving high-quality spectral results and quantitative metabolic measurements. The experimental minimization of B0 variation is performed in a process called B0 shimming. In this article, we summarize the concepts of B0 field shimming using spherical harmonic shimming techniques, specific strategies for B0 homogenization and crucial factors to consider for implementation and use in both brain and body. In addition, experts' recommendations are provided for minimum requirements for B0 shim hardware and evaluation criteria for the primary outcome of adequate B0 shimming for MRS and MRSI, such as the water spectroscopic linewidth.

The fast Padé transform for noisy magnetic resonance spectroscopic data from the prostate: potential contribution to individualized prostate cancer care

Magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) can enhance prostate cancer diagnostics, but have limitations that are largely due to reliance upon conventional Fourier-based signal processing. MRS of the prostate is exceedingly difficult, due to high spectral density with numerous multiplet resonances. We apply advanced signal processing methods through the fast Pade transform (FPT) to time signals generated according to in vitro MRS data as encoded from normal glandular and stromal prostate as well as from prostate cancer. Random Gauss-distributed zero mean noise is added to the noise-free time signal. The high resolution capabilities are demonstrated: at short partial signal lengths $$(N_{\mathrm{P}})$$ , converged total and component spectra from the prostate are generated by the FPT. In comparison, Fourier-based processing provides only rough, uninformative total shape spectra. Detailed analysis reveals the powerful, complementary features of the two variants $$\hbox {FPT}^{(\pm )}$$ of the FPT in separating the copious spurious content from genuine resonances. At short $$N_{\mathrm{P}}$$ , the FPT resolved all the physical resonances, including multiplets and closely overlapping peaks of different metabolites, exactly reconstructing all the input spectral parameters, from which the metabolite concentrations were precisely computed. Systematic study of noise-corrupted time signals in the controlled setting is a critical step in benchmarking the FPT for clinical applications. We discuss how these results could increase the diagnostic accuracy of MRS and MRSI of the prostate, and how this could contribute to a more individualized care of patients with prostate cancer.

Quantification by the fast Padé transform of magnetic resonance spectroscopic data encoded at 1.5 T: implications for brain tumor diagnostics

Magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) are widely applied in brain tumor diagnostics. Notwithstanding the important achievements, there are major problems in MRS and MRSI for neuro-oncology due to inadequate signal processing. In this proof-of-concept study, we apply the fast Pade transform (FPT) to MRS time signals of short signal length $$(N = 512)$$ encoded from a standard test phantom head on a 1.5 T MR scanner. The employed phantom head contains a number of major metabolites that are also detectable by way of MRS scans of in vivo human brain. Detailed parametric analysis is performed by which quantification is achieved with full reliability. The effectiveness of the FPT-based signal-noise separation is confirmed in handling these experimentally-encoded MRS time signals. The $$\hbox {FPT}^{(+)}$$ variant of the FPT shows particularly favorable capabilities for distinguishing the genuine from the numerous spurious resonances in the presence of the unavoidable noise, as is typical of data encoded at MR clinical scanners. Exhaustive examination of the convergence process is performed to confirm the stability of the reconstructed spectral parameters. Statistical analysis, as a procedure called “parameter averaging” demonstrates the accuracy and precision of the reconstructed complex-valued fundamental frequencies and amplitudes. This includes the dense regions of the spectrum, containing several very small and/or very closely overlapping resonances. Overall, the obtained results confirm that Pade-optimized MRS and MRSI can be directly used in our fully automated matlab program for in vivo encoded data with complete fidelity within neuro-oncology, with anticipated benefit for brain tumor diagnostics.

