Abstract

BackgroundCardiovascular magnetic resonance (CMR) represents the clinical gold standard for the assessment of biventricular morphology and function. Since manual post-processing is time-consuming and prone to observer variability, efforts have been directed towards automated volumetric quantification. In this study, we sought to validate the accuracy of a novel approach providing fully automated quantification of biventricular volumes and function in a “real-world” clinical setting.MethodsThree-hundred CMR examinations were randomly selected from the local data base. Fully automated quantification of left ventricular (LV) mass, LV and right ventricular (RV) end-diastolic and end-systolic volumes (EDV/ESV), stroke volume (SV) and ejection fraction (EF) were performed overnight using commercially available software (suiteHEART®, Neosoft, Pewaukee, Wisconsin, USA). Parameters were compared to manual assessments (QMass®, Medis Medical Imaging Systems, Leiden, Netherlands). Sub-group analyses were further performed according to image quality, scanner field strength, the presence of implanted aortic valves and repaired Tetralogy of Fallot (ToF).ResultsBiventricular automated segmentation was feasible in all 300 cases. Overall agreement between fully automated and manually derived LV parameters was good (LV-EF: intra-class correlation coefficient [ICC] 0.95; bias − 2.5% [SD 5.9%]), whilst RV agreement was lower (RV-EF: ICC 0.72; bias 5.8% [SD 9.6%]). Lowest agreement was observed in case of severely altered anatomy, e.g. marked RV dilation but normal LV dimensions in repaired ToF (LV parameters ICC 0.73–0.91; RV parameters ICC 0.41–0.94) and/or reduced image quality (LV parameters ICC 0.86–0.95; RV parameters ICC 0.56–0.91), which was more common on 3.0 T than on 1.5 T.ConclusionsFully automated assessments of biventricular morphology and function is robust and accurate in a clinical routine setting with good image quality and can be performed without any user interaction. However, in case of demanding anatomy (e.g. repaired ToF, severe LV hypertrophy) or reduced image quality, quality check and manual re-contouring are still required.

Highlights

  • Cardiovascular magnetic resonance (CMR) imaging is the gold standard for the assessment of cardiac function and morphology [1, 2]

  • To extract clinically relevant information such as Left ventricular (LV) mass, LV and right ventricular (RV) end-diastolic and end-systolic volume (EDV/End-systolic volume (ESV)), stroke volume (SV) and ejection fraction (EF), accurate post-processing of the cine CMR images is required

  • Agreement was assessed between the fully automated algorithm and expert consensus contours based on the Society for Cardiovascular Magnetic Resonance (SCMR) consensus data consisting of 15 cases with different pathologies [12]

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Summary

Introduction

Cardiovascular magnetic resonance (CMR) imaging is the gold standard for the assessment of cardiac function and morphology [1, 2]. Post-processing is typically performed manually by delineating endocardial and epicardial LV borders as well as endocardial RV borders in all short-axis (SAX) slices covering the ventricles from atrioventricular ring to apex, in both end-diastolic and end-systolic phases. This task is time-consuming, tedious and subject to observer-variability [2, 5,6,7]. We sought to validate the accuracy of a novel approach providing fully automated quantification of biventricular volumes and function in a “real-world” clinical setting

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