e61Abstracts / Journal of Electrocardiology 44 (2011) e1–e64

ED parameters can be successfully determined. Specifically, PC signalsexhibited one significant minimum of the cost function in the searchedvolume of the thorax in nearly two thirds of cases, and in the rest, it wasmore than one minimum. The RNMS error was the smallest when thesignal amplitude was high and was around 5% for the first PC of theQRS complex and the T wave and 10% for the second PC of both QRSand T waves, whereas it was much greater for the P wave. The error wasindependent of the subject subgroup.Conclusion: Though resembling the classic ECG vector analysis, the newmethod offers additional information: it provides separate EDs for differentPC signals and a 3-dimensional location of EDs in the thorax, which mayfurther help to interpret the conventional ECG.

doi:10.1016/j.jelectrocard.2010.12.148

P69The relationship between ST-dynamics during reperfusion and theinfarct size in experimental myocardial infarctionMarina Demidovaa, Jesper van der Palsb, David Erlingeb,Victor Tichonenkoc, Pyotr PlatonovdaFederal Center of Heart, Blood and Endocrinology, St. Petersburg, RussiabLund University and Lund University Hospital, Lund, SwedencMechnikov Medical Academy, St. Petersburg, RussiadSkåne University Hospital and Center for Integrative Electrocardiology atLund University (CIEL), Lund, Sweden

Background: Exacerbation of ST-elevation associated with reperfusionhas been reported in patients with myocardial infarction. However, thecause of the “reperfusion peak” and its relation to the size of myocardialdamage have not been explored. The aim of our study was to assess thecorrelation between the ST behavior during reperfusion, the area atrisk (AAR), and infarct size (IS) during experimental myocardialinfarction (MI)Methods: In 15 anesthetized pigs (40-50 kg), ischemia was induced by 40-minute-long inflation of a PCI balloon placed in left anterior descendingartery immediately distal to the first diagonal branch. Left anteriordescending artery occlusion and restoration of blood flow were verifiedby coronary angiography. ST-segment elevation dynamics analysis wasbased on continuous 12-lead electrocardiogram (ECG) initiated before theocclusion and ended 4 hours following reperfusion. Both AAR and IS wereevaluated by ex vivo single-photon emission computed tomography andmagnetic resonance imaging, respectively.Results: The occlusion caused anteroseptal MI. The AAR was 42% ±9%, and IS was 26% ± 7% of left ventricular mass. Reperfusion wasalways accompanied by transitory exacerbation of ST elevation thatreached 1299 ± 503 μV vs 570 ± 220 μV at the end of occlusion, P b,001, exceeded the maximal ST elevation during occlusion (918 ± 417μV, P b ,05), and resolved by the end of reperfusion period (90 ± 30μV, P b ,001). Exacerbation of ST elevation during reperfusion stronglycorrelated with the final infarct size (r = 0,64, P = ,025) but not withAAR (r = 0,43, P = 0,17).Conclusion: Restoration of blood flow in the infarct-related artery isaccompanied by transitory exacerbation of the ST-segment elevation thatexceeds the level reached during occlusion. Marked correlations between STelevation exacerbation and the final infarct size were found.

doi:10.1016/j.jelectrocard.2010.12.149

P70A computationally efficient patient-specific simulation model for theinvestigation of arrhythmia mechanismsAlessandro Cristoforetti, Michela Masè, Flavia RavelliDepartment of Physics, University of Trento, Povo - Trento, Italy

Background: Computer simulation has become a valuable tool for the studyand comprehension of arrhythmia mechanisms and the prediction of

treatment outcome. The development of models with detailed patient-specific anatomy and electrophysiology is essential to improve predictiveaccuracy; nevertheless, the high computational load of realistic modelshinders their clinical application. In this work, we introduce a patient-specific computational model combined with a novel fast-solving algorithmbased on a multiresolution approach, to perform computationally efficientrealistic simulations. Representative simulations are shown in a case study ofa patient developing postoperative left atrial flutter.

Methods: The personalization of the model was achieved by fusion of highquality 3D-CT cardiac imaging and electroanatomical mapping data.Specifically, a detailed reconstruction of the left atrial surface wassemiautomatically obtained from CT data by a marker-controlled watershedsegmentation. The electrophysiological information and ablation points werecorrectly positioned on the atrial geometry by an automatic registration basedon a best-matching stochastic approach. Single-cell electrophysiology wasmodeled by the Courtemanche human atrial ionicmodel and integrated on theatrial mesh using a finite volume numerical scheme. A novel adaptive meshrefinement algorithm (AMRA) for unstructured triangular grids wasimplemented to increase computational efficiency. Adaptive mesh refine-ment algorithm adapted the local resolution of the mesh to the local trend ofthe state variables by means of a nested triangle subdivision.