Abstract 1484: Pancreatic cancer and normal pancreas water content and its impact in metabolite quantification

Abstract The absence of early symptoms in pancreatic cancer creates a critical need for identifying new noninvasive biomarkers. Magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) are being evaluated in the diagnosis of several solid malignancies. A hallmark of most solid tumors is the detection of elevated phosphocholine (PC) and total choline (tCho). We previously observed elevated levels of tCho in several pancreatic cancer cell lines and tumor xenografts (1). Initial single voxel studies performed in humans suggest that the tCho signal normalized to water may be relatively high in normal pancreas compared to pancreatic tumor (2). Since metabolites are normalized to the water signal it is important to determine differences in its content for accurate quantification. Here, we quantified tCho in orthotopic and subcutaneous Panc1 pancreatic xenografts, and in normal pancreas. 1H MRSI acquired on a 9.4T spectrometer showed heterogeneous tCho signal in orthotopic tumors. To further determine differences in tCho, tumor tissues and pancreas were embedded in agarose and imaged ex vivo with 1H MRSI. Concentration of tCho was 3.38 ± 0.95 mM in orthotopic tumors, 1.32 ± 0.59 mM in subcutaneous tumors, and 1.27 ± 0.52 mM in normal pancreas (n = 2), when using the uncorrected water signal for normalization. Despite a much higher tCho signal in the subcutaneous tumors, tCho concentrations were comparable to the pancreas. We next estimated the water content of the tumors and the pancreas as a ratio of wet weight to dry weight (measured after 72h of lyophilization) and confirmed a significantly higher water content in tumors compared to the pancreas (wet to dry weight ratio of ∼ 6 vs ∼ 4). A separate set of tumors were freeze-clamped and used for high-resolution 1H MRS. Tumor and pancreas extracts were obtained using a dual-phase extraction method and 1H MR spectra were acquired as previously described (3). To determine the tCho concentration, peak integrations from spectra for choline, PC and glycerophosphocholine were compared to an internal standard. Integrals of the metabolites of interest were determined and normalized first to the tissue wet weight. Once the tCho concentration in tumors and pancreas was corrected for differences in water content, a two-fold higher tCho concentration was observed in tumor tissue compared to normal pancreas. These data support the use of 1H MRSI that provides a tCho map rather than the placement of single voxels to address heterogeneities in the pancreas and in pancreatic cancers. The results highlight the importance of quantifying water content in the calculation of metabolite concentration when comparing different tissues. Work supported by NIH P50CA103175. (1) Penet et al., Clin Cancer Res (2014). (2) Ma et al., Journal of computer assisted tomography (2011). (3) Shah et al., NMR Biomed (2012). Citation Format: Marie-France Penet, Balaji Krishnamachary, Tariq Shah, Yelena Mironchik, Anirban Maitra, Zaver M. Bhujwalla. Pancreatic cancer and normal pancreas water content and its impact in metabolite quantification. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1484. doi:10.1158/1538-7445.AM2015-1484

Evaluation of Hyperpolarized [1-13C]-Pyruvate by Magnetic Resonance to Detect Ionizing Radiation Effects in Real Time

Ionizing radiation (IR) cytotoxicity is primarily mediated through reactive oxygen species (ROS). Since tumor cells neutralize ROS by utilizing reducing equivalents, we hypothesized that measurements of reducing potential using real-time hyperpolarized (HP) magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) can serve as a surrogate marker of IR induced ROS. This hypothesis was tested in a pre-clinical model of anaplastic thyroid carcinoma (ATC), an aggressive head and neck malignancy. Human ATC cell lines were utilized to test IR effects on ROS and reducing potential in vitro and [1-13C] pyruvate HP-MRS/MRSI imaging of ATC orthotopic xenografts was used to study in vivo effects of IR. IR increased ATC intra-cellular ROS levels resulting in a corresponding decrease in reducing equivalent levels. Exogenous manipulation of cellular ROS and reducing equivalent levels altered ATC radiosensitivity in a predictable manner. Irradiation of ATC xenografts resulted in an acute drop in reducing potential measured using HP-MRS, reflecting the shunting of reducing equivalents towards ROS neutralization. Residual tumor tissue post irradiation demonstrated heterogeneous viability. We have adapted HP-MRS/MRSI to non-invasively measure IR mediated changes in tumor reducing potential in real time. Continued development of this technology could facilitate the development of an adaptive clinical algorithm based on real-time adjustments in IR dose and dose mapping.

