Dataset Information

Feature tracking compared with tissue tagging measurements of segmental strain by cardiovascular magnetic resonance.

ABSTRACT:

Background

Left ventricular segmental wall motion analysis is important for clinical decision making in cardiac diseases. Strain analysis with myocardial tissue tagging is the non-invasive gold standard for quantitative assessment, however, it is time-consuming. Cardiovascular magnetic resonance myocardial feature-tracking (CMR-FT) can rapidly perform strain analysis, because it can be employed with standard CMR cine-imaging. The aim is to validate segmental peak systolic circumferential strain (peak SCS) and time to peak systolic circumferential strain (T2P-SCS) analysed by CMR-FT against tissue tagging, and determine its intra and inter-observer variability.

Methods

Patients in whom both cine CMR and tissue tagging has been performed were selected. CMR-FT analysis was done using endocardial (CMR-FTendo) and mid-wall contours (CMR-FTmid). The Intra Class Correlation Coefficient (ICC) and Pearson correlation were calculated.

Results

10 healthy volunteers, 10 left bundle branch block (LBBB) and 10 hypertrophic cardiomyopathy patients were selected. With CMR-FT all 480 segments were analyzable and with tissue tagging 464 segments.Significant differences in mean peak SCS values of the total study group were present between CMR-FTendo and tissue tagging (-23.8 ± 9.9% vs -13.4 ± 3.3%, p<0.001). Differences were smaller between CMR-FTmid and tissue tagging (-16.4 ± 6.1% vs -13.4 ± 3.3%, p=0.001). The ICC of the mean peak SCS of the total study group between CMR-FTendo and tissue tagging was low (0.19 (95%-CI-0.10-0.49), p=0.02). Comparable results were seen between CMR-FTmid and tissue tagging. In LBBB patients, mean T2P-SCS values measured with CMR-FTendo and CMR-FTmid were 418 ± 66 ms, 454 ± 60 ms, which were longer than with tissue tagging, 376 ± 55 ms, both p<0.05. ICC of the mean T2P-SCS between CMR-FTendo and tissue tagging was 0.64 (95%-CI-0.36-0.81), p<0.001, this was better in the healthy volunteers and LBBB group, whereas the ICC between CMR-FTmid and tissue tagging was lower.The intra and inter-observer agreement of segmental peak SCS with CMR-FTmid was lower compared with tissue tagging; similar results were seen for segmental T2P-SCS.

Conclusions

The intra and inter-observer agreement of segmental peak SCS and T2P-SCS is substantially lower with CMR-FTmid compared with tissue tagging. Therefore, current segmental CMR-FTmid techniques are not yet applicable for clinical and research purposes.

SUBMITTER: Wu L

PROVIDER: S-EPMC3926943 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Myocardial strain is increasingly recognized as an important assessment for myocardial function. In addition, it also improves outcome prediction. However, there is lack of standardization in strain evaluation by cardiovascular magnetic resonance (CMR). In this study we compared strain values using multiple techniques and multiple vendor products. METHODS:Prospectively recruited patients with cardiomyopathy of diverse etiology (N = 77) and healthy controls (N = 10) underwent CMR on a 1.5 T scanner. Tagging, displacement encoding with stimulated echoes (DENSE) and balanced stead state free precession cine imaging were acquired on all subjects. A single matched mid left ventricular (LV) short axis plane was used for the comparisons of peak circumferential (Ecc) and radial strain (Err) and a 4-chamber view for longitudinal strain (Ell). Tagging images were analyzed using harmonic phase (HARP) and displacement encoding with stimulated echoes (DENSE) images using a proprietary program. Feature tracking (FT) was evaluated using 3 commercially available software from Tomtec Imaging Systems, Cardiac Image Modeller (CIM), and Circle Cardiovascular Imaging. Tagging data were used as reference. Statistic analyses were performed using paired t-test, intraclass correlation coefficient (ICC), Bland Altman limits of agreement and coefficient of variations. RESULTS:Average LV ejection fraction was 50% (range 32 to 62%). Regional LV wall motion abnormalities were present in 48% of the analyzed planes. The average Ecc was - 13 ± 4%, - 13 ± 4%, - 16 ± 6%, - 10 ± 3% and - 14 ± 4% for tagging, DENSE, Tomtec, CIM and Circle, respectively, with the best agreement seen in DENSE and Circle with tagging. The Err was highly varied with poor agreement across the techniques, 32 ± 24%, 40 ± 28%, 47 ± 26%, 64 ± 33% and 23 ± 9% for tagging, DENSE, Tomtec, CIM and Circle, respectively. The average Ell was - 14 ± 4%, - 8 ± 3%, - 13 ± 5%, - 11 ± 3% and - 12 ± 4% for tagging, DENSE, Tomtec, CIM and Circle, respectively with the best agreement seen in Tomtec and Circle with tagging. In the intra- and inter-observer agreement analysis the reproducibility of each technique was good except for Err by HARP. CONCLUSIONS:Small but important differences are evident in Ecc and Ell comparisons among vendors while large differences are seen in Err assessment. Our findings suggest that CMR strain values are technique and vendor dependent. Hence, it is essential to develop reference standard from each technique and analytical product for clinical use, and to sequentially compare patient data using the same software.

Project description:BackgroundCardiovascular magnetic resonance (CMR) 2D feature tracking (FT) left ventricular (LV) myocardial strain has seen widespread use to characterize myocardial deformation. Yet, validation of CMR FT measurements remains scarce, particularly for regional strain. Therefore, we aimed to perform intervendor comparison of 3 different FT software against tagging.MethodsIn 61 subjects (18 healthy subjects, 18 patients with chronic myocardial infarction, 15 with dilated cardiomyopathy, and 10 with LV hypertrophy due to hypertrophic cardiomyopathy or aortic stenosis) were prospectively compared global (G) and regional transmural peak-systolic Lagrangian longitudinal (LS), circumferential (CS) and radial strains (RS) by 3 FT software (cvi42, Segment, and Tomtec) among each other and with tagging at 3T. We also evaluated the ability of regional LS, CS, and RS by different FT software vs tagging to identify late gadolinium enhancement (LGE) in the 18 infarct patients.ResultsGLS and GCS by all 3 software had an excellent agreement among each other (ICC = 0.94-0.98 for GLS and ICC = 0.96-0.98 for GCS respectively) and against tagging (ICC = 0.92-0.94 for GLS and ICC = 0.88-0.91 for GCS respectively), while GRS showed inconsistent agreement between vendors (ICC 0.10-0.81). For regional LS, the agreement was good (ICC = 0.68) between 2 vendors but less vs the 3rd (ICC 0.50-0.59) and moderate to poor (ICC 0.44-0.47) between all three FT software and tagging. Also, for regional CS agreement between 2 software was higher (ICC = 0.80) than against the 3rd (ICC = 0.58-0.60), and both better agreed with tagging (ICC = 0.70-0.72) than the 3rd (ICC = 0.57). Regional RS had more variation in the agreement between methods ranging from good (ICC = 0.75) to poor (ICC = 0.05). Finally, the accuracy of scar detection by regional strains differed among the 3 FT software. While the accuracy of regional LS was similar, CS by one software was less accurate (AUC 0.68) than tagging (AUC 0.80, p < 0.006) and RS less accurate (AUC 0.578) than the other two (AUC 0.76 and 0.73, p < 0.02) to discriminate segments with LGE.ConclusionsWe confirm good agreement of CMR FT and little intervendor difference for GLS and GCS evaluation, with variable agreement for GRS. For regional strain evaluation, intervendor difference was larger, especially for RS, and the diagnostic performance varied more substantially among different vendors for regional strain analysis.

