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Gadolinium-based contrast agents (GBCAs) are commonly used for enhancement in MR imaging and have long been considered safe when administered at recommended doses. However, since the report that nephrogenic systemic fibrosis is linked to the use of GBCAs in subjects with severe renal diseases, accumulating evidence has suggested that GBCAs are not cleared entirely from our bodies; some GBCAs are deposited in our tissues, including the brain. GBCA deposition in the brain is mostly linked to the specific chelate structure of the GBCA: linear GBCAs were responsible for brain deposition in almost all reported studies. This review aimed to summarize the current knowledge about GBCA brain deposition and discuss its clinical implications.

Gadolinium-based contrast agents (GBCAs) are frequently used in patients undergoing magnetic resonance imaging. In GBCAs gadolinium (Gd) is present in a bound chelated form. Gadolinium is a rare-earth element, which is normally not present in human body. Though the blood elimination half-life of contrast agents is about 90 minutes, recent studies demonstrated that some tissues retain gadolinium, which might further pose a health threat due to toxic effects of free gadolinium. It is known that the bone tissue can serve as a gadolinium depot, but so far only bulk measurements were performed. Here we present a summary of experiments in which for the first time we mapped gadolinium in bone biopsy from a male patient with idiopathic osteoporosis (without indication of renal impairment), who received MRI 8 months prior to biopsy. In our studies performed by means of synchrotron radiation induced micro- and submicro-X-ray fluorescence spectroscopy (SR-XRF), gadolinium was detected in human cortical bone tissue. The distribution of gadolinium displays a specific accumulation pattern. Correlation of elemental maps obtained at ANKA synchrotron with qBEI images (quantitative backscattered electron imaging) allowed assignment of Gd structures to the histological bone structures. Follow-up beamtimes at ESRF and Diamond Light Source using submicro-SR-XRF allowed resolving thin Gd structures in cortical bone, as well as correlating them with calcium and zinc.

Conventional approaches to material decomposition in spectral CT face challenges related to precise algorithm calibration across imaged conditions and low signal quality caused by variable object size and reduced dose. In this proof-of-principle study, a deep learning approach to multi-material decomposition was developed to quantify iodine, gadolinium, and calcium in spectral CT. A dual-phase network architecture was trained using synthetic datasets containing computational models of cylindrical and virtual patient phantoms. Classification and quantification performance was evaluated across a range of patient size and dose parameters. The model was found to accurately classify (accuracy: cylinders – 98%, virtual patients – 97%) and quantify materials (mean absolute percentage difference: cylinders – 8–10%, virtual patients – 10–15%) in both datasets. Performance in virtual patient phantoms improved as the hybrid training dataset included a larger contingent of virtual patient phantoms (accuracy: 48% with 0 virtual patients to 97% with 8 virtual patients). For both datasets, the algorithm was able to maintain strong performance under challenging conditions of large patient size and reduced dose. This study shows the validity of a deep-learning based approach to multi-material decomposition trained with in-silico images that can overcome the limitations of conventional material decomposition approaches.

Ménière’s Disease (MD) is difficult to diagnose and evaluate objectively over the course of treatment. Recently, several studies have reported MD diagnoses by MRI-based endolymphatic hydrops (EH) analysis. However, this method is time-consuming and complicated. Therefore, a fast, objective, and accurate evaluation tool is necessary. The purpose of this study was to develop an algorithm that can accurately analyze EH on intravenous (IV) gadolinium (Gd)-enhanced inner-ear MRI using artificial intelligence (AI) with deep learning. In this study, we developed a convolutional neural network (CNN)-based deep-learning model named INHEARIT (INner ear Hydrops Estimation via ARtificial InTelligence) for the automatic segmentation of the cochlea and vestibule, and calculation of the EH ratio in the segmented region. Measurement of the EH ratio was performed manually by a neuro-otologist and neuro-radiologist and by estimation with the INHEARIT model and were highly consistent (intraclass correlation coefficient = 0.971). This is the first study to demonstrate that automated EH ratio measurements are possible, which is important in the current clinical context where the usefulness of IV-Gd inner-ear MRI for MD diagnosis is increasing.

