Dataset Information

Reproducibility of small animal cine and scar cardiac magnetic resonance imaging using a clinical 3.0 tesla system.

ABSTRACT:

Background

To evaluate the inter-study, inter-reader and intra-reader reproducibility of cardiac cine and scar imaging in rats using a clinical 3.0 Tesla magnetic resonance (MR) system.

Methods

Thirty-three adult rats (Sprague-Dawley) were imaged 24 hours after surgical occlusion of the left anterior descending coronary artery using a 3.0 Tesla clinical MR scanner (Philips Healthcare, Best, The Netherlands) equipped with a dedicated 70 mm solenoid receive-only coil. Left-ventricular (LV) volumes, mass, ejection fraction and amount of myocardial scar tissue were measured. Intra-and inter-observer reproducibility was assessed in all animals. In addition, repeat MR exams were performed in 6 randomly chosen rats within 24 hours to assess inter-study reproducibility.

Results

The MR imaging protocol was successfully completed in 32 (97%) animals. Bland-Altman analysis demonstrated high intra-reader reproducibility (mean bias%: LV end-diastolic volume (LVEDV), -1.7%; LV end-systolic volume (LVESV), -2.2%; LV ejection fraction (LVEF), 1.0%; LV mass, -2.7%; and scar mass, -1.2%) and high inter-reader reproducibility (mean bias%: LVEDV, 3.3%; LVESV, 6.2%; LVEF, -4.8%; LV mass, -1.9%; and scar mass, -1.8%). In addition, a high inter-study reproducibility was found (mean bias%: LVEDV, 0.1%; LVESV, -1.8%; LVEF, 1.0%; LV mass, -4.6%; and scar mass, -6.2%).

Conclusions

Cardiac MR imaging of rats yielded highly reproducible measurements of cardiac volumes/function and myocardial infarct size on a clinical 3.0 Tesla MR scanner system. Consequently, more widely available high field clinical MR scanners can be employed for small animal imaging of the heart e.g. when aiming at serial assessments during therapeutic intervention studies.

SUBMITTER: Manka R

PROVIDER: S-EPMC3878577 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Reproducibility of small animal cine and scar cardiac magnetic resonance imaging using a clinical 3.0 tesla system.

Manka Robert R Jahnke Cosima C Hucko Thomas T Dietrich Thore T Gebker Rolf R Schnackenburg Bernhard B Graf Kristof K Paetsch Ingo I

BMC medical imaging 20131217

<h4>Background</h4>To evaluate the inter-study, inter-reader and intra-reader reproducibility of cardiac cine and scar imaging in rats using a clinical 3.0 Tesla magnetic resonance (MR) system.<h4>Methods</h4>Thirty-three adult rats (Sprague-Dawley) were imaged 24 hours after surgical occlusion of the left anterior descending coronary artery using a 3.0 Tesla clinical MR scanner (Philips Healthcare, Best, The Netherlands) equipped with a dedicated 70 mm solenoid receive-only coil. Left-ventricul ...[more]

PMID: 24345214

Similar Datasets

Project description:ObjectivesTo determine the test-retest reproducibility and observer variability of CMR-derived LA function, using (i) LA strain (LAS) and strain rate (LASR), and (ii) LA volumes (LAV) and emptying fraction (LAEF).MethodsSixty participants with and without cardiovascular disease (aortic stenosis (AS) (n = 16), type 2 diabetes (T2D) (n = 28), end-stage renal disease on haemodialysis (n = 10) and healthy volunteers (n = 6)) underwent two separate CMR scans 7-14 days apart. LAS and LASR, corresponding to LA reservoir, conduit and contractile booster-pump function, were assessed using Feature Tracking software (QStrain v2.0). LAEF was calculated using the biplane area length method (QMass v8.1). Both were assessed using 4- and 2-chamber long-axis standard steady-state free precession cine images, and average values were calculated. Intra- and inter-observer variabilities were assessed in 10 randomly selected participants.ResultsThe test-retest reproducibility was moderate to poor for all strain and strain rate parameters. Overall, strain and strain rate corresponding to reservoir phase (LAS_r, LASR_r) were the most reproducible, yielding the smallest coefficient of variance (CoV) (29.9% for LAS_r, 28.9% for LASR_r). The test-retest reproducibility for LAVs and LAEF was good: LAVmax CoV = 19.6% ICC = 0.89, LAVmin CoV = 27.0% ICC = 0.89 and total LAEF CoV = 15.6% ICC = 0.78. The inter- and intra-observer variabilities were good for all parameters except for conduit function.ConclusionThe test-retest reproducibility of LA strain and strain rate assessment by CMR utilising Feature Tracking is moderate to poor across disease states, whereas LA volume and emptying fraction are more reproducible on CMR. Further improvements in LA strain quantification are needed before widespread clinical application.Key points• LA strain and strain rate assessment using Feature Tracking on CMR has moderate to poor test-retest reproducibility across disease states. • The test-retest reproducibility for the biplane method of assessing LA function is better than strain assessment, with lower coefficient of variances and narrower limits of agreement on Bland-Altman plots. • Biplane LA volumetric measurement also has better intra- and inter-observer variability compared to strain assessment.