Project description:AIMS:A multitude of cardiac magnetic resonance (CMR) techniques are used for myocardial strain assessment; however, studies comparing them are limited. We sought to compare global longitudinal (GLS), circumferential (GCS), segmental longitudinal (SLS), and segmental circumferential (SCS) strain values, as well as reproducibility between CMR feature tracking (FT), tagging (TAG), and fast-strain-encoded (fast-SENC) CMR techniques. METHODS AND RESULTS:Eighteen subjects (11 healthy volunteers and seven patients with heart failure) underwent two CMR scans (1.5T, Philips) with identical parameters. Global and segmental strain values were measured using FT (Medis), TAG (Medviso), and fast-SENC (Myocardial Solutions). Friedman's test, linear regression, Pearson's correlation coefficient, and Bland-Altman analyses were used to assess differences and correlation in measured GLS and GCS between the techniques. Two-way mixed intra-class correlation coefficient (ICC), coefficient of variance (COV), and Bland-Altman analysis were used for reproducibility assessment. All techniques correlated closely for GLS (Pearson's r: 0.86-0.92) and GCS (Pearson's r: 0.85-0.94). Intra-observer and inter-observer reproducibility was excellent in all techniques for both GLS (ICC 0.92-0.99, CoV 2.6-10.1%) and GCS (ICC 0.89-0.99, CoV 4.3-10.1%). Inter-study reproducibility was similar for all techniques for GLS (ICC 0.91-0.96, CoV 9.1-10.8%) and GCS (ICC 0.95-0.97, CoV 7.6-10.4%). Combined segmental intra-observer reproducibility was good in all techniques for SLS (ICC 0.914-0.953, CoV 12.35-24.73%) and SCS (ICC 0.885-0.978, CoV 10.76-19.66%). Combined inter-study SLS reproducibility was the worst in FT (ICC 0.329, CoV 42.99%), while fast-SENC performed the best (ICC 0.844, CoV 21.92%). TAG had the best reproducibility for combined inter-study SCS (ICC 0.902, CoV 19.08%), while FT performed the worst (ICC 0.766, CoV 32.35%). Bland-Altman analysis revealed considerable inter-technique biases for GLS (FT vs. fast-SENC 3.71%; FT vs. TAG 8.35%; and TAG vs. fast-SENC 4.54%) and GCS (FT vs. fast-SENC 2.15%; FT vs. TAG 6.92%; and TAG vs. fast-SENC 2.15%). Limits of agreement for GLS ranged from ±3.1 (TAG vs. fast-SENC) to ±4.85 (FT vs. TAG) for GLS and ±2.98 (TAG vs. fast-SENC) to ±5.85 (FT vs. TAG) for GCS. CONCLUSIONS:We found significant differences in measured GLS and GCS between FT, TAG, and fast-SENC. Global strain reproducibility was excellent for all techniques. Acquisition-based techniques had better reproducibility than FT for segmental strain.

Project description:ObjectivesThe purpose of this study was to determine the prognostic value of feature-tracking global longitudinal strain (GLS) measured during vasodilator stress cardiac magnetic resonance (CMR) imaging.BackgroundPrior studies have suggested that blunted myocardial strain during dobutamine stress echocardiography may be associated with adverse prognosis. Recent developments in CMR feature-tracking techniques now allow assessment of strain in clinical practice using standard cine images without specialized pulse sequences or complex post-processing. Whether feature-tracking GLS measured during vasodilator stress provides independent and incremental prognostic data is unclear.MethodsConsecutive patients undergoing stress perfusion CMR were prospectively enrolled (n = 535). Feature-tracking stress GLS was measured immediately after regadenoson perfusion. Patients were followed for major adverse cardiac events (MACE): death, nonfatal myocardial infarction, heart failure hospitalization, sustained ventricular tachycardia, and late revascularization. Cox proportional hazards regression modeling was used to examine the association between stress GLS and MACE. The incremental prognostic value of stress GLS was assessed in nested models.ResultsOver a median follow-up of 1.5 years, 82 patients experienced MACE. By Kaplan-Meier analysis, patients with stress GLS ≥ median (-19%) had significantly reduced event-free survival compared with those with stress GLS < median (log-rank p < 0.001). Stress GLS was significantly associated with risk of MACE after adjustment for clinical and imaging risk factors including ischemia, ejection fraction, and late gadolinium enhancement (hazard ratio: 1.267; p < 0.001). Addition of stress GLS into a model with clinical and imaging predictors resulted in significant increase in the C-index (from 0.80 to 0.85; p = 0.031) and a continuous net reclassification improvement of 0.898 (95% confidence interval: 0.565 to 1.124).ConclusionsFeature-tracking stress GLS measured during vasodilator stress CMR is an independent predictor of MACE in patients with known or suspected coronary artery disease, incremental to common clinical and imaging risk factors. These findings suggest a role for feature-tracking derived stress GLS in identifying patients at highest risk of adverse events following stress CMR.

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