AJP - Heart pressure measurements
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Am J Physiol Heart Circ Physiol 294: H2150-H2157, 2008. First published February 29, 2008; doi:10.1152/ajpheart.01312.2007
0363-6135/08 $8.00
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
294/5/H2150    most recent
01312.2007v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Web of Science (2)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Henkens, I. R.
Right arrow Articles by Vliegen, H. W.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Henkens, I. R.
Right arrow Articles by Vliegen, H. W.

Improved ECG detection of presence and severity of right ventricular pressure load validated with cardiac magnetic resonance imaging

Ivo R. Henkens,1 Koen T. B. Mouchaers,2 Anton Vonk-Noordegraaf,2 Anco Boonstra,2 Cees A. Swenne,1 Arie C. Maan,1 Sum-Che Man,1 Jos W. R. Twisk,3 Ernst E. van der Wall,1 Martin J. Schalij,1 and Hubert W. Vliegen1

1Department of Cardiology, Leiden University Medical Center, Leiden; and Departments of 2Pulmonology and 3Clinical Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, the Netherlands

Submitted 9 November 2007 ; accepted in final form 25 February 2008


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 DISCLOSURES
 REFERENCES
 
The study aimed to assess whether the 12-lead ECG-derived ventricular gradient, a vectorial representation of ventricular action potential duration heterogeneity directed toward the area of shortest action potential duration, can improve ECG diagnosis of chronic right ventricular (RV) pressure load. ECGs from 72 pulmonary arterial hypertension patients recorded <30 days before onset of therapy were compared with ECGs from matched healthy control subjects (n = 144). Conventional ECG criteria for increased RV pressure load were compared with the ventricular gradient. In 38 patients a cardiac magnetic resonance (CMR) study had been performed within 24 h of the ECG. By multivariable analysis, combined use of conventional ECG parameters (rsr' or rsR' in V1, R/S > 1 with R > 0.5 mV in V1, and QRS axis >90°) had a sensitivity of 89% and a specificity of 93% for presence of chronic RV pressure load. However, the ventricular gradient not only had a higher diagnostic accuracy for chronic RV pressure load by receiver operating characteristic analysis [areas under the curve (AUC) = 0.993, SE 0.004 vs. AUC = 0.945, SE 0.021, P < 0.05], but also discriminated between mild-to-moderate and severe RV pressure load. CMR identified an inverse relation between the ventricular gradient and RV mass, and a trend toward a similar relation with RV volume. In conclusion, chronically increased RV pressure load is electrocardiographically reflected by an altered ventricular gradient associated with RV remodeling-related changes in ventricular action potential duration heterogeneity. The use of the ventricular gradient allows ECG detection of even mildly increased RV pressure load.

hypertension; pulmonary; right ventricular hypertrophy; diagnosis; ventricular gradient; electrocardiogram

MODERATELY INCREASED CHRONIC right ventricular (RV) pressure load is hard to detect noninvasively because of the position and mass of the RV (7, 13, 23). Conventional 12-lead ECG parameters of increased RV pressure load lack diagnostic accuracy, precluding their use for screening purposes (3, 16, 26, 31, 34), partly because the chest electrodes predominantly overlie the left ventricle (LV) and partly because the 12-lead ECG renders 12 separate one-dimensional projections of the three-dimensional (3-D) cardiac vector in time (25), but not in the least because the RV mass is relatively low compared with the LV mass. This scalar ECG representation hampers the direct appreciation of the ECG as a recording of a 3-D process. However, a synthesized vectorcardiogram can be easily derived mathematically from the ECG, allowing the calculation of electrocardiographic 3-D parameters. One of these parameters is the ventricular gradient (VG), a 3-D measure of ventricular action potential duration (APD) heterogeneity oriented from the area with the longest APD toward the area with the shortest APD (11, 18). The VG (mV·ms) is the sum of the 3-D integrals of both the QRS complex and the T wave (net area subtended by the heart vector over the QRS complex and the T wave) (11, 18). A change in magnitude and/or orientation of the VG signifies a change in APD heterogeneity (11, 19). APD changes due to chronic RV pressure load must therefore change the VG (19). In a rat model, we recently demonstrated that the VG changes markedly during the development of pulmonary arterial hypertension (PAH), a model of chronic RV pressure load (17). We therefore decided to study the use of the VG in diagnosing chronic RV pressure load. In humans, however, comparison of ECGs at the time of diagnosis of PAH with ECGs from a disease-free state is, in general, not feasible, since PAH remains undetected for a long time (22). ECGs from PAH patients were therefore compared with ECGs from healthy controls. To further appreciate the diagnostic potential of the VG in chronic RV pressure load, all ECGs were also evaluated for the conventional criteria of increased right heart load (27).


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 DISCLOSURES
 REFERENCES
 
Patients. The study complies with the Declaration of Helsinki. Patient data were gathered as part of routine clinical care in the VU University Medical Center and were analyzed retrospectively. Healthy control subjects gave written informed consent for the present study, which was approved by The Institutional Ethical Review Board of the Leiden University Medical Center.

