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Dataset results
78 results for “cardiac magnetic resonance imaging”
Myocardial Blood Volume Measurement by Real-Time Myocardial Perfusion Echocardiography Correlates to Myocardial Compressibility by Cardiac Magnetic Resonance Imaging in Healthy Subjects
ClinicalTrials.gov study NCT04724304. IPD Sharing: NO. Countries: 1. Publications: 0.
Correlation Between Triglyceride Glucose Index and Myocardial Injury Assessed by Cardiac Magnetic Resonance Imaging (CMR) in Patients With STEMI
ClinicalTrials.gov study NCT07261514. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Ischemic Time and Extent of Myocardial Infarction (MI) With Cardiac Magnetic Resonance Imaging (CMRI) in Patients With ST Elevation Myocardial Infarction (STEMI) and Primary Percutaneous Coronary Inte
ClinicalTrials.gov study NCT01401881. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Stress Adenosine Cardiac Magnetic Resonance (MR) Comparison With Single Photon Emission Computed Tomography (SPECT) Imaging
ClinicalTrials.gov study NCT00864591. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Cardiac Magnetic Resonance Imaging and Pulmonary Perfusion
ClinicalTrials.gov study NCT01100008. IPD Sharing: NO. Countries: 1. Publications: 0.
Comparison of Nexfin Pulse Contour Analysis and Cardiac Magnetic Resonance Imaging for the Measurement of Cardiac Output
ClinicalTrials.gov study NCT01639313. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Dobutamine Stress Cardiac Magnetic Resonance Versus Echocardiography for the Assessment of Outcome. Are the Two Imaging Modalities Comparable?
ClinicalTrials.gov study NCT01568502. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Assessment of Cardiac Involvement of Common Cold in High Performing Athletes by Cardiac Magnetic Resonance Imaging (MRI)
ClinicalTrials.gov study NCT00739895. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Respiratory Motion Correction of Cardiac Combined Positron Emission Tomography and Magnetic Resonance Imaging (PET/MRI)
ClinicalTrials.gov study NCT03200132. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Effect of Short-term Bed Rest on Cardiac Function Measured by Cardiac Magnetic Resonance Imaging
ClinicalTrials.gov study NCT06644872. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Cardiac Magnetic Resonance Imaging for Detecting Endothelial Dysfunction
ClinicalTrials.gov study NCT00808535. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Synchrony in Cardiac Conduction: Assessing the Effects of Pacing on Cardiac Performance Through Magnetic Resonance Imaging and Advanced ECG-imaging
ClinicalTrials.gov study NCT06843135. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Cardiac Implantable Electronic Device Magnetic Resonance Imaging Registry
ClinicalTrials.gov study NCT02459379. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Lipid Rich Necrotic Core Lesion Detected by Cardiac Magnetic Resonance Imaging (CMR)
ClinicalTrials.gov study NCT01284270. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Advanced Cardiac Magnetic Resonance Imaging for Assessment of Obstructive Coronary Artery Disease: ADVOCATE-CMR
ClinicalTrials.gov study NCT06419894. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Dataset related to the article " Automated Left and Right Ventricular Chamber Segmentation in Cardiac Magnetic Resonance Images Using Dense Fully Convolutional Neural Network"
<p>This record contains raw data related to the article " Automated left and right ventricular chamber segmentation in cardiac magnetic resonance images using dense fully convolutional neural network"</p> <p><br> Background and objective: Segmentation of the left ventricular (LV) myocardium (Myo) and RV endocardium on cine cardiac magnetic resonance (CMR) images represents an essential step for cardiacfunction evaluation and diagnosis. In order to have a common reference for comparing segmentation algorithms, several CMR image datasets were made available, but in general they do not include the most apical and basal slices, and/or gold standard tracing is limited to only one of the two ventricles, thus not fully corresponding to real clinical practice. Our aim was to develop a deep learning (DL) approach for automated segmentation of both RV and LV chambers from short-axis (SAX) CMR images, reporting separately the performance for basal slices, together with the applied criterion of choice.