Results: Although performed on a detailed left atrial mesh of 350K nodes,10 seconds of left atrial flutter simulation (time step 0.05 milliseconds)required 9 hours of calculation using Matlab programming platform on a2 × 2660-MHz processor. This was accomplished by AMRA implemen-tation, which, keeping 15% of the nodes computationally active, reducedthe overall calculation time under 20% of the full-resolution integrationtime, without affecting significantly the propagation accuracy. Similarly topatient data, the simulation model accurately reproduced a clockwisereentrant circuit rotating around the common trunk of the left pulmonaryveins and involving the ridge between the veins and left atrial appendage.Simulations evidenced the role of ablation lines as critical pathways of thereentry, suggesting their involvement in the creation of a substrate inpostablative arrhythmias.

Conclusion: These results demonstrate the feasibility of fast patient-specificarrhythmia simulations by combining an anatomically and electrophysio-logically personalized computer model with an innovative computationallyefficient solving algorithm. Efficient realistic models may improve theunderstanding of specific arrhythmia mechanisms in the single patient, thusoptimizing therapy planning and guidance.

doi:10.1016/j.jelectrocard.2010.12.150

P71Time-frequency analysis of venous stenosis: a comparative studyPablo Vasqueza,b, Marco Munguiaa,b, Elisabeth Mattssonc,Bengt Manderssona

aElectrical and Information Technology Department, Lund University,SwedenbNational University of Engineering, Managua, NicaraguacDepartment of Nephrology, SUS Skåne University Hospital, Sweden

A common complication in hemodialysis patients is that of thrombosis.Very often, the reason of thrombosis is stenosis. Stenosis is an abnormalnarrowing of a bodily canal, which can be caused by calcification orwhen the vessel's wall is exposed to abnormal physical stress liketurbulence or high blood pressure. Previous research results have shownthat stenosis has 2 basic acoustical effects: a general increase in thesound level and an introduction of new high-frequency components inthe power spectra.Phonoangiography, the quantitative analysis of sound produced by bloodflow, is an inexpensive and noninvasive tool that can be used formonitoring the vessels functioning. Time-frequency analysis tools havebeen found to be helpful in characterizing the murmurs produced byoccluded veins and arteries, for example, in the diagnosis of coronary andcarotid arteries diseases. In the present work, we apply 3 different time-frequency techniques to exploit the spectral content of the murmurs:empirical mode decomposition, wavelet packets, and principal component

e62 Abstracts / Journal of Electrocardiology 44 (2011) e1–e64

analysis (PCA). A database of recordings consisting of a group of patientscurrently undergoing hemodialysis treatment 3 times a week at theDepartment of Clinical Physiology, Lund University Hospital, is used inthis study for testing the different algorithms. A set of features taken fromthe coefficients obtained from the 3 methods is selected; in the second step,2 pattern recognition schemes with supervised learning are used to classifythe selected features and label the recording as coming from a stenotic ornonstenotic segment, in an automatic way. As a summary, a comparison ofthe results is presented.

doi:10.1016/j.jelectrocard.2010.12.151

P72Improved detection of ischemic heart disease by combininghigh-frequency electrocardiogram analysis withstress echocardiographyJin-Oh Choia, Guy Amitb, Linda R. Davrathb, Ga Yeon Leea,Eunkyung Kima, Sung-A Changa, Sung-Ji Parka, Sang-Chol Leea,Seung Woo Parka, Jae K. Oha

aSunkyunkwan University School of Medicine, Samsung Medical Center,Seoul, South KoreabBiological Signal Processing Ltd, Tel Aviv, Israel

Background: Analysis of high-frequency QRS components (HFQRS) wererecently reported to improve the diagnostic accuracy of electrocardiogram(ECG) treadmill test (ETT). We sought to evaluate the clinical usefulness ofHFQRS analysis during exercise echocardiography (echoCG) in detectingischemic heart disease (IHD).Methods: We evaluated 156 patients (age 58 ± 10 years, 103 men) whoperformed stress echoCG and either invasive angiography (n = 57) orcomputed tomography angiography (CTA; n = 99), which were used as thecriterion standard for comparison. Exclusion criteria included indetermi-nate CTA, QRS greater than 120 milliseconds, significant valve disease,resting wall motion abnormalities, previous cardiac surgery, andinsufficient maximal HR. Electrocardiogram treadmill test was performedusing the HyperQ System (BSP Ltd, Tel Aviv, Israel) that enablesautomatic ST-segment analysis and measures changes in HFQRS intensity

