- Email: [email protected]
Clinical ECG mapping and imaging of cardiac electrical excitation
Journal of Electrocardiology Vol. 35 Supplement 2002
Clinical ECG Mapping and Imaging of Cardiac Electrical Excitation
Bernhard Tilg, PhD,* Friedrich Hanser, PhD,* Robert Modre-Osprian, PhD,* Gerald Fischer, PhD,* Bernd Messnarz, MSc,* Thomas Berger, MD,† Florian Hintringer, MD,† Otmar Pachinger, MD,† and Franz Xaver Roithinger, MD†
Abstract: Combining electrocardiographic mapping and 3D⫹time anatomical data enables noninvasively the imaging of the electrical excitation sequence in the human heart. A bidomain-theory based surface heart model activation time imaging approach was employed to image single beat data of atrial and ventricular depolarisation. Activation time maps were reconstructed for three patients who underwent an electrophysiologic study. The sinus rhythm and a rhythm according to a pacing protocol were reconstructed for two patients. For the third patient the accessory pathway of the WPW syndrome was localized. For focal arrhythmias, this model-based imaging approach might allow the guidance and evaluation of antiarrhythmic interventions, for instance, in case of catheter ablation or drug therapy. Key words: Activation time imaging, clinical validation, electrocardiographic inverse problem, body surface ECG mapping.
Atrial and ventricular arrhythmias and their therapeutic treatment play a significant role in clinical electrocardiology (1). Within the last several years, new methodology has been established for the clinical assessment of atrial and ventricular activation. In addition to standard techniques, sophisticated invasive technology, such as electroanatomical mapping or noncontact mapping, has been
included into clinical electrophysiogical (EP) procedures (2,3). Noninvasive inverse electrocardiography may further enhance the spectrum, especially for targeting focal arrhythmias and patient selection. Recently, a method for catheter-based electroanatomical mapping has been introduced that combines electrophysiological information, such as the sequence of cardiac activation, with a 3D image of the cardiac chamber (2). The timing of unipolar and bipolar signals, which are related to a reference signal, enables the recording and display of activation times on a 3D map in relation to the position of the catheter in the heart. The advantage of the CARTO (Biosense Webster Inc, Johnson & Johnson Company) system in clinical electrophysiology is the ability to reposition the ablation catheter to any spot of the target chamber without relying on fluoroscopy. This technique, however, shows significant limitations when it comes to acquiring
From the *University for *Health Informatics and Technology Tyrol; and the †Department of Cardiology, University Hospital Innsbruck, Innsbruck, Austria. This study was supported by the Austrian Federal Ministry for Education, Science and Culture and by the Austrian Science Fund, grant START Y144. Reprint requests: Bernhard Tilg, PhD, Professor, Institute for Medical Signal Processing and Imaging, University for Health Informatics and Technology Tyrol, Innrain 98, 6020 Innsbruck, Austria; e-mail: [email protected]. Copyright 2002, Elsevier Science (USA). All rights reserved. 0022-0736/02/350S-0012$35.00/0 doi:10.1054/jelc.2002.37159
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82 Journal of Electrocardiology Vol. 35 Supplement 2002 single beat activation maps. In addition, the invasive procedures can not be used for screening patients in order to decide the optimal individual therapeutic procedure (eg, drug, ablative, or hybrid therapy). Noninvasive imaging approaches overcome these limitations and provide in a noninvasive way information about electrical excitation. From a clinical point of view, this might have several benefits. For a clinical validation of inverse electrocardiography, however, electroanatomical CARTO maps may serve as the golden standard. Combining magnetic resonance imaging (MRI) of the torso anatomy with body surface ECG mapping enables noninvasive imaging of the primary electrical sources in the human heart (4 –13). The primary source in the cardiac muscle is the spatio-temporal transmembrane potential distribution (TPD) (14,15). In the inverse problem parameters describing features of TPD or the epicardial potential are estimated (4,5,9,11,12). The epicardial potential and the potential on all other conductivity interfaces are related to TPD by an integral equation. The most established inverse formulations are the imaging of the AT map on the entire surface of the heart and the imaging of the epicardial potential pattern. In the surface heart AT imaging approach the underlying source model is based on an isotropic bidomain formulation with TPD as the primary source term. In applying a proper inverse algorithm, this approach enables single beat reconstruction of single focal, multiple focal and more distributed activation patterns. Additionally, it can distinguish between areas with early and late activation. The surface heart AT imaging approach is currently under clinical evaluation and ongoing technical development. Potential clinical applications are noninvasive imaging of atrial and ventricular ectopic beats and pre-excited activation. So far, clinical validation of inverse electrocardiography has not been accomplished. First results are available for the torso tank model (11,12). Only a few promising results are reported in humans (10,13,16). Clinical validation is of utmost importance in order to show the applicability and the stability of the electrocardiographic inverse approach under clinical conditions. Theoretical studies employing a computer or a phantom model can only investigate the theoretical limitations of the inverse modeling approach. For clinical validation, the reference method (“the golden standard”) should provide, in principle, the same information as calculated in the inverse modeling approach. In the surface heart AT imaging method in which the AT map is determined on the endo- and epicardium of the ventricle or atrium, the catheter mapping techniques can be
applied for validation. Preferably, an ECG-gated geometry description of the target chamber and the AT map should be available invasively. Such an AT map is, in general, derived from the potential map. For stable cardiac rhythms this information can be gained, eg, by the CARTO system (2). CARTO enables the coupling to the MRI reference frame with regard to the external marker positions and anatomical markers, which is important for a quantitative validation approach. In this study we investigated the applicability of the surface heart AT imaging method in three patients. The ECG-gated geometrical models obtained from MRI and the reconstructed AT maps were compared with the electroanatomical CARTO maps. In case of WPW syndrome, the invasive localization of the accessory pathway was qualitatively compared with the findings from the invasive catheter procedure. The presented AT imaging method permits the reconstruction of single focal, multiple focal, and more distributed activation patterns. Potentially promising clinical applications are the noninvasive imaging of atrial and ventricular ectopic beats as well as pre-excited activation.