<br> Method: A retrospectively selected database (DB1) of 210 cine sequences (3 pathology groups) was considered: images (GE, 1.5 T) were acquired at Centro Cardiologico Monzino (Milan, Italy), and end-diastolic (ED) and end-systolic frames (ES) were manually segmented (gold standard, GS). Automatic ED and ES RV and LV segmentation were performed with a U-Net inspired architecture, where skip connections were redesigned introducing dense blocks to alleviate the semantic gap between the U-Net encoder and decoder. The proposed architecture was trained including: A) the basal slices where the Myo surrounded<br> the LV for at least the 50% and all the other slice; B) all the slices where the Myo completely surrounded the LV. To evaluate the clinical relevance of the proposed architecture in a practical use case scenario, a graphical user interface was developed to allow clinicians to revise, and correct when needed, the automatic segmentation. Additionally, to assess generalizability, analysis of CMR images obtained in 12 healthy volunteers (DB2) with different equipment (Siemens, 3T) and settings was performed.<br> Results: The proposed architecture outperformed the original U-Net. Comparing the performance on DB1 between the two criteria, no significant differences were measured when considering all slices together, but were present when only basal slices were examined. Automatic and manually-adjusted segmentation<br> performed similarly compared to the GS (bias±95%LoA): LVEDV -1±12 ml, LVESV -1±14 ml, RVEDV 6±12 ml, RVESV 6±14 ml, ED LV mass 6±26 g, ES LV mass 5±26 g). Also, generalizability showed very similar performance, with Dice scores of 0.944 (LV), 0.908 (RV) and 0.852 (Myo) on DB1, and 0.940 (LV), 0.880 (RV), and 0.856 (Myo) on DB2.<br> Conclusions: Our results support the potential of DL methods for accurate LV and RV contours segmentation and the advantages of dense skip connections in alleviating the semantic gap generated when high level features are concatenated with lower level feature. The evaluation on our dataset, considering separately the performance on basal and apical slices, reveals the potential of DL approaches for fast, accurate and reliable automated cardiac segmentation in a real clinical setting.<br> </p>
Brugada Syndrome: New Insights From Cardiac Magnetic Resonance and Electroanatomical Imaging
<p>Dataset from Pappone C, Santinelli V, Mecarocci V, Tondi L, Ciconte G, Manguso F, Sturla F, Vicedomini G, Micaglio E, Anastasia L, Pica S, Camporeale A, Lombardi M. Brugada Syndrome: New Insights From Cardiac Magnetic Resonance and Electroanatomical Imaging. Circ Arrhythm Electrophysiol. 2021 Nov;14(11):e010004. doi: 10.1161/CIRCEP.121.010004. Epub 2021 Oct 25. PMID: 34693720.</p> <p>Abstract</p> <p><strong>Background: </strong>Brugada syndrome (BrS) is considered a purely electrical disease with variable electrical substrates. Variable rates of mechanical abnormalities have been also reported. Whether exists a link between electrical and mechanical abnormalities has never been previously explored. This investigational physiopathological study aimed to determine the relationship between the substrate size/location, as exposed by ajmaline provocation, and the severity of mechanical abnormalities, as assessed by cardiac magnetic resonance in patients with BrS.</p> <p><strong>Methods: </strong>Twenty-four consecutive high-risk patients with BrS (mean age, 38±11 years, 17 males), presenting with malignant syncope and documented polymorphic ventricular tachycardia/ventricular fibrillation, and candidate to implantable cardioverter defibrillator implantation, underwent cardiac magnetic resonance and electroanatomic maps. During each examination, ajmaline test (1 mg/kg over 5 minutes) was performed. Cardiac magnetic resonance findings were compared with 24 age, sex, and body surface area-matched controls. In patients with BrS, the correlation between the electrical substrate extent and right ventricular regional mechanical abnormalities before/after ajmaline challenge was analyzed.