Between December 1999 and December 2005, 565 consecutive patients were evaluated with a right heart catheterization because of suspected PAH, defined as a mean pulmonary artery pressure (PAP) >25 mmHg and pulmonary capillary wedge pressure <15 mmHg. PAH was considered to be idiopathic when identifiable causes for pulmonary hypertension (i.e., congenital heart disease, portal hypertension, collagen vascular disease, HIV infection, left heart disease, hypoxic pulmonary disease, or chronic thromboembolic disease) were excluded (3, 14). One hundred ten patients were identified with idiopathic PAH. A digitally stored ECG recorded within 30 days before diagnostic right heart catheterization was available in 72 patients (15 male).

Right heart catheterization. All PAH patients underwent right heart catheterization, during which right atrial pressure, PAP, pulmonary capillary wedge pressure, and mixed venous oxygen saturation were measured. Cardiac output was calculated using Fick's principle. Oxygen consumption was measured during right heart catheterization. Pulmonary vascular resistance (in mmHg·l–1·min) was calculated by dividing the transpulmonary gradient (pressure difference between mean PAP and pulmonary capillary wedge pressure) by cardiac output.

ECG analysis. Conventional 10-s ECGs were recorded by certified ECG technicians using the standard 12-lead electrode configuration with patients in supine position. ECGs were recorded on commercially available electrocardiographs (MAC VU and MAC 5000, GE Healthcare; and Megacart, Siemens), at a paper speed of 25 mm/s; sensitivity 1 mV = 10 mm; sample frequency of 500 Hz. All ECGs were assessed for the presence of conventional 12-lead ECG criteria of RV hypertrophy (27). ECGs were also analyzed with LEADS, our noncommercial, research-oriented ECG analysis program that automatically renders amplitudes, areas, and vector directions (10). In short, LEADS automatically selects beats for averaging based on signal quality criteria (baseline, noise). This selection of beats is then reviewed and edited by the investigator. The thus selected beats are then averaged by LEADS. After manually reviewing and editing the onset and end of the QRS complex, a synthesized vectorcardiogram is generated with the inverse Dower matrix (10, 12). Parameters derived from this vectorcardiogram, such as the VG magnitude (mV·ms) and spatial orientation (azimuth°, orientation in the transversal plane, and elevation°, deviation from the transversal plane), are then calculated. The VG is defined as: {int}H(t)·dt, in which H(t) is the heart vector, as represented in the X, Y, and Z leads of the vectorcardiogram (5). This integral, taken over the QRST interval, is nonzero due to action potential morphologic differences in the ventricles, most often thought of as APD differences (11). Orientation of the axes is in accordance with the American Heart Association recommendations: x-axis positive from right to left, y-axis positive in craniocaudal direction, and z-axis positive in anteroposterior direction (24). Control ECGs were selected from a large database of healthy students of the Leiden University Medical Faculty. All ECGs were scrutinized for normality according to the Minnesota criteria by an experienced cardiologist (4). Prior to the use of the selected ECGs for comparison in this study, all ECGs were anonymized. All ECGs were analyzed twice by the first author (I. R. Henkens), and a third time by the second author (K. T. B. Mouchaers) to determine the intraobserver and interobserver variability for calculating the VG. Because the VG depends on heart rate (38) and sex, but not on age (unpublished observations), we matched each patient ECG for heart rate and sex with two ECGs from healthy subjects.

Cardiac magnetic resonance imaging. In 38 patients, cardiac magnetic resonance (CMR) imaging had been performed on a Siemens 1.5 T Sonata scanner (Siemens Medical Solutions, Erlangen, Germany) within 24 h of the ECG recording, as previously described (35). Cardiac short-axis cine images of both RV and LV were acquired from base to apex at 10-mm slice distance. A blinded observer delineated RV and LV endocardial and epicardial contours manually, and MASS software (Dept. of Radiology, Leiden University Medical Center, Leiden, the Netherlands) was used to obtain RV and LV mass ratios and RV and LV end-diastolic volume ratios.

Statistical analysis. The SPSS for Windows Software package (version 12.0.1, SPSS, Chicago, IL) was used for data analysis. Normally distributed values are presented as means and SD. Independent t-tests were used for comparison of PAH patients and healthy controls. Comparison of three categories was performed with one-way analysis of variance with post hoc Bonferroni correction. To determine the discriminative power of dichotomous variables for diagnosing PAH, cross-tabulations were used for determination of sensitivity and specificity. To determine the diagnostic value of vectorcardiogram-derived parameters compared with conventional electrocardiographic parameters, we used a receiver operating characteristic (ROC) analysis. Areas under the curve (AUC) were compared using the method proposed by Hanley and McNeil (15), which corrects for existing correlations between ROC curves derived from the same cases. Binary logistic regression analysis was used to determine the optimal model for classification of increased RV afterload for both ECG-derived variables and vectorcardiogram-derived variables. Subsequently, the optimal model was used in a bootstrapping analysis to determine the accuracy of the odds ratio (OR) in this classification model. Pearson correlation analysis was used for analysis of intraobserver and interobserver variability, as well as for comparison of the VG with CMR-derived variables of RV mass, and volume. A value of P < 0.05 was considered to be statistically significant.


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 DISCLOSURES
 REFERENCES
 
Patient characteristics at the time of the diagnostic right heart catheterization are presented in Table 1. Controls (n = 144, 30 male) were younger than patients (mean age: 19.7 ± 1.3 yr vs. 43.7 ± 22.8 yr; P < 0.001). Mean heart rate was 82 ± 17 beats/min in PAH patients vs. 80 ± 14 beats/min in controls (P = 0.47). Calculation of the VG proved to be highly reproducible, with both excellent intraobserver (r = 0.994, P < 0.001) and interobserver agreement (r = 0.992, P < 0.001).


View this table:
[in this window]
[in a new window]

  		Table 1. PAH patient characteristics

 
Typical examples of RV and PAPs with the corresponding ECG and vectorcardiogram findings are presented in Fig. 1 for a healthy subject (catheterized for exclusion of familial PAH after inconclusive transthoracic contrast echocardiography), a patient with moderate PAH, and a patient with severe PAH. It can be appreciated from leads I and aVF that an intermediate frontal plane QRS axis is present in the subject without PAH as well as in the patient with moderate PAH, whereas a right axis deviation is present in the patient with severe PAH. Furthermore, lead V1 is within normal limits for both the subject without PAH and the patient with moderate PAH, whereas lead V1 qualifies for RV hypertrophy in the patient with severe PAH: R > S and R > 5 mm, initial P wave > 1 mm high and wide, and the T wave is discordant with the QRS, reflecting RV strain. A closer look at the projection of the VG on the x-, y-, and z-axes reveals that the VG projection on the x-axis (net QRST area in the X lead) becomes smaller proportional to the degree of chronic RV pressure load. The lower panels illustrate also that chronic RV pressure load leads to a proportionate decrease in QRS and T integral vectors and to an increase in QRS-T spatial angle (Table 2), together resulting in a smaller and differently oriented VG.


Figure 1
View larger version (71K):
[in this window]
[in a new window]

  		Fig. 1. The effect of different levels of chronic right ventricular (RV) pressure load on the ECG and vectorcardiogram is illustrated in a patient without pulmonary arterial hypertension (PAH) (catheterized for exclusion of familial PAH after inconclusive transthoracic contrast echocardiography; left), a patient with moderate PAH (middle), and a patient with severe PAH (right), respectively. Top panels: RV and pulmonary artery (PA) pressures (PAP). Horizontal lines, mean PAP. Mean PAP = 11 mmHg in the patient without PAH, mean PAP = 43 mmHg in the patient with moderate PAH, and mean PAP = 64 mmHg in the patient with severe PAH. Of note is that the pressure scale is set at 0–20 mmHg in the control subject with normal RV pressure load, whereas the pressure scale is set at 0–100 mmHg in the patients with moderate and severe PAH. Second row panels: corresponding ECG leads I, aVF, and V1; no ECG abnormalities are present in the patient with moderate PAH, despite a chronically elevated RV pressure load. Third row panels: the ventricular gradient (VG) projections (QRST integral) on the x-, y-, and z-axis, revealing that the VG projection on the x-axis gradually becomes smaller, proportionate to the degree of chronic RV pressure load. The relation between the QRS integral, the T-wave integral, and the VG is illustrated in the bottom row for the VG projection on the x-axis (VGX) in the frontal plane. The VG (solid black line) is the vectorial sum of the QRS (dashed gray line) and T (solid gray line) integrals. VGX is the projection of the VG on the x-axis (dashed black line). Of note is that all numbers in the bottom panels are expressed in mV·ms, with a scale of 0–75 mV·ms for the control subject with normal RV pressure load and a scale of 0–25 mV·ms for the patients with moderate and severe PAH.

 

View this table:
[in this window]
[in a new window]

  		Table 2. Differences in ECG-derived variables between control subjects and patients with moderate or severe PAH

 
In general, conventional ECG criteria had low diagnostic accuracy for the presence of increased RV afterload (Table 3). With a sensitivity of 84% and a specificity of 96%, a QRS axis >90° in the frontal plane was the conventional ECG parameter with the highest individual diagnostic accuracy for chronically increased RV pressure load (Table 3). Multivariable binary logistic regression analysis performed in a backward stepwise fashion (removal if P > 0.10, inclusion if P < 0.05, a priori chance of PAH = 0.33) rendered the following formula for optimal prediction of presence of PAH: y = 2.204·(presence of rSr' or rSR' in lead V1) + 3.079·(presence of R:S > 1 in lead V1 with R > 0.5 mV) + 4.542·(presence of QRS axis >90°) – 6.679 (sensitivity = 89% and specificity = 94%; P < 0.001). Receiver-operating-curve analyses for diagnosis of increased RV pressure load are presented in Fig. 2. Although sensitivity and specificity did not differ importantly between the prediction based on a multivariable analysis compared with the single prediction of the presence of QRS axis > 90°, the multivariable prediction showed a larger AUC than QRS axis > 90° alone.


View this table:
[in this window]
[in a new window]

  		Table 3. Diagnosis of chronically increased right ventricular pressure load with conventional ECG criteria

 

Figure 2
View larger version (19K):
[in this window]
[in a new window]

  		Fig. 2. Receiver operating characteristic (ROC) curves for diagnosis of increased RV pressure load. Solid black line, ROC of the VG projection on the x-axis [continuous variable; area under the curve (AUC) = 0.993]; solid gray line, ROC of the presence of a QRS axis >90° in the frontal plane (dichotomous variable; AUC = 0.900); coarse dashed line, ROC of the QRS axis in the frontal plane (continuous variable; AUC = 0.904); fine dashed line, ROC of the composite model of conventional ECG criteria: y = 2.204·(presence of rSr' or rSR' in lead V1) + 3.079·(presence of R:S >1 in lead V1 with R > 0.5 mV) + 4.542·(presence of QRS axis >90°) – 6.679 (AUC = 0.945).

 
Significant differences in the VG were observed, however, between PAH patients and healthy controls. In general, in PAH patients the VG assumed a different orientation from healthy controls and was also considerably smaller: 34.8 ± 17.5 vs. 85.9 ± 27.6 mV·ms (P < 0.001; Fig. 3). It is easily appreciated from the bottom right panel that VG magnitude alone cannot accurately separate PAH patients and healthy controls. Multivariable analysis showed that a combination of VG magnitude and orientation had superior discriminating power to either variable alone, especially the VG projection on the x-axis. Multivariable analysis in a stepwise forward fashion (inclusion if P < 0.01, removal if P > 0.05), including the respective orthogonal projections of the mean QRS integrals, mean T-wave integrals, and the mean VGs, illustrated that of all the significantly related single variables, the VG projection on the x-axis was the variable with the highest discriminating power (Table 2). PAH patients and controls were therefore compared for the VG projection on the x-axis. The VG magnitude projection on the x-axis (AUC = 0.993) had a significantly larger AUC than presence of a QRS axis > 90° (dichotomous variable; AUC = 0.900, z-score = 3.36, P < 0.01), QRS axis in the frontal plane (continuous variable; AUC = 0.904, z-score = 2.89, P < 0.01), and the composite model of conventional ECG parameters (AUC = 0.945, z-score = 2.27, P < 0.05); see Fig. 2. Binary logistic regression analysis rendered the following formula for prediction of the presence of increased RV pressure load by the x component of the VG: y = –0.195·VGX + 6.195 (OR = 0.82 for each unit increase in VG projection on the x-axis) with a sensitivity of 97% and a specificity of 94%. Bootstrapping analysis validated the adequacy of this model, rendering a 95% confidence interval for the OR of 0.74–0.91 (P < 0.001) based on a normal distribution of the regression coefficients over the bootstrap samples. To assess whether the VG projection on the x-axis could differentiate between mild-to-moderate and severe PAH, patients were stratified in two categories according to mean PAP level: mean PAP = 25–45 mmHg (n = 16) and mean PAP > 45 mmHg (n = 56). Figure 4 illustrates that the VG projection on the x-axis was already markedly decreased in patients with mildly to moderately increased RV pressure load (mean PAP = 25–45 mmHg), and even more in patients with a severely increased RV pressure load (mean PAP > 45 mmHg). One-way analysis of variance showed that PAH patients with a mean PAP = 25–45 mmHg had a VG projection on the x-axis that was significantly lower than in controls (17.5 ± 15.0 mV·ms vs. 68.1 ± 22.0 mV·ms, P < 0.001), but still higher than in PAH patients with a mean PAP > 45 mmHg (17.5 ± 15.0 mV·ms vs. 2.8 ± 16.1 mV·ms; P = 0.033). Here, too, the projection of the VG on the x-axis showed the highest discriminating power, since the VG magnitude alone did not differentiate between patients with a mean PAP = 25–45 mmHg and patients with a mean PAP > 45 mmHg, although VG magnitude in both groups of PAH patients was lower than in controls (Table 2). Since the VG is the vectorial sum of the QRS and T integrals, projections of QRS and T integrals as well as the QRS-T spatial angle were also calculated. Mean QRS integral and mean T-wave integral magnitudes and projections on the x-, y-, and z-axes were generally different between controls and PAH patients, although the distinction between mild-to-moderate PAH and severe PAH could only be made by QRS integral projections on the x- and z-axes, the T-wave integral projection on the z-axis, and again the VG projection on the x-axis (Table 2). Overall, the QRS-T spatial angle was higher in patients with a chronically increased RV afterload than controls, signifying a higher degree of discordance between depolarization and repolarization (Table 2).


Figure 3
View larger version (44K):
[in this window]
[in a new window]

  		Fig. 3. Superimposed representations of the spatial orientation of all individual VG vectors in the frontal, transversal, and sagittal planes, and of the VG vector magnitude in the Vector-Y plane. Left-side plots: normal subjects. Right-side plots: PAH patients. Insets are frontal, transversal, and sagittal MRI slices of one arbitrarily chosen normal subject (left) and PAH patient (right). The MRI insets are chosen in such a way that the AV-node area is in the origin, which parallels the usual vectorial representation of the electrical heart activity. VG azimuths can be directly appreciated in the transversal plane, while the VG magnitudes and elevations can be directly appreciated in the Vector-Y plane. Of note is that this Vector-Y plane is a different plane for each vector; therefore, there is no representative MRI slice that can serve as an inset for the Vector-Y plane. All VG-Y planes have been superimposed to allow comparison of all VG magnitudes and elevations. These images illustrate that although in subjects with normal RV pressure load there is considerable heterogeneity in both VG orientation and magnitude, the VG orientation is quite different in PAH patients and VG magnitude is generally lower. Because of the heterogeneity of disease severity among PAH patients, the VG orientation and VG magnitude vary considerably among PAH patients. {circ}, an individual VG.