Materials and Methods Study Protocol Three male patients, 65Y (A), 24Y (B), and 21Y (C) with structurally normal hearts underwent EP studies. Informed consent was obtained from all patients before any diagnostic and therapeutic procedure. The study was approved by the local ethics committee. Patient B and C suffered from a WolffParkinson-White (WPW) syndrome while Patient A suffered from an atrial flutter. Before treatment in the catheter laboratory individual anatomical data were obtained from MRI using a Magnetom Vision Plus™ 1.5T scanner. Atrial and ventricular geometries were recorded in CINE-mode during breathhold (expiration, short axis scans, 4 and 6mm spacing). The lungs and the torso shape were recorded in T1-FLASH-mode during flat breath-hold (expiration, axial scans, 10mm spacing). Twelve markers (vitamin E capsules, 7 anatomical landmarks on the anterior and lateral chest wall, 5 electrode positions on the patient’s back) were used to couple all geometrical data to the MRI frame. From these data sets boundary element volume conductor models were constructed (8,14,16,17). A volume conductor model was constructed from the patient’s individual MRI data set. The conduc-
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Fig. 1. (A) Four axial MRI scans from patient A from an anterior left lateral view. Large spheres indicate the 7 reference marker positions. Small pheres indicate the anterior electrode positions. (B) BEM volume conductor model for patient A from an anterior left lateral view. Small and large spheres indicate the electrode positions and the WCT, respectively. The atrial and ventricular model were constructed for the end-diastolic phase.
tivity interfaces of the chest, the lungs, the blood mass, and the surface of the ventricle or the atrium were taken into account. These interfaces are extracted from the axial (chest, lungs) and from the CINE short-axis (blood mass, ventricle, atrium) MRI scans. A commercial software package was used for contour detection and segmentation (Amira, TGS Template Graphics Software, Inc.; Merignac Cedex, France). This software package provides tools for interactively segmenting 3D imaging data. After segmentation and initial triangulation of each individual surface, a mesh optimisation was performed based on a 3D Delaunay algorithm. The shape and the distribution of the triangles play an important role, especially for BEM calculations, in order to achieve good numerical performance in the forward and inverse problem. The BEM volume conductor model for patient A is depicted in Fig. 1 (right panel) from an anterior left lateral view. The 3 electrodes on the right arm, left arm, and on the left leg, defined the reference terminal. They are indicated by large spheres. The entire model comprised of 6794 triangles. The ventricular and atrial surface consisted of 1462 and 1600 triangles, and of 731 and 790 nodal points, respectively. The ventricular and atrial model were constructed from CINE short-axis scans at 0 and 600 ms trigger delay after the R-peak. For patient B and C, again, an individual volume conductor model was constructed. The entire mesh consisted of similar numbers of triangles. For all patients the following conductivities were assumed for the different thorax compartments: chest (0.20 SM⫺1), lungs (0.08 SM⫺1), blood mass (0.60 SM⫺1), intracellular effective conductivity (0.10 SM⫺1). The patients were moved to the catheter laboratory and ECG mapping data were recorded during and after the EP study. Electrocardiographic map-
ping data were collected in 62-channels by the Mark-8 system (Biosemi, V. O. F., Amsterdam, The Netherlands). A Wilson Central Terminal (WCT) defined the reference potential (17). The sampling rate was 2048Hz. Signals were bandpass filtered with a lower and upper edge frequency of 0.3Hz and 400Hz, respectively. The AC-resolution of the system is 500nV/bit (16 bit per channel). Radiotransparent carbon electrodes were used in order to allow simultaneous X-ray examination. The positions of 52 electrodes on the anterior and lateral chest wall were digitized by the FASTRAK system (Polhemus, Inc., Colchester, Vermont). Additionally, the positions of the 7 anterior and lateral landmarks were digitized in order to allow coordinate transformation to the MRI frame. The locations of the 5 posterior electrodes were identical with the position of the 5 posterior MRI markers. Figure 1 (left panel) shows four axial MRI scans in the MRI frame with the 7 reference positions and anterior electrode positions. The ECG raw data were pre-processed by baseline correction, but no additional filtering was applied. The transfer matrix was calculated applying the boundary element method with linear triangular elements. The AT map was estimated from single beat ECG mapping data by decomposing the nonlinear inverse problem into a sequence of linear problem formulations. At each step of iteration the regularization parameter was determined with the L-curve method. More detailed information on this inverse approach can be found elsewhere (8,9). Geometrical Modeling of the Human Atrium Because of the complex anatomy of the human atrium there are several aspects in the evaluation of
84 Journal of Electrocardiology Vol. 35 Supplement 2002
Fig. 2. Ventricular sinus rhythm AT map from an anterior-posterior view for patient A. (A) The anterior epicardium. The posterior epicardium is not visible. (B) The endocardium of RV and LV.
a “good” surface model (16,18,19). First, specific care has to be taken on the MRI protocol in obtaining scans with a high gray-value contrast. The models were obtained from short-axis scans with 4-mm slice thickness in a CINE-mode during breath-hold. The atrial epicardium was modeled assuming a uniform wall thickness of 4 mm for the LA and RA free wall. Specific attention has to be paid to the identification of the pulmonary veins, the VCS and VCI as well as to the TA and MA. The modeling of these structures is important for this kind of inverse formulation. Because of the sophisticated curvature and of the individual endo- and epicardial boundary element surfaces the proper meshing is of utmost importance in order to obtain a high-quality transfer matrix relating the transmembrane potential on this source-containing surface to the ECG mapping data.
into a sequence of linear problem formulations. These linear ill-posed problems were solved employing special spatio-temporal regularization (2nd order Tikhonov regularization) in combination with a characteristic template function of TPD). An initial guess was calculated by the so-called critical point theorem. At each step of iteration the regularization parameter was determined with the Lcurve method. More detailed information on this inverse approach can be found elsewhere (8,9). The following abbreviations are used throughout the paper: Mitral and tricuspid annulus (MA, TA), right and left atrial appendage (RAA, LAA), right upper and right lower pulmonary vein (RUPV, RLPV), left upper and left lower pulmonary vein (LUPV, LLPV), vena cava superior and vena cava inferior (VCS, VCI), coronary sinus (CS), ostium (O).
Inverse Procedure
Results The ECG raw data were pre-processed by baseline correction, but no additional filtering was applied. In our bidomain theory based surface heart model formulation the primary electrical sources in the cardiac muscle is the transmembrane potential distribution (TPD). Applying bioelectromagnetic field theory, the potential on the chest surface is related to TPD by a Fredholm integral equation of second kind. Thus, a compact operator maps TPD onto the ECG mapping data. Consequently, the determination of AT from ECG mapping data constitutes a nonlinear inverse ill-posed problem. The nonlinear relationship between TPD and AT makes the problem nonlinear. The inverse procedure is inherently unstable unless physiologically meaningful and valid constraints can be imposed. The transfer matrix was calculated applying the boundary element method with linear triangular elements. The AT map was estimated from single beat ECG mapping data by decomposing the nonlinear inverse problem
The AT maps were reconstructed from single beat ECG mapping data. The isochrones in Fig. 2, 3 are shown in steps of 5 ms. The isochrones in Fig. 4 are shown in steps of 10 ms. The reconstructed sinus rhythm AT map on RV and LV for patient A is shown in Fig. 2. The right panel does not depict the anterior epicardium. Early endocardial activation in RV occurred at 18ms. A second endocardial breakthrough at 35 ms is on the endocardial left lateral free wall of LV. As can be seen in Fig. 2, the first epicardial breakthrough is on the anterior epicardium of RV at 29 ms. The interval of the entire ventricular depolarization was determined to be 88 ms. The left and right heart base are activated electrically at 80 ms and 88 ms, respectively. These findings are in good qualitative agreement with the sinus rhythm pattern from the isolated Langendorff-perfused human heart. For the imaging of the electrical excitation in RA and LA, sinus and paced
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Fig. 3. AT map of a CS-O pacing protocol for patient A on the endocardium of RA and LA from a (A) posterior-anterior and (B) caudal oblique view.
rhythm data were available for patient A. Pacing was performed at the CS-O, at the catheter electrode position no. 7-8. This electrode position anatomically corresponded to the posterior septal area, in between RA and LA. Figure 3 (left panel) depicts the estimated AT map on the endocardium of RA and LA for CS-O pacing from a posterior-anterior view. Earliest activation was determined at the posterior-septal site of LA at 2ms. The LLPV and RLPV area are activated at 60ms. The anteriorseptal area of LA is depolarized at 90ms. Earliest activation of RA occurs at 13ms, i.e., 9ms after the first breakthrough in LA. In RA, the excitation wave spreads continuously towards RAA and SVC. The SVC area is activated at 70ms. The right panel in Fig. 3 depicts the same AT map from a caudal oblique view. For CS-O pacing, a CARTO map for RA was available. This electroanatomical catheter map was coupled to the 3D ⫹ time anatomical model of RA, using the 7 external reference marker positions. After acquiring the catheter map, these
Fig. 4. (A) Epicardial and (B) endocardial WPW-sinus rhythm AT map for patient B. The accessory pathway was localized at the left posterior site of the ventricle.
