A multi-residue method for trace analysis of pesticides in soils with special emphasis on rigorous quality control.

A multi-residue trace analytical method is presented to accurately quantify 146 currently used pesticides in (agricultural) soils with varying soil properties. Pesticides were extracted using an optimized quick, easy, cheap, effective, rugged, and safe (QuEChERS) approach and chemical analysis was carried out by liquid chromatography coupled to tandem mass spectrometry (triple quadrupole). Quantification was based on matrix-matched internal standards calibration, using 95 isotopically labeled analyte analogues. In contrast to the common approach of method validation using soils freshly spiked with analytes shortly before the extraction, our method is additionally validated via an in-house prepared partly aged soil, which contains all target pesticides and via agricultural field soils with native pesticide residues. The developed method is highly sensitive (median method limit of quantification: 0.2 ng/g), precise (e.g., median intra-day and inter-day method precision both ~ 4% based on field soils), and true ((i) quantified pesticide concentrations of the partly aged soil remained stable during 6 months, were close to the initially spiked nominal concentration of 10 ng/g, and thus can be used to review trueness in the future; (ii) median freshly spiked relative recovery: 103%; and (iii) participation in a ring trial: median z-scores close to one (good to satisfactory result)). Its application to selected Swiss (agricultural) soils revealed the presence of in total 77 different pesticides with sum concentrations up to 500 ng/g. The method is now in use for routine soil monitoring as part of the Swiss Action Plan for Risk Reduction and Sustainable Use of Plant Protection Products.

Geochemical Soil Atlas of Switzerland - Distribution of Toxic Elements.

Chemical elements such as copper and molybdenum are essential for animal and human health but may become toxic at elevated concentrations depending on the exposure and intake rate. Other elements such as mercury pose a threat to human health at already low concentrations. The soil acts as the main source of these elements for plant uptake and is thus driving accumulation along the food chain. However, in Switzerland, no nationwide information on elemental distributions in soils has existed up to now. The geochemical soil atlas of Switzerland will fill this gap by presenting the concentration ranges and the spatial distribution of 20 elements in the topsoil. In this summary, we present the methodological approaches and some main findings of the atlas with a focus on toxic elements as well as elements that can be or are toxic at higher concentrations.

Pesticides in Agricultural Soils: Major Findings from Various Monitoring Campaigns in Switzerland.

Synthetic pesticides are widely applied in modern agriculture, where they are used against diseases, pests, and weeds to secure crop yield and quality. However, their intensive application has led to widespread contamination of the environment, including soils. Due to their inherent toxicity, they might pose a risk to soil health by causing harm to non-target organisms and disrupting ecosystem services in both agricultural and other exposed soils. Following the Swiss National Action Plan on the reduction of pesticide risks, Agroscope has conducted several soil monitoring studies that are briefly presented here. All of them resort to different multi-residue trace analytical approaches to simultaneously quantify up to about 150 modern pesticides by either accelerated solvent, or Quick, Easy, Cheap, Efficient, Rugged, Safe (QuEChERS) extraction, followed by separation and detection with liquid chromatography-triple quadrupole mass spectrometry. While partly still in progress, our investigations led to the following major findings this far: Multiple pesticides are commonly present in soils, with individual concentrations in agricultural soils often reaching up to a few tens of µg/kg. Pesticide occurrence and concentrations in agricultural soils primarily depend on land use, land use history and cultivated crops. Pesticides can prevail much longer than predicted by their half-lives, and were found in soils even decades after conversion from conventional to organic farming. Corresponding residual fractions can be in the order of a few percent of the originally applied amounts. We further found negative associations of pesticide residues with the abundance of beneficial soil life, underpinning their potential risk to the fertility of agricultural soils. Traces of pesticides are also detected in soils to which they were never applied, indicating contamination, e.g., via spray drift or atmospheric deposition. These results confirm the general notion of both scientists and legislators that prospective risk assessments (RA; as executed during registration and use authorization) should be confirmed and adjusted by retrospective RA (e.g., by environmental monitoring studies of currently used compounds) to jointly lead to an overall reduced environmental risk of pesticides.

Data-driven myelin water imaging based on T1 and T2 relaxometry.