 

Figure 4
View larger version (14K):
[in this window]
[in a new window]

  		Fig. 4. In healthy controls (assumed mean PAP < 25 mmHg, n = 144), the VG projection on the x-axis is much larger than in patients with a chronically increased RV pressure load (mean PAP > 25 mmHg, n = 72). Furthermore, the VG projection on the x-axis allows distinction between a mildly to moderately elevated RV pressure load (mean PAP = 25–45 mmHg) and a severely elevated RV pressure load (mean PAP > 45 mmHg, n = 56).

 
CMR showed that RV mass was related to the VG projection on the x-axis (Fig. 5A), and a trend was observed toward a relation between a higher RV volume and a smaller VG projection on the x-axis (Fig. 5B).


Figure 5
View larger version (10K):
[in this window]
[in a new window]

  		Fig. 5. RV mass showed an inverse relation with the VG projection on the x-axis (r = –0.323, P = 0.048) (A), and there was a trend toward a similar inverse relation between a higher RV end-diastolic volume and the VG projection on the x-axis (r = –0.308, P = 0.067) (B). RVEDVI, RV end-diastolic volume indexed for body surface area; LVEDVI, left ventricular end-diastolic volume indexed for body surface area.

 

   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
DISCLOSURES
 REFERENCES
 
The key finding of the present study is that it proves that the ECG-derived VG is highly accurate in detecting chronic increase in RV pressure load, and as such it can be used to distinguish between normal RV pressure load, mildly to moderately increased RV pressure load, and severely increased chronic RV pressure load. Furthermore, the ECG-derived VG proved to be of higher diagnostic accuracy for chronically increased RV pressure load than conventional ECG parameters. Available CMR data suggest that VG changes in PAH patients reflect changes in APD heterogeneity related to RV remodeling as a result of an increased RV pressure load.

Vectorcardiography vs. electrocardiography. The general approach toward ECG interpretation is one directed at individual leads overlying cardiac regions of interest, whereas each lead is derived from the same heart vector. Although a projection of the VG in a direction of interest is essentially a similar simplification of assessing a 3-D process in time, this projection nevertheless holds all information derived from the two limb leads and six chest leads (25). The vectorcardiogram takes into account that ECG leads have a different sensitivity (among others because of the variation in proximity to the heart) and does not suffer from the problem that onset QRS, end QRS, and end T instants may differ per lead (25). The ECG-derived VG therefore renders robust results. Since calculation of the VG requires only straightforward integration over the QRST complex of the instantaneous heart vector (that can be synthesized from the ECG leads by a simple matrix multiplication) (12), this algorithm can easily be implemented in existing ECG analysis software, as we did in our LEADS program.

Despite the recognition of certain ECG characteristics in newborns and patients with an increased RV afterload, the diagnostic potential of conventional 12-lead ECG parameters for increased RV afterload has been reported as insufficient for clinical use or screening purposes (2, 26, 29, 32). The results of our study support this view, yet underline the importance of using the full potential of an electrocardiogram. Contemporary software now renders (synthesized) vectorcardiogram-derived calculations with such ease that clinical application of this information is certainly feasible (10).

Rationale for using the VG. The VG is oriented toward the left and slightly anteroinferior in healthy persons (Fig. 3) within a smaller range than the mean QRS axis orientation in the frontal plane (38). The VG is the integrated ventricular APD heterogeneity, which is the 3-D sum of the integrated ventricular depolarization and repolarization heterogeneities (11). As such, the VG has a strong physiological link to the way in which the ventricular APD distribution is affected by chronic RV pressure load. Any intraindividual change in the VG magnitude and orientation signifies an alteration in APD heterogeneity in the ventricles, and hence a change in myocardial electrophysiological properties (11, 19). Chou et al. (8) evaluated the use of QRS loop area for diagnosis of RV hypertrophy. As discussed by the authors, the QRS loop area is the sum of all depolarization vectors, allowing appreciation of the resultant spatial orientation and the ratio of leftward and rightward oriented forces, rendering evaluation of quantitative conventional ECG parameters of RV hypertrophy superfluous (8). Cowdery et al. (9) recognized the importance of the QRS loop area, and they further improved diagnostic accuracy for RV hypertrophy by interpreting QRS amplitude in the transversal plane (60% sensitivity and 96% specificity). Kawaguchi (20) further concluded that repolarization characteristics should not be overlooked, since in his diagnostic model for RV hypertrophy, the combined T loop area and direction rendered the best result. The high diagnostic accuracy for the presence of chronic RV pressure load of the 3D V-G (Fig. 3), which is the sum of QRS and T integrals, is in accordance with these reports regarding changes in QRS complex and T-wave morphology in patients with an increased RV pressure load (8, 9, 20).