reference points were digitized in the CARTO device coordinate system. This information was then used to transform the catheter map to the MRI frame. The first endocardial breakthroughs determined in the eletroanatomical catheter map and in the reconstructed AT map of RA were compared in order to obtain a quantitative localization criterion. The mean geometrical error between the modeled RA and the points of the catheter map was determined to be 6.4 mm. The localization error of the first endocardial breakthrough was 6 mm. The global AT pattern was in good qualitatively agreement with the electroanatomical map. Patient B suffered from a WPW syndrome. Surface ECG data suggested the accessory pathway of the WPW to be somewhere in the left posterior or left anterior region of the ventricle. Figure 4 depicts the reconstructed WPW-sinus rhythm AT map in ms from a posterior view. As can be clearly seen in Figure 4 the accessory pathway was at the posterior region of the left ventricle. Successful radio-frequency
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Discussion
Fig. 5. Movie frames for the RV pacing propagation pattern for patient C from an anterior-posterior view. The numbers indicate the times during ventricular depolarization. Epicardium is depicted in a transparent style.
catheter ablation was performed at this site. A comparison between reconstructed and invasive data (radio frequency ablation sites) could be done only qualitatively. From the results we concluded a localization accuracy smaller than 15 mm. The right panel of Figure 4 depicts the AT map only on the endocardium of RV and LV. The epicardium is indicated in a transparent style. Patient C also suffered from a WPW syndrome. For this patient a RV pacing protocol was performed. The stimulation catheter was positioned at the right lateral wall of RV. Pacing was done during the ventricular enddiastolic phase. Figure 5 depicts the reconstructed spread of excitation on the endocardium of RV and LV at different times (30, 40, 50, 60, 70, 80, 90, 100, 110 ms) from an anterior-posterior view. The epicardium again is depicted in a transparent style. Movie frames beginning at the left upper panel are shown at 9 subsequent times. Black indicates electrically activated myocardium. White indicates the resting phase. Again, the localization accuracy could be verified only qualitatively. As can be seen in Figure 5, the first endocardial breakthrough was reconstructed at 28 ms on the right wall of RV. The first endocardial breakthrough on LV occurred at 48 ms, suggesting electrical conduction from RV to LV also through the Purkinje fibre network. The interval of the entire ventricular depolarization was 116 ms.
We presented a method for the imaging of the AT map on the surface of the atrium and ventricle from ECG mapping data. The individual thorax models of the patients were constructed from 3D⫹time MRI data. ECG and MRI data were coupled in time and space. Results were presented for sinus and paced rhythms. The bidomain theory based surface heart model AT imaging approach constitutes an excellent basis for the electrocardiographic inverse problem formulation. As long as we are dealing with cardiac excitation it not only allows to image the isochrones on the endocardium and epicardium, it also enables the incorporation of a mathematical and physically based model for the relationship between the AT map and the surface ECG mapping data. One of the advantages of the presented AT imaging approach is its non-sensitivity with regard to (relatively small) changes in the amplitudes of the surface ECG mapping data. The absolute values of the a priori conductivities of the different compartments in the patient’s thorax do, therefore, not play that important role in the modeling process. This circumstance dramatically improves the stability of the AT imaging approach with respect to modeling errors belonging to changes in the amplitudes. On the contrary, we convincingly found that errors related to the temporal information of the data are of significant importance for the stability of the AT imaging approach. The consideration of an accurate source-containing surface model for the atrium or the ventricle, and their coupling in time and space to the ECG mapping data is one of the critical aspects. This surface modeling together with the coupling of the data influences the temporal information and the associated numerical stability. In this study we tried to perform this heart surface modeling and data coupling as accurately as possible. We demonstrated that AT imaging within the human atrium and ventricle from paced and sinus rhythm ECG mapping data is feasible under clinical conditions. Of course, the imaging of spontaneous rhythms, like the onset of flutter or spontaneous foci from the pulmonary veins, will be another important milestone in the development and clinical establishment of this novel diagnostic imaging technique. To the extent to which this method may be applicable at the present development stage and to our experience attained up to now, there are some important aspects for a successful imaging of the target activation pattern. First, not surprisingly, an accurate model of the target source-containing surface coupled as exactly as possible in time and space with the ECG mapping data is of utmost
Imaging of Cardiac Electrical Excitation •
importance. Second, the target ECG wave for which imaging has to be performed should uniquely represent the underlying activation process. In clinical situations this often is not the case and signalsubtraction techniques will therefore have a huge methodical impact. Third, the applied inverse approach must show a good numerical performance to extract a unique and stable inverse solution in the presence of a noisy environment. In summary, the atrial and ventricular AT imaging results are very promising and give hope that further research will bring this new diagnostic tool closer to clinical applications. From the current point of view, it can be expected that this novel model-based imaging technique will have a significant impact on cardiac MRI, in particular on interventional MRI.