Long acquisition times preclude the application of multiecho spin echo (MESE) sequences for myelin water fraction (MWF) mapping in daily clinical practice. In search of alternative methods, previous studies of interest explored the biophysical modeling of MWF from measurements of different tissue properties that can be obtained in scan times shorter than those required for the MESE. In this work, a novel data-driven estimation of MWF maps from fast relaxometry measurements is proposed and investigated. T1 and T2 relaxometry maps were acquired in a cohort of 20 healthy subjects along with a conventional MESE sequence. Whole-brain quantitative mapping was achieved with a fast protocol in 6 min 24 s. Reference MWF maps were derived from the MESE sequence (TA = 11 min 17 s) and their data-driven estimation from relaxometry measurements was investigated using three different modeling strategies: two general linear models (GLMs) with linear and quadratic regressors, respectively; a random forest regression model; and two deep neural network architectures, a U-Net and a conditional generative adversarial network (cGAN). Models were validated using a 10-fold crossvalidation. The resulting maps were visually and quantitatively compared by computing the root mean squared error (RMSE) between the estimated and reference MWF maps, the intraclass correlation coefficients (ICCs) between corresponding MWF values in different brain regions, and by performing Bland-Altman analysis. Qualitatively, the estimated maps appear to generally provide a similar, yet more blurred MWF contrast in comparison with the reference, with the cGAN model best capturing MWF variabilities in small structures. By estimating the average adjusted coefficient of determination of the GLM with quadratic regressors, we showed that 87% of the variability in the MWF values can be explained by relaxation times alone. Further quantitative analysis showed an average RMSE smaller than 0.1% for all methods. The ICC was greater than 0.81 for all methods, and the bias smaller than 2.19%. It was concluded that this work confirms the notion that relaxometry parameters contain a large part of the information on myelin water and that MWF maps can be generated from T1 /T2 data with minimal error. Among the investigated modeling approaches, the cGAN provided maps with the best trade-off between accuracy and blurriness. Fast relaxometry, like the 6 min 24 s whole-brain protocol used in this work in conjunction with machine learning, may thus have the potential to replace time-consuming MESE acquisitions.

MRI software for diffusion-perfusion mismatch analysis may impact on patients' selection and clinical outcome.

OBJECTIVE: Impact of different MR perfusion software on selection and outcome of patients with acute ischemic stroke (AIS) and large vessel occlusion (LVO) treated by endovascular thrombectomy (EVT) is unclear. We aimed at comparing two commercial MRI software, semi-automated with unadjusted (method A) and adjusted mask (method B), and fully automated (method C) in this setting. METHODS: MRI from 144 consecutive AIS patients with anterior circulation LVO was retrospectively analysed. All diffusion- and perfusion-weighted images (DWI-PWI) were post-processed with the three methods using standard thresholds. Concordance for core and hypoperfusion volumes was assessed with Lin's test. Clinical outcome was compared between groups in patients who underwent successful EVT in the early and late time window. RESULTS: Mean core volume was higher and mean hypoperfusion volume was lower in method C than in methods A and B. In the early time window, methods A and B found fewer patients with a mismatch ratio ≤ 1.2 than method C (1/67 [1.5%] vs. 12/67 [17.9%], p = 0.0013). In the late time window, methods A and B found fewer patients with a mismatch ratio < 1.8 than method C (3/46 [6.5%] and 2/46 [4.3%] vs. 18/46 [39.1%], p ≤ 0.0002). More patients with functional independence at 3 months would not have been treated using method C versus methods A and B in the early (p = 0.0063) and late (p ≤ 0.011) time window. CONCLUSIONS: MRI software for DWI-PWI analysis may influence patients' selection before EVT and clinical outcome. KEY POINTS: • Method C detects fewer patients with favourable mismatch profile. • Method C might underselect more patients with functional independence at 3 months. • Software used before thrombectomy may influence patients' outcome.

Fast and high-resolution myelin water imaging: Accelerating multi-echo GRASE with CAIPIRINHA.

PURPOSE: Although several MRI methods have been explored to achieve in vivo myelin quantification, imaging the whole brain in clinically acceptable times and sufficiently high resolution remains challenging. To address this problem, this work investigates the acceleration of multi-echo T2 acquisitions based on the multi-echo gradient and spin echo (GRASE) sequence using CAIPIRINHA undersampling and adapted k-space reordering patterns. METHODS: A prototype multi-echo GRASE sequence supporting CAIPIRINHA parallel imaging was implemented. Multi-echo T2 data were acquired from 12 volunteers using the implemented sequence (1.6 × 1.6 × 1.6 mm3 , 84 slices, acquisition time [TA] = 10:30 min) and a multi-echo spin echo (MESE) sequence as reference (1.6 × 1.6 × 3.2 mm3 , single-slice, TA = 5:41 min). Myelin water fraction (MWF) maps derived from both acquisitions were compared via correlation and Bland-Altman analyses. In addition, scan-rescan datasets were acquired to evaluate the repeatability of the derived maps. RESULTS: Resulting maps from the MESE and multi-echo GRASE sequences were found to be correlated (r = 0.83). The Bland-Altman analysis revealed a mean bias of -0.2% (P = .24) with the limits of agreement ranging from -3.7% to 3.3%. The Pearson's correlation coefficient among MWF values obtained from the scan-rescan datasets was found to be 0.95 and the mean bias equal to 0.11% (P = .32), indicating good repeatability of the retrieved maps. CONCLUSION: By combining a 3D multi-echo GRASE sequence with CAIPIRINHA sampling, whole-brain MWF maps were obtained in 10:30 min with 1.6 mm isotropic resolution. The good correlation with conventional MESE-based maps demonstrates that the implemented sequence may be a promising alternative to time-consuming MESE acquisitions.

Long-term stability of soil bacterial and fungal community structures revealed in their abundant and rare fractions.

Despite the importance of soil microorganisms for ecosystem services, long-term surveys of their communities are largely missing. Using metabarcoding, we assessed temporal dynamics of soil bacterial and fungal communities in three land-use types, i.e., arable land, permanent grassland, and forest, over five years. Soil microbial communities remained relatively stable and differences over time were smaller than those among sites. Temporal variability was highest in arable soils. Indications for consistent shifts in community structure over five years were only detected at one site for bacteria and at two sites for fungi, which provided further support for long-term stability of soil microbial communities. A sliding window analysis was applied to assess the effect of OTU abundance on community structures. Partial communities with decreasing OTU abundances revealed a gradually decreasing structural similarity with entire communities. This contrasted with the steep decline of OTU abundances, as subsets of rare OTUs (<0.01%) revealed correlations of up to 0.97 and 0.81 with the entire bacterial and fungal communities. Finally, 23.4% of bacterial and 19.8% of fungal OTUs were identified as scarce, i.e., neither belonging to site-cores nor correlating to environmental factors, while 67.3% of bacterial and 64.9% of fungal OTUs were identified as rare but not scarce. Our results demonstrate high stability of soil microbial communities in their abundant and rare fractions over five years. This provides a step towards defining site-specific normal operating ranges of soil microbial communities, which is a prerequisite for detecting community shifts that may occur due to changing environmental conditions or anthropogenic activities.

Reduced-iodine-dose dual-energy coronary CT angiography: qualitative and quantitative comparison between virtual monochromatic and polychromatic CT images.

OBJECTIVES: To quantitatively evaluate the impact of virtual monochromatic images (VMI) on reduced-iodine-dose dual-energy coronary computed tomography angiography (CCTA) in terms of coronary lumen segmentation in vitro, and secondly to assess the image quality in vivo, compared with conventional CT obtained with regular iodine dose. MATERIALS AND METHODS: A phantom simulating regular and reduced iodine injection was used to determine the accuracy and precision of lumen area segmentation for various VMI energy levels. We retrospectively included 203 patients from December 2017 to August 2018 (mean age, 51.7 ± 16.8 years) who underwent CCTA using either standard (group A, n = 103) or reduced (group B, n = 100) iodine doses. Conventional images (group A) were qualitatively and quantitatively compared with 55-keV VMI (group B). We recorded the location of venous catheters. RESULTS: In vitro, VMI outperformed conventional CT, with a segmentation accuracy of 0.998 vs. 1.684 mm2, respectively (p < 0.001), and a precision of 0.982 vs. 1.229 mm2, respectively (p < 0.001), in simulated overweight adult subjects. In vivo, the rate of diagnostic CCTA in groups A and B was 88.4% (n = 91/103) vs. 89% (n = 89/100), respectively, and noninferiority of protocol B was inferred. Contrast-to-noise ratios (CNR) of lumen versus fat and muscle were higher in group B (p < 0.001) and comparable for lumen versus calcium (p = 0.423). Venous catheters were more often placed on the forearm or hand in group B (p < 0.001). CONCLUSION: In vitro, low-keV VMI improve vessel area segmentation. In vivo, low-keV VMI allows for a 40% iodine dose and injection rate reduction while maintaining diagnostic image quality and improves the CNR between lumen versus fat and muscle. KEY POINTS: • Dual-energy coronary CT angiography is becoming increasingly available and might help improve patient management. • Compared with regular-iodine-dose coronary CT angiography, reduced-iodine-dose dual-energy CT with low-keV monochromatic image reconstructions performed better in phantom-based vessel cross-sectional segmentation and proved to be noninferior in vivo. • Patients receiving reduced-iodine-dose dual-energy coronary CT angiography often had the venous catheter placed on the forearm or wrist without compromising image quality.

Accelerated MP2RAGE imaging using Cartesian phyllotaxis readout and compressed sensing reconstruction.

PURPOSE: MP2RAGE T1 -weighted imaging has been shown to be beneficial for various applications, mainly because of its good grey-white matter contrast, its B1 -robustness and ability to derive T1 maps. Even using parallel imaging, the method requires long acquisition times, especially at high resolution. This work aims at accelerating MP2RAGE imaging using compressed sensing. METHODS: A pseudo-phyllotactic Cartesian MP2RAGE readout was implemented allowing for flexible reordering and undersampling factors. The sampling pattern was first optimized based on fully sampled data and a compressed sensing reconstruction. Changes in contrast ratios, automated brain segmentation results, and quantitative T1 values were used for benchmarking. In vivo undersampled data from eleven healthy subjects were then acquired using a 4-fold acceleration with the optimized sampling pattern. The resulting images were compared to the standard parallel imaging MP2RAGE protocol by visual inspection and using the above quality metrics. RESULTS: The application of incoherent undersampling and iterative compressed sensing reconstruction on MP2RAGE acquisitions allows for a 57% time reduction (corresponding to 4-fold undersampling with maintained reference lines, TA = 3:35 minutes) compared to the reference protocol using parallel imaging (GRAPPAx3 acceleration, TA = 8:22 minutes) while obtaining images with similar image quality, morphometric (volume differences = [0.07 ± 1.2-3.8 ± 1.9]%) and T1 -mapping outcomes (T1 error = [6 ± 5.1-37 ± 12.3] ms depending on the different structures). CONCLUSION: A whole-brain MP2RAGE acquisition is feasible with compressed sensing in less than 4 minutes without appreciably compromising image quality.

Model-based super-resolution reconstruction of T2 maps.

PURPOSE: High-resolution isotropic T2 mapping of the human brain with multi-echo spin-echo (MESE) acquisitions is challenging. When using a 2D sequence, the resolution is limited by the slice thickness. If used as a 3D acquisition, specific absorption rate limits are easily exceeded due to the high power deposition of nonselective refocusing pulses. A method to reconstruct 1-mm3 isotropic T2 maps is proposed based on multiple 2D MESE acquisitions. Data were undersampled (10-fold) to compensate for the prolonged scan time stemming from the super-resolution acquisition. THEORY AND METHODS: The proposed method integrates a classical super-resolution with an iterative model-based approach to reconstruct quantitative maps from a set of undersampled low-resolution data. The method was tested on numerical and multipurpose phantoms, and in vivo data. T2 values were assessed with a region-of-interest analysis using a single-slice spin-echo and a fully sampled MESE acquisition in a phantom, and a MESE acquisition in healthy volunteers. RESULTS: Numerical simulations showed that the best trade-off between acceleration and number of low-resolution datasets is 10-fold acceleration with 4 acquisitions (acquisition time = 18 min). The proposed approach showed improved resolution over low-resolution images for both phantom and brain. Region-of-interest analysis of the phantom compartments revealed that at shorter T2 , the proposed method was comparable with the fully sampled MESE. For the volunteer data, the T2 values found in the brain structures were consistent across subjects (8.5-13.1 ms standard deviation). CONCLUSION: The proposed method addresses the inherent limitations associated with high-resolution T2 mapping and enables the reconstruction of 1 mm3 isotropic relaxation maps with a 10 times faster acquisition.

Quantitative brain relaxation atlases for personalized detection and characterization of brain pathology.

