In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods.

Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions.

Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse single modality multicentre datasets. However, these surveys rarely focused on evaluation metrics and lacked a checklist for computational data harmonisation studies. In this systematic review, we summarise the computational data harmonisation approaches for multi-modality data in the digital healthcare field, including harmonisation strategies and evaluation metrics based on different theories. In addition, a comprehensive checklist that summarises common practices for data harmonisation studies is proposed to guide researchers to report their research findings more effectively. Last but not least, flowcharts presenting possible ways for methodology and metric selection are proposed and the limitations of different methods have been surveyed for future research.

Accelerated 3D whole-brain T1, T2, and proton density mapping: feasibility for clinical glioma MR imaging.

PURPOSE: Advanced MRI-based biomarkers offer comprehensive and quantitative information for the evaluation and characterization of brain tumors. In this study, we report initial clinical experience in routine glioma imaging with a novel, fully 3D multiparametric quantitative transient-state imaging (QTI) method for tissue characterization based on T1 and T2 values. METHODS: To demonstrate the viability of the proposed 3D QTI technique, nine glioma patients (grade II-IV), with a variety of disease states and treatment histories, were included in this study. First, we investigated the feasibility of 3D QTI (6:25 min scan time) for its use in clinical routine imaging, focusing on image reconstruction, parameter estimation, and contrast-weighted image synthesis. Second, for an initial assessment of 3D QTI-based quantitative MR biomarkers, we performed a ROI-based analysis to characterize T1 and T2 components in tumor and peritumoral tissue. RESULTS: The 3D acquisition combined with a compressed sensing reconstruction and neural network-based parameter inference produced parametric maps with high isotropic resolution (1.125 × 1.125 × 1.125 mm3 voxel size) and whole-brain coverage (22.5 × 22.5 × 22.5 cm3 FOV), enabling the synthesis of clinically relevant T1-weighted, T2-weighted, and FLAIR contrasts without any extra scan time. Our study revealed increased T1 and T2 values in tumor and peritumoral regions compared to contralateral white matter, good agreement with healthy volunteer data, and high inter-subject consistency. CONCLUSION: 3D QTI demonstrated comprehensive tissue assessment of tumor substructures captured in T1 and T2 parameters. Aiming for fast acquisition of quantitative MR biomarkers, 3D QTI has potential to improve disease characterization in brain tumor patients under tight clinical time-constraints.

Correction of motion-induced susceptibility artifacts and B0 drift during proton resonance frequency shift-based MR thermometry in the pelvis with background field removal methods.

PURPOSE: The linear change of the water proton resonance frequency shift (PRFS) with temperature is used to monitor temperature change based on the temporal difference of image phase. Here, the effect of motion-induced susceptibility artifacts on the phase difference was studied in the context of mild radio frequency hyperthermia in the pelvis. METHODS: First, the respiratory-induced field variations were disentangled from digestive gas motion in the pelvis. The projection onto dipole fields (PDF) as well as the Laplacian boundary value (LBV) algorithm were applied on the phase difference data to eliminate motion-induced susceptibility artifacts. Both background field removal (BFR) algorithms were studied using simulations of susceptibility artifacts, a phantom heating experiment, and volunteer and patient heating data. RESULTS: Respiratory-induced field variations were negligible in the presence of the filled water bolus. Even though LBV and PDF showed comparable results for most data, LBV seemed more robust in our data sets. Some data sets suggested that PDF tends to overestimate the background field, thus removing phase attributed to temperature. The BFR methods even corrected for susceptibility variations induced by a subvoxel displacement of the phantom. The method yielded successful artifact correction in 2 out of 4 patient treatment data sets during the entire treatment duration of mild RF heating of cervical cancer. The heating pattern corresponded well with temperature probe data. CONCLUSION: The application of background field removal methods in PRFS-based MR thermometry has great potential in various heating applications and body regions to reduce motion-induced susceptibility artifacts that originate outside the region of interest, while conserving temperature-induced PRFS. In addition, BFR automatically removes up to a first-order spatial B0 drift.

A phase-cycled temperature-sensitive fast spin echo sequence with conductivity bias correction for monitoring of mild RF hyperthermia with PRFS.