4.
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Conclusion 10.
We demonstrated that the surface heart AT inverse formulation and the applied inverse approach are able to image sinus and coronary sinus paced atrial activation sequences with sufficient accuracy. The inverse solutions displayed good numerical stability. It turned out that an accurate ECG-gated modeling of the atrial surfaces and a coupling of this model, as accurately as possible, to the ECG mapping data is of utmost importance. Also, the coupling of the CARTO maps with the geometrical models of the target chambers has to be done very carefully in order to allow a quantitative validation. Further clinical validation studies will be focused on more complex pacing protocols and on atrial and ventricular arrhythmias. Of course, the imaging of spontaneous abnormal rhythms, eg, foci from the pulmonary veins or a flutter circuit in the right atrium, will be the next very important milestone in the clinical establishment and in the process of clinical validation of inverse electrocardiography.
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References 17. 1. SippensGroenewegen A, Lesh MD, Roithinger FX, et al: Body surface mapping of counterclockwise and clockwise typical atrial flutter: A comparative analysis with endocardial activation sequence mapping. J Am Col Cardiol 35:1276, 2000 2. Gepstein L, Hayam G, Ben-Haim SA: A novel method for nonfluoroscopic catheter-based electroanatomical mapping of the heart: In vitro and in vivo accuracy results. Circulation 95:1611, 1997 3. Hindricks G, Kottkamp H: Simultaneous noncontact
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19.
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mapping of left atrium in patients with paroxysmal atrial fibrillation. Circulation 104:297, 2001 Cuppen J, van Oosterom A: Model studies with inversely calculated isochrones of ventricular depolarization. IEEE Trans Biomed Eng 31:652, 1984 Greensite F: The mathematical basis for imaging cardiac electrical function. Crit Rev Biomed Eng 22:347, 1994 Huiskamp GJ, van Oosterom A: The depolarization sequence of the human heart computed from measured body surface potentials. IEEE Trans Biomed Eng 35:1047, 1988 Huiskamp GJ, Greensite F: A new method for myocardial activation imaging. IEEE Trans Biomed Eng 44:433, 1997 Modre R, Tilg B, Fischer G, et al: An iterative algorithm for myocardial activation time imaging. Comput Meth Prog Bio 64:1, 2001 Modre R, Tilg B, Fischer G, et al: Noninvasive myocardial activation time imaging: A novel inverse algorithm applied to clinical ECG mapping data. IEEE Trans Biomed Eng 49:1153, 2002 Ostendorp TF, Pesola K: Non-invasive determination of the activation sequence of the heart: Validation by comparison with invasive human data, in Murray A, Swiryn S (eds): Computers in Cardiology 1998, p 313 Burnes JE, Taccardi B, Rudy Y: A noninvasive imaging modality for cardiac arrhythmias. Circulation 102:2152, 2000 Oster HS, Taccardi B, Lux RL, et al: Noninvasive electrocardiographic imaging. Reconstruction of epicardial potentials, electrograms, and isochrones and localization of single and multiple electrocardiac events. Circulation 96:1012, 1997 Tilg B, Modre R, Fischer G, SippensGroenewegen A, et al: Noninvasive imaging of the activation time map within the atrium and ventricle-a validation study in humans. Proceedings NASPE 2001, Washington, DC, Pace 24(4), Part II, 718, 2001 Fischer G, Tilg B, Modre R, Huiskamp GJ, et al: A bidomain model based FEM-BEM coupling formulation for anisotropic cardiac tissue. Ann Biomed Eng 28:1229, 2000 Geselowitz DB, Miller WT 3rd: A bidomain model for anisotropic cardiac muscle. Ann Biomed Eng 11:191, 1983 Tilg B, Fischer G, Modre R, et al: Model-based imaging of cardiac electrical excitation in humans. IEEE Trans Med Imag 21:1430, 2002 Fischer G, Tilg B, Modre R, et al: On modeling the Wilson Central Terminal in the Boundary and Finite Element Method. IEEE Trans Biomed Eng 49:217, 2002 Harrild DM, Henriquez CS: A computer model of normal conduction in the human atria. Circ Res 87:e25, 2000 Lesh MD, Roithinger FX: Atrial tachycardia, in A.J. Camm and N.Y. Armonk, Eds. Clinical approaches to tachyarrhythmias, vol 11, Futura Publishing Company Inc, 2000
Clinical ECG Mapping and Imaging of Cardiac Electrical Excitation
Bernhard Tilg, PhD,* Friedrich Hanser, PhD,* Robert Modre-Osprian, PhD,* Gerald Fischer, PhD,* Bernd Messnarz, MSc,* Thomas Berger, MD,† Florian Hintringer, MD,† Otmar Pachinger, MD,† and Franz Xaver Roithinger, MD†
Abstract: Combining electrocardiographic mapping and 3D⫹time anatomical data enables noninvasively the imaging of the electrical excitation sequence in the human heart. A bidomain-theory based surface heart model activation time imaging approach was employed to image single beat data of atrial and ventricular depolarisation. Activation time maps were reconstructed for three patients who underwent an electrophysiologic study. The sinus rhythm and a rhythm according to a pacing protocol were reconstructed for two patients. For the third patient the accessory pathway of the WPW syndrome was localized. For focal arrhythmias, this model-based imaging approach might allow the guidance and evaluation of antiarrhythmic interventions, for instance, in case of catheter ablation or drug therapy. Key words: Activation time imaging, clinical validation, electrocardiographic inverse problem, body surface ECG mapping.
Atrial and ventricular arrhythmias and their therapeutic treatment play a significant role in clinical electrocardiology (1). Within the last several years, new methodology has been established for the clinical assessment of atrial and ventricular activation. In addition to standard techniques, sophisticated invasive technology, such as electroanatomical mapping or noncontact mapping, has been
included into clinical electrophysiogical (EP) procedures (2,3). Noninvasive inverse electrocardiography may further enhance the spectrum, especially for targeting focal arrhythmias and patient selection. Recently, a method for catheter-based electroanatomical mapping has been introduced that combines electrophysiological information, such as the sequence of cardiac activation, with a 3D image of the cardiac chamber (2). The timing of unipolar and bipolar signals, which are related to a reference signal, enables the recording and display of activation times on a 3D map in relation to the position of the catheter in the heart. The advantage of the CARTO (Biosense Webster Inc, Johnson & Johnson Company) system in clinical electrophysiology is the ability to reposition the ablation catheter to any spot of the target chamber without relying on fluoroscopy. This technique, however, shows significant limitations when it comes to acquiring
From the *University for *Health Informatics and Technology Tyrol; and the †Department of Cardiology, University Hospital Innsbruck, Innsbruck, Austria. This study was supported by the Austrian Federal Ministry for Education, Science and Culture and by the Austrian Science Fund, grant START Y144. Reprint requests: Bernhard Tilg, PhD, Professor, Institute for Medical Signal Processing and Imaging, University for Health Informatics and Technology Tyrol, Innrain 98, 6020 Innsbruck, Austria; e-mail: [email protected]. Copyright 2002, Elsevier Science (USA). All rights reserved. 0022-0736/02/350S-0012$35.00/0 doi:10.1054/jelc.2002.37159
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82 Journal of Electrocardiology Vol. 35 Supplement 2002 single beat activation maps. In addition, the invasive procedures can not be used for screening patients in order to decide the optimal individual therapeutic procedure (eg, drug, ablative, or hybrid therapy). Noninvasive imaging approaches overcome these limitations and provide in a noninvasive way information about electrical excitation. From a clinical point of view, this might have several benefits. For a clinical validation of inverse electrocardiography, however, electroanatomical CARTO maps may serve as the golden standard. Combining magnetic resonance imaging (MRI) of the torso anatomy with body surface ECG mapping enables noninvasive imaging of the primary electrical sources in the human heart (4 –13). The primary source in the cardiac muscle is the spatio-temporal transmembrane potential distribution (TPD) (14,15). In the inverse problem parameters describing features of TPD or the epicardial potential are estimated (4,5,9,11,12). The epicardial potential and the potential on all other conductivity interfaces are related to TPD by an integral equation. The most established inverse formulations are the imaging of the AT map on the entire surface of the heart and the imaging of the epicardial potential pattern. In the surface heart AT imaging approach the underlying source model is based on an isotropic bidomain formulation with TPD as the primary source term. In applying a proper inverse algorithm, this approach enables single beat reconstruction of single focal, multiple focal and more distributed activation patterns. Additionally, it can distinguish between areas with early and late activation. The surface heart AT imaging approach is currently under clinical evaluation and ongoing technical development. Potential clinical applications are noninvasive imaging of atrial and ventricular ectopic beats and pre-excited activation. So far, clinical validation of inverse electrocardiography has not been accomplished. First results are available for the torso tank model (11,12). Only a few promising results are reported in humans (10,13,16). Clinical validation is of utmost importance in order to show the applicability and the stability of the electrocardiographic inverse approach under clinical conditions. Theoretical studies employing a computer or a phantom model can only investigate the theoretical limitations of the inverse modeling approach. For clinical validation, the reference method (“the golden standard”) should provide, in principle, the same information as calculated in the inverse modeling approach. In the surface heart AT imaging method in which the AT map is determined on the endo- and epicardium of the ventricle or atrium, the catheter mapping techniques can be
applied for validation. Preferably, an ECG-gated geometry description of the target chamber and the AT map should be available invasively. Such an AT map is, in general, derived from the potential map. For stable cardiac rhythms this information can be gained, eg, by the CARTO system (2). CARTO enables the coupling to the MRI reference frame with regard to the external marker positions and anatomical markers, which is important for a quantitative validation approach. In this study we investigated the applicability of the surface heart AT imaging method in three patients. The ECG-gated geometrical models obtained from MRI and the reconstructed AT maps were compared with the electroanatomical CARTO maps. In case of WPW syndrome, the invasive localization of the accessory pathway was qualitatively compared with the findings from the invasive catheter procedure. The presented AT imaging method permits the reconstruction of single focal, multiple focal, and more distributed activation patterns. Potentially promising clinical applications are the noninvasive imaging of atrial and ventricular ectopic beats as well as pre-excited activation.