PURPOSE: To exploit the improved comparability and hardware independency of quantitative MRI, databases of MR physical parameters in healthy tissue are required, to which tissue properties of patients can be compared. In this work, normative values for longitudinal and transverse relaxation times in the brain were established and tested in single-subject comparisons for detection of abnormal relaxation times. METHODS: Relaxometry maps of the brain were acquired from 52 healthy volunteers. After spatially normalizing the volumes into a common space, T1 and T2 inter-subject variability within the healthy cohort was modeled voxel-wise. A method for a single-subject comparison against the atlases was developed by computing z-scores with respect to the established healthy norms. The comparison was applied to two multiple sclerosis and one clinically isolated syndrome cases for a proof of concept. RESULTS: The established atlases exhibit a low variation in white matter structures (median RMSE of models equal to 32 ms for T1 and 4 ms for T2 ), indicating that relaxation times are in a narrow range for normal tissues. The proposed method for single-subject comparison detected relaxation time deviations from healthy norms in the example patient data sets. Relaxation times were found to be increased in brain lesions (mean z-scores >5). Moreover, subtle and confluent differences (z-scores ~2-4) were observed in clinically plausible regions (between lesions, corpus callosum). CONCLUSIONS: Brain T1 and T2 quantitative norms were derived voxel-wise with low variability in healthy tissue. Example patient deviation maps demonstrated good sensitivity of the atlases for detecting relaxation time alterations.

CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis.

The central vein sign (CVS) is an efficient imaging biomarker for multiple sclerosis (MS) diagnosis, but its application in clinical routine is limited by inter-rater variability and the expenditure of time associated with manual assessment. We describe a deep learning-based prototype for automated assessment of the CVS in white matter MS lesions using data from three different imaging centers. We retrospectively analyzed data from 3 T magnetic resonance images acquired on four scanners from two different vendors, including adults with MS (n = 42), MS mimics (n = 33, encompassing 12 distinct neurological diseases mimicking MS) and uncertain diagnosis (n = 5). Brain white matter lesions were manually segmented on FLAIR* images. Perivenular assessment was performed according to consensus guidelines and used as ground truth, yielding 539 CVS-positive (CVS+ ) and 448 CVS-negative (CVS- ) lesions. A 3D convolutional neural network ("CVSnet") was designed and trained on 47 datasets, keeping 33 for testing. FLAIR* lesion patches of CVS+ /CVS- lesions were used for training and validation (n = 375/298) and for testing (n = 164/150). Performance was evaluated lesion-wise and subject-wise and compared with a state-of-the-art vesselness filtering approach through McNemar's test. The proposed CVSnet approached human performance, with lesion-wise median balanced accuracy of 81%, and subject-wise balanced accuracy of 89% on the validation set, and 91% on the test set. The process of CVS assessment, in previously manually segmented lesions, was ~ 600-fold faster using the proposed CVSnet compared with human visual assessment (test set: 4 seconds vs. 40 minutes). On the validation and test sets, the lesion-wise performance outperformed the vesselness filter method (P < 0.001). The proposed deep learning prototype shows promising performance in differentiating MS from its mimics. Our approach was evaluated using data from different hospitals, enabling larger multicenter trials to evaluate the benefit of introducing the CVS marker into MS diagnostic criteria.

Re: Does Gadoterate Meglumine Cause Gadolinium Retention in the Brain of Children? A Case-Control Study.

LEVEL OF EVIDENCE: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2020;52:636-637.

The "central vein sign" in patients with diagnostic "red flags" for multiple sclerosis: A prospective multicenter 3T study.

BACKGROUND: The central vein sign (CVS) has been shown to help in the differential diagnosis of multiple sclerosis (MS), but most prior studies are retrospective. OBJECTIVES: To prospectively assess the diagnostic predictive value of the CVS in diagnostically difficult cases. METHODS: In this prospective multicenter study, 51 patients with suspected MS who had clinical, imaging, or laboratory "red flags" (i.e. features atypical for MS) underwent 3T fluid-attenuated inversion recovery (FLAIR*) magnetic resonance imaging (MRI) for CVS assessment. After the diagnostic work-up, expert clinicians blinded to the results of the CVS assessment came to a clinical diagnosis. The value of the CVS to prospectively predict an MS diagnosis was assessed. RESULTS: Of the 39 patients who received a clinical diagnosis by the end of the study, 27 had MS and 12 received a non-MS diagnosis that included systemic lupus erythematosus, sarcoidosis, migraine, Sjögren disease, SPG4-spastic-paraparesis, neuromyelitis optica, and Susac syndrome. The percentage of perivenular lesions was higher in MS (median = 86%) compared to non-MS (median = 21%; p < 0.0001) patients. A 40% perivenular lesion cutoff was associated with 97% accuracy and a 96% positive/100% negative predictive value. CONCLUSION: The CVS detected on 3T FLAIR* images can accurately predict an MS diagnosis in patients suspected to have MS, but with atypical clinical, laboratory, and imaging features.