Table 1Diagnostic performance of HFQRS, ETT and stress echocardiography

Sensitivity (%) Specificity (%)

HFQRS analysis 64 78Computerized ST analysis 38⁎ 80Stress echoCG + HFQRS 79 75Stress echoCG + ETT 58⁎⁎ 82

⁎ Statistically significant differences (P b .05) vs HFQRS.⁎⁎ Statistically significant differences (P b .05) vs Echo + HFQRS.

Fig. 1. The area under receiver-operating characteristics curve for variousischemia detection schemes, indicating the accuracy of detection.

during exercise. Patients with HFQRS intensity reduction of 50% or morein at least 3 leads were considered ischemic.Results: Significant IHD was found in 48 patients (31%). High-frequencyQRS components was significantly more sensitive than ST-segmentanalysis, with similar specificity (Table 1). Stress echoCG combined withHFQRS was more sensitive than the conventional combination with ETT.High-frequency QRS components provided an incremental diagnostic value(P b .001) over pretest, ETT, and echoCG parameters (Fig. 1). Usingoptimized cutoff points, the combined model achieved sensitivity andspecificity of 86% and 80%, respectively.Conclusion: High-frequency QRS components analysis during stressechoCG is feasible and may provide additional information for the detectionof significant IHD.

doi:10.1016/j.jelectrocard.2010.12.152

P73Influence of individual torso geometry on inverse solution to 2 dipolesJana Svehlikovaa, Jana Macugovaa, Marie Turzovaa, Milan Tyslera,Michal Kaniab, Roman ManiewskibaInstitute of Measurement Science SAS, Bratislava, SlovakiabInstitute of Biocybernetics and Biomedical Engineering PAS, Warsaw,Poland

Background: Recently, body surface potentials measured on patients withcoronary artery disease were used for testing the method for identification oflocal ischemic lesions by an inverse solution with 2 dipoles. A standard torsomodel with main inhomogeneities and 154 predefined positions of dipoleswas used. The 15 different realistic individual models of torso were used toevaluate their influence on the result of the inverse identification.Methods: Difference QRST integral maps (DIMs) computed for 8 malepatients by subtracting the integral map at rest from the map during exerciseat load of 75W were considered as the representation of possible localrepolarization changes induced by stress. For each patient, inverse solutionswith 2 dipoles were computed from 64 measured leads using 15 realisticallyshaped torso models. The individual models were created from magneticresonance images of real male subjects and include the heart and main torsoinhomogeneities such as lungs and ventricular cavities. The position of leadV2 was assigned with respect to the fourth intercostal level. The referencepoint (RP) at the base of the left ventricular septum was defined on eachheart model, and the difference of the z coordinate of the RP and V2 positionwas evaluated. The predefined positions of dipoles were established in eachmodel of ventricles. The results of inverse solutions obtained using theserealistic models and the standard torso model were compared.Results: The mean vertical difference between positions of RP and V2computed as zV2-zRP was 2.45 cm (from −1.81 to 4.53). For the standardtorso model, this value was −1.25 cm, so for most of the observed models,the position of heart in relation to lead V2 was considerably lower than inrecently used standard model. Therefore, we compared the inverse resultsobtained with previous standard model and at least 3 most similar individualmodels with vertical differences of −1.81, −1.23, and −0.18 cm. Despitethat, we got the same locations only for 4 of the 8 tested cases/patients.Conclusion: The proposed inverse solution is very sensitive to the verticalposition of the heart in the torso model. The fourth intercostal level generallyused for positioning of leads V1 and V2 on the torso was apparently not inconstant relationship with internal position of the heart. For inverse solution,this relationship should be necessarily known for each particular patient.

doi:10.1016/j.jelectrocard.2010.12.153

P74

Utility of heart simplicity inspection with pocket size eventelectrocardiogram in the citizens marathon rallyYukio Ozawaa, Kouji Matsubarab, Yuji Kasamakic, Masakatsu Otac

aMJG Cardiovascular Institute, Saitama City, JapanbCard Guard JapancNihon University School of Medicine, Japan