Materials and Methods Study Protocol Three male patients, 65Y (A), 24Y (B), and 21Y (C) with structurally normal hearts underwent EP studies. Informed consent was obtained from all patients before any diagnostic and therapeutic procedure. The study was approved by the local ethics committee. Patient B and C suffered from a WolffParkinson-White (WPW) syndrome while Patient A suffered from an atrial flutter. Before treatment in the catheter laboratory individual anatomical data were obtained from MRI using a Magnetom Vision Plus™ 1.5T scanner. Atrial and ventricular geometries were recorded in CINE-mode during breathhold (expiration, short axis scans, 4 and 6mm spacing). The lungs and the torso shape were recorded in T1-FLASH-mode during flat breath-hold (expiration, axial scans, 10mm spacing). Twelve markers (vitamin E capsules, 7 anatomical landmarks on the anterior and lateral chest wall, 5 electrode positions on the patient’s back) were used to couple all geometrical data to the MRI frame. From these data sets boundary element volume conductor models were constructed (8,14,16,17). A volume conductor model was constructed from the patient’s individual MRI data set. The conduc-
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Fig. 1. (A) Four axial MRI scans from patient A from an anterior left lateral view. Large spheres indicate the 7 reference marker positions. Small pheres indicate the anterior electrode positions. (B) BEM volume conductor model for patient A from an anterior left lateral view. Small and large spheres indicate the electrode positions and the WCT, respectively. The atrial and ventricular model were constructed for the end-diastolic phase.
tivity interfaces of the chest, the lungs, the blood mass, and the surface of the ventricle or the atrium were taken into account. These interfaces are extracted from the axial (chest, lungs) and from the CINE short-axis (blood mass, ventricle, atrium) MRI scans. A commercial software package was used for contour detection and segmentation (Amira, TGS Template Graphics Software, Inc.; Merignac Cedex, France). This software package provides tools for interactively segmenting 3D imaging data. After segmentation and initial triangulation of each individual surface, a mesh optimisation was performed based on a 3D Delaunay algorithm. The shape and the distribution of the triangles play an important role, especially for BEM calculations, in order to achieve good numerical performance in the forward and inverse problem. The BEM volume conductor model for patient A is depicted in Fig. 1 (right panel) from an anterior left lateral view. The 3 electrodes on the right arm, left arm, and on the left leg, defined the reference terminal. They are indicated by large spheres. The entire model comprised of 6794 triangles. The ventricular and atrial surface consisted of 1462 and 1600 triangles, and of 731 and 790 nodal points, respectively. The ventricular and atrial model were constructed from CINE short-axis scans at 0 and 600 ms trigger delay after the R-peak. For patient B and C, again, an individual volume conductor model was constructed. The entire mesh consisted of similar numbers of triangles. For all patients the following conductivities were assumed for the different thorax compartments: chest (0.20 SM⫺1), lungs (0.08 SM⫺1), blood mass (0.60 SM⫺1), intracellular effective conductivity (0.10 SM⫺1). The patients were moved to the catheter laboratory and ECG mapping data were recorded during and after the EP study. Electrocardiographic map-
ping data were collected in 62-channels by the Mark-8 system (Biosemi, V. O. F., Amsterdam, The Netherlands). A Wilson Central Terminal (WCT) defined the reference potential (17). The sampling rate was 2048Hz. Signals were bandpass filtered with a lower and upper edge frequency of 0.3Hz and 400Hz, respectively. The AC-resolution of the system is 500nV/bit (16 bit per channel). Radiotransparent carbon electrodes were used in order to allow simultaneous X-ray examination. The positions of 52 electrodes on the anterior and lateral chest wall were digitized by the FASTRAK system (Polhemus, Inc., Colchester, Vermont). Additionally, the positions of the 7 anterior and lateral landmarks were digitized in order to allow coordinate transformation to the MRI frame. The locations of the 5 posterior electrodes were identical with the position of the 5 posterior MRI markers. Figure 1 (left panel) shows four axial MRI scans in the MRI frame with the 7 reference positions and anterior electrode positions. The ECG raw data were pre-processed by baseline correction, but no additional filtering was applied. The transfer matrix was calculated applying the boundary element method with linear triangular elements. The AT map was estimated from single beat ECG mapping data by decomposing the nonlinear inverse problem into a sequence of linear problem formulations. At each step of iteration the regularization parameter was determined with the L-curve method. More detailed information on this inverse approach can be found elsewhere (8,9). Geometrical Modeling of the Human Atrium Because of the complex anatomy of the human atrium there are several aspects in the evaluation of
84 Journal of Electrocardiology Vol. 35 Supplement 2002
Fig. 2. Ventricular sinus rhythm AT map from an anterior-posterior view for patient A. (A) The anterior epicardium. The posterior epicardium is not visible. (B) The endocardium of RV and LV.