Pulmonary embolism during pregnancy: a 17-year single-center retrospective MDCT pulmonary angiography study.

OBJECTIVES: To determine the prevalence of pulmonary embolism (PE) and alternative diagnoses detected by computed tomography pulmonary angiography (CTPA) in pregnant women; and to assess changes over time regarding radiation dose, technical quality, and examination frequency. MATERIALS AND METHODS: This retrospective study included all pregnant women referred for CTPA due to clinically suspected PE over 17 years. Two blinded radiologists reviewed the CTPAs in consensus with regard to PE, alternative diagnoses, and technical quality. We retrieved patient data regarding radiation dose metrics and associated clinical and laboratory parameters. Subgroup comparisons were performed (Wilcoxon and Kruskal-Wallis tests). RESULTS: Of the 237 identified patients, 8 (3.3%) were excluded due to inadequate technical CTPA quality, and 229 patients were analyzed (mean age, 31.7 years; mean gestational age, 28 ± 7 weeks). The four different CT systems used over the study period had similar technical quality (p = 0.28). Of 229 patients 16 (7%) patients had PE, 144 (62.9%) had no abnormal findings, and 69 (30.1%) had an alternative diagnosis (consolidation, other pulmonary opacities, pleural effusion, and basal atelectasis). Gestational age, symptoms, and D-dimer levels were not significantly different between patients with or without PE (p > 0.05). Over time, radiation dose exposure decreased by 30% (p < 0.001), while the number of annual examinations increased by > 4-folds. CONCLUSIONS: In pregnant women, CTPA rarely indicates PE and more often shows alternative diagnoses. Over 17 years, the use of CTPA in pregnancy has notably increased, while the radiation dose exposure has decreased by one third. KEY POINTS: • The use of CTPA in pregnancy has steadily risen over the last 17 years • In pregnant women, CTPA rarely reveals PE and more often shows alternative diagnoses • Recent technical improvements have substantially decreased the radiation dose exposure inherent in CTPA without reducing diagnostic image quality.

"Dark-blood" dual-energy computed tomography angiography for thoracic aortic wall imaging.

OBJECTIVES: To assess the capability of a newly developed material decomposition method from contrast-enhanced dual-energy CT images, aiming to better visualize the aortic wall and aortic intramural hematoma (IMH), compared with true non-contrast (TNC) CT. MATERIALS AND METHODS: Twenty-two patients (11 women; mean age, 61 ± 20 years) with acute chest pain underwent 25 dual-layer non-contrast and contrast-enhanced CT. CT-angiography images were retrospectively processed using two-material decomposition analysis, where we defined the first material as the content of a region of interest placed in the ascending aorta for each patient, and the second material as water. Two independent radiologists assessed the images from the second material termed "dark-blood" images and the TNC images regarding contrast-to-noise ratio (CNR) between the wall and the lumen, diagnostic quality regarding the presence of aortic wall thickening, and the inner/outer vessel wall conspicuity. RESULTS: Diagnostic quality scores in normal aortic segments were 0.9 ± 0.3 and 2.7 ± 0.6 (p < 0.001) and wall conspicuity scores were 0.7 ± 0.5 and 1.8 ± 0.3 (p < 0.001) on TNC and dark-blood images, respectively. In aortic segments with IMH, diagnostic quality scores were 1.7 ± 0.5 and 2.4 ± 0.6 (p < 0.001) and wall conspicuity scores were 0.7 ± 0.7 and 1.8 ± 0.3 (p < 0.001) on TNC and dark-blood images, respectively. In normal aortic segments, CNRs were 0.3 ± 0.2 and 2.8 ± 0.9 on TNC and dark-blood images, respectively (p < 0.001). In aortic segments with IMH, CNRs were 0.3 ± 0.2 and 4.0 ± 1.0 on TNC and dark-blood images, respectively (p < 0.001). CONCLUSIONS: Compared with true non-contrast CT, dark-blood material decomposition maps enhance quantitative and qualitative image quality for the assessment of normal aortic wall and IMH. KEY POINTS: • Current dual-energy CT-angiography provides virtual non-contrast and bright-blood images. • Dark-blood images represent a new way to assess the vascular wall structure with dual-energy CT and can improve the lumen-to-wall contrast compared with true non-contrast CT. • This dual-energy CT material decomposition method is likely to improve contrast resolution in other applications as well, taking advantage of the high spatial resolution of CT.