OBJECTIVE: Mild hyperthermia (HT) treatments are generally monitored by phase-referenced proton resonance frequency shift calculations. A novel phase and thus temperature-sensitive fast spin echo (TFSE) sequence is introduced and compared to the double echo gradient echo (DEGRE) sequence. THEORY AND METHODS: For a proton resonance frequency shift (PRFS)-sensitive TFSE sequence, a phase cycling method is applied to separate even from odd echoes. This method compensates for conductivity change-induced bias in temperature mapping as does the DEGRE sequence. Both sequences were alternately applied during a phantom heating experiment using the clinical setup for deep radio frequency HT (RF-HT). The B0 drift-corrected temperature values in a region of interest around temperature probes are compared to the temperature probe data and further evaluated in Bland-Altman plots. The stability of both methods was also tested within the thighs of three volunteers at a constant temperature using the subcutaneous fat layer for B0-drift correction. RESULTS: During the phantom heating experiment, on average TFSE temperature maps achieved double temperature-to-noise ratio (TNR) efficiency in comparison with DEGRE temperature maps. In-vivo images of the thighs exhibit stable temperature readings of ± 1 °C over 25 min of scanning in three volunteers for both methods. On average, the TNR efficiency improved by around 25% for in vivo data. CONCLUSION: A novel TFSE method has been adapted to monitor temperature during mild HT.

A diffusion model-free framework with echo time dependence for free-water elimination and brain tissue microstructure characterization.

PURPOSE: The compartmental nature of brain tissue microstructure is typically studied by diffusion MRI, MR relaxometry or their correlation. Diffusion MRI relies on signal representations or biophysical models, while MR relaxometry and correlation studies are based on regularized inverse Laplace transforms (ILTs). Here we introduce a general framework for characterizing microstructure that does not depend on diffusion modeling and replaces ill-posed ILTs with blind source separation (BSS). This framework yields proton density, relaxation times, volume fractions, and signal disentanglement, allowing for separation of the free-water component. THEORY AND METHODS: Diffusion experiments repeated for several different echo times, contain entangled diffusion and relaxation compartmental information. These can be disentangled by BSS using a physically constrained nonnegative matrix factorization. RESULTS: Computer simulations, phantom studies, together with repeatability and reproducibility experiments demonstrated that BSS is capable of estimating proton density, compartmental volume fractions and transversal relaxations. In vivo results proved its potential to correct for free-water contamination and to estimate tissue parameters. CONCLUSION: Formulation of the diffusion-relaxation dependence as a BSS problem introduces a new framework for studying microstructure compartmentalization, and a novel tool for free-water elimination.

Real valued diffusion-weighted imaging using decorrelated phase filtering.

PURPOSE: Because of the intrinsic low signal-to-noise ratio in diffusion-weighted imaging (DWI), magnitude processing often causes an overestimation of the signal's amplitude. This results in low-estimation accuracy of diffusion models and reduced contrast because of a superposition of the image signal and the noise floor. We adopt a new phase correction (PC) technique that yields real valued diffusion data while maintaining a Gaussian noise distribution. METHODS: We conduct simulations of the noise propagation in the echo-planar imaging reconstruction chain to determine the spatial noise correlation in the image. Using the correlation pattern, optimized filter kernels are derived to estimate the true phase of the signal in each voxel. Furthermore, we adopt an outlier detection technique to replace the real value by the magnitude in case of substantial signal loss resulting from incorrect PC. RESULTS: The benefits of our method are demonstrated on Monte Carlo simulations, DWI data acquired from healthy volunteer experiments, estimated parameters of the diffusion kurtosis imaging model, and the model-free diffusion spectrum imaging technique. The improved PC approach significantly reduces the noise bias and only slightly increases the sensitivity to local phase variations. CONCLUSION: PC can enhance the usefulness of higher b-values, allowing deeper insights into tissue microstructure. Magn Reson Med 77:559-570, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Model-based denoising in diffusion-weighted imaging using generalized spherical deconvolution.