A meta-analysis of studies using MR spectroscopy for evaluating suspicious lesions after radiation therapy of primary brain tumors

Primary brain tumors frequently return after radiation therapy (RT). In addition, RT can provoke changes in brain tissue that are difficult to distinguish from tumor recurrence using magnetic resonance imaging. Magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) have been applied quite extensively with the aim of better differentiating recurrent brain tumors from radiation necrosis. To the best of our knowledge, however, there have not been any published papers within this context in which the results of MRS and MRSI have been analyzed in a comprehensive, integrative manner. Through meta-analysis, the present paper aims to determine which metabolite concentration ratios could potentially be the most reliable for differentiating post-RT recurrent brain tumor from radiation necrosis. We systematically reviewed the literature to find empirical studies of patients treated with RT for primary malignant brain tumors, and who developed a new lesion post-RT, which was assessed using MRS or MRSI. Reported data from individual patients were entered into a single data set for detailed statistical analysis. Six articles were identified that fulfilled the criteria for inclusion in the present study. From these, quantitative MRS/MRSI data were provided for sixty-three patients with recurrent brain tumors and for thirty-eight patients with radiation necrosis. Higher choline to creatine and choline to N-Acetyl Aspartate (NAA) concentration ratios were associated with a significantly greater likelihood of recurrent tumor, as opposed to radiation necrosis. This was found with and without statistical adjustment for high grade of the primary tumor, echo time (TE) and static magnetic field strength (B0). Higher NAA to creatine and lactate to choline concentration ratios were associated with a significantly greater likelihood of radiation necrosis as opposed to recurrent tumor, both with and without adjustment for tumor grade, TE and B0. Only the lactate to choline concentration ratio yielded 100 % correct prediction of all the cases for which data were available. However, data on lactate to choline concentration ratios were available for less than one-third of the patients; these were all recorded at long TE, at which most of the major signal components for the other metabolites have decayed to the level of background noise. No cutpoint values for the choline to creatine or choline to NAA concentration ratios could be identified that optimally distinguished recurrent tumor from radiation necrosis. We conclude that metabolite concentration ratios assessed within MRS/MRSI could potentially be helpful in distinguishing tumor recurrence from radiation necrosis. However, optimal distinction of these two entities has not yet been provided, mainly because of the nearly exclusive reliance upon the conventional estimations by post-processing of Fourier spectral envelopes with various fitting computations that are all equivocal. In order to more accurately identify recurrent brain tumor post-RT as opposed to radiation-induced changes, a more advanced and unequivocal mathematical approach for quantification of MRS/MRSI signals is needed. The answer of choice to this quest is offered by the universally applicable method of rational functions from the mathematical theory of approximations. The most salient feature of rational functions is their capability to accurately describe the essential behavior of generic systems by means of the least number of quantifying parameters, as an indispensable prerequisite for a parsimonious mathematical modeling. The most established rational response function, which has passed the test of time across interdisciplinary research, is the Pade approximant. Adapted to signal processing and accordingly called the fast Pade transform, this versatile method is the optimal spectral analyzer for MRS/MRSI data. It is within such a strategy that the questions addressed in this study could be answered in an adequate manner.

Metabolic Tumor Imaging Using Magnetic Resonance Spectroscopy

The adaptability and the genomic plasticity of cancer cells, and the interaction between the tumor microenvironment and co-opted stromal cells, coupled with the ability of cancer cells to colonize distant organs, contribute to the frequent intractability of cancer. It is becoming increasingly evident that personalized molecular targeting is necessary for the successful treatment of this multifaceted and complex disease. Noninvasive imaging modalities such as magnetic resonance (MR), positron emission tomography (PET), and single-photon emission computed tomography (SPECT) are filling several important niches in this era of targeted molecular medicine, in applications that span from bench to bedside. In this review we focus on noninvasive magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) and their roles in future personalized medicine in cancer. Diagnosis, the identification of the most effective treatment, monitoring treatment delivery, and response to treatment are some of the broad areas into which MRS techniques can be integrated to improve treatment outcomes. The development of novel probes for molecular imaging--in combination with a slew of functional imaging capabilities--makes MRS techniques, especially in combination with other imaging modalities, valuable in cancer drug discovery and basic cancer research.