Hydrophilic interaction chromatography (HILIC) coupled with inductively coupled plasma mass spectrometry (ICP-MS) were optimised for the direct determination of gadolinium-based contrast agents in tap water. In comparison to our previous work, a new developed zwitterionic HILIC column (ZIC- c HILIC) was used for speciation of Gd-containing contrast agents. The limit of quantification (LOQ) for the five contrast agents Gd-BOPTA, Gd-DPTA-BMA, Gd-BT-DO3A, Gd-DOTA and Gd-DTPA are in the range of 5–12 ng Gd per litre. Additionally, a new internal standard, Pr-DOTA, was investigated to correct intensity drifts, minor and major changes in the sample volumes and possible matrix effects. With the speciation method described, tap water samples from the area of Berlin were analysed and for the first time, three Gd species, Gd-BT-DO3A, Gd-DOTA and Gd-BOPTA, were found in tap water samples at concentrations of about 10–20 ng Gd per litre. These are the same Gd species which have been previously detected predominantly in surface waters of the Berlin area.

The use of environmental tracers brings comprehensive benefits to the management of water resources since it helps to prevent their pollution, minimize public health risks, and thus reduce the impact of urbanization. In Brazil, the Guarani Aquifer System (GAS) has strategic and environmental importance, making its preservation and sustainable exploitation mandatory. The present study aimed at evaluating sources of contamination in the GAS using the combination of geochemical data and two environmental tracers: nitrate isotopes ( 15 N NO3 and 18 O NO3 ) and one rare earth element (Gadolinium—Gd). For that, five wells—four exploiting the GAS and one the Bauru Aquifer System (BAS)—were selected to discuss the human inputs in groundwater used for public supply in an urban area. Traditional physicochemical analyses were conducted for six campaign samplings and nitrate monitoring for this period was evaluated on a time scale, also considering the accumulated rainfall. Besides that, the double isotopic method (DIM), e.g., δ 18 O NO3 e δ 15 N NO3 , was applied to identify the fractionation and enable the distinction of the nitrate contamination source. In addition, the determination of anomalies of Gd, a wastewater-derived contaminant, was also performed to verify recent human inputs in groundwater. The results show that the local existence of nitrate in the GAS and BAS—even at low concentrations (values from 0.26 to 6.68 mg L −1 )—originated from anthropogenic inputs (septic waste), as indicates the typical isotopic signals ratio in the isotopic approach. Associated with that, the evaluation of Gd permitted the separation of groundwater samples into older or more recent leakages. The use of environmental tracers to assess anthropogenic inputs in groundwater reiterates the importance of adopting more effective protection strategies for water resources management systems, in order to prevent contamination. Graphical Abstract

Background Unlike most other commodities, rare earth elements (REEs) are part of a wide range of applications needed for daily life all over the world. These applications range from cell phones to electric vehicles to wind turbines. They are often declared as part of “green technology” and, therefore, often called “green elements”. However, their production and use are not only useful but also risky to the environment and human health, as many studies have shown. Consequently, the range of global research efforts is broad and highly variable, and therefore difficult to capture and assess. Hence, this study aims to assess the global parameters of global research on REE in the context of environment and health (REE eh ). In addition to established bibliometric parameters, advanced analyses using market driver and scientific infrastructure values were carried out to provide deep insight into incentives, necessities, and barriers to international research. Results The focus of REE research is in line with national aspirations, especially from the major global players, China and the USA. Whereas globally, regional research interests are related to market interests, as evidenced by the inclusion of drivers such as electric vehicles, wind turbines, and permanent magnets. The topics receiving the most attention are related to gadolinium used for magnetic resonance imaging and the use of ceria nanoparticles. Since both are used for medical purposes, the medical research areas are equally profiled and mainly addressed in high-income countries. Nevertheless, environmental issues are increasingly in focus. Conclusions There is still a need for research that is independent and open-ended. For this, market-independent technologies, substitutes and recycling of REEs need to be addressed scientifically. The results of this study are relevant for all stakeholders, from individual scientists to planners to funders, to improve future research strategies in line with these research mandates. Graphical Abstract