Project description:ObjectivesHypertrophic cardiomyopathy (HCM) often requires repeated enhanced cardiac magnetic resonance (CMR) imaging to detect fibrosis. We aimed to develop a practical model based on cine imaging to help identify patients with high risk of fibrosis and screen out patients without fibrosis to avoid unnecessary injection of contrast.MethodsA total of 273 patients with HCM were divided into training and test sets at a ratio of 7:3. Logistic regression analysis was used to find predictive image features to construct CMR model. Radiomic features were derived from the maximal wall thickness (MWT) slice and entire left ventricular (LV) myocardium. Extreme gradient boosting was used to build radiomic models. Integrated models were established by fusing image features and radiomic models. The model performance was validated in the test set and assessed by ROC and calibration curve and decision curve analysis (DCA).ResultsWe established five prediction models, including CMR, R1 (based on the MWT slice), R2 (based on the entire LV myocardium), and two integrated models (ICMR+R1 and ICMR+R2). In the test set, ICMR+R2 model had an excellent AUC value (0.898), diagnostic accuracy (89.02%), sensitivity (92.54%), and F1 score (93.23%) in identifying patients with positive late gadolinium enhancement. The calibration plots and DCA indicated that ICMR+R2 model was well-calibrated and presented a better net benefit than other models.ConclusionsA predictive model that fused image and radiomic features from the entire LV myocardium had good diagnostic performance, robustness, and clinical utility.Key points• Hypertrophic cardiomyopathy is prone to fibrosis, requiring patients to undergo repeated enhanced cardiac magnetic resonance imaging to detect fibrosis over their lifetime follow-up. • A predictive model based on the entire left ventricular myocardium outperformed a model based on a slice of the maximal wall thickness. • A predictive model that fused image and radiomic features from the entire left ventricular myocardium had excellent diagnostic performance, robustness, and clinical utility.

Project description:IntroductionAs the life expectancy of children with congenital heart disease (CHD) is rapidly increasing and the adult population with CHD is growing, there is an unmet need to improve clinical workflow and efficiency of analysis. Cardiovascular magnetic resonance (CMR) is a noninvasive imaging modality for monitoring patients with CHD. CMR exam is based on multiple breath-hold 2-dimensional (2D) cine acquisitions that should be precisely prescribed and is expert and institution dependent. Moreover, 2D cine images have relatively thick slices, which does not allow for isotropic delineation of ventricular structures. Thus, development of an isotropic 3D cine acquisition and automatic segmentation method is worthwhile to make CMR workflow straightforward and efficient, as the present work aims to establish.MethodsNinety-nine patients with many types of CHD were imaged using a non-angulated 3D cine CMR sequence covering the whole-heart and great vessels. Automatic supervised and semi-supervised deep-learning-based methods were developed for whole-heart segmentation of 3D cine images to separately delineate the cardiac structures, including both atria, both ventricles, aorta, pulmonary arteries, and superior and inferior vena cavae. The segmentation results derived from the two methods were compared with the manual segmentation in terms of Dice score, a degree of overlap agreement, and atrial and ventricular volume measurements.ResultsThe semi-supervised method resulted in a better overlap agreement with the manual segmentation than the supervised method for all 8 structures (Dice score 83.23 ± 16.76% vs. 77.98 ± 19.64%; P-value ≤0.001). The mean difference error in atrial and ventricular volumetric measurements between manual segmentation and semi-supervised method was lower (bias ≤ 5.2 ml) than the supervised method (bias ≤ 10.1 ml).DiscussionThe proposed semi-supervised method is capable of cardiac segmentation and chamber volume quantification in a CHD population with wide anatomical variability. It accurately delineates the heart chambers and great vessels and can be used to accurately calculate ventricular and atrial volumes throughout the cardiac cycle. Such a segmentation method can reduce inter- and intra- observer variability and make CMR exams more standardized and efficient.

Dataset Information

Reproducibility of small animal cine and scar cardiac magnetic resonance imaging using a clinical 3.0 tesla system.

Background

Methods

Results

Conclusions

Publications

Reproducibility of small animal cine and scar cardiac magnetic resonance imaging using a clinical 3.0 tesla system.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets