World Journal of Cardiovascular Diseases, 2013, 3, 380-388 WJCD Published Online August 2013 (
Magnetocardiography capabilities in myocardium
injuries diagnosis
V. Sosnytskyy1, I. Chaikovsky2*, L. Stadnyuk3, G. Miasnykov2, A. Kazmirchyk2,
T. Sosnytska2, O. Gurjeva1
1National Scientific Center, M. D. Strajesko Institute of Cardiology, Academy of Medical Sciences of Ukraine, Kiev, Ukraine
2General Military-Medical Clinical Center, Kiev, Ukraine
3P. L. Shupik National Medical Academy of Postgraduate Education, Kiev, Ukraine
Email: *
Received 9 May 2013; revised 28 June 2013; accepted 15 July 2013
Copyright © 2013 V. Sosnytskyy et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Objective: The electrophysiological properties of the
myocardium are extremely heterogeneous. Verifica-
tion of new magnetocardiography (MCG) signs ap-
pears an important aspect for severity assessment of
ischemic myocardium damage, ischemic heart disease
(IHD) course prognosis, determining of indications
for preventive “aggressive” therapy and estimation of
its efficacy in patients with IHD. The objective of this
research was the investigation of magnetocardiogra-
phy (MCG) capabilities in diagnosis of ischemic and
inflammatory myocardial injuries using new MCG
markers of the spatiotemporal organization of myo-
cardium excitation. Methods and results: There were
128 patients examined in three groups. Group 1 con-
tained 34 healthy volunteers. Group 2 contained 62
patients with IHD diagnosis. Group 3 included 32
comparatively young patients with acute myocarditis
diagnosis. MCG-mapping of patients was performed
at rest on the 7-channel MCG-scanners “Cardiomag-
scan” V 3.1 (Company KMG, Ukraine) in non-shiel-
ded MCG laboratory. 11 MCG markers were deter-
mined for selected time intervals of the cardiac cycle.
Obtained data provided evidences about significant
differences in values of proposed MCG markers for
various groups. In patients with AMI, rate of pa-
rameters change is higher than without AMI
(Sub-groups 2.1 and 2.2 differ by 8 MCG markers).
Patients of 2nd and 3rd groups are different from
healthy patients by 8 of 11 markers. Analysis of the
obtained data has demonstrated good capabilities of
MCG in differential diagnostics. Application of dis-
criminatory analysis allowed us to get classification
functions, which could be used (with 82% accuracy)
to qualify the just examined patient to the investi-
gated categories. Conclusion: Based on the new me-
thodological approach during the studies, the most
informative MCG-criteria of space-temporal organi-
zation of myocardium excitation in patients with IHD
has been proposed. The method is able to distinguish
healthy subjects and myocarditis patients and pa-
tients with IHD without previous MI with high sensi-
tivity and specificity.
Keywords: Transmural Electric Heterogeneity;
Magnetocardiography; Myocardial Ischemia;
Myocarditis; Differential Diagnostics
Nowadays routine clinic-functional diagnostic methods
of ischemic heart disease (IHD) are mostly based on
clinical signs of disease and ECG ST segment shift in
rest and during functional tests. It is well known that
changes of ST segment and T wave could be aroused not
only from IHD, but also from many other diseases. Di-
agnostic difficulties are frequently caused by abnormal
clinical implication of IHD, including painless myocar-
dial ischemia. Coronary angiography (CAG) still remains
the basic method for IHD diagnosis. CAG is usually used
for patients with IHD symptoms and with positive or
controversial results of screening tests (stress ECG, stress
echocardiography) in order to confirm availability and
expansion of vascular injuries, for estimation of revas-
cularization feasibility and adequacy, coronary athero-
sclerosis progression or regression. At the same time, in
being dependent of the population distinctions of the
examined series, 19% to 57% of the examined patients
may not have significant coronary artery stenosis [1].