PURPOSE: Diffusion MRI often suffers from low signal-to-noise ratio, especially for high b-values. This work proposes a model-based denoising technique to address this limitation. METHODS: A generalization of the multi-shell spherical deconvolution model using a Richardson-Lucy algorithm is applied to noisy data. The reconstructed coefficients are then used in the forward model to compute denoised diffusion-weighted images (DWIs). The proposed method operates in the diffusion space and thus is complementary to image-based denoising methods. RESULTS: We demonstrate improved image quality on the DWIs themselves, maps of neurite orientation dispersion and density imaging, and diffusional kurtosis imaging (DKI), as well as reduced spurious peaks in deterministic tractography. For DKI in particular, we observe up to 50% error reduction and demonstrate high image quality using just 30 DWIs. This corresponds to greater than fourfold reduction in scan time if compared to the widely used 140-DWI acquisitions. We also confirm consistent performance in pathological data sets, namely in white matter lesions of a multiple sclerosis patient. CONCLUSION: The proposed denoising technique termed generalized spherical deconvolution has the potential of significantly improving image quality in diffusion MRI. Magn Reson Med 78:2428-2438, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Diffusion in realistic biophysical systems can lead to aliasing effects in diffusion spectrum imaging.

PURPOSE: Diffusion spectrum imaging (DSI) is an imaging technique that has been successfully applied to resolve white matter crossings in the human brain. However, its accuracy in complex microstructure environments has not been well characterized. THEORY AND METHODS: Here we have simulated different tissue configurations, sampling schemes, and processing steps to evaluate DSI performances' under realistic biophysical conditions. A novel approach to compute the orientation distribution function (ODF) has also been developed to include biophysical constraints, namely integration ranges compatible with axial fiber diffusivities. RESULTS: Performed simulations identified several DSI configurations that consistently show aliasing artifacts caused by fast diffusion components for both isotropic diffusion and fiber configurations. The proposed method for ODF computation showed some improvement in reducing such artifacts and improving the ability to resolve crossings, while keeping the quantitative nature of the ODF. CONCLUSION: In this study, we identified an important limitation of current DSI implementations, specifically the presence of aliasing due to fast diffusion components like those from pathological tissues, which are not well characterized, and can lead to artifactual fiber reconstructions. To minimize this issue, a new way of computing the ODF was introduced, which removes most of these artifacts and offers improved angular resolution. Magn Reson Med 76:1837-1847, 2016. © 2015 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.

Bias and precision analysis of diffusional kurtosis imaging for different acquisition schemes.

PURPOSE: Diffusional kurtosis imaging (DKI) is an approach to characterizing the non-Gaussian fraction of water diffusion in biological tissue. However, DKI is highly susceptible to the low signal-to-noise ratio of diffusion-weighted images, causing low precision and a significant bias due to Rician noise distribution. Here, we evaluate precision and bias using weighted linear least squares fitting of different acquisition schemes including several multishell schemes, a diffusion spectrum imaging (DSI) scheme, as well as a compressed sensing reconstruction of undersampled DSI scheme. METHODS: Monte Carlo simulations were performed to study the three-dimensional distribution of the apparent kurtosis coefficient (AKC). Experimental data were acquired from one healthy volunteer with multiple repetitions, using the same acquisition schemes as for the simulations. RESULTS: The angular distribution of the bias and precision were very inhomogeneous. While axial kurtosis was significantly overestimated, radial kurtosis was underestimated. The precision of radial kurtosis was up to 10-fold lower than axial kurtosis. CONCLUSION: The noise bias behavior of DKI is highly complex and can cause overestimation as well as underestimation of the AKC even within one voxel. The acquisition scheme with three shells, suggested by Poot et al, provided overall the best performance. Magn Reson Med 76:1684-1696, 2016. © 2016 International Society for Magnetic Resonance in Medicine.

Probing lactate secretion in tumours with hyperpolarised NMR.

Most tumours exhibit a high rate of glycolysis and predominantly produce energy by lactic acid fermentation. To maintain energy production and prevent toxicity, the lactate generated needs to be rapidly transported out of the cell. This is achieved by monocarboxylate transporters (MCTs), which therefore play an essential role in cancer metabolism and development. In vivo experiments were performed on eight male Fisher F344 rats bearing a subcutaneous mammary carcinoma after injection of hyperpolarised [1-(13) C]pyruvate. A Gd(III)DO3A complex that binds to pyruvate and its metabolites was used to efficiently destroy the extracellular magnetisation after hyperpolarised lactate had been formed. Moreover, a pulse sequence including a frequency-selective saturation pulse was designed so that the pyruvate magnetisation could be destroyed to exclude effects arising from further conversion. Given this preparation, metabolite transport out of the cell manifested as additional decay and apparent cell membrane transporter rates could thus be obtained using a reference measurement without a relaxation agent. In addition to slice-selective spectra, spatially resolved maps of apparent membrane transporter activity were acquired using a single-shot spiral gradient readout. A considerable increase in decay rate was detected for lactate, indicating rapid transport out of the cell. The alanine signal was unaltered, which corresponds to a slower efflux rate. This technique could allow for better understanding of tumour metabolism and progression, and enable treatment response measurements for MCT-targeted cancer therapies. Moreover, it provides vital insights into the signal kinetics of hyperpolarised [1-(13) C]pyruvate examinations. Copyright © 2016 John Wiley & Sons, Ltd.