There is a distinct evolution of ECG characteristics with developing PAH (17). Changes in VG with increasing RV pressure load are best assessed in 3-D, although single-lead assessment is theoretically possible (18, 19). Much as we observed in rats (17), a higher RV pressure load effectively cancels out the net LV contribution to the VG (Fig. 1, bottom panel) (1, 6, 17). Obviously, this cancellation effect occurs because RV pressure load-induced RV hypertrophy introduces APD heterogeneity substantially opposing the net LV APD heterogeneity. Thus, mild-to-moderate elevation of RV pressure load decreases VG magnitude, whereas VG orientation is largely maintained (Table 2 and Fig. 4). Further elevation of RV pressure load does not necessarily lead to a further decrease of VG magnitude, although it may drastically affect VG orientation (Figs. 1 and 4 and Table 2) (11). A comparison with CMR studies in a subgroup of patients showed that RV pressure load-induced changes in APD heterogeneity were related to changes in RV-to-LV mass ratio rather than to changes in RV-to-LV volume ratio. In steadily developing PAH, hypertrophy occurs already with mildly elevated PAP, before dilatation of the RV is seen. (17, 36). This may explain the closer association of the VG projection on the x-axis with RV hypertrophy rather than with RV dilatation.

Limitations. In the absence of available ECGs from the time before development of PAH, we compared the ECGs of patients with a mildly to moderately elevated RV afterload as well as the ECGs of patients with a severely elevated RV afterload with the ECGs of healthy control subjects. Since we may assume that idiopathic PAH patients once had a normal RV afterload, comparison with ECGs from healthy individuals seems to be the most obvious alternative (30, 33). This cross-sectional approach allows appreciation of the supposed evolution of changes in the VG in response to an increasing RV pressure load. The selection of patients with idiopathic PAH precludes application of our findings to patients with important lung disease or left-sided heart disease. However, since even a mildly to moderately elevated RV pressure load was associated with marked differences in the VG, the ECG seems a suitable screening tool for increased RV pressure load in selected groups of patients, such as relatives of patients with familial PAH, patients with HIV, systemic sclerosis, portal hypertension, or other diseases associated with development of PAH (2, 26). Despite the obvious advantages of simply projecting the VG in the direction of interest (the x-axis), a potential downside of this approach is the observed nonlinear relation between PAH severity and the degree of chronic RV pressure load (Fig. 4), which precludes classification of chronic RV pressure load beyond the categories of normal, mild-to-moderate, and severe RV pressure load. The size of our study group did not permit use of a learning set and test set. However, bootstrapping analysis confirmed the validity of the proposed predictive model of increased RV pressure load. The uneven sample sizes of mild-to-moderate PAH patients and severe PAH groups is suboptimal, yet a representative reflection of the high number of PAH patients with a mean PAP > 45 mmHg at the time of diagnosis. The limited sample size of patients with mild-to-moderate PAH in our study may have affected the ability of the other ECG variables to discriminate between mild-to-moderate PAH and severe PAH.

Clinical implications. In patients with a genetic profile or disease known to predispose to PAH, serial ECG recording may prove a feasible concept for early detection of an increasing RV afterload. Apart from incorporation of calculations based on the VG into software for electrocardiographs, another way of indirectly assessing the presence of chronic RV pressure load may be to calculate QRST areas in a lead with a lead vector that assumes about the direction of the x-axis, such as lead I or V6. Whether such an individual lead-based VG approximation will prove to be of similar diagnostic accuracy deserves further study. Screening for PAH among patients at risk is still subject to debate, but it is generally regarded as very costly because of the high rate of false negative diagnoses with the available tools for noninvasive detection (28, 37). The improved ECG detection of RV pressure load using the VG may dramatically cut the cost of screening. Whether sequential ECG recording allows for early distinction of "responders" from "nonresponders" to PAH-attenuating therapy by detection of VG changes, a distinction currently made by repetitive 6-min walking tests, cardiac magnetic resonance imaging or right heart catheterization deserves further study (21, 35). In patients without congenital or acquired left-sided heart disease and/or pulmonary disease, the VG may prove to be an important tool for screening purposes and follow-up.

In conclusion, chronically increased right ventricular pressure load induces changes in ventricular APD heterogeneity, which are reflected by distinct changes in the ventricular gradient. The ECG-derived ventricular gradient can be used with high accuracy for detection of chronically increased right ventricular pressure load, and it is a potentially useful tool for follow-up in selected groups of patients. VG changes in PAH patients likely reflect changes in ventricular APD heterogeneity related to RV remodeling as a result of an increased RV pressure load.


   DISCLOSURES
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 DISCLOSURES
REFERENCES
 
This study was supported by an unrestricted research grant from Actelion Pharmaceuticals Nederland, Woerden, The Netherlands.


