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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.

This study was supported in part by the European Research Council Innovative Medicines Initiative (DRAGON#, H2020-JTI-IMI2 101005122), the AI for Health Imaging Award (CHAIMELEON##, H2020-SC1-FA-DTS-2019-1 952172), the UK Research and Innovation Future Leaders Fellowship (MR/V023799/1), the British Heart Foundation (Project Number: TG/18/5/34111, PG/16/78/32402), the SABRE project supported by Boehringer Ingelheim Ltd, the European Union's Horizon 2020 research and innovation programme (ICOVID, 101016131), the Euskampus Foundation (COVID19 Resilience, Ref. COnfVID19), and the Basque Government (consolidated research group MATHMODE, Ref. IT1294-19, and 3KIA project from the ELKARTEK funding program, Ref. KK-2020/00049)., 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., European Research Council Innovative Medicines Initiative H2020-JTI-IMI2 101005122, AI for Health Imaging Award H2020-SC1-FA-DTS-2019-1 952172, UK Research & Innovation (UKRI) MR/V023799/1, British Heart Foundation TG/18/5/34111 PG/16/78/32402, Boehringer Ingelheim, European Commission 101016131, Euskampus Foundation COnfVID19, Basque Government IT1294-19, Basque Government (3KIA project from the ELKARTEK funding program) KK-2020/00049

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.

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.

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.

Background: Non-invasive tumor characterization and monitoring are among the key goals of medical imaging. Using hyperpolarized 13C-labelled metabolic probes fast metabolic pathways can be probed in real-time, providing new opportunities for tumor characterization. In this in vitro study, we investigated whether measurement of apparent diffusion coefficient (ADC) measurements and magnetic resonance spectroscopy (MRS) of co-polarized 13C-labeled pyruvic acid and fumaric acid can non-invasively detect both necrosis and changes in lactate export, which are parameters indicative of tumor aggressiveness. Methods: 13C-labeled pyruvic acid and fumaric acid were co-polarized in a preclinical hyperpolarizer and the dissolved compounds were added to prepared samples of 8932 pancreatic cancer and MCF-7 breast carcinoma cells. Extracellular lactate concentrations and cell viability were measured in separate assays. Results: The mean ratios of the ADC values of lactate and pyruvate (ADClac/ADCpyr) between MCF-7 (0.533 ± 0.015, n = 3) and 8932 pancreatic cancer cells (0.744 ± 0.064, n = 3) showed a statistically significant difference (p = 0.048). 8932 cells had higher extracellular lactate concentrations in the extracellular medium (22.97 ± 2.53 ng/µl) compared with MCF-7 cells (7.52 ± 0.59 ng/µl; p < 0.001). Fumarate-to-malate conversion was only detectable in necrotic cells, thereby allowing clear differentiation between necrotic and viable cells. Conclusion: We provide evidence that MRS of hyperpolarized 13C-labelled pyruvic acid and fumaric acid, with their respective conversions to lactate and malate, are useful for characterization of necrosis and lactate efflux in tumor cells.

PURPOSE To introduce a robust methodology for fast 1 H MRSI of the brain at 3T with improved SNR and reduced phase-related artifacts. METHOD An accelerated acquisition scheme using echo-planar spectroscopic imaging (EPSI) was combined with the overdiscrete reconstruction framework. This approach enables the interleaved acquisition of a water reference scan at each phase encoding step, maximizing its correlation with the water-suppressed measurement. Moreover, a generalized high-order phase correction was incorporated into the reconstruction pipeline. The spatial-temporal phase correction term was estimated from the reference scan and interpolated to high resolution using a polynomial basis. The method was implemented at 3T and validated with phantom and in vivo experiments. RESULTS The methodology showed the elimination of spectral artifacts generated by phase disturbances and achieved mean SNR gains in vivo of 3.18 and 1.19 compared to standard reconstructions with corrections performed at nominal and high resolution, respectively. EPSI scans with interleaved water acquisition showed to be robust to system instabilities and potentially to patient motion. Moreover, phase distortions were effectively corrected in a single step, avoiding additional reference measurements and post-processing steps. CONCLUSION The overdiscrete reconstruction framework with high-order phase correction allowed to effectively correct for distortions, related to B0 inhomogeneities, B0 drift, eddy currents, and system vibrations. Furthermore, the presented reconstruction method, combined with EPSI acquisitions, demonstrated improved measurement stability, substantial SNR enhancement, better spectral linewidth, and effective artifact removal.

