Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network.

Objective. In MR-only clinical workflow, replacing CT with MR image is of advantage for workflow efficiency and reduces radiation to the patient. An important step required to eliminate CT scan from the workflow is to generate the information provided by CT via an MR image. In this work, we aim to demonstrate a method to generate accurate synthetic CT (sCT) from an MR image to suit the radiation therapy (RT) treatment planning workflow. We show the feasibility of the method and make way for a broader clinical evaluation.Approach. We present a machine learning method for sCT generation from zero-echo-time (ZTE) MRI aimed at structural and quantitative accuracies of the image, with a particular focus on the accurate bone density value prediction. The misestimation of bone density in the radiation path could lead to unintended dose delivery to the target volume and results in suboptimal treatment outcome. We propose a loss function that favors a spatially sparse bone region in the image. We harness the ability of the multi-task network to produce correlated outputs as a framework to enable localization of region of interest (RoI) via segmentation, emphasize regression of values within RoI and still retain the overall accuracy via global regression. The network is optimized by a composite loss function that combines a dedicated loss from each task.Main results. We have included 54 brain patient images in this study and tested the sCT images against reference CT on a subset of 20 cases. A pilot dose evaluation was performed on 9 of the 20 test cases to demonstrate the viability of the generated sCT in RT planning. The average quantitative metrics produced by the proposed method over the test set were-(a) mean absolute error (MAE) of 70 ± 8.6 HU; (b) peak signal-to-noise ratio (PSNR) of 29.4 ± 2.8 dB; structural similarity metric (SSIM) of 0.95 ± 0.02; and (d) Dice coefficient of the body region of 0.984 ± 0.Significance. We demonstrate that the proposed method generates sCT images that resemble visual characteristics of a real CT image and has a quantitative accuracy that suits RT dose planning application. We compare the dose calculation from the proposed sCT and the real CT in a radiation therapy treatment planning setup and show that sCT based planning falls within 0.5% target dose error. The method presented here with an initial dose evaluation makes an encouraging precursor to a broader clinical evaluation of sCT based RT planning on different anatomical regions.

CHAIMELEON Project: Creation of a Pan-European Repository of Health Imaging Data for the Development of AI-Powered Cancer Management Tools.

The CHAIMELEON project aims to set up a pan-European repository of health imaging data, tools and methodologies, with the ambition to set a standard and provide resources for future AI experimentation for cancer management. The project is a 4 year long, EU-funded project tackling some of the most ambitious research in the fields of biomedical imaging, artificial intelligence and cancer treatment, addressing the four types of cancer that currently have the highest prevalence worldwide: lung, breast, prostate and colorectal. To allow this, clinical partners and external collaborators will populate the repository with multimodality (MR, CT, PET/CT) imaging and related clinical data. Subsequently, AI developers will enable a multimodal analytical data engine facilitating the interpretation, extraction and exploitation of the information stored at the repository. The development and implementation of AI-powered pipelines will enable advancement towards automating data deidentification, curation, annotation, integrity securing and image harmonization. By the end of the project, the usability and performance of the repository as a tool fostering AI experimentation will be technically validated, including a validation subphase by world-class European AI developers, participating in Open Challenges to the AI Community. Upon successful validation of the repository, a set of selected AI tools will undergo early in-silico validation in observational clinical studies coordinated by leading experts in the partner hospitals. Tool performance will be assessed, including external independent validation on hallmark clinical decisions in response to some of the currently most important clinical end points in cancer. The project brings together a consortium of 18 European partners including hospitals, universities, R&D centers and private research companies, constituting an ecosystem of infrastructures, biobanks, AI/in-silico experimentation and cloud computing technologies in oncology.

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.

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.

Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy and Imaging.

In the past decades, new methods for tumor staging, restaging, treatment response monitoring, and recurrence detection of a variety of cancers have emerged in conjunction with the state-of-the-art positron emission tomography with 18F-fluorodeoxyglucose ([18F]-FDG PET). 13C magnetic resonance spectroscopic imaging (13CMRSI) is a minimally invasive imaging method that enables the monitoring of metabolism in vivo and in real time. As with any other method based on 13C nuclear magnetic resonance (NMR), it faces the challenge of low thermal polarization and a subsequent low signal-to-noise ratio due to the relatively low gyromagnetic ratio of 13C and its low natural abundance in biological samples. By overcoming these limitations, dynamic nuclear polarization (DNP) with subsequent sample dissolution has recently enabled commonly used NMR and magnetic resonance imaging (MRI) systems to measure, study, and image key metabolic pathways in various biological systems. A particularly interesting and promising molecule used in 13CMRSI is [1-13C]pyruvate, which, in the last ten years, has been widely used for in vitro, preclinical, and, more recently, clinical studies to investigate the cellular energy metabolism in cancer and other diseases. In this article, we outline the technique of dissolution DNP using a 3.35 T preclinical DNP hyperpolarizer and demonstrate its usage in in vitro studies. A similar protocol for hyperpolarization may be applied for the most part in in vivo studies as well. To do so, we used lactate dehydrogenase (LDH) and catalyzed the metabolic reaction of [1-13C]pyruvate to [1-13C]lactate in a prostate carcinoma cell line, PC3, in vitro using 13CMRSI.

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.

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.

Multimodal assessment of in vivo metabolism with hyperpolarized [1-13C]MR spectroscopy and 18F-FDG PET imaging in hepatocellular carcinoma tumor-bearing rats.

UNLABELLED: Abnormalities of tumor metabolism can be exploited for molecular imaging. PET imaging of (18)F-FDG is a well-established method using the avid glucose uptake of tumor cells. (13)C MR spectroscopic imaging (MRSI) of hyperpolarized [1-(13)C]pyruvate and its metabolites, meanwhile, represents a new method to study energy metabolism by visualizing, for example, the augmented lactate dehydrogenase activity in tumor cells. Because of rapid signal loss, this method underlies strict temporal limitations, and the acquisition of data-encoding spatial, temporal, and spectral information within this time frame-is challenging. The object of our study was to compare spectroscopic images with (18)F-FDG PET images for visualizing tumor metabolism in a rat model. METHODS: (13)C MRSI with IDEAL (Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation) chemical shift imaging in combination with single-shot spiral acquisition was used to obtain dynamic data from 23 rats bearing a subcutaneous hepatocellular carcinoma and from reference regions of the same animals. Static and dynamic analysis of (18)F-FDG PET images of the same animals was performed. The data were analyzed qualitatively (visual assessment) and quantitatively (magnitude and dynamics of (18)F-FDG uptake, (13)C MRSI dynamics, and physiologic parameters). RESULTS: In most animals increased [1-(13)C]lactate signals in the tumor could be detected by simple display of integrated [1-(13)C]lactate images with corresponding enhanced (18)F-FDG uptake. Low [1-(13)C]pyruvate or [1-(13)C]lactate signals did not correlate with histologic or physiologic parameters. Significantly less pyruvate reached the tumors than the gastrointestinal tract, but in tumors a significantly higher amount of pyruvate was converted to lactate and alanine within seconds after intravenous administration. CONCLUSION: This study reveals that PET and (13)C MRSI can be used to visualize increased glycolytic flux in malignant tissue. The combination of signals will allow the quantitative dissection of substrate metabolism, with respect to uptake and downstream metabolic pathways. Although hyperpolarized [1-(13)C]pyruvate increases the sensitivity of MR imaging, signal-to-noise ratio constraints still apply for spatially and temporally resolved (13)C MRSI, emphasizing the need for further MR methodologic development. These first imaging data suggest the feasibility of (13)C MRSI for future clinical use.

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.

Non-invasive determination of plant biomass with microwave resonators.

Non-invasive and rapid determination of plant biomass would be beneficial for a number of research aims. Here, we present a novel device to non-invasively determine plant water content as a proxy for plant biomass. It is based on changes of dielectric properties inside a microwave cavity resonator induced by inserted plant material. The water content of inserted shoots leads to a discrete shift in the centre frequency of the resonator. Calibration measurements with pure water showed good spatial homogeneity in the detection volume of the microwave resonators and clear correlations between water content and centre frequency shift. For cut tomato and tobacco shoots, linear correlations between fresh weight and centre frequency shift were established. These correlations were used to continuously monitor diel growth patterns of intact plants and to determine biomass increase over several days. Interferences from soil and root water were excluded by shielding pots with copper. The presented proof of principle shows that microwave resonators are promising tools to quantitatively detect the water content of plants and to determine plant biomass. As the method is non-invasive, integrative and fast, it provides the opportunity for detailed, dynamic analyses of plant growth, water status and phenotype.