*Corresponding author. Search and verification of new electrophysiological
V. Sosnytskyy et al. / World Journal of Cardiovascular Diseases 3 (2013) 380-388 381
signs appears important aspects for severity assessment
of ischemic myocardium damage, IHD course prognosis,
determining of indications for preventive “aggressive”
therapy and estimation of its efficacy in patients with
IHD. Magnetocardiography (MCG) is a noninvasive
measurement technology for magnetic signals generated
by the heart’s electrical activity sources [2]. As compared
to ECG, advantages of MCG are determined by its ex-
treme sensitivity to tangential components of myocardial
currents and lover (as opposed to ECG) dependency of
monitored magnetic field parameters against the influ-
ence of multilayer anisotropic conductive medium, sur-
rounding the current source. Furthermore, MCG is sensi-
tive to vortex flows (circular currents, injury currents),
which couldn’t be registered with ECG at all. Thereby,
MCG is able to detect activation disorders caused by
myocardial ischemia more accurately and at an earlier
stage than ECG [5]. During investigations of limitations
of the IHD diagnosis at rest, it was determined that MCG
exceeds ECG with diagnosis accuracy 60% - 90% for
different examined populations [6-10]. Analysis of the
current density distribution maps allowed to distinguish
IHD-patients with and without haemodynamically sig-
nificant stenosis with 62.8% sensitivity and 61.3% speci-
ficity [7]. K. Toltstrup in his investigation of 75 patients
with acute retrosternal pain notes that while stress
EchoCG possesses sensitivity 91.3% and specificity 75%,
MCG in rest possesses sensitivity 87.1% and specificity
85.7% [9]. As a result of investigation of the patients’
group with stable exertional angina before carrying out
the coronary arteriography, Chen, et al. [10] have dem-
onstrated the specificity of MCG scanning up to 97% and
sensitivity—80% to 85%. During retrosternal pain in
patients with complete block of the left bundle-branch, it
is important to perform early diagnosis of acute coronary
syndrome. Park, et al. [11] have identified high sensiti-
vity and specificity of MCG as compared to Troponin I
Non-coronary myocardial diseases, particularly myo-
carditis, are often accompanied by expressed pain syn-
drome, but clinically available practical methods of dif-
ferential diagnostics are insufficiently informative.
Objective of this research was to investigate MCG ca-
pabilities in diagnosis of ischemic and inflammatory
myocardial injuries using new MCG markers of the spa-
tiotemporal organization of myocardium excitation.
2.1. Basic Characteristics of Examined Patients
There were 128 patients examined in three groups.
Group 1 contained 34 healthy volunteers aged from 27
to 40 years (mean age 36 ± 6.4 years), passed through the
comprehensive laboratory and instrumental research,
including ECG at rest and post-exercise ECG, Echo-CG.
Group 2 contained 62 patients with the diagnosis of
IHD. The following criteria were used to exclude pa-
tients from examination: complete block of the left bun-
dle-branch on the ECG, Stage IIB-III of chronic heart
failure, severe diabetes, Stage III of hypertensive disease,
renal and hepatic failure, obstructive respiratory diseases,
locomotorium diseases preventing exercise testing. Pa-
tients of the Group 2 were divided into 2 Sub-groups (2.1
and 2.2). Sub-group 2.1 was composed on the base of
random retrospective study of data obtained in examina-
tion of 183 patients during 2001-2002 years in the Kath.
Krankenhaus, Department of Medicine, Philippusstift
(Essen, Germany). MCG examinations were performed
using MCG system MCG-7 (SQUIG AG, Germany) with
participation of authors of this paper as MCG-7 system
developers. 30 patients with low-grade indications of
IHD resulted from the clinical and instrumental research
were selected from the common examined group. Se-
lected patients had slightly changed ECG, neither myo-
cardial infarction (MI) anamnesis, nor signs of myocar-
dial hypertrophy according to Echo-CG results; thereat,
according to the angiographic study data, stenosis of one,
two or three vessels or of trunk of the left coronary artery
with diameter less than 50% were detected in all of these
patients. Mean age of examined patients was 55 ± 10
Sub-group 2.2. In order to estimate informative value
of new MCG markers at rest in patients with acute MI
(AMI) dependent on myocardial ischemia signs avail-
ability, detected during exercise test, we have analyzed
examination results of 32 patients with Q-wave AMI (30
man and 1 women) 31 - 70 years old (mean age 54.2 ±
1.8 years), which underwent medical treatment in the
intensive care unit of the NSC “M. D. Strajesko Institute
of Cardiology”, NAS of Ukraine. AMI diagnosis was
determined on the base of standard criteria [12]. On the
10th - 12th day of AMI, patients were subjected to exer-
cise examination (treadmill test under modified Bruce
protocol using treadmill “Cardioperfect”, USA), and to
MCG. During exercise test myocardial ischemia signs
were detected in 21 patients (Sub-group 2.2A); in 11
patients (Sub-group 2.2B), test findings were negative.
Sub-groups were comparable both by clinical-anamnesis
data and by medical treatment.
Group 3 included 32 comparatively young patients (17
to 29 years, mean age 23 ± 2.4 years), which underwent
medical treatment in the non-coronary heart diseases and
clinical rheumatology unit of NSC “M. D. Strajesko In-
stitute of Cardiology”, NAS of Ukraine, and in the rheu-
matology unit of General Military-Medical Clinical
Center DM of Ukraine with acute myocarditis. “Myocar-
ditis” was diagnosed on the base of disease relation with
recently previous virus infection or presence of the
chronic infection nidus in the body, results of clinical
instrumental and laboratory researches and with account
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V. Sosnytskyy et al. / World Journal of Cardiovascular Diseases 3 (2013) 380-388
of diagnostic criteria, recommended by New York Heart
Association. Young ages of patients make it possible to
decrease significantly the IHD probability.
2.2. Magnetocardiography
MCG-mapping of patients was performed at rest on the
7-channel MCG-scanners “Cardiomagscan” V 3.1 (Com-
pany KMG, Ukraine) in non-shielded MCG laboratory
premise of the NSC “M. D. Strajesko Institute of Cardi-
ology”, NAS of Ukraine and in MCG laboratory of the
General Military-Medical Clinical Center DM of Uk-
Magnetic field of the heart was registered in 36 points
of the 8 cm pitch rectangular grid 3 × 3 with simultane-
ous recording of the second standard ECG lead. On the
base of 36 synchronous averaged MCG-curves momen-
tary, equi-induction maps of magnetic field distribution
were plotted using 2D interpolation algorithms. In con-
trary to the previous MCG investigations using “inverse
solution” algorithm, equi-induction maps of magnetic
field distribution were transformed into current density
vectors (CDV) distribution maps, followed-up by appli-
cation of original indicants.
Each CDV distribution map was used for calculation
of single-step magnitudes of the maximal and global
current density, and then curves were plotted represent-
ing variations of these values during the overall cardiac
cycle or its separate segments. Duration of the maximum
CDV was used as the maximum density value (Max).
Arithmetic sum of duration values of all CDV for given
single-step map was used as the global current density
magnitude (Sum). Every following point of the curves
(separate single-step map) was plotted with 4 ms interval
for ventricular depolarization and 10 ms for ventricular
repolarization. Then cardio-cycle intervals durations
were sequentionally calculated using current density
variation curves. Time points when variation curves of
maximum or global current density values reached zero
line were considered as start and end of the time interval.
More detailed description of this magnetic mapping
technology and basic data interpretation concept is re-
viewed in [13].
In order to estimate temporal organization of ventricu-
lar depolarization, we have chosen the following MCG
1) time interval duration from the start of the QRS
complex to the R-wave peak—t1;
2) magnitude of the maximum (MaxR) and global
(SumR) current densities at the R-wave peak;
3) depolarization interval duration—QRS;
4) angle difference between directions of the maxi-
mum CDV at the R and T peaks—Delta RT
In order to estimate disturbance ratio of the temporal
organization of ventricular repolarization, we have cho-
sen the following time intervals:
1) interval of the regional electric heterogeneity (be-
ginning——of ST- Ta), which characterize the regional
electric heterogene- ity of myocardium in the “ischemia
window”; this interval was divided onto two
sub-intervals D1 and D2, where deviation (displacement)
of the maximum current density vector was estimated
compared to its original value. In addition, at the moment
of 80 ms from the J-point we have registered direction
angle of the maximum current density vector and esti-
mated its deviation from the normal direction limits
(Delta 80);
2) myocardium transmural electric heterogeneity in-
terval (Ta-e) was also splitted onto two equal sub-in-
tervals D3 and D4, where deviation of the maximum cur-
rent density vector was also estimated.