Automated MRI-based volumetry of basal ganglia and thalamus at the chronic phase of cortical stroke.

PURPOSE: We aimed at assessing the potential of automated MR morphometry to assess individual basal ganglia and thalamus volumetric changes at the chronic phase after cortical stroke. METHODS: Ninety-six patients (mean age: 65 ± 18 years, male 55) with cortical stroke at the chronic phase were retrospectively included. Patients were scanned at 1.5 T or 3 T using a T1-MPRAGE sequence. Resulting 3D images were processed with the MorphoBox prototype software to automatically segment basal ganglia and thalamus structures, and to obtain Z scores considering the confounding effects of age and sex. Stroke volume was estimated by manual delineation on T2-SE imaging. Z scores were compared between ipsi- and contralateral stroke side and according to the vascular territory. Potential relationship between Z scores and stroke volume was assessed using the Spearman correlation coefficient. RESULTS: Basal ganglia and thalamus volume Z scores were lower ipsilaterally to MCA territory stroke (p values < 0.034) while they were not different between ipsi- and contralateral stroke sides in non-MCA territory stroke (p values > 0.37). In MCA territory stroke, ipsilateral caudate nucleus (rho = - 0.34, p = 0.007), putamen (rho = - 0.50, p < 0.001), pallidum (rho = - 0.44, p < 0.001), and thalamus (rho = - 0.48, p < 0.001) volume Z scores negatively correlated with the cortical stroke volume. This relation was not influenced by cardiovascular risk factors or time since stroke. CONCLUSION: Automated MR morphometry demonstrated atrophy of ipsilateral basal ganglia and thalamus at the chronic phase after cortical stroke in the MCA territory. The atrophy was related to stroke volume. These results confirm the potential role for automated MRI morphometry to assess remote changes after stroke.

Patient respiratory-triggered quantitative T2 mapping in the pancreas.

BACKGROUND: Long acquisition times and motion sensitivity limit T2 mapping in the abdomen. Accelerated mapping at 3 T may allow for quantitative assessment of diffuse pancreatic disease in patients during free-breathing. PURPOSE: To test the feasibility of respiratory-triggered quantitative T2 analysis in the pancreas and correlate T2 -values with age, body mass index, pancreatic location, main pancreatic duct dilatation, and underlying pathology. STUDY TYPE: Retrospective single-center pilot study. POPULATION: Eighty-eight adults. FIELD STRENGTH/SEQUENCE: Ten-fold accelerated multiecho-spin-echo 3 T MRI sequence to quantify T2 at 3 T. ASSESSMENT: Two radiologists independently delineated three regions of interest inside the pancreatic head, body, and tail for each acquisition. Means and standard deviations for T2 values in these regions were determined. T2 -value variation with demographic data, intraparenchymal location, pancreatic duct dilation, and underlying pancreatic disease was assessed. STATISTICAL TESTS: Interreader reliability was determined by calculating the interclass coefficient (ICCs). T2 values were compared for different pancreatic locations by analysis of variance (ANOVA). Interpatient associations between T2 values and demographical, clinical, and radiological data were calculated (ANOVA). RESULTS: The accelerated T2 mapping sequence was successfully performed in all participants (mean acquisition time, 2:48 ± 0:43 min). Low T2 value variability was observed across all patients (intersubject) (head: 60.2 ± 8.3 msec, body: 63.9 ± 11.5 msec, tail: 66.8 ± 16.4 msec). Interreader agreement was good (ICC, 0.82, 95% confidence interval: 0.77-0.86). T2 -values differed significantly depending on age (P < 0.001), location (P < 0.001), main pancreatic duct dilatation (P < 0.001), and diffuse pancreatic disease (P < 0.03). DATA CONCLUSION: The feasibility of accelerated T2 mapping at 3 T in moving abdominal organs was demonstrated in the pancreas, since T2 values were stable and reproducible. In the pancreatic parenchyma, T2 -values were significantly dependent on demographic and clinical parameters. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:410-416.

In vitro optimization and comparison of CT angiography versus radial cardiovascular magnetic resonance for the quantification of cross-sectional areas and coronary endothelial function.

