A Method to Minimise the Impact of ECG Marker Inaccuracies on the Spatial QRS-T angle: Evaluation on 1,512 Manually Annotated ECGs

William J Young,Stefan Van Duijvenboden,Julia Ramírez,Aled Jones,Andrew Tinker,Patricia B Munroe,Pier D Lambiase,Michele Orini

doi:10.1016/j.bspc.2020.102305

Abstract

The spatial QRS-T angle (QRS-Ta) derived from the vectorcardiogram (VCG) is a strong risk predictor for ventricular arrhythmia and sudden cardiac death with potential use for mass screening. Accurate QRS-Ta estimation in the presence of ECG delineation errors is crucial for its deployment as a prognostic test. Our study assessed the effect of inaccurate QRS and T-wave marker placement on QRS-Ta estimation and proposes a robust method for its calculation.Reference QRS-Ta measurements were derived from 1,512 VCGs manually annotated by three expert reviewers. We systematically changed onset and offset timings of QRS and T-wave markers to simulate inaccurate placement. The QRS-Ta was recalculated using a standard approach and our proposed algorithm, which limits the impact of VCG marker inaccuracies by defining the vector origin as an interval preceding QRS-onset and redefines the beginning and end of QRS and T-wave loops.Using the standard approach, mean absolute errors (MAE) in peak QRS-Ta were >40% and sensitivity and precision in the detection of abnormality (>105°) were <80% and <65% respectively, when QRS-onset was delayed or QRS-offset anticipated >15 ms. Using our proposed algorithm, MAE for peak QRS-Ta were reduced to <4% and sensitivity and precision of abnormality were >94% for inaccuracies up to ±15 ms. Similar results were obtained for mean QRS-Ta.In conclusion, inaccuracies of QRS and T-wave markers can significantly influence the QRS-Ta. Our proposed algorithm provides robust QRS-Ta measurements in the presence of inaccurate VCG annotation, enabling its use in large datasets.

Highlights

With the availability of increasingly large data-sets and improved computational abilities, there has been renewed interest in the utility of markers derived from the vectorcardiogram (VCG) such as the spatial QRS-T angle (QRS-Ta), to improve cardiovascular risk prediction [1]
The QRS-Ta has potential to improve clinical decision making in patients with ischaemic heart dis ease, as abnormal values are associated with occurrence of life-threatening ventricular arrhythmias, identifying those who may benefit most from an implantable cardioverter-defibrillator (ICD) [6]
Reannotation by a 3rd Reviewer was required in 13 VCGs (0.9%) for QRS onset (QRSon), 35 (2.3%) for QRS end (QRSend) and 164 (10.8%) for T-wave end (Tend)

Summary

Introduction

With the availability of increasingly large data-sets and improved computational abilities, there has been renewed interest in the utility of markers derived from the vectorcardiogram (VCG) such as the spatial QRS-T angle (QRS-Ta), to improve cardiovascular risk prediction [1]. A crucial aspect yet to be formally assessed is the impact of errors in QRS and T-wave marker placement on the QRS-Ta (which in standard algo rithms determines the origin, start and end of the spatial loops). This needs to be evaluated for the development of algorithms designed to fully automatically analyse large datasets

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