11 MCG markers {designations in tables} were deter-
mined for selected time intervals of the cardiac cycle:
{N1}QRSduration of the QRS complex (ms); {N2}
Delta 80maximum current density vector deviation
from the normal direction at 80 ms moment from the
J-point; {N3}D1; {N4}D2; {N5}D3; {N6}D4
(D1, D2, D3, D4maximum current density vector devia-
tion at 4 ST-T sub-intervals (starting at 60 ms from the
J-point)); {N7}Ta-etime interval duration from the
peak to the end of Т-wave; {N8}Delta RTdifference
between direction angles of the maximum current density
vector at R and T peaks; {N9}SumR/SumТratio of
the global current density at the R-peak to the global
current density at the T-peak; {N10}MaxR/MaxТ
ratio of the global maximum current density at the R-
peak to the maximum current density at the T-peak; {N11}
(QRSt1)/t1symmetry factor of the QRS complex.
Obtained results were processed with variation and
non-parametric statistics methods using applied statistics
software packages “Microsoft Excel” and “Statistica” for
Windows by calculation of arithmetic mean (M) and
standard error of mean (m) values for each variation se-
ries. Deviations validity was determined using Student’s
t-criterion. Deviations were assumed valid for P < 0.05.
Discriminatory analysis has been performed in order to
determine possibility of results prognostication by MCG-
data. The “model” was applied allowing prediction con-
cerning the set particular patient would belong to. For
this purpose we used step-by-step discriminatory analy-
sis with inclusion of the variable with maximum contri-
bution into differences between data sets at each analysis
2.3. Results
Results of the primary data procession are listed in Ta-
bles 1(a) and (b) and 2(a) and (b).
Obtained data evidence about significant differences in
values of proposed MCG markers for various groups.
Thus, patients of Groups 2 and 3 differ from healthy pa-
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V. Sosnytskyy et al. / World Journal of Cardiovascular Diseases 3 (2013) 380-388
Copyright © 2013 SciRes.
Table 1. Values of MCG markers in groups and sub-groups (M ± m).
QRS (ms) Delta 80 D1 D
2 D
3 D
1 77.8 ± 1.73 3.1 ± 0.64 3.2 ± 0.54 2.7 ± 0.34 2.6 ± 0.36 4.5 ± 0.4
2 80.2 ± 1.69 52.2 ± 7.56 7.9 ± 0.75 8 ± 0.84 5.6 ± 0.68 10.4 ± 1.3
2.1 73.2 ± 1.77 61.6 ± 11.4 7.2 ± 1.06 5.5 ± 0.96 3.9 ± 0.71 8.2 ± 1.3
2.2.A 87.8 ± 3.2 51.9 ± 14.3 10.4 ± 1.44 12.8 ± 1.55 8.1 ± 1.4 15.9 ± 2.8
2.2.B 84.7 ± 2.79 27.3 ± 8.87 5.0 ± 0.69 5.5 ± 1.06 5.5 ± 1.51 5.9 ± 1.1
3 83.6 ± 2.43 36.8 ± 8.92 7.8 ± 1.52 7.9 ± 1.72 6.5 ± 1.53 14.4 ± 2.5
Ta-e Delta RT SumR/SumT MaxR/MaxT (QRS-t1)/t1
1 110.3 ± 1.66 21.2 ± 1.95 4.8 ± 0.3 3.6 ± 0.25 1.4 ± 0.06
2 96.6 ± 2.11 65.7 ± 7.17 5.1 ± 0.4 4 ± 0.26 1.4 ± 0.05
2.1 93 ± 2.31 31.2 ± 4.21 6.4 ± 0.7 4.3 ± 0.42 1.3 ± 0.05
2.2.A 105.2 ± 4.06 125.8 ± 11.7 3.4 ± 0.4 3.7 ± 0.41 1.6 ± 0.11
2.2.B 90 ± 5.05 45.4 ± 6.6 4.5 ± 0.6 3.7 ± 0.5 1.5 ± 0.12
3 102.7 ± 5.24 40.4 ± 3.91 8.6 ± 0.8 5.2 ± 0.48 1.6 ± 0.1
Table 2. Student’s test results for deviations validity of MCG markers in different groups.