BACKGROUND: Our objectives were first to determine the optimal coronary computed tomography angiography (CTA) protocol for the quantification and detection of simulated coronary artery cross-sectional area (CSA) differences in vitro, and secondly to quantitatively compare the performance of the optimized CTA protocol with a previously validated radial coronary cardiovascular magnetic resonance (CMR) technique. METHODS: 256-multidetector CTA and radial coronary CMR were used to obtain images of a custom in vitro resolution phantom simulating a range of physiological responses of coronary arteries to stress. CSAs were automatically quantified and compared with known nominal values to determine the accuracy, precision, signal-to-noise ratio (SNR), and circularity of CSA measurements, as well as the limit of detection (LOD) of CSA differences. Various iodine concentrations, radiation dose levels, tube potentials, and iterative image reconstruction algorithms (ASiR-V) were investigated to determine the optimal CTA protocol. The performance of the optimized CTA protocol was then compared with a radial coronary CMR method previously developed for endothelial function assessment under both static and moving conditions. RESULTS: The iodine concentration, dose level, tube potential, and reconstruction algorithm all had significant effects (all p <  0.001) on the accuracy, precision, LOD, SNR, and circularity of CSA measurements with CTA. The best precision, LOD, SNR, and circularity with CTA were achieved with 6% iodine, 20 mGy, 100 kVp, and 90% ASiR-V. Compared with the optimized CTA protocol under static conditions, radial coronary CMR was less accurate (- 0.91 ± 0.13 mm2 vs. -0.35 ± 0.04 mm2, p <  0.001), but more precise (0.08 ± 0.02 mm2 vs. 0.21 ± 0.02 mm2, p <  0.001), and enabled the detection of significantly smaller CSA differences (0.16 ± 0.06 mm2 vs. 0.52 ± 0.04 mm2; p <  0.001; corresponding to CSA percentage differences of 2.3 ± 0.8% vs. 7.4 ± 0.6% for a 3-mm baseline diameter). The same results held true under moving conditions as CSA measurements with CMR were less affected by motion. CONCLUSIONS: Radial coronary CMR was more precise and outperformed CTA for the specific task of detecting small CSA differences in vitro, and was able to reliably identify CSA changes an order of magnitude smaller than those reported for healthy physiological vasomotor responses of proximal coronary arteries. However, CTA yielded more accurate CSA measurements, which may prove useful in other clinical scenarios, such as coronary artery stenosis assessment.

Molecular detection and quantification of slug parasitic nematodes from the soil and their hosts.

Terrestrial gastropod molluscs are widely distributed and are well known as pests of many types of plants that are notoriously difficult to control. Many species of nematodes are able to parasitize land snails and slugs, but few of them are lethal to their host. Species and/or populations of mollusc-parasitic nematodes (MPNs) that kill their hosts are promising for biological control purposes. The recent discovery of new nematode species of the genus Phasmarhabditis in Europe and the associations between Alloionema spp. and slugs are expanding the possibilities of using MPNs as control agents. However, very little is known about the distribution and ecology of these species. Using molecular techniques based on qPCR methods for quick identification and quantification of various species of MPN isolated directly from the soil or from infected hosts can assist in providing information on their presence and persistence, as well as the composition of natural assemblages. Here, we developed new primers and probes for five species of the genus Phasmarhabditis and one species of the genus Alloionema. We employed these novel molecular techniques and implemented a published molecular set to detect MPN presence in soil samples coming from natural and agricultural areas in Switzerland. We also developed a method that allows the detection and quantification of Phasmarhabditis hermaphrodita directly from the tissues of their slug host in a laboratory experiment. The new molecular approaches were optimized to a satisfactory limit of detection of the species, with only few cross-amplifications with closely related species in late cycles (>32). Using these tools, we detected MPNs in 7.5% of sampled sites, corresponding to forest areas (P. hermaphrodita and Alloionema appendiculatum) and wheat-oriented agricultural areas (Phasmarhabditis bohemica). Moreover, we confirmed that the method can be used to detect the presence of P. hermaphrodita inside slug hosts, with more detections in the susceptible slug Deroceras larvae compared to the resistant Arion vulgaris. These primers/probe sets provide a novel and quick tool to identify MPNs from soil samples and infected slugs without having to culture and retrieve all nematode life stages, as well as a new tool to unravel the ecology of nematode-slug complexes.