1,720,958 research outputs found
Effect of comprehensive initial training on the variability of left ventricular measures using fast-SENC cardiac magnetic resonance imaging
No full textCardiac magnetic resonance (CMR) is becoming the imaging modality of choice in multicenter studies where highly reproducible measurements are necessary. The purpose of this study was to assess the effect of comprehensive initial training on reproducibility of quantitative left ventricular (LV) parameters estimated using strain-encoded (SENC) imaging. Thirty participants (10 patients with heart failure (HF) and preserved LV ejection fraction (HFpEF), 10 patients with HF and reduced LV ejection fraction (HFrEF) and 10 healthy volunteers) were examined using fast-SENC imaging. Four observers with different experience in non-invasive cardiac imaging completed comprehensive initial training course and were invited to perform CMR data analysis. To assess agreement between observers, LV volumes, mass, ejection fraction (LVEF), global longitudinal strain (GLS) and global circumferential strain (GCS) were estimated using dedicated software (MyoStrain, USA). To test intraobserver agreement data analysis was repeated after 4 weeks. SENC imaging and analysis were fast and were completed in less than 5 minutes. LV end-diastolic volume index (LVEDVi), LVEF and strain were significantly lower in HFpEF patients than in healthy volunteers (p = 0.019 for LVEDVi; p = 0.023 for LVEF; p = 0.004 for GLS and p < 0.001 for GCS). All LV functional parameters were further reduced in HFrEF. Excellent interobserver agreement was found for all LV parameters independently of the level of experience. The reproducibility of LV mass was lower, especially at the intraobserver level (ICC 0.91; 95% CI 0.74-0.96). LV volumetric and functional parameters derived using fast-SENC imaging, are highly reproducible. The appropriate initial training is relevant and allows to achieve highest concordance in fast-SENC measurements
Cardiovascular MRI–derived Right Atrial Strain for Improved Risk Stratification in Patients with Severe Aortic Stenosis
No full textCardiac MRI–derived imaging markers demonstrated significant prognostic value in individuals with severe aortic stenosis, with right atrial strain independently predicting cardiovascular mortality and enabling identification of additional high-risk subgroups.Purpose To assess the prognostic implications of cardiac MRI–derived imaging markers in individuals with severe aortic stenosis (AS). Materials and Methods This prospective study (German Clinical Trials Register, DRKS00024479) enrolled individuals with severe AS who underwent cardiac MRI before transcatheter aortic valve replacement (TAVR) from January 2017 to March 2022. Image analyses included myocardial volumes, cardiac MRI feature tracking–derived left atrial (LA) and right atrial (RA) as well as left ventricular (LV) and right ventricular (RV) strain, myocardial T1 mapping, and late gadolinium enhancement analyses. Cardiovascular (CV) mortality was defined as primary clinical end point. Cox proportional hazards models were used to determine the association between cardiac MRI–derived parameters and CV mortality. Results The final analysis included 145 participants (median age, 80 years [IQR, 75–83 years]; 91 male). Participants who experienced CV death during follow-up had significantly enlarged RV end-diastolic volumes (median, 82.9 [IQR, 70.8–96.0] mL/m 2 vs 62.8 [54.7–76.0] mL/m 2 ; P < .001) and impaired strain values of all cardiac chambers compared with those who survived (LV global longitudinal strain [GLS], −18.1% [−13.1% to −20.4%] vs −22.5% [−16.1% to −27.3%], P = .02; RV GLS, −22.9% [−18.6% to −25.4%] vs −27.9% [−22.9% to −32.0%], P = .002; LA atrial reservoir strain [Es], 9.5% [7.2%–15.4%] vs 14.3% [9.0%–18.1%], P = .04; RA Es, 12.4% [6.8%–14.4%] vs 16.2% [11.2%–22.1%], P < .001). RA reservoir strain independently helped predict CV mortality after adjustment for other cardiac MRI markers and clinical parameters of heart failure (hazard ratio, 0.82 [95% CI: 0.71, 0.95]; P = .008). Within the subgroup of participants with high extracellular volume values, RA strain further identified participants with AS at high risk for CV mortality ( P = .001 on log-rank testing). Conclusion In individuals with AS undergoing TAVR, several cardiac MRI parameters were significantly associated with CV mortality. RA strain was an independent predictor of CV mortality and may provide more optimized patient management. Keywords: Cardiac MRI, Aortic Stenosis, TAVR, Risk Assessment, Strain Analyses German Clinical Trials Register no. DRKS00024479 Supplemental material is available for this article. © RSNA, 2025Cardiac MRI–derived imaging markers demonstrated significant prognostic