MCG-markers (part 1)
Comparison Groups
QRS (ms) Delta 80 D1 D
2 D
3 D
1 - 2 0.320 <0.001 <0.001 <0.001 <0.001 <0.001
1 - 3 0.055 0.001 0.007 0.006 0.018 0.001
2 - 3 0.251 0.194 0.971 0.988 0.592 0.165
2.1 - 2.2 <0.001 0.598 0.077 <0.001 0.011 0.024
2.1 - 2.2.A <0.001 0.598 0.077 <0.001 0.011 0.024
2.2.А - 2.2.B 0.474 0.154 0.002 <0.001 0.224 0.004
2.1 - 2.2.B 0.002 0.023 0.089 0.993 0.334 0.204
2.1 - 3 0.146 0.001 0.236 <0.05 0.672 0.233
MCG-markers (part 2)
Comparison Groups
Ta-Te Delta RT SumR/SumT MaxR/MaxT (QRS-t1)/t1
1 - 2 <0.001 <0.001 0.678 0.003 0.977
1 - 3 0.010 <0.001 <0.001 0.003 0.089
2 - 3 0.286 0.003 <0.001 0.027 0.080
2.1 - 2.2 0.013 <0.001 0.001 0.259 0.016
2.1 - 2.2A 0.013 <0.001 0.001 0.259 0.016
2.2А - 2.2B 0.028 <0.001 0.143 0.917 0.435
2.1 - 2.2.B 0.597 0.083 0.056 0.366 0.147
2.1 - 3 0.067 0.078 0.048 0.875 0.048
V. Sosnytskyy et al. / World Journal of Cardiovascular Diseases 3 (2013) 380-388
tients by 8 of 11 markers; herewith patients with myo-
carditis were additionally different by the value of SumR/
SumT. Groups 2 and 3 were different from each other by
the values of 3 parameters.
It’s interesting to compare MCG markers for different
courses of IHD (in sub-groups of the Group 2). In pa-
tients with AMI, rate of parameters changes is higher
than without AMI (Sub-groups 2.1 and 2.2 differ by 8
MCG markers). Among patients with AMI data analysis
have demonstrated much higher rate of MCG changes
under the positive stress-test (Sub-group 2.2A as com-
pared to 2.2B), moreover these sub-groups were different
from each another by 5 MCG markers values. Therefore,
when compared to the Sub-group 2.1 (without MI in
anamnesis), Sub-group 2.2A differed by 8 parameters,
while Sub-group 2.2Bonly by 2 parameters.
Analysis of obtained data has demonstrated good ca-
pabilities of MCG in differential diagnostics.
Application of discriminatory analysis allowed us to
get classification functions, that could be used (with cer-
tain accuracy) to qualify just examined patient to the
investigated categories. Table 3 demonstrates the input
of each variable to the patients qualifying model to one
or another group.
Value of Wilks’ Lambda 0.35, p-level p = 0.0001 at
F-criterion 11.5 evidence about rather good discrimina-
tion. Using classification functions, obtained as a result
of discriminative analysis, we can qualify patient to one
of three investigated categories with 82% accuracy.
There are three discriminant functions (a discriminant
function is a linear combination of the discriminating
variables) obtained with standardized coefficients for the
three most informative variables, selected by the pro-
gramTable 4.