   FOOTNOTES
 

Address for reprint requests and other correspondence: C. A. Swenne, Cardiology Dept., Leiden Univ. Medical Center, P. O. Box 9600, 2300 RC Leiden, The Netherlands (e-mail: c.a.swenne{at}lumc.nl)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   REFERENCES
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 DISCLOSURES
 REFERENCES
 

  1. Abildskov JA, Burgess MJ, Millar K, Wyatt R, Baule G. The primary T wave–a new electrocardiographic waveform. Am Heart J 81: 242–249, 1971.[CrossRef][Web of Science][Medline]
  2. Ahearn GS, Tapson VF, Rebeiz A, Greenfield JC Jr. Electrocardiography to define clinical status in primary pulmonary hypertension and pulmonary arterial hypertension secondary to collagen vascular disease. Chest 122: 524–527, 2002.[CrossRef][Web of Science][Medline]
  3. Barst RJ, McGoon M, Torbicki A, Sitbon O, Krowka MJ, Olschewski H, Gaine S. Diagnosis and differential assessment of pulmonary arterial hypertension. J Am Coll Cardiol 43: 40S–47S, 2004.[Abstract/Free Full Text]
  4. Blackburn H. Electrocardiographic classification for population comparisons. The Minnesota code. J Electrocardiol 2: 5–9, 1969.[Medline]
  5. Burger HC. A theoretical elucidation of the notion ventricular gradient. Am Heart J 53: 240–246, 1957.[CrossRef][Web of Science][Medline]
  6. Burgess MJ, Millar K, Abildskov JA. Cancellation of electrocardiographic effects during ventricular recovery. J Electrocardiol 2: 101–107, 1969.[Medline]
  7. Chemla D, Castelain V, Herve P, Lecarpentier Y, Brimioulle S. Haemodynamic evaluation of pulmonary hypertension. Eur Respir J 20: 1314–1331, 2002.[Abstract/Free Full Text]
  8. Chou TC, Masangkay MP, Young R, Conway GF, Helm RA. Simple quantitative vectorcardiographic criteria for the diagnosis of right ventricular hypertrophy. Circulation 48: 1262–1267, 1973.[Abstract/Free Full Text]
  9. Cowdery CD, Wagner GS, Starr JW, Rogers G, Greenfield JC Jr. New vectorcardiographic criteria for diagnosing right ventricular hypertrophy in mitral stenosis: comparison with electrocardiographic criteria. Circulation 62: 1026–1032, 1980.[Abstract/Free Full Text]
  10. Draisma HHM, Swenne CA, Van de Vooren H. LEADS: an interactive research oriented ECG/VCG. Comput Cardiol 32: 515–518, 2005.
  11. Draisma HHM, Schalij MJ, van der Wall EE, Swenne CA. Elucidation of the spatial ventricular gradient and its link with dispersion of repolarization. Heart Rhythm 3: 1092–1099, 2006.[CrossRef][Web of Science][Medline]
  12. Edenbrandt L, Pahlm O. Vectorcardiogram synthesized from a 12-lead ECG: superiority of the inverse Dower matrix. J Electrocardiol 21: 361–367, 1988.[CrossRef][Web of Science][Medline]
  13. Farb A, Burke AP, Virmani R. Anatomy and pathology of the right ventricle (including acquired tricuspid and pulmonic valve disease). Cardiol Clin 10: 1–21, 1992.[Medline]
  14. Galie N, Torbicki A, Barst R, Dartevelle P, Haworth S, Higenbottam T, Olschewski H, Peacock A, Pietra G, Rubin LJ, Simonneau G, Priori SG, Garcia MA, Blanc JJ, Budaj A, Cowie M, Dean V, Deckers J, Burgos EF, Lekakis J, Lindahl B, Mazzotta G, McGregor K, Morais J, Oto A, Smiseth OA, Barbera JA, Gibbs S, Hoeper M, Humbert M, Naeije R, Pepke-Zaba J. Guidelines on diagnosis and treatment of pulmonary arterial hypertension. The Task Force on Diagnosis and Treatment of Pulmonary Arterial Hypertension of the European Society of Cardiology. Eur Heart J 25: 2243–2278, 2004.[Free Full Text]
  15. Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 148: 839–843, 1983.[Abstract/Free Full Text]
  16. Harrigan RA, Jones K. ABC of clinical electrocardiography. Conditions affecting the right side of the heart. BMJ 324: 1201–1204, 2002.[Free Full Text]
  17. Henkens IR, Mouchaers KT, Vliegen HW, van der Laarse WJ, Swenne CA, Maan AC, Draisma HH, Schalij I, van der Wall EE, Schalij MJ, Vonk-Noordegraaf A. Early changes in rat hearts with developing pulmonary arterial hypertension can be detected with three-dimensional electrocardiography. Am J Physiol Heart Circ Physiol 293: H1300–H1307, 2007.[Abstract/Free Full Text]
  18. Hurst JW. Thoughts about the ventricular gradient and its current clinical use (Part I of II). Clin Cardiol 28: 175–180, 2005.[CrossRef][Web of Science][Medline]
  19. Hurst JW. Thoughts about the ventricular gradient and its current clinical use (part II of II). Clin Cardiol 28: 219–224, 2005.[CrossRef][Web of Science][Medline]
  20. Kawaguchi Y. Studies on deflection area vectors of QRS and T and ventricular gradient in right ventricular hypertrophy. Jpn Circ J 49: 395–405, 1985.[Medline]
  21. Kawut SM, Palevsky HI. Surrogate end points for pulmonary arterial hypertension. Am Heart J 148: 559–565, 2004.[CrossRef][Web of Science][Medline]