17-allyamino-17-demethoxygeldanamycin treatment results in a magnetic resonance spectroscopy-detectable elevation in choline-containing metabolites associated with increased expression of choline transporter SLC44A1 and phospholipase A2

Introduction17-allyamino-17-demethoxygeldanamycin (17-AAG), a small molecule inhibitor of Hsp90, is currently in clinical trials in breast cancer. However, 17-AAG treatment often results in inhibition of tumor growth rather than shrinkage, making detection of response a challenge. Magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) are noninvasive imaging methods than can be used to monitor metabolic biomarkers of drug-target modulation. This study set out to examine the MRS-detectable metabolic consequences of Hsp90 inhibition in a breast cancer model.MethodsMCF-7 breast cancer cells were investigated, and MRS studies were performed both on live cells and on cell extracts. 31P and 1H MRS were used to determine total cellular metabolite concentrations and 13C MRS was used to probe the metabolism of [1,2-13C]-choline. To explain the MRS metabolic findings, microarray and RT-PCR were used to analyze gene expression, and in vitro activity assays were performed to determine changes in enzymatic activity following 17-AAG treatment.ResultsTreatment of MCF-7 cells with 17-AAG for 48 hours caused a significant increase in intracellular levels of choline (to 266 ± 18% of control, P = 0.05) and phosphocholine (PC; to 181 ± 10% of control, P = 0.001) associated with an increase in expression of choline transporter SLC44A1 and an elevation in the de novo synthesis of PC. We also detected an increase in intracellular levels of glycerophosphocholine (GPC; to 176 ± 38% of control, P = 0.03) associated with an increase in PLA2 expression and activity.ConclusionsThis study determined that in the MCF-7 breast cancer model inhibition of Hsp90 by 17-AAG results in a significant MRS-detectable increase in choline, PC and GPC, which is likely due to an increase in choline transport into the cell and phospholipase activation. 1H MRSI can be used in the clinical setting to detect levels of total choline-containing metabolite (t-Cho, composed of intracellular choline, PC and GPC). As Hsp90 inhibitors enter routine clinical use, t-Cho could thus provide an easily detectable, noninvasive metabolic biomarker of Hsp90 inhibition in breast cancer patients.

Quantitation of magnetic resonance spectroscopy signals: the jMRUI software package

The software package jMRUI with Java-based graphical user interface enables user-friendly time-domain analysis of magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) and HRMAS-NMR signals. Version 3.x has been distributed in more than 1200 groups or hospitals worldwide. The new version 4.x is a plug-in platform enabling the users to add their own algorithms. Moreover, it offers new functionalities compared to versions 3.x. The quantum-mechanical simulator based on NMR-SCOPE, the quantitation algorithm QUEST and the main MRSI functionalities are described. Quantitation results of signals obtained in vivo from a mouse and a human brain are given.

The general concept of signal–noise separation (SNS): mathematical aspects and implementation in magnetic resonance spectroscopy

Magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) are increasingly recognized as potentially key modalities in cancer diagnostics. It is, therefore, urgent to overcome the shortcomings of current applications of MRS and MRSI. We explain and substantiate why more advanced signal processing methods are needed, and demonstrate that the fast Pade transform (FPT), as the quotient of two polynomials, is the signal processing method of choice to achieve this goal. In this paper, the focus is upon distinguishing genuine from spurious (noisy and noise-like) resonances; this has been one of the thorniest challenges to MRS. The number of spurious resonances is always several times larger than the true ones. Within the FPT convergence is achieved through stabilization or constancy of the reconstructed frequencies and amplitudes. This stabilization is a veritable signature of the exact number of resonances. With any further increase of the partial signal length N, towards the full signal length N, i.e., passing the stage at which full convergence has been reached, it is found that all the fundamental frequencies and amplitudes “stay put”, i.e., they still remain constant. Moreover, machine accuracy is achieved here, proving that when the FPT is nearing convergence, it approaches straight towards the exact result with an exponential convergence rate (the spectral convergence). This proves that the FPT is an exponentially accurate representation of functions customarily encountered in spectral analysis in MRS and beyond. The mechanism by which this is achieved, i.e., the mechanism which secures the maintenance of stability of all the spectral parameters and, by implication, constancy of the estimate for the true number of resonances is provided by the so-called pole-zero cancellation, or equivalently, the Froissart doublets. This signifies that all the additional poles and zeros of the Pade spectrum will cancel each other, a remarkable feature unique to the FPT. The FPT is safe-guarded against contamination of the final results by extraneous resonances, since each pole due to spurious resonances stemming from the denominator polynomial will automatically coincide with the corresponding zero of the numerator polynomial, thus leading to the pole-zero cancellation in the polynomial quotient of the FPT. Such pole-zero cancellations can be advantageously exploited to differentiate between spurious and genuine content of the signal. Since these unphysical poles and zeros always appear as pairs in the FPT, they are viewed as doublets. Therefore, the pole-zero cancellation can be used to disentangle noise as an unphysical burden from the physical content in the considered signal, and this is the most important usage of the Froissart doublets in MRS. The general concept of signal–noise separation (SNS) is thereby introduced as a reliable procedure for separating physical from non-physical information in MRS, MRSI and beyond.

Molecular imaging through 1H MRS and MRSI in everyday routine: Improvements in various clinical applications and parameter optimization of spectroscopic imaging sequences

In the era of molecular imaging, in vivo 1H magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) are impacting dramatically upon virtually all areas of clinical medicine. MRS and MRSI should be able to identify key biochemical changes, much before the tumour becomes detectable by other functional imaging methods that mainly rely upon single markers that are not entirely sensitive or specific for malignant activity. Combined with other imaging techniques a rapidly advancing modality like MRI offer the ability to estimate the presence of metabolites yields much information regarding tissue. Molecular imaging through magnetic resonance could be potentially suited for screening and repeated monitoring since it entails no exposure to ionizing radiation. Incorporation of these tools in clinical practice is, however, limited due to the considerable amount of user intervention. In this work, various acquisition parameters and their effects in spectrum quality are investigated. In order to assess the quality of various spectroscopic techniques (2D and multi-slice MRSI, multiple echo SI), a series of experiments were conducted using a standard solution. The application of water and fat suppression techniques and their compatibility with other parameters were also investigated. The stability of the equipment, the appearance of errors and artifacts and the reproducibility of the results were also examined to obtain useful conclusions for the interaction of acquisition parameters. All the data were processed with specialized computer software (jMRUI 2.2) to analyze various aspects of the measurements and quantify various parameters such as signal-to-noise ratio (SNR), full-width at half-maximum (FWHM), peak height and j-modulation. The experience acquired from the conducted experiments was successfully applied in acquisition parameter optimization and improvement of clinical applications (two dimensional (2D) MRSI of prostate, brain and muscle MRS) by significantly improving the spectrum quality, SNR (up to 75%), spatial resolution in 2D MRSI, water and fat suppression and in some cases reducing exam times (up to 60%).

Noninvasive QuantitativeIn VivoMapping and Metabolism of Boronophenylalanine (BPA) by Nuclear Magnetic Resonance (NMR) Spectroscopy and Imaging

10B-enriched L-p-boronophenylalanine (BPA) is one of the compounds used in boron neutron capture therapy (BNCT). In this study, several variations of nuclear magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) were applied to investigate the uptake, clearance and metabolism of the BPA-fructose complex (BPA-F) in normal mouse kidneys, rat oligodendroglioma xenografts, and rat blood. Localized 1H MRS was capable of following the uptake and clearance of BPA-F in mouse kidneys with temporal resolution of a few minutes, while 1H MRSI was used to image the BPA distribution in the kidney with a spatial resolution of 9 mm3. The results also revealed significant dissociation of the BPA-F complex to free BPA. This finding was corroborated by 1H and 11B NMR spectroscopy of rat blood samples as well as of tumor samples excised from mice after i.v. injection of BPA-F. This investigation demonstrates the feasibility of using 1H MRS and MRSI to follow the distribution of BPA in vivo, using NMR techniques specifically designed to optimize BPA detection. The implementation of such procedures could significantly improve the clinical efficacy of BNCT.

