Magnetocardiography capabilities in myocardium injuries diagnosis

doi:10.4236/wjcd.2013.35059

Paper Menu >>

Journal Menu >>

World Journal of Cardiovascular Diseases, 2013, 3, 380-388 WJCD

http://dx.doi.org/10.4236/wjcd.2013.35059 Published Online August 2013 (http://www.scirp.org/journal/wjcd/)

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: *[email protected]

Received 9 May 2013; revised 28 June 2013; accepted 15 July 2013

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

ABSTRACT

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

1. INTRODUCTION

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

OPEN ACCESS

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

investigation.

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. MATERIALS AND METHODS

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

years.

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

V. Sosnytskyy et al. / World Journal of Cardiovascular Diseases 3 (2013) 380-388

382

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-

raine.

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

markers:

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}—QRS—duration of the QRS complex (ms); {N2}—

Delta 80—maximum 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, D4—maximum current density vector devia-

tion at 4 ST-T sub-intervals (starting at 60 ms from the

J-point)); {N7}—Ta-e—time interval duration from the

peak to the end of Т-wave; {N8}—Delta RT—difference

between direction angles of the maximum current density

vector at R and T peaks; {N9}—SumR/SumТ—ratio 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}

—(QRS—t1)/t1—symmetry 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

step.

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-

V. Sosnytskyy et al. / World Journal of Cardiovascular Diseases 3 (2013) 380-388

383

OPEN ACCESS

Table 1. Values of MCG markers in groups and sub-groups (M ± m).

(a)

MCG-markers

Groups

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

(b)

MCG-markers

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.

(a)

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

(b)

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

384

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 2.2B—only 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-

gram—Table 4.

Resulted discriminant functions have the following

form:

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



 



 

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

F-remove

(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







3. DISCUSSION

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

groups.

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-e—is 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

[28].

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-

V. Sosnytskyy et al. / World Journal of Cardiovascular Diseases 3 (2013) 380-388

386

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 2.1—93.0 ± 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 groups—are caused by the differences in

intensity and localization of the hypoxia processes, in-

herent to ischemia and inflammatory process in myocar-

dium.

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.

4. CONCLUSIONS

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

V. Sosnytskyy et al. / World Journal of Cardiovascular Diseases 3 (2013) 380-388 387

hence, to determine revasculization feasibility.

REFERENCES

[1] Kemp, H.G., Kronmal, R.A., Vietstra, R.E. and Frye, R.L.

(1986) Seven year survival of patients with normal coro-

nary arteriograms: A CASS registry study. Journal of the

American College of Cardiology, 7, 479-483.

doi:10.1016/S0735-1097(86)80456-9

[2] Malmivuo, J. and Plonsey, R. (1995) Bioelectromagnet-

ism: Principles and applications of bioelectric and bio-

magnetic fields. New York: Oxford University Press.

doi:10.1093/acprof:oso/9780195058239.001.0001

[3] Stroink, G., Moshage, W. and Achenbach, S. (1998) Car-

diomagnetism. In: Andr. W. and Nowak, H., Eds., Mag-

netism in Medicine, Wiley-VCH, Berlin, 136-189.

[4] Tavarozzi, I., Comani, S., Del Gratta, C., Di Luzio, S.,

Romani, G.L., Gallina, S., et al. (2002) Magneto-cardio-

graphy: Current status and perspectives. Part II: Clinical

applications. Italian Heart Journal, 3, 151-165.

[5] Fenici, R., Brisinda, D. and Meloni, A.M. (2005) Clinical

application of magnetocardiography. Expert Review of

Molecular Diagnostics, 5, 291-313.

doi:10.1586/14737159.5.3.291

[6] Van Leeuwen, P., Hailer, B., Lange, S. and Grцnemeyer,

D. (2003) Spatial distribution of repolarization times in

patients with coronary artery disease. Pacing and Clinical

Electrophysiology, 26, 1706-1714.

doi:10.1046/j.1460-9592.2003.t01-1-00256.x

[7] Hailer, B., Chaikovsky, I., Auth-Eisernitz, S., Schafer, H.

and Van Leeuwen, P. (2005) The value of magnetocar-

diography in patients with and without relevant stenoses

of the coronary arteries using an unshielded system. Pac-

ing and Clinical Electrophysiology, 28, 8-11.

d oi:10.1111/j.15 40-8159.2005.09318.x

[8] Park, J.W., Hill, P.M., Chung, N., Hugenholtz, P.G. and

Jung, F. (2005) Magnetocardiography predicts coronary

artery disease in patients with acute chest pain. Annals of

Noninvasive Electrocardiology, 10, 312-323.

d oi:10.1111/j.15 42-474X.2005.00634.x

[9] Tolstrup, K., Madsen, B.E., Ruiz, J.A., Greenwood, S.D,

Camacho, J., Siegel, R.J., et al. (2006) Non-invasive rest-

ing magnetocardiographic imaging for the rapid detection

of ischemia in subjects presenting with chest pain. Cardi-

ology, 106, 270-276. doi:10.1159/000093490

[10] Chen, Y. (2005) Resting magnetocardiographic imaging

can accurately detect obstructive coronary artery disease

in patient with chronic ischaemia. Journal of the Ameri-

can College of Cardiology, 45, 27-69.