</p> <p><strong>Results: </strong>After ajmaline, patients with BrS showed a reduction of right ventricular (RV) ejection fraction (<em>P</em><0.001), associated with decreased transversal displacement (U, <em>P</em><0.001) and longitudinal strain (ε, <em>P</em><0.001) localized at RV outflow tract. In patients with BrS significant preajmaline/postajmaline changes of transversal displacement (ΔU, <em>P</em><0.001) and longitudinal strain (Δε, <em>P</em><0.001) were found. In the control group, no mechanical changes were observed after ajmaline. The electrical substrate consistently increased after ajmaline from 1.7±2.8 cm<sup>2</sup> to 14.2±7.3 cm<sup>2</sup> (<em>P</em><0.001), extending from the RV outflow tract to the neighboring segments of the RV anterior wall. Postajmaline RV ejection fraction inversely correlated with postajmaline substrate extent (<em>r</em>=-0.830, <em>P</em><0.001). In patients with BrS and normal controls, cardiac magnetic resonance detected neither myocardial fibrosis nor RV outflow tract morphological abnormalities.</p> <p><strong>Conclusions: </strong>BrS is a dynamic RV electromechanical disease, where functional abnormalities correlate with the maximal extent of the substrate size.</p>
Data set from the article Petrini M, Alì M, Cannaò PM, Zambelli D, Cozzi A, Codari M, Malavazos AE, Secchi F, Sardanelli F. Epicardial adipose tissue volume in patients with coronary artery disease or non-ischaemic dilated cardiomyopathy: evaluation with cardiac magnetic resonance imaging. Clin Radiol. 2019 Jan;74(1):81.e1-81.e7. doi: 10.1016/j.crad.2018.09.006. Epub 2018 Oct 15. PMID: 30336943.
<p>Data set from the article Petrini M, Alì M, Cannaò PM, Zambelli D, Cozzi A, Codari M, Malavazos AE, Secchi F, Sardanelli F. Epicardial adipose tissue volume in patients with coronary artery disease or non-ischaemic dilated cardiomyopathy: evaluation with cardiac magnetic resonance imaging. Clin Radiol. 2019 Jan;74(1):81.e1-81.e7. doi: 10.1016/j.crad.2018.09.006. Epub 2018 Oct 15. PMID: 30336943.</p> <p> </p> <p>This is the abstract:</p> <p><strong>Aim: </strong> To compare the amount of epicardial adipose tissue (EAT) in patients with coronary artery disease (CAD) or non-ischaemic dilated cardiomyopathy (NIDCM) with that in patients with negative cardiac magnetic resonance imaging (CMR).</p> <p><strong>Materials and methods: </strong> One hundred and fifty patients (median age 57 years, interquartile range [IQR] 46-66 years) who underwent CMR were evaluated retrospectively: 50 with CAD, 50 with NIDCM, and 50 with negative CMR. For each patient, the EAT mass index (EATMI) to body surface area, end-diastolic volume index (EDVI), end-systolic volume index (ESVI), stroke volume (SV), ejection fraction (EF) for both ventricles, and left ventricle (LV) mass index were estimated. Intra and inter-reader reproducibility was tested in a random subset of 30 patients, 10 for each group. Mann-Whitney U test, Kruskal-Wallis test, Spearman's correlation, and Bland-Altman statistics were used.</p> <p><strong>Results: </strong> The EATMI in CAD patients (median 15.7 g/m<sup>2</sup>, IQR 8.3-25.7) or in NIDCM patients (15.9 g/m<sup>2</sup>, 11.5-18.1) was significantly higher than that in negative CMR patients (9.1 g/m<sup>2</sup>, 6-12; p<0.001 both). No significant difference was found between CAD and NIDCM patients (p=1.000). A correlation between EATMI and LV mass index was found in NIDCM patients (r=0.455, p=0.002). Intra- and inter-reader reproducibility were up to 80% and 72%, respectively.</p> <p><strong>Conclusion: </strong> Patients with NIDCM or CAD exhibited an increased EATMI in comparison to negative CMR patients. CMR can be used to estimate EAT with good reproducibility.</p>
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