What is the clinical evidence from this study?

Study design: Observational. Population: Healthy volunteers (n=60). Intervention: Threshold-based (TB) quantification method vs. Conventional (Conv) quantification method. Primary outcome: Global intraclass correlation coefficient (G-ICC) for interobserver agreement of all investigated parameters (p=<0.0001).

What does this research mean for the field?

Threshold-based quantification significantly improves interobserver agreement for left and right ventricular CMR parameters compared to conventional methods, regardless of observer experience level. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

February 28, 2018Open Access

Left and right ventricular parameters corrected with threshold-based quantification method in a normal cohort analyzed by three independent observers with various training-degree

Q: What are the key findings of this study?

Threshold-based quantification significantly improved interobserver agreement for left and right ventricular CMR parameters compared to conventional methods (global ICC 0.92 vs 0.86, p<0.0001).

Q: What does this research mean for the field?

Threshold-based quantification significantly improves interobserver agreement for left and right ventricular CMR parameters compared to conventional methods, regardless of observer experience level. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Key Result

Threshold-based quantification significantly improved interobserver agreement for left and right ventricular CMR parameters compared to conventional methods (global ICC 0.92 vs 0.86, p<0.0001).

Study Design

Type

Observational (n=60)

Multicenter

Structured PICO

Does threshold-based quantification improve interobserver agreement and alter measured LV and RV parameters compared to conventional contouring in healthy volunteers?

Population

60 healthy Caucasian volunteers (30 males, 30 females), mean age 25.6 ± 4.7 years, free of cardiovascular diseases.

Intervention

Threshold-based (TB) semi-automatic quantification method (Medis 7.6 QMass) for measuring LV and RV parameters including trabeculae and papillary muscles

Comparator

Conventional (Conv) manual contouring method where trabeculae and papillary muscles are included in the ventricular cavity

Outcome

Differences in LV and RV parameters (EF, EDV, ESV, SV, mass) and interobserver variability (intraclass correlation coefficient) between the two methods across three observers with varying experiencesurrogate

Threshold-based semi-automatic quantification of trabeculae and papillary muscles significantly improves interobserver agreement for LV and RV CMR parameters regardless of reader experience compared to conventional manual contouring.

Main Result

Absolute Event Rate: 0.92% vs 0.86%

p-value: p=<0.0001

Limitations

Limited patient number
Lack of scan-rescan reproducibility
High differences of ICC values between methods may partially come from altering ranges of measured parameters

Abstract

While cardiac magnetic resonance (CMR) is the reference method to evaluate left and right ventricular functions, volumes and masses, there is no widely accepted method for the quantitative analysis of trabeculae and papillary muscles (TPM). The aim of this study was to investigate the effect of TPM quantification on left and right ventricular CMR values in a normal cohort and to investigate interobserver variability of threshold-based (TB) analysis by three independent observers with variant experience in CMR. At our clinic, 60 healthy volunteers (30 males, mean age 25.6 ± 4.7 years) underwent CMR scan performed on a 1.5T Philips Achieva MR machine. On short-axis cine images, endo- and epicardial contours were detected by three independent observers with variable experience in CMR (low- ca. 120, mid- > 800, high-experienced > 5000 original CMR cases). Using Conv and TB methods (Medis 7.6 QMass software Leiden, The Netherland), we measured LV and RV ejection fractions, end-diastolic, end-systolic, stroke volumes and masses. We used TB method for quantifying TPM in ventricles using epicardial contour layers. Interobserver variability was evaluated, and the observer’s experience as an impact on variability of each investigated parameters was assessed. Comparing Conv and TB quantification methods’ significant difference were detected for all LV and RV parameters in case of all observers (H, M and L p < 0.0001). The global intraclass correlation coefficient (G-ICC) representing interobserver agreement for all investigated parameters was lower with Conv method (G-ICCConv vs. G-ICCTB 0.86 vs. 0.92 p < 0.0001). The ICC of LV parameters was higher using TB quantification (LV-ICCConv vs. LV-ICCTB 0.92 vs. 0.96 p < 0.0001), and for the evaluation of RV values, the TB method also had significantly higher interobserver agreement (RV-ICCConv vs. RV-ICCTB 0.80 vs. 0.89 p < 0.0001). The TB algorithm could be a consistent method to assess LV and RV CMR values, and to measure trabeculae and papillary muscles quantitatively in various level of experience in CMR.

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