Prostate lesions detected with multiparametric magnetic resonance imaging (mpMRI) are classified for their malignant potential according to the Prostate Imaging-Reporting And Data System (PI-RADS™2). In this study, we evaluate the diagnostic accuracy of the mpMRI with and without gadolinium, with emphasis on the added diagnostic value of the dynamic contrast enhancement (DCE). The study was retrospective for 286 prostate lesions / 213 eligible patients, n = 116/170, and 49/59% malignant for the peripheral (Pz) and transitional zone (Tz), respectively. A stereotactic MRI-guided prostate biopsy served as the histological ground truth. All patients received a mpMRI with DCE. The influence of DCE in the prediction of malignancy was analyzed by blinded assessment of the imaging protocol without DCE and the DCE separately. Significant (CSPca) and insignificant (IPca) prostate cancers were evaluated separately to enhance the potential effects of the DCE in the detection of CSPca. The Receiver Operating Characteristics Area Under Curve (ROC-AUC), sensitivity (Se) and specificity (Spe) of PIRADS-without-DCE in the Pz was 0.70/0.47/0.86 for all cancers (IPca and CSPca merged) and 0.73/0.54/0.82 for CSPca. PIRADS-with-DCE for the same patients showed ROC-AUC/Se/Spe of 0.70/0.49/0.86 for all Pz cancers and 0.69/0.54/0.81 for CSPca in the Pz, respectively, p>0.05 chi-squared test. Similar results for the Tz, AUC/Se/Spe for PIRADS-without-DCE was 0.75/0.61/0.79 all cancers and 0.67/0.54/0.71 for CSPca, not influenced by DCE (0.66/0.47/0.81 for all Tz cancers and 0.61/0.39/0.75 for CSPca in Tz). The added Se and Spe of DCE for the detection of CSPca was 88/34% and 78/33% in the Pz and Tz, respectively. DCE showed no significant added diagnostic value and lower specificity for the prediction of CSPca compared to the non-enhanced sequences. Our results support that gadolinium might be omitted without mitigating the diagnostic accuracy of the mpMRI for prostate cancer.

We investigated the tracking potential of a magnetic resonance imaging (MRI) probe made of gadolinium-doped mesoporous silica MCM-41 (Gd(2)O(3)@MCM-41) nanoparticles for transplanted bone mesenchymal stem cells (MSCs) and neural stem cells (NSCs) in vivo. The nanoparticles, synthesized using a one-step synthetic method, possess hexagonal mesoporous structures with appropriate assembly of nanoscale Gd(2)O(3) clusters. They show little cytotoxicity against proliferation and have a lower effect on the inherent differentiation potential of these labeled stem cells. The tracking of labeled NSCs in murine brains was dynamically determined with a clinical 3T MRI system for at least 14 days. The migration of labeled NSCs identified by MRI corresponded to the results of immunofluorescence imaging. Our study confirms that Gd(2)O(3)@MCM-41 particles can serve as an ideal vector for long-term MRI tracking of MSCs and NSCs in vivo.

Objectives The aim of this study was to evaluate the feasibility and accuracy of dual-layer spectral detector CT (SDCT) for the quantification of clinically encountered gadolinium concentrations. Methods The cardiac chamber of an anthropomorphic thoracic phantom was equipped with 14 tubular inserts containing different gadolinium concentrations, ranging from 0 to 26.3 mg/mL (0.0, 0.1, 0.2, 0.4, 0.5, 1.0, 2.0, 3.0, 4.0, 5.1, 10.6, 15.7, 20.7 and 26.3 mg/mL). Images were acquired using a novel 64-detector row SDCT system at 120 and 140 kVp. Acquisitions were repeated five times to assess reproducibility. Regions of interest (ROIs) were drawn on three slices per insert. A spectral plot was extracted for every ROI and mean attenuation profiles were fitted to known attenuation profiles of water and pure gadolinium using in-house-developed software to calculate gadolinium concentrations. Results At both 120 and 140 kVp, excellent correlations between scan repetitions and true and measured gadolinium concentrations were found ( R  > 0.99, P  < 0.001; ICCs > 0.99, CI 0.99–1.00). Relative mean measurement errors stayed below 10% down to 2.0 mg/mL true gadolinium concentration at 120 kVp and below 5% down to 1.0 mg/mL true gadolinium concentration at 140 kVp. Conclusion SDCT allows for accurate quantification of gadolinium at both 120 and 140 kVp. Lowest measurement errors were found for 140 kVp acquisitions. Key Points • Gadolinium quantification may be useful in patients with contraindication to iodine. • Dual-layer spectral detector CT allows for overall accurate quantification of gadolinium. • Interscan variability of gadolinium quantification using SDCT material decomposition is excellent.