Multiparametric human hepatocellular carcinoma characterization and therapy response evaluation by hyperpolarized (13) C MRSI.

Individual tumor characterization and treatment response monitoring based on current medical imaging methods remain challenging. This work investigates hyperpolarized (13) C compounds in an orthotopic rat hepatocellular carcinoma (HCC) model system before and after transcatheter arterial embolization (TAE). HCC ranks amongst the top six most common cancer types in humans and accounts for one-third of cancer-related deaths worldwide. Early therapy response monitoring could aid in the development of personalized therapy approaches and novel therapeutic concepts. Measurements with selectively (13) C-labeled and hyperpolarized urea, pyruvate and fumarate were performed in tumor-bearing rats before and after TAE. Two-dimensional, slice-selective MRSI was used to obtain spatially resolved maps of tumor perfusion, cell energy metabolic conversion rates and necrosis, which were additionally correlated with immunohistochemistry. All three injected compounds, taken together with their respective metabolites, exhibited similar signal distributions. TAE induced a decrease in blood flow into the tumor and thus a decrease in tumor to muscle and tumor to liver ratios of urea, pyruvate and its metabolites, alanine and lactate, whereas conversion rates remained stable or increased on TAE in tumor, muscle and liver tissue. Conversion from fumarate to malate successfully indicated individual levels of necrosis, and global malate signals after TAE suggested the washout of fumarase or malate itself on necrosis. This study presents a combination of three (13) C compounds as novel candidate biomarkers for a comprehensive characterization of genetically and molecularly diverse HCC using hyperpolarized MRSI, enabling the simultaneous detection of differences in tumor perfusion, metabolism and necrosis. If, as in this study, bolus dynamics are not required and qualitative perfusion information is sufficient, the desired information could be extracted from hyperpolarized fumarate and pyruvate alone, acquired at higher fields with better spectral separation. Copyright © 2016 John Wiley & Sons, Ltd.

Quantified pH imaging with hyperpolarized (13) C-bicarbonate.

PURPOSE: Because pH plays a crucial role in several diseases, it is desirable to measure pH in vivo noninvasively and in a spatially localized manner. Spatial maps of pH were quantified in vitro, with a focus on method-based errors, and applied in vivo. METHODS: In vitro and in vivo (13) C mapping were performed for various flip angles for bicarbonate (BiC) and CO2 with spectral-spatial excitation and spiral readout in healthy Lewis rats in five slices. Acute subcutaneous sterile inflammation was induced with Concanavalin A in the right leg of Buffalo rats. pH and proton images were measured 2 h after induction. RESULTS: After optimizing the signal to noise ratio of the hyperpolarized (13) C-bicarbonate, error estimation of the spectral-spatial excited spectrum reveals that the method covers the biologically relevant pH range of 6 to 8 with low pH error (< 0.2). Quantification of pH maps shows negligible impact of the residual bicarbonate signal. pH maps reflect the induction of acute metabolic alkalosis. Inflamed, infected regions exhibit lower pH. CONCLUSION: Hyperpolarized (13) C-bicarbonate pH mapping was shown to be sensitive in the biologically relevant pH range. The mapping of pH was applied to healthy in vivo organs and interpreted within inflammation and acute metabolic alkalosis models.

Metabolic imaging of hyperpolarized [1-(13) C]acetate and [1-(13) C]acetylcarnitine - investigation of the influence of dobutamine induced stress.