Spectroscopic imaging through magnetic resonance for brain tumour diagnostics: Recent achievements, dilemmas and potential solutions via advances in signal processing

In the very recent period Magnetic Resonance Spectroscopy (MRS) and Spectroscopic Imaging (MRSI) have become key diagnostic modalities for neuro-oncology. MRS and MRSI are now applied extensively for initial detection of brain tumours, for histopathologic classification, tumour localization and grading, as well as for assessment of response to therapy and for follow-up surveillance, striving, in particular, for earlier identification of recurrence. In this paper we review the current state of the art of MRS and MRSI for brain tumour diagnostics, highlighting the achievements, as well as remaining dilemmas. Clearly, MRS and MRSI represent an important advance for the detection and characterisation of tumours of the brain. However, there are still important shortcomings of the present applications of MRS and MRSI in neuro-oncology. First of all, very few of the currently assessed metabolite concentrations or ratios unequivocally distinguish intra-cerebral tumours from normal brain tissue. Moreover, changes in each of the metabolite concentrations and ratios are non-specific for cancer of the brain. In other words, non-neoplastic processes such as infection, stroke, demyelinating disorders, inter alia, frequently show spectral changes that are identical to those seen in brain tumours. Histopathological characterization and tumour grading, both crucial for clinical decision-making, have been greatly aided by MRS and MRSI. However, there are numerous contradictory findings in the literature. We demonstrate in this paper that many of the shortcomings of MRS and MRSI for neuro-oncology are directly related to the reliance upon the conventional Fourier-based framework for data analysis. We review the distinct advantages of the Fast Pade Transform (FPT) relative to the Fast Fourier Transform (FFT). Our focus is on those salient features of the FPT that are of critical clinical relevance for achieving an overall improved diagnostic performance of MRS and MRSI. These features are extremely stable and rapid convergence, as well as highly accurate quantification estimates of spectra from in vivo MRS time signals, as presently illustrated for data from the brain of a healthy volunteer. The next, and urgently needed step, is to more widely apply the FPT to in vivo MRS and MRSI signals from patients with brain tumours with the aim of tackling, in actual practice, the diagnostic dilemmas still plaguing neuro-oncology.

Spectroscopic imaging through magnetic resonance for brain tumour diagnostics: Recent achievements, dilemmas and potential solutions via advances in signal processing

In the very recent period Magnetic Resonance Spectroscopy (MRS) and Spectroscopic Imaging (MRSI) have become key diagnostic modalities for neuro-oncology. MRS and MRSI are now applied extensively f...

Magnetic resonance spectroscopy in cerebral ischemia and infarction

Proton magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) are promising techniques for the noninvasive investigation of brain metabolism in vivo. They can be implemented routinely on most clinical scanners, and typically have a spatial resolution of approximately 1 to 10 cm 3 with scan times of 5 to 20 minutes. Various compounds can be detected in proton MRS of the brain. Compounds that are of particular importance in cerebrovascular disease are lactate (as a marker of ischemia) and N-acetyl aspartate (NAA), which is believed to be primarily of neuronal/axonal origin. The time-course of the changes in these compounds during ischemia is blood-flow dependent and potentially could be used to stratify acute stroke patients into different treatment protocols and to monitor the effects of treatment. However, many technical challenges have to be overcome (in particular, the development of fast MRSI techniques to reduce scan times) before this goal is realized. Also, more research is required to understand the significance of spectral changes during ischemia, and to compare the relative value of MRSI with other emerging MRI techniques, such as diffusion- and perfusion-weighted MRI.