A cross-sectional study to test equivalence of low- versus intermediate-flip angle dynamic susceptibility contrast MRI measures of relative cerebral blood volume in patients with high-grade gliomas at 1.5 Tesla field strength

Introduction1.5 Tesla (1.5T) remain a significant field strength for brain imaging worldwide. Recent computer simulations and clinical studies at 3T MRI have suggested that dynamic susceptibility contrast (DSC) MRI using a 30° flip angle (“low-FA”) with model-based leakage correction and no gadolinium-based contrast agent (GBCA) preload provides equivalent relative cerebral blood volume (rCBV) measurements to the reference-standard acquisition using a single-dose GBCA preload with a 60° flip angle (“intermediate-FA”) and model-based leakage correction. However, it remains unclear whether this holds true at 1.5T. The purpose of this study was to test this at 1.5T in human high-grade glioma (HGG) patients.MethodsThis was a single-institution cross-sectional study of patients who had undergone 1.5T MRI for HGG. DSC-MRI consisted of gradient-echo echo-planar imaging (GRE-EPI) with a low-FA without preload (30°/P-); this then subsequently served as a preload for the standard intermediate-FA acquisition (60°/P+). Both normalized (nrCBV) and standardized relative cerebral blood volumes (srCBV) were calculated using model-based leakage correction (C+) with IBNeuro™ software. Whole-enhancing lesion mean and median nrCBV and srCBV from the low- and intermediate-FA methods were compared using the Pearson’s, Spearman’s and intraclass correlation coefficients (ICC).ResultsTwenty-three HGG patients composing a total of 31 scans were analyzed. The Pearson and Spearman correlations and ICCs between the 30°/P-/C+ and 60°/P+/C+ acquisitions demonstrated high correlations for both mean and median nrCBV and srCBV.ConclusionOur study provides preliminary evidence that for HGG patients at 1.5T MRI, a low FA, no preload DSC-MRI acquisition can be an appealing alternative to the reference standard higher FA acquisition that utilizes a preload

Hybrid Forecasting Methods—A Systematic Review

Time series forecasting has been performed for decades in both science and industry. The forecasting models have evolved steadily over time. Statistical methods have been used for many years and were later complemented by neural network approaches. Currently, hybrid approaches are increasingly presented, aiming to combine both methods’ advantages. These hybrid forecasting methods could lead to more accurate predictions and enhance and improve visual analytics systems for making decisions or for supporting the decision-making process. In this work, we conducted a systematic literature review using the PRISMA methodology and investigated various hybrid forecasting approaches in detail. The exact procedure for searching and filtering and the databases in which we performed the search were documented and supplemented by a PRISMA flow chart. From a total of 1435 results, we included 21 works in this review through various filtering steps and exclusion criteria. We examined these works in detail and collected the quality of the prediction results. We summarized the error values in a table to investigate whether hybrid forecasting approaches deliver better results. We concluded that all investigated hybrid forecasting methods perform better than individual ones. Based on the results of the PRISMA study, the possible applications of hybrid prediction approaches in visual analytics systems for decision making are discussed and illustrated using an exemplary visualization

Recommendation of Scientific Publications—A Real-Time Text Analysis and Publication Recommendation System

Studies have shown that although having more information improves the quality of decision-making, information overload causes adverse effects on decision quality. Visual analytics and recommendation systems counter this adverse effect on decision-making. Accurately identifying relevant information can reduce the noise during exploration and improve decision-making. These countermeasures also help scientists make correct decisions during research. We present a novel and intuitive approach that supports real-time collaboration. In this paper, we instantiate our approach to scientific writing and propose a system that supports scientists. The proposed system analyzes text as it is being written and recommends similar publications based on the written text through similarity algorithms. By analyzing text as it is being written, it is possible to provide targeted real-time recommendations to improve decision-making during research by finding relevant publications that might not have been otherwise found in the initial research phase. This approach allows the recommendations to evolve throughout the writing process, as recommendations begin on a paragraph-based level and progress throughout the entire written text. This approach yields various possible use cases discussed in our work. Furthermore, the recommendations are presented in a visual analytics system to further improve scientists’ decision-making capabilities

Coronavirus Pandemic and Mental Health During Pregnancy: COVID-19 And Pregnants’ Mental Health