PURPOSE: The metabolism of acetate in the heart resembles fatty acid metabolism, which is altered in several diseases like ischemia, diabetes mellitus, and heart failure. A signal-to-noise ratio (SNR) optimized imaging framework for in vivo measurements of hyperpolarized [1-(13) C]acetate and its metabolic product [1-(13) C]acetylcarnitine (ALCAR) in rats at 3 Tesla (T) is presented in this work. METHODS: A spectrospatial pulse was combined with IDEAL encoding to acquire well separated metabolic maps. The influence of dobutamine induced stress onto this metabolic system was investigated in spectra and in an imaging study. RESULTS: An increase of the ALCAR to acetate ratio with dobutamine induced stress was shown in slice selective spectra containing the rat hearts and skeletal muscles. Metabolic maps of acetate and ALCAR were acquired with an acceptable SNR. Quantification of the apparent conversion rate showed stable results in the heart in a time-window of 30 s. The effect of dobutamine on the signal intensities was shown to originate mainly from skeletal than cardiac muscles. CONCLUSION: The acetate activation was mapped with hyperpolarized [1-(13) C]acetate in a clinical 3T system. Quantitative measurement of the activity was possible in the heart, indicating that dobutamine induced stress does not improve the ALCAR SNR in the heart.

Comparison of acquisition schemes for hyperpolarised ¹³C imaging.

The aim of this study was to characterise and compare widely used acquisition strategies for hyperpolarised (13)C imaging. Free induction decay chemical shift imaging (FIDCSI), echo-planar spectroscopic imaging (EPSI), IDEAL spiral chemical shift imaging (ISPCSI) and spiral chemical shift imaging (SPCSI) sequences were designed for two different regimes of spatial resolution. Their characteristics were studied in simulations and in tumour-bearing rats after injection of hyperpolarised [1-(13)C]pyruvate on a clinical 3-T scanner. Two or three different sequences were used on the same rat in random order for direct comparison. The experimentally obtained lactate signal-to-noise ratio (SNR) in the tumour matched the simulations. Differences between the sequences were mainly found in the encoding efficiency, gradient demand and artefact behaviour. Although ISPCSI and SPCSI offer high encoding efficiencies, these non-Cartesian trajectories are more prone than EPSI and FIDCSI to artefacts from various sources. If the encoding efficiency is sufficient for the desired application, EPSI has been proven to be a robust choice. Otherwise, faster spiral acquisition schemes are recommended. The conclusions found in this work can be applied directly to clinical applications.

Multi-directional anisotropy from diffusion orientation distribution functions.

PURPOSE: To evaluate a model-independent, multi-directional anisotropy (MDA) metric that is analytically and experimentally equivalent to fractional anisotropy (FA) in single-direction diffusivity, but potentially superior to FA in its sensitivity to the underlying anisotropy of multi-directional diffusivity. MATERIALS AND METHODS: An expression for MDA was defined from the orientation distribution function (ODF) and its analytical relation to FA was derived. Simulations of single and crossed double-fibers were performed using a compressed-sensing-accelerated diffusion-spectrum-imaging (CS-DSI) scheme. In vivo brain imaging using CS-DSI was performed on eight healthy subjects. MDA was compared with FA and with another ODF-based metric known as generalized FA (GFA). RESULTS: In simulated single-direction fibers, MDA was shown to be equivalent to FA (from FA = 0.2 to 0.8). In crossed fibers, MDA provided superior differentiation of the underlying anisotropy as compared to FA and GFA. In vivo analysis shows that the MDA was superior to both FA (P = 0.015) and GFA (P = 0.021) in terms of its relative accuracy in crossed fiber regions. CONCLUSION: MDA provides a potentially superior measure of fiber anisotropy relative to conventional FA or GFA, and may be used to improve the assessment of disease in regions with multi-directional brain fibers.

Parameterization of hyperpolarized (13)C-bicarbonate-dissolution dynamic nuclear polarization.

OBJECTIVE: (13)C metabolic MRI using hyperpolarized (13)C-bicarbonate enables preclinical detection of pH. To improve signal-to-noise ratio, experimental procedures were refined, and the influence of pH, buffer capacity, temperature, and field strength were investigated. MATERIALS AND METHODS: Bicarbonate preparation was investigated. Bicarbonate was prepared and applied in spectroscopy at 1, 3, 14 T using pure dissolution, culture medium, and MCF-7 cell spheroids. Healthy rats were imaged by spectral-spatial spiral acquisition for spatial and temporal bicarbonate distribution, pH mapping, and signal decay analysis. RESULTS: An optimized preparation technique for maximum solubility of 6 mol/L and polarization levels of 19-21% is presented; T1 and SNR dependency on field strength, buffer capacity, and pH was investigated. pH mapping in vivo is demonstrated. CONCLUSION: An optimized bicarbonate preparation and experimental procedure provided improved T1 and SNR values, allowing in vitro and in vivo applications.

