Hippocampal atrophy in people with memory deficits: results from the population-based IPREA study

ABSTRACT Background: Clinical studies have shown that hippocampal atrophy is present before dementia in people with memory deficits and can predict dementia development. The question remains whether this association holds in the general population. This is of interest for the possible use of hippocampal atrophy to screen population for preventive interventions. The aim of this study was to assess hippocampal volume and shape abnormalities in elderly adults with memory deficits in a cross-sectional population-based study. Methods: We included individuals participating in the Italian Project on the Epidemiology of Alzheimer Disease (IPREA) study: 75 cognitively normal individuals (HC), 31 individuals with memory deficits (MEM), and 31 individuals with memory deficits not otherwise specified (MEMnos). Hippocampal volumes and shape were extracted through manual tracing and the growing and adaptive meshes (GAMEs) shape-modeling algorithm. We investigated between-group differences in hippocampal volume and shape, and correlations with memory deficits. Results: In MEM participants, hippocampal volumes were significantly smaller than in HC and were mildly associated with worse memory scores. Memory-associated shape changes mapped to the anterior hippocampus. Shape-based analysis detected no significant difference between MEM and HC, while MEMnos showed shape changes in the posterior hippocampus compared with HC and MEM groups. Conclusions: These findings support the discriminant validity of hippocampal volumetry as a biomarker of memory impairment in the general population. The detection of shape changes in MEMnos but not in MEM participants suggests that shape-based biomarkers might lack sensitivity to detect Alzheimer's-like pathology in the general populatio

Whole brain resting-state analysis reveals decreased functional connectivity in major depression

Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within six months before inclusion) and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxelwise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: 1) decreased bilateral amygdala and left anterior insula connectivity in an affective network, 2) reduced connectivity of the left frontal pole in a network associated with attention and working memory, and 3) decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or grey matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Modélisation et correction des inhomogénéités d\u27intensité en imagerie cérébrale par résonance magnétique

Ce travail concerne la modélisation et la correction des inhomogénéités d\u27intensité en imagerie cérébrale par résonance magnétique. Le premier volet de nos travaux modélise l\u27intensité d\u27un pixel en fonction des paramètres physiques liés à l\u27objet et à l\u27imageur. Nous proposons ensuite quatre méthodes d\u27estimation afin de calculer les profils de sensibilité en émission et détection des antennes radio-fréquence pour des objets homogènes et hétérogènes. La deuxième partie de notre travail consiste en la correction des images obtenues par résonance magnétique. Nous avons développé une première approche fondée sur les paramètres issus de la modélisation précédente. L\u27autre est fondée sur la coopération de deux algorithmes privilégiant des informations soit spatiales, soit fréquentielles. Ces méthodes ont été validées sur des données réelles issues de fantômes et du cerveau d\u27un volontaire sain. Les résultats obtenus sont très satisfaisants et ouvrent de nouvelles voies algorithmiques

Mapping Displacement and Deformation of the Heart With Local Sine-Wave Modeling

The new SinMod method extracts motion from magnetic resonance imaging (MRI)-tagged (MRIT) image sequences. Image intensity in the environment of each pixel is modeled as a moving sine wavefront. Displacement is estimated at subpixel accuracy. Performance is compared with the harmonic-phase analysis (HARP) method, which is currently the most common method used to detect motion in MRIT images. SinMod can handle line tags, as well as speckle patterns. In artificial images (tag distance six pixels), SinMod detects displacements accurately (error < 0.02 pixels). Effects of noise are suppressed effectively. Sharp transitions in motion at the boundary of an object are smeared out over a width of 0.6 tag distance. For MRIT images of the heart, SinMod appears less sensitive to artifacts, especially later in the cardiac cycle when image quality deteriorates. For each pixel, the quality of the sine-wave model in describing local image intensity is quantified objectively. If local quality is low, artifacts are avoided by averaging motion over a larger environment. Summarizing, SinMod is just as fast as HARP, but it performs better with respect to accuracy of displacement detection, noise reduction, and avoidance of artifacts.Cardiovascular Aspects of Radiolog

Feasibility and accuracy of dual-layer spectral detector computed tomography for quantification of gadolinium : a phantom study

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  0.99, 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

Accumulation-depuration potential and natural occurrence of Microcystin-LR toxin in basil