  22. Kim NH. Diagnosis and evaluation of the patient with pulmonary hypertension. Cardiol Clin 22: 367–3vi, 2004.[CrossRef][Web of Science][Medline]
  23. Kosiborod M, Wackers FJ. Assessment of right ventricular morphology and function. Semin Respir Crit Care Med 24: 245–262, 2003.[CrossRef][Web of Science][Medline]
  24. Kossmann CE, Brody DA, Burch GE, Hecht HE, Johnston FD, Kay C, Lepeschkin E, Pipberger HV, Baule G, Berson AS, Briller SA, Geselowitz DB, Horan LG, Schmitt OH. Report of committee on electrocardiography, American Heart Association. Recommendations for standardization of leads and of specifications for instruments in electrocardiography and vectorcardiography. Circulation 35: 583–602, 1967.[Free Full Text]
  25. MacFarlane PW, Edenbrandt L, Pahlm O. 12 Lead Vectorcardiography. Oxford, UK: Butterworth-Heinemann, 1995.
  26. McGoon M, Gutterman D, Steen V, Barst R, McCrory DC, Fortin TA, Loyd JE. Screening, early detection, and diagnosis of pulmonary arterial hypertension: ACCP evidence-based clinical practice guidelines. Chest 126: 14S–34S, 2004.[CrossRef][Web of Science][Medline]
  27. Mirvis DM, Goldberger AL. Electrocardiography. In: Braunwald's Heart Disease, edited by Zipes DP, Libby P, Bonow RO, and Braunwald E. Philadelphia, PA: Saunders, 2004, p. 120–125.
  28. Mukerjee D, St GD, Knight C, Davar J, Wells AU, Du Bois RM, Black CM, Coghlan JG. Echocardiography and pulmonary function as screening tests for pulmonary arterial hypertension in systemic sclerosis. Rheumatology (Oxford) 43: 461–466, 2004.[CrossRef][Medline]
  29. Penaloza D, Rias-Stella J. The heart and pulmonary circulation at high altitudes: healthy highlanders and chronic mountain sickness. Circulation 115: 1132–1146, 2007.[Abstract/Free Full Text]
  30. Perros F, Dorfmuller P, Humbert M. Current insights on the pathogenesis of pulmonary arterial hypertension. Semin Respir Crit Care Med 26: 355–364, 2005.[CrossRef][Web of Science][Medline]
  31. Punukollu G, Gowda RM, Vasavada BC, Khan IA. Role of electrocardiography in identifying right ventricular dysfunction in acute pulmonary embolism. Am J Cardiol 96: 450–452, 2005.[CrossRef][Web of Science][Medline]
  32. Rich S, Dantzker DR, Ayres SM, Bergofsky EH, Brundage BH, Detre KM, Fishman AP, Goldring RM, Groves BM, Koerner SK. Primary pulmonary hypertension. A national prospective study. Ann Intern Med 107: 216–223, 1987.[CrossRef][Web of Science][Medline]
  33. Rubin LJ. Pathology and pathophysiology of primary pulmonary hypertension. Am J Cardiol 75: 51A–54A, 1995.[CrossRef][Medline]
  34. Sukhija R, Aronow WS, Ahn C, Kakar P. Electrocardiographic abnormalities in patients with right ventricular dilation due to acute pulmonary embolism. Cardiology 105: 57–60, 2006.[CrossRef][Web of Science][Medline]
  35. Van Wolferen SA, Marcus JT, Boonstra A, Marques KM, Bronzwaer JG, Spreeuwenberg MD, Postmus PE, Vonk-Noordegraaf A. Prognostic value of right ventricular mass, volume, and function in idiopathic pulmonary arterial hypertension. Eur Heart J 28: 1250–1257, 2007.[Abstract/Free Full Text]
  36. Vonk-Noordegraaf A, Marcus JT, Holverda S, Roseboom B, Postmus PE. Early changes of cardiac structure and function in COPD patients with mild hypoxemia. Chest 127: 1898–1903, 2005.[CrossRef][Web of Science][Medline]
  37. Williams MH, Handler CE, Akram R, Smith CJ, Das C, Smee J, Nair D, Denton CP, Black CM, Coghlan JG. Role of N-terminal brain natriuretic peptide (N-TproBNP) in scleroderma-associated pulmonary arterial hypertension. Eur Heart J 27: 1485–1494, 2006.[Abstract/Free Full Text]
  38. Yano K, Pipberger HV. Spatial magnitude, orientation, and velocity of the normal and abnormal QRS complex. Circulation 29: 107–117, 1964.[Abstract/Free Full Text]



This article has been cited by other articles:


Home page
 ChestHome page
I. R. Henkens, C. T.-J. Gan, S. A. van Wolferen, M. Hew, A. Boonstra, J. W. R. Twisk, O. Kamp, E. E. van der Wall, M. J. Schalij, A. Vonk Noordegraaf, et al.
ECG Monitoring of Treatment Response in Pulmonary Arterial Hypertension Patients
Chest, December 1, 2008; 134(6): 1250 - 1257.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
294/5/H2150    most recent
01312.2007v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Web of Science (2)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Henkens, I. R.
Right arrow Articles by Vliegen, H. W.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Henkens, I. R.
Right arrow Articles by Vliegen, H. W.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Visit Other APS Journals Online
Copyright © 2008 by the American Physiological Society.