Magnetic resonance imaging (MRI) has evolved into an outstandingly versatile diagnostic modality, as it has the ability to non-invasively produce detailed information on a tissue’s structure and function. Complementary data is normally obtained in separate measurements, either as contrast-weighted images, which are fast and simple to acquire, or as quantitative parametric maps, which offer an absolute quantification of underlying biophysical effects, such as relaxation times or flow. Here, we demonstrate how to acquire and reconstruct data in a transient-state with a dual purpose: 1 – to generate contrast-weighted images that can be adjusted to emphasise clinically relevant image biomarkers; exemplified with signal modulation according to flow to obtain angiography information, and 2 – to simultaneously infer multiple quantitative parameters with a single, highly accelerated acquisition. This is achieved by introducing three novel elements: a model that accounts for flowing blood, a method for sequence design using smooth flip angle excitation patterns that incorporates both parameter encoding and signal contrast, and the reconstruction of temporally resolved contrast-weighted images. From these images we simultaneously obtain angiography projections and multiple quantitative maps. By doing so, we increase the amount of clinically relevant data without adding measurement time, creating new dimensions for biomarker exploration and adding value to MR examinations for patients and clinicians alike.

Purpose: To develop an accelerated Cartesian MRF implementation using a multi-shot EPI sequence for rapid simultaneous quantification of T1 and T2 parameters. Methods: The proposed Cartesian MRF method involved the acquisition of highly subsampled MR images using a 16-shot EPI readout. A linearly varying flip angle train was used for rapid, simultaneous T1 and T2 quantification. The accuracy of parametric map estimations were improved by using an iterative projection algorithm. The results were compared to a conventional spiral MRF implementation. The acquisition time per slice was 8s and this method was validated on a phantom and a healthy volunteer brain in vivo. Results: Joint T1 and T2 estimations using the 16-shot EPI readout are in good agreement with the spiral implementation using the same acquisition parameters (deviation less than 3% for T1 and less than 4% for T2) for the healthy volunteer brain. The T1 and T2 values also agree with the conventional values previously reported in the literature. The visual quality of the multi-parametric maps generated by the multi-shot EPI-MRF and spiral-MRF implementations were comparable. Conclusion: The multi-shot EPI-MRF method generated accurate quantitative multi-parametric maps similar to conventional Spiral - MRF. This multi-shot approach achieved provides an alternative for performing MRF using an accelerated Cartesian readout, thereby increasing the potential usability of MRF., Comment: 12 pages, 11 main figures, 2 supplementry figures, preprint of accepted abstract

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 [1-13C]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 [1-13C]pyruvate examinations. Copyright © 2016 John Wiley & Sons, Ltd.

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.

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.

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

This study aims to develop a silent, fast and 3D method for T1 and proton density (PD) mapping, while generating time series of T1-weighted (T1w) images with bias-field correction. Undersampled T1w images at different effective inversion times (TIs) were acquired using the inversion recovery prepared RUFIS sequence with an interleaved k-space trajectory. Unaliased images were reconstructed by constraining the signal evolution to a temporal subspace which was learned from the signal model. Parameter maps were obtained by fitting the data to the signal model, and bias-field correction was conducted on T1w images. Accuracy and repeatability of the method was accessed in repeated experiments with phantom and volunteers. For the phantom study, T1 values obtained by the proposed method were highly consistent with values from the gold standard method, R2 = 0.9976. Coefficients of variation (CVs) ranged from 0.09% to 0.83%. For the volunteer study, T1 values from gray and white matter regions were consistent with literature values, and peaks of gray and white matter can be clearly delineated on whole-brain T1 histograms. CVs ranged from 0.01% to 2.30%. The acoustic noise measured at the scanner isocenter was 2.6 dBA higher compared to the in-bore background. Rapid and with low acoustic noise, the proposed method is shown to produce accurate T1 and PD maps with high repeatability by reconstructing sparsely sampled T1w images at different TIs using temporal subspace. Our approach can greatly enhance patient comfort during examination and therefore increase the acceptance of the procedure.

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.

Molecular imaging is a medical and scientific discipline that enables a perturbation-free visualization of functional molecular processes in living organisms. It differs from the conventional imaging techniques by using probes known as biomarkers or tracers that interact physically or chemically with their surroundings and target certain metabolic processes or abnormalities. In this chapter, we want to present a closer look at today's most used and most promising molecular imaging modalities. We focus on modalities based on magnetic resonance spectroscopy and imaging combined with hyperpolarized probes, radiotracer-based single photon emission computed tomography (SPECT) and positron emission tomography (PET). Finally, emerging optical imaging modalities including bioluminescence imaging (BLI), fluorescence imaging (FI) and multi-spectral optoacoustic tomography (MSOT) are also described.