Resulted discriminant functions have the following
Group10.02N21.33 N9 10.83 N11
0.04 N80.31N70.07 N6
0.23 N40.02N328.14
  
Group20.01N2 1.35 N9 10.62N11
0.04N80.31N70.01 N6
0.23 N40.02N325.29
 
Group30.01 N2 1.91 N9 13.52N11
0.04N80.28 N70.05 N6
0.40N40.11 N336.16
  
Every new observation is calculated vs. these three
functions. New patient would be qualified to the class
with maximum qualification value (i.e., with high prob-
ability he has correspondent disease).
Scattering graph of canonical values allows to visual-
ize variability of results and to observe the data cloud for
Table 3. Summary table for discriminatory analysis of data for
three main groups (Groups 1, 2, 3).
Wilks’ Lambda F-remove
(2.129) p-level
N2—Delta 80 0.39 7.40 0.001
N9—SumR/SumТ 0.49 25.83 0.000
N11—(QRS- t1)/t10.39 8.24 0.000
N8—Delta RT 0.40 9.50 0.000
N7—Ta-e 0.39 6.59 0.002
N6—D4 0.38 6.09 0.003
N4—D2 0.38 5.71 0.004
N3—D1 0.36 2.29 0.105
Table 4. Standardized (normalized) coefficients of the dis-
criminant function.
Group 1 Group 2 Group 3
p = 0.32374 p = 0.44604 p = 0.23022
N2—Delta 80 0.02 0.01 0.01
N9—SumR/SumТ 1.33 1.35 1.91
N11—(QRS- t1)/t1 10.83 10.62 13.52
N8—Delta RT 0.04 0.01 0.04
N7—Ta-e 0.31 0.26 0.28
N6—D4 0.07 0.01 0.05
N4—D2 0.23 0.31 0.40
N3—D1 0.02 0.04 0.11
Constant 28.14 25.29 36.16
each selected group. Scattering graph of canonical values
(Figure 1) represents the patient groups splitting.
It’s very important to develop new differential criteria
between IHD patients with slight ECG changes and
without MI in anamnesis and with myocarditis with in-
distinct clinical implications.
Using discriminatory analysis we have obtained dis-
criminant functions with standardized coefficients for the
most informative MCG markers of the Sub-group 2.1
and Group 3 (Tables 5, 6).
Value of Wilks’ Lambda 0.57, p-level p = 0.0001 at
F-criterion 5.77 evidence about rather good discrimination.
Using classification functions, obtained as a result of
discriminative analysis, we can qualify patient to one of
two investigated categories with 82% accuracy.
As a result of discriminative analysis, obtained dis-
criminant functions have following form:
Sub-group2.10.59N20.90N9 1.13 N11
0.004 N8 0.16 N70.03N6
0.17 N426.58 N3 36.16
 
 
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V. Sosnytskyy et al. / World Journal of Cardiovascular Diseases 3 (2013) 380-388 385
Table 5. Summary table for discriminatory analysis of data for
the Sub-group 2.1 and Group 3.
Wilks’ Lambda
(2.129) p-level
N1—QRS 0.60 2.18 0.146
N9—SumR/SumТ 0.72 14.02 0.000
N11—(QRS- t1)/t1 0.62 4.11 0.048
N2—Delta 80 0.64 5.98 0.018
N4—D2 0.61 3.85 0.045
N6—D4 0.59 1.46 0.233
N3—D1 0.59 1.44 0.236
Table 6. Coefficients of the discriminant function for the
Sub-group 2.1 and the Group 3.