a “good” surface model (16,18,19). First, specific care has to be taken on the MRI protocol in obtaining scans with a high gray-value contrast. The models were obtained from short-axis scans with 4-mm slice thickness in a CINE-mode during breath-hold. The atrial epicardium was modeled assuming a uniform wall thickness of 4 mm for the LA and RA free wall. Specific attention has to be paid to the identification of the pulmonary veins, the VCS and VCI as well as to the TA and MA. The modeling of these structures is important for this kind of inverse formulation. Because of the sophisticated curvature and of the individual endo- and epicardial boundary element surfaces the proper meshing is of utmost importance in order to obtain a high-quality transfer matrix relating the transmembrane potential on this source-containing surface to the ECG mapping data.
into a sequence of linear problem formulations. These linear ill-posed problems were solved employing special spatio-temporal regularization (2nd order Tikhonov regularization) in combination with a characteristic template function of TPD). An initial guess was calculated by the so-called critical point theorem. At each step of iteration the regularization parameter was determined with the Lcurve method. More detailed information on this inverse approach can be found elsewhere (8,9). The following abbreviations are used throughout the paper: Mitral and tricuspid annulus (MA, TA), right and left atrial appendage (RAA, LAA), right upper and right lower pulmonary vein (RUPV, RLPV), left upper and left lower pulmonary vein (LUPV, LLPV), vena cava superior and vena cava inferior (VCS, VCI), coronary sinus (CS), ostium (O).
Inverse Procedure
Results The ECG raw data were pre-processed by baseline correction, but no additional filtering was applied. In our bidomain theory based surface heart model formulation the primary electrical sources in the cardiac muscle is the transmembrane potential distribution (TPD). Applying bioelectromagnetic field theory, the potential on the chest surface is related to TPD by a Fredholm integral equation of second kind. Thus, a compact operator maps TPD onto the ECG mapping data. Consequently, the determination of AT from ECG mapping data constitutes a nonlinear inverse ill-posed problem. The nonlinear relationship between TPD and AT makes the problem nonlinear. The inverse procedure is inherently unstable unless physiologically meaningful and valid constraints can be imposed. The transfer matrix was calculated applying the boundary element method with linear triangular elements. The AT map was estimated from single beat ECG mapping data by decomposing the nonlinear inverse problem
The AT maps were reconstructed from single beat ECG mapping data. The isochrones in Fig. 2, 3 are shown in steps of 5 ms. The isochrones in Fig. 4 are shown in steps of 10 ms. The reconstructed sinus rhythm AT map on RV and LV for patient A is shown in Fig. 2. The right panel does not depict the anterior epicardium. Early endocardial activation in RV occurred at 18ms. A second endocardial breakthrough at 35 ms is on the endocardial left lateral free wall of LV. As can be seen in Fig. 2, the first epicardial breakthrough is on the anterior epicardium of RV at 29 ms. The interval of the entire ventricular depolarization was determined to be 88 ms. The left and right heart base are activated electrically at 80 ms and 88 ms, respectively. These findings are in good qualitative agreement with the sinus rhythm pattern from the isolated Langendorff-perfused human heart. For the imaging of the electrical excitation in RA and LA, sinus and paced
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Fig. 3. AT map of a CS-O pacing protocol for patient A on the endocardium of RA and LA from a (A) posterior-anterior and (B) caudal oblique view.
rhythm data were available for patient A. Pacing was performed at the CS-O, at the catheter electrode position no. 7-8. This electrode position anatomically corresponded to the posterior septal area, in between RA and LA. Figure 3 (left panel) depicts the estimated AT map on the endocardium of RA and LA for CS-O pacing from a posterior-anterior view. Earliest activation was determined at the posterior-septal site of LA at 2ms. The LLPV and RLPV area are activated at 60ms. The anteriorseptal area of LA is depolarized at 90ms. Earliest activation of RA occurs at 13ms, i.e., 9ms after the first breakthrough in LA. In RA, the excitation wave spreads continuously towards RAA and SVC. The SVC area is activated at 70ms. The right panel in Fig. 3 depicts the same AT map from a caudal oblique view. For CS-O pacing, a CARTO map for RA was available. This electroanatomical catheter map was coupled to the 