In vivo measurement of apparent diffusion coefficients of hyperpolarized ¹³C-labeled metabolites.

The combination of hyperpolarized MRS with diffusion weighting (dw) allows for determination of the apparent diffusion coefficient (ADC), which is indicative of the intra- or extracellular localization of the metabolite. Here, a slice-selective pulsed-gradient spin echo sequence was implemented to acquire a series of dw spectra from rat muscle in vivo to determine the ADCs of multiple metabolites after a single injection of hyperpolarized [1- ¹³C]pyruvate. An optimal control optimized universal-rotation pulse was used for refocusing to minimize signal loss caused by B1 imperfections. Non-dw spectra were acquired interleaved with the dw spectra and these were used to correct for signal decay during the acquisition as a result of T1 decay, pulse imperfections, flow etc. The data showed that the ADC values for [1- ¹³C]lactate (0.4-0.7 µm² /ms) and [1- ¹³C]alanine (0.4-0.9 µm² /ms) were about a factor of two lower than the ADC of [1- ¹³C]pyruvate (1.1-1.5 µm²/ms). This indicates a more restricted diffusion space for the former two metabolites consistent with lactate and alanine being intracellular. The higher ADC for pyruvate (similar to the proton ADC) reflected that the injected substance was not confined inside the muscle cells but also present extracellular.

Saturation-recovery metabolic-exchange rate imaging with hyperpolarized [1-13C] pyruvate using spectral-spatial excitation.

Within the last decade hyperpolarized [1-13C] pyruvate chemical-shift imaging has demonstrated impressive potential for metabolic MR imaging for a wide range of applications in oncology, cardiology, and neurology. In this work, a highly efficient pulse sequence is described for time-resolved, multislice chemical shift imaging of the injected substrate and obtained downstream metabolites. Using spectral-spatial excitation in combination with single-shot spiral data acquisition, the overall encoding is evenly distributed between excitation and signal reception, allowing the encoding of one full two-dimensional metabolite image per excitation. The signal-to-noise ratio can be flexibly adjusted and optimized using lower flip angles for the pyruvate substrate and larger ones for the downstream metabolites. Selectively adjusting the excitation of the down-stream metabolites to 90° leads to a so-called "saturation-recovery" scheme with the detected signal content being determined by forward conversion of the available pyruvate. In case of repetitive excitations, the polarization is preserved using smaller flip angles for pyruvate. Metabolic exchange rates are determined spatially resolved from the metabolite images using a simplified two-site exchange model. This novel contrast is an important step toward more quantitative metabolic imaging. Goal of this work was to derive, analyze, and implement this "saturation-recovery metabolic exchange rate imaging" and demonstrate its capabilities in four rats bearing subcutaneous tumors.

Diffusion of hyperpolarized (13) C-metabolites in tumor cell spheroids using real-time NMR spectroscopy.

The detection of tumors noninvasively, the characterization of their progression by defined markers and the monitoring of response to treatment are goals of medical imaging techniques. In this article, a method which measures the apparent diffusion coefficients (ADCs) of metabolites using hyperpolarized (13) C diffusion-weighted spectroscopy is presented. A pulse sequence based on the pulsed gradient spin echo (PGSE) was developed that encodes both kinetics and diffusion information. In experiments with MCF-7 human breast cancer cells, we detected an ADC of intracellularly produced lactate of 1.06 ± 0.15 µm(2) /ms, which is about one-half of the value measured with pyruvate in extracellular culture medium. When monitoring tumor cell spheroids during progressive membrane permeabilization with Triton X-100, the ratio of lactate ADC to pyruvate ADC increases as the fraction of dead cells increases. Therefore, (13) C ADC detection can yield sensitive information on changes in membrane permeability and subsequent cell death. Our results suggest that both metabolic label exchange and (13) C ADCs can be acquired simultaneously, and may potentially serve as noninvasive biomarkers for pathological changes in tumor cells.