value in individuals with severe aortic stenosis, with right atrial strain independently predicting cardiovascular mortality and enabling identification of additional high-risk subgroups.Purpose To assess the prognostic implications of cardiac MRI–derived imaging markers in individuals with severe aortic stenosis (AS). Materials and Methods This prospective study (German Clinical Trials Register, DRKS00024479) enrolled individuals with severe AS who underwent cardiac MRI before transcatheter aortic valve replacement (TAVR) from January 2017 to March 2022. Image analyses included myocardial volumes, cardiac MRI feature tracking–derived left atrial (LA) and right atrial (RA) as well as left ventricular (LV) and right ventricular (RV) strain, myocardial T1 mapping, and late gadolinium enhancement analyses. Cardiovascular (CV) mortality was defined as primary clinical end point. Cox proportional hazards models were used to determine the association between cardiac MRI–derived parameters and CV mortality. Results The final analysis included 145 participants (median age, 80 years [IQR, 75–83 years]; 91 male). Participants who experienced CV death during follow-up had significantly enlarged RV end-diastolic volumes (median, 82.9 [IQR, 70.8–96.0] mL/m 2 vs 62.8 [54.7–76.0] mL/m 2 ; P < .001) and impaired strain values of all cardiac chambers compared with those who survived (LV global longitudinal strain [GLS], −18.1% [−13.1% to −20.4%] vs −22.5% [−16.1% to −27.3%], P = .02; RV GLS, −22.9% [−18.6% to −25.4%] vs −27.9% [−22.9% to −32.0%], P = .002; LA atrial reservoir strain [Es], 9.5% [7.2%–15.4%] vs 14.3% [9.0%–18.1%], P = .04; RA Es, 12.4% [6.8%–14.4%] vs 16.2% [11.2%–22.1%], P < .001). RA reservoir strain independently helped predict CV mortality after adjustment for other cardiac MRI markers and clinical parameters of heart failure (hazard ratio, 0.82 [95% CI: 0.71, 0.95]; P = .008). Within the subgroup of participants with high extracellular volume values, RA strain further identified participants with AS at high risk for CV mortality ( P = .001 on log-rank testing). Conclusion In individuals with AS undergoing TAVR, several cardiac MRI parameters were significantly associated with CV mortality. RA strain was an independent predictor of CV mortality and may provide more optimized patient management. Keywords: Cardiac MRI, Aortic Stenosis, TAVR, Risk Assessment, Strain Analyses German Clinical Trials Register no. DRKS00024479 Supplemental material is available for this article. © RSNA, 202
Understanding and improving risk assessment after myocardial infarction using automated left ventricular shape analysis
Full text linkObjectives
This study aimed to identify novel 3-dimensional (3D) imaging end-systolic (ES) shape and contraction descriptors toward risk-related features and superior prognosis in acute myocardial infarction (AMI).
Background
Left ventricular ejection fraction (LVEF) and end-systolic volume (ESV) remain the main imaging biomarkers for post-AMI risk stratification. However, they are limited to global systolic function and fail to capture functional and anatomical regional abnormalities, hindering their performance in risk stratification.
Methods
A multicenter cohort of AMI survivors (n = 1,021; median age 63 years; 74.5% male) who underwent cardiac magnetic resonance (CMR) at a median of 3 days after infarction were considered for this study. The clinical end point was the 12-month rate of major adverse cardiac events (MACE; n = 73), consisting of all-cause death, reinfarction, and new congestive heart failure. A fully automated pipeline was developed to segment CMR images, build 3D statistical models of shape and contraction in AMI, and find the 3D patterns related to MACE occurrence.
Results
The novel ES shape markers proved to be superior to ESV (median cross-validated area under the receiver-operating characteristic curve 0.681 [IQR 0.679-0.684] vs 0.600 [0.598-0.602]; P < 0.001); and 3D contraction to LVEF (0.716 [0.714-0.718] vs 0.681 [0.679-0.684]; P < 0.001) in MACE occurrence prediction. They also contributed to a significant improvement in a multivariable setting including CMR markers, cardiovascular risk factors, and basic patient characteristics (0.747 [0.745-0.749]; P < 0.001). Based on these novel 3D descriptors, 3 impairments caused by AMI were identified: global, anterior, and basal, the latter being the most complementary signature to already known predictors.
Conclusions
The quantification of 3D differences in ES shape and contraction, enabled by a fully automated pipeline, improves post-AMI risk prediction and identifies shape and contraction patterns related to MACE occurrence
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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