Introduction: Accumulation of hepatotoxic cyanobacterial toxins, like microcystin-LR (MC-LR), in edible crops through irrigation with contaminated water can result in human health risks. Purpose: To assess the accumulation and depuration potential of MC-LR in basil under an optimized laboratory condition and to quantify its natural occurrence in basil plant samples collected from different markets in Belgium. Methods: Basil plants in hydroculture were exposed to 5, 10 or 50 µg L-1 MC-LR for seven days. The depuration process was assessed by transferring plants to uncontaminated Hoagland solution for another seven days. Moreover, 50 basil products were collected from the Belgian markets. Basil leaves (lab and market) and roots (lab only) were analyzed using a validated UHPLC-MS/MS-based method to quantify MC-LR. ELISA and HRMS-techniques were applied to verify MC-LR presence in accumulation and depuration samples. Results: Concentration dependent accumulation of MC-LR was observed in both basil leaves and roots, reaching for the highest treatment condition up to 87.90 µg kg-1 and 143.80 µg kg-1, respectively. The basil roots accumulated more toxin compared to the leaves. Depuration was observed for all treatment conditions in both roots and leaves. At least six replicates were included and the whole experiment was repeated two times. These results were corroborated by both the ELISA and HRLCMS at the highest treatment condition. Moreover, MC-LR was detected below LOQ (1 µg kg-1) in one market sample. Significance: These results show the potential of basil to accumulate MC-LR from irrigation water, potentially resulting in human exposure to high levels of toxin. For the first time in Belgium, MC-LR was also detected in a vegetable from the market, showing human exposure through vegetables is already a reality. This study is financially supported by FPS Public Health, Safety of the Food Chain and Environment (SP 21/5 CYANTIR 1) and the EU Imptox project (Grant agreement 965173)

Feasibility and accuracy of dual-layer spectral detector computed tomography for quantification of gadolinium : a phantom study

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  0.99, 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

Accuracy of iodine quantification using dual energy CT in latest generation dual source and dual layer CT

Objective: To determine the accuracy of iodine quantification with dual energy computed tomography (DECT) in two high-end CT systems with different spectral imaging techniques. Methods: Five tubes with different iodine concentrations (0, 5, 10, 15, 20 mg/ml) were analysed in an anthropomorphic thoracic phantom. Adding two phantom rings simulated increased patient size. For third-generation dual source CT (DSCT), tube voltage combinations of 150Sn and 70, 80, 90, 100 kVp were analysed. For dual layer CT (DLCT), 120 and 140 kVp were used. Scans were repeated three times. Median normalized values and interquartile ranges (IQRs) were calculated for all kVp settings and phantom sizes. Results: Correlation between measured and known iodine concentrations was excellent for both systems (R = 0.999–1.000, p < 0.0001). For DSCT, median measurement errors ranged from −0.5% (IQR −2.0, 2.0%) at 150Sn/70 kVp and −2.3% (IQR −4.0, −0.1%) at 150Sn/80 kVp to −4.0% (IQR −6.0, −2.8%) at 150Sn/90 kVp. For DLCT, median measurement errors ranged from −3.3% (IQR −4.9, −1.5%) at 140 kVp to −4.6% (IQR −6.0, −3.6%) at 120 kVp. Larger phantom sizes increased variability of iodine measurements (p < 0.05). Conclusion: Iodine concentration can be accurately quantified with state-of-the-art DECT systems from two vendors. The lowest absolute errors were found for DSCT using the 150Sn/70 kVp or 150Sn/80 kVp combinations, which was slightly more accurate than 140 kVp in DLCT. Key Points: • High-end CT scanners allow accurate iodine quantification using different DECT techniques. • Lowest measurement error was found in scans with largest photon energy separation. • Dual-source CT quantified iodine slightly more accurately than dual layer CT

The Effects of Iodine Attenuation on Pulmonary Nodule Volumetry using Novel Dual-Layer Computed Tomography Reconstructions

OBJECTIVES: To assess the effect of iodine attenuation on pulmonary nodule volumetry using virtual non-contrast (VNC) and mono-energetic reconstructions. METHODS: A consecutive series of patients who underwent a contrast-enhanced chest CT scan were included. Images were acquired on a novel dual-layer spectral CT system. Conventional reconstructions as well as VNC and mono-energetic images at different keV levels were used for nodule volumetry. RESULTS: Twenty-four patients with a total of 63 nodules were included. Conventional reconstructions showed a median (interquartile range) volume and diameter of 174 (87 - 253) mm(3) and 6.9 (5.4 - 9.9) mm, respectively. VNC reconstructions resulted in a significant volume reduction of 5.5% (2.6 - 11.2%; p<0.001). Mono-energetic reconstructions showed a correlation between nodule attenuation and nodule volume (Spearman correlation 0.77, (0.49 - 0.94)). Lowering the keV resulted in increased volumes while higher keV levels resulted in decreased pulmonary nodule volumes compared to conventional CT. CONCLUSIONS: Novel dual-layer spectral CT offers the possibility to reconstruct VNC and mono-energetic images. Those reconstructions show that higher pulmonary nodule attenuation results in larger nodule volumes. This may explain the reported underestimation in nodule volume on non-contrast enhanced compared to contrast-enhanced acquisitions. KEY POINTS: • Pulmonary nodule volumes were measured on virtual non-contrast and mono-energetic reconstructions • Mono-energetic reconstructions showed that higher attenuation results in larger volumes • This may explain the reported nodule volume underestimation on non-contrast enhanced CT • Mostly metastatic pulmonary nodules were evaluated, results might differ for benign nodules