The ventricular gradient in electrocardiography: What is it, and how can we use it?

The seminar is held by Cees A. Swenne, Professor at the Leiden University Medical Center (The Netherlands) in the framework of the Master's Degree course "Context-sensitive design of medical devices"

  • Date: 19 MAY 2022  from 14:00 to 16:00

  • Event location: Room 2.13 - UOS - Via dell’Università, 50 - Cesena - In presence and online event

  • Type: Seminar


The ventricular gradient (VG) in electrocardiography (not to be interchanged with pressure gradients that can be measured in the heart) is defined as the QRST area (areas with negative amplitudes are subtracted from areas with positive amplitudes). When measured in a single ECG lead the result is a scalar, when measured in the vectorcardiogram, the scalar QRST areas in the X, Y, and Z leads form the x-, y-, and z-components of the ventricular gradient vector, this vector is usually called the spatial ventricular gradient (SVG). The SVG can be seen as the vectorial sum of the QRS and T integral vectors, and these vectors have the spatial orientation of the QRS- and the T-axis, respectively. The angle between the QRS- and T- integral vectors is called the spatial angle, SA. The SVG is considered to be a measure of action potential morphology heterogeneity in the heart. The SA is considered to be a measure of concordance-discordance of the ECG. As such, SVG and SA are general ECG variables that carry important information about the electrical properties of the heart.

In this presentation the historical background of the VG is discussed, the original concepts formulated in the nineteen-thirties by Wilson, the formal mathematical definition of the SVG by Burger in the late forties, and the possible use in clinical electrocardiography. Examples are given of applications in the setting of the detection of pulmonary hypertension in the ECG, ECG hysteresis during and after exercise, prediction of arrhythmias, and VG properties of extrasystoles. Because of the tight mathematical relationship between SA and SVG, some applications of SA will also be discussed.



Cees A. Swenne is an associate professor affiliated with the Cardiology Department of the Leiden University Medical Center, Leiden, The Netherlands. He is also the course director of the biomedical engineering master’s degree course “Physiological signal processing and modeling in cardiology” in the Faculty of Engineering, Università Politecnica delle Marche, Ancona, Italy. He studied physics at the Technical University in Eindhoven, the Netherlands, and did his Ph.D. in the Faculty of Medicine of the University of Utrecht, the Netherlands, in 1984. As a biomedical engineer, he held positions in the Department of Physiological Signal Processing of the Institute of Medical Physics TNO, Utrecht, the Netherlands, and in the Biomedical Instrumentation Unit TNO in the Amsterdam Medical Center, Amsterdam, the Netherlands. From 1986 he was affiliated with the Leiden University Medical Center. His major teaching and research interests are electrocardiography/vectorcardiography (arrhythmias, ischemia), neurocardiology (syncope, exercise training & rehabilitation, music), cardiovascular physiology (especially electrocardiology, electrophysiology and arrhythmias, syncope, baroreflex and blood pressure control, physical exercise, training and rehabilitation, neurocardiology), computerized physiological signal processing and modeling of physiological processes related to the cardiovascular system, and psychometrics. He served as a course director of several courses relating to these subjects, for students in medicine, biomedical sciences and biomedical engineering. He served as a chairman of the exam quality control committee in the Leiden University Medical Center, as an executive editor of the Journal of Electrocardiology, and was program chair of the ISCE meeting in 2019. He supervised the master thesis work of around 40 students and the Ph.D. thesis work of 11 students. He was a reviewer for around 50 scientific journals and authored more than 250 papers (h-index 40).


prof. Stefano Severi

Associate Professor

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