Sub-group 2.1 Group 3
p = 0.48387 p = 0.51613
N1—QRS 0.59 0.64
N9—SumR/SumТ 0.90 1.22
N11—(QRS- t1)/t1 1.13 3.23
N2—Delta 80 0.00 0.02
N4—D2 0.16 0.25
N6—D4 0.03 0.01
N3—D1 0.17 0.24
Constant 26.58 36.84
Group30.64 N21.22 N93.23N11
0.004N80.25 N70.01 N6
0.24 N4 36.84 N336.16
Compared to the surface ECG, MCG has more selective
capabilities for registration of electric activity on the
certain depth of myocardium [19], i.e. provides possibil-
ity to estimate electromagnetic activity predominantly of
those heart’s areas (and muscular layers) with maximum
ions flow density. That is why MCG markers, related to
the “ischemia window”, are more informative in detec-
tion of slightly ischemic myocardium even at rest, while
ECG changes appears only during ischemia enhancement
under exercise testing [20]. Actually, in our investigation,
the most effective MCG markers where ones calculated
on JT interval, namely Delta 80, D1 and D2, which char-
acterize abnormal angular displacement of CDV at the
beginning of the “ischemia window” and position chan-
ges of ST-segment, which is in agreement with results of
foreign authors [21].
It’s known that duration of action potential (AP) could
Figure 1. Scattering graph of canonical values for three patient
be increased due to repolarization delay, which became
apparent in prolongation of its 3rd phase. In order to de-
scribe such changes of AP, L. Hondeghem, et al. have
proposed to use “triangulation” expression [22] having in
mind a phenomenon of AP’s form approaching to the
triangle shape. It has been proposed to determine train-
gulation degree as AP time interval duration at 90% and
30% repolarization level. According to the data of nu-
merous researches, triangulation enhancement, indepen-
dently of its mechanism and causes, evidences about
myocardium injury and probability increasing arrhythmia
progress [25-27]. On the ECG, different triangulation
degree appears as T-wave flattening and/or widening. It
could be supposed, that triangulation degree enhance-
ment and Ta-e interval elongation reflect the nature of
same effects. In several papers, C. Antzelevich, et al.
claim that Ta-eis only ECG marker, which could be
used to judge about degree of arrhythmogenic readiness
of myocardium, as a consequence of it’s injury [23, 24].
In this paper, we have used new approach to the estima-
tion of the triangulation repolarization degree (Ta-e dura-
tion) on the base of changes analysis of the global cur-
rent density curve, which for our opinion increases sig-
nificantly accuracy and reproducibility of results. Such
approach to the analysis of transmural electric heteroge-
neity was used by authors for the first time for examina-
tion of patients with ventricular rhythm disturbances
It’s very interesting that Ta-e duration changes analysis
demonstrates that in some cases triangulation degree
could be decreased (duration shortening of Tapex-Tend
interval). For example, as compared to the healthy pa-
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V. Sosnytskyy et al. / World Journal of Cardiovascular Diseases 3 (2013) 380-388
tients, this marker is lower in the Sub-group 2.1 and
Group 3. At the same time, this marker is higher in 2.2A
as compared to 2.2B. It could be supposed, that Tapex-Tend
time interval shortening mechanism is caused by pre-
domination of the functional changes of ions flow den-
sity over the structural changes. Under conditions of
combined, hypoxia occurs molecular oxygen deficiency
in the myocardial tissues, and intensity of oxidation
processes falls behind the glycolysis intensity. Molecular
oxygen, being the final acceptor of protons, is required
for the ATP synthesis. As a result of the entire complex
of metabolic disorders, ATP synthesis is disrupted and
deficiencies of energetic and plastic resources of cells
appear and lead to the myocardium functions disorder.
Na-K-dependent ATP-ase inhibition leads to disorder of
the Na-K pump function, which results in non-homoge-
nous shortening of the third phase of AP, and hence to
increasing of the transmural electric heterogeneity. This
should be resulted in duration changes of the Ta-e interval,
which was shorter in patients with slightly ischemic
myocardium (Sub-group 2.193.0 ± 2.31 vs. 110.3 ±
1.66; p < 0.05), as compared to the volunteers of the
control group. However, presence of the structural
changes and ischemia cause ion mechanisms activation,
promoting prolongation of the repolarization at the cost
of AP 3rd phase (Sub-group 2.2A and Sub-group 2.2B
105.2 ± 4.06 vs. 90 ± 5.05; p < 0.05). This result is very
interesting in the sense of comparison of MCG data of
AMI patients depending upon ischemia symptoms
availability according to the stress-test results with clini-
cal ECG control. Yet at the rest conditions, there was
high changes degree revealed of the 5 MCG markers
under positive stress-test (Sub-group 2.2A as compared
to the Sub-group 2.2B). Thus markers D1 (10.4 ± 1.44 vs.
5.0 ± 0.69; p < 0.05), D2 (12.8 ± 1.55 vs. 5.5 ± 1.06; p <
0.05), D4 (15.9 ± 2.89 vs. 5.9 ± 1.18; p < 0.05), Ta-e
(105.2 ± 4.06 vs. 90.0 ± 5.05; p < 0.05) and Delta RT
(125.8 ± 11.7 vs. 45.4 ± 6.6; p < 0.05) reliably demon-
strate differences between the two sub-groups. Thereby,
this paper offers good challenge towards MCG applica-
tion as additional, safe and cost effective stratification
method of AMI patients for disease course prognosis,
medical treatment differentiation and its effectiveness
control. Employment of the reperfusion and antithrom-
botic therapy results in mosaic pattern of the formed ne-
crotic zone, interleaved with superior myocardium zones
(being at most in ischemic or “stunned” condition). In
such patients, reticular microscopic myocardial fibrosis
is present [14]. And even magnetic-resonance technique
is not able to detect such tiny myocardial injuries in vivo
[15-17]. At the same time, MCG could be sensitive even
to slight changes of repolarization homogeneity, caused
by such fibrosis [18]. We don’t exclude possibility of
new terms appearance for notification of analyzed MCG
markers, because investigated phenomena could have
different content as compared to standard ECG.
The analysis of MCG markers myocardium excitation
abnormalities in myocarditis patients makes it possible to
separate differential features as compared to IHD with
indistinct clinical and ECG-changes. It could be sup-
posed, that the basic reason of the markers variability in
two patient groupsare caused by the differences in
intensity and localization of the hypoxia processes, in-
herent to ischemia and inflammatory process in myocar-
This conclusion is supported by the fact that the values
of MCG markers Delta 80, appeared during the time in-
terval, correspondent to the “ischemia window”, were
different for Sub-group 2.1 and Group 3 (61.6 ± 11.4 vs.
36.8 ± 8.92; p < 0.001). Explanation of increased value
of D2 marker in patients with myocarditis as compared to
the IHD patients (7.9 ± 1.72 vs. 5.5 ± 0.96; p < 0.05)
could be based on our principal conception for MCG
data interpretation [19], which claims that CDV direction
corresponds to the direction of tissues, where the ions
flow was activated. In this case, it could be stated, that
increase in CDV deviation on D2 interval demonstrates
the regional abnormal heterogeneity of the ions flow in
differently directed myocardium layers. It should be
noted reliable increase of the markers SumR/SumT values
(8.6 ± 0.8 vs. 6.4 ± 0.71; p < 0.001) in patients with
myocarditis, which reflect mutual changes between cur-
rent densities at the peaks of R and T waves as dissocia-
tion between transmembrane ion flows during activation
and recovery.
Limitations. There are several limitations in this study.
First, the results must however be viewed with caution as
the groups of patients are rather small and differ in a
number of characteristics. The number of control sub-
jects examined in this study was also relatively small.
Recently, as the primary sources are spread over a larger
region, reconstructed current density distributions may
be used to identify changes in cardiac electric activity
although the non-uniqueness of the inverse problem re-
quires that results must be viewed with caution. Finally,
conformation of the obtained result of discriminative
analysis would be desirable in a larger series.
1) Magnetocardiography using new markers is a new
instrument for differential diagnostics of the myocardium
electrical injuries of ischemic and inflammatory genesis.
The method is able to distinguish between healthy sub-
jects and patients with myocarditis and patients with IHD
without previous MI with high sensitivity and specificity.
2) MCG in patients with acute myocardial infarction
could be useful to detect ischemic myocardium and
Copyright © 2013 SciRes. OPEN ACCESS
V. Sosnytskyy et al. / World Journal of Cardiovascular Diseases 3 (2013) 380-388 387
hence, to determine revasculization feasibility.
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