Background: COVID-19 is an enveloped RNA virus, declared as a pandemic in 2020. The pandemic and the policies around it for controlling the infection have caused major psychological stress on the population, especially a high-risk group: the pregnant women. This study evaluates the anxiety and depression of pregnant women, in the first six months of COVID-19 pandemic in Iran.Methods: In this cross-sectional study, all pregnant women, visiting the obstetrics clinic of Mahdiyeh hospital, were enrolled in this study. Among them, women with no prior psychological disorder or use anti-anxiety or antidepressant drug were included in the study and were asked to complete the hospital anxiety and depression scale (HADS) questionnaire. Also, the demographic information, obstetrics history and past medical history of each patient were collected. Data were analyzed using SPSS software, version 22, using descriptive statistics (mean and standard deviation), t test, chi-square and Bonferroni post hoc tests. Significant levels were considered at P ≤ 0.05.Results: Overall, 465 pregnant women with a mean ± SD age of 26.75 ± 5.71 years were included in the study. The mean ± SD HADS score of the women was 12.00 ± 6.09 and 240 (51.6%) of the women had abnormal HADS score. Among the demographic properties, a significant association was seen between gravidity and HADS score (P < 0.05).Conclusion: COVID-19 can cause a considerable level of stress in women during their pregnancy, which can lead to adverse pregnancy outcomes. Among pregnant women, primigravida and multigravida (more than two previous pregnancy) ones were at higher risk of experiencing anxiety or depression

Coronavirus Pandemic and Mental Health During Pregnancy

Background: COVID-19 is an enveloped RNA virus, declared as a pandemic in 2020. The pandemic and the policies around it for controlling the infection have caused major psychological stress on the population, especially a high-risk group: the pregnant women. This study evaluates the anxiety and depression of pregnant women, in the first six months of COVID-19 pandemic in Iran. Methods: In this cross-sectional study, all pregnant women, visiting the obstetrics clinic of Mahdiyeh hospital, were enrolled in this study. Among them, women with no prior psychological disorder or use anti-anxiety or antidepressant drug were included in the study and were asked to complete the hospital anxiety and depression scale (HADS) questionnaire. Also, the demographic information, obstetrics history and past medical history of each patient were collected. Data were analyzed using SPSS software, version 22, using descriptive statistics (mean and standard deviation), t test, chisquare and Bonferroni post hoc tests. Significant levels were considered at P≤0.05. Results: Overall, 465 pregnant women with a mean±SD age of 26.75±5.71 years were included in the study. The mean±SD HADS score of the women was 12.00±6.09 and 240 (51.6%) of the women had abnormal HADS score. Among the demographic properties, a significant association was seen between gravidity and HADS score (P<0.05). Conclusion: COVID-19 can cause a considerable level of stress in women during their pregnancy, which can lead to adverse pregnancy outcomes. Among pregnant women, primigravida and multigravida (more than two previous pregnancy) ones were at higher risk of experiencing anxiety or depression

A cross-sectional study to test equivalence of low- versus intermediate-flip angle dynamic susceptibility contrast MRI measures of relative cerebral blood volume in patients with high-grade gliomas at 1.5 Tesla field strength

Introduction1.5 Tesla (1.5T) remain a significant field strength for brain imaging worldwide. Recent computer simulations and clinical studies at 3T MRI have suggested that dynamic susceptibility contrast (DSC) MRI using a 30° flip angle ("low-FA") with model-based leakage correction and no gadolinium-based contrast agent (GBCA) preload provides equivalent relative cerebral blood volume (rCBV) measurements to the reference-standard acquisition using a single-dose GBCA preload with a 60° flip angle ("intermediate-FA") and model-based leakage correction. However, it remains unclear whether this holds true at 1.5T. The purpose of this study was to test this at 1.5T in human high-grade glioma (HGG) patients.MethodsThis was a single-institution cross-sectional study of patients who had undergone 1.5T MRI for HGG. DSC-MRI consisted of gradient-echo echo-planar imaging (GRE-EPI) with a low-FA without preload (30°/P-); this then subsequently served as a preload for the standard intermediate-FA acquisition (60°/P+). Both normalized (nrCBV) and standardized relative cerebral blood volumes (srCBV) were calculated using model-based leakage correction (C+) with IBNeuro™ software. Whole-enhancing lesion mean and median nrCBV and srCBV from the low- and intermediate-FA methods were compared using the Pearson's, Spearman's and intraclass correlation coefficients (ICC).ResultsTwenty-three HGG patients composing a total of 31 scans were analyzed. The Pearson and Spearman correlations and ICCs between the 30°/P-/C+ and 60°/P+/C+ acquisitions demonstrated high correlations for both mean and median nrCBV and srCBV.ConclusionOur study provides preliminary evidence that for HGG patients at 1.5T MRI, a low FA, no preload DSC-MRI acquisition can be an appealing alternative to the reference standard higher FA acquisition that utilizes a preload