[11] Park, J.W. et al. (2005) Magnetocardiography predicts

coronary artery disease in bundle brunch block patients

with acute chest pain. Journal of Electrocardiology, 40,

S53.

[12] Van de Werf, F., Ardissino, D., Betriu, A. et al. (2003)

Management of acute myocardial infarction in patients

presenting with ST-segment elevation: The task force on

the management of acute myocardial infarction of the

european society of cardiology. European Heart Jour-

nal, 24, 28-66. doi:10.1016/S0195-668X(02)00618-8

[13] Sosnytskyy, V.M., Vojtovich, I.D., Bojchak, M.P., My-

asnikov, G.V., Chaikovsky, I.A. and Sosnitskaya, T.V.

(2011) Magnetic mapping of the heart-new information

technology of noninvasive electrophysiology. Reports of

the National Academy of Sciences of Ukraine, 1, 166-171.

[14] Ertl, G. and Frantz, S. (2005) Healing after myocardial

infarction. Cardiovascular Research, 66, 22-32,

doi:10.1016/j.cardiores.2005.01.011

[15] Casolo G., Minneci S., Manta R., et al. (2006) Identifica-

tion of the ischemic etiology of heart failure by cardio-

vascular magnetic resonance imaging: Diagnostic accu-

racy of late gadolinium enhancement. American Heart

Journal, 151, 101-108. doi:10.1016/j.ahj.2005.03.068

[16] Ibrahim, T., Bulow, H.P., Hackl, T., et al. (2006) Diag-

nostic value of contrast-enhanced magnetic resonance

imaging and single-photon emission computed tomo-

gramphy for detection of myocardial necrosis early after

acute myocardial infarction. Journal of the American

College of Cardiology, 49, 208-216.

[17] Kaandorp, T.A., Lamb, H.J., Viergever, E.P., et al. (2007)

Scar tissue on contrast-enhanced MRI predicts left ven-

tricular remodelling after acute infarction. Heart, 93, 375-

376. doi:10.1136/hrt.2006.097675

[18] Goerning, M., Liehr, M., Tute, C., Schlosser, M.,

Haueisen, J., Figulla, H. and Leder, U. (2009) Magneto-

cardiography based spatiotemporal correlation analysis is

superior to conventional ECG analysis for identifying

myocardial injury. Annals of Biomedical Engineering, 37,

107-111. doi:10.1007/s10439-008-9598-5

[19] Sosnitskiy, V.N., Stadnyuk, L.A. and Sosnitskaya, T.V.

(2004) Magnetocardiography: New insights onto old

ideas. Heart and Vessels, 4, 73-78.

[20] Ikefuji, H., Nomura, M., Nakaya, Y. et al. (2007) Visu-

alization of cardiac dipole using a current density map:

Detection of cardiac current undetectable by electrocar-

diography using magnetocardiography. Journal of Inves-

tigative Medicine, 54, 116-123. doi:10.2152/jmi.54.116

[21] Jarusevicius, G., Navickas, R., Vainoras, A. et al.( 2004)

JT interval changes in acute myocardial infarction fol-

lowing coronary angioplasty, Medicina (Kaunas), 40, 90-

93.

[22] Hondeghem, L.M., Carlsson, L., Duker, G. (2001) Insta-

bility and triangulation of the action potential predict se-

rious proarrhythmia, but action potential duration pro-

longation is antiarrhythmic. Circulation, 103, 2004-2013.

doi:10.1161/01.CIR.103.15.2004

[23] Antzelevitch, С. (2005) Modulation of transmural repo-

larization. Annals of the New York Academy of Sciences,

1047, 314-323

[24] Emori, T. and Antzelevitch, C. (2001) Cellular basis for

complex T wave and arrhythmic activity following com-

bined I (kr) and I (ks) block. Journal of Cardiovascular

Electrophysiology, 12, 1369-1378.

doi:10.1046/j.1540-8167.2001.01369.x

[25] Lu, H.R., Vlaminckx, E., Van Ammel, K., De Clerck, F.

(2002) Drug—induced long QT in isolated rabbit Pur-

kinje fibers: Importance of action potential duration, tri-

V. Sosnytskyy et al. / World Journal of Cardiovascular Diseases 3 (2013) 380-388

388

OPEN ACCESS

angulation and early after depolarization. European Jour-

nal of Pharmacology, 452, 183-152.

doi:10.1016/S0014-2999(02)02246-X

[26] Milberg, P., Hilker, E., Ramtin, S., et al. (2007) Proar-

rhythmia as a class effect of quinolones: Increased dis-

persion of repolarization and triangulation of action po-

tential predict torsades de points. Journal of Cardiovas-

cular Electrophysiology, 18, 647-654.

d oi:10.1111/j.15 40-8167.2007.00793.x

[27] Kuzmin, V.S. and Rozenshtraukh, L.V. (2010) Ionic me-

chanisms as action of the III class antiarrhythmic drugs.

Cardiology, 7, 49-61.

[28] Sosnytskyy, V.M., Stadnyuk, L.A. and Sosnytska, T.V.

(2010) Detection of the Ca2+ overload in patients pre-

senting with delayed aftedepolarization using cardiac

magnetic field mapping at rest. European Heart Journal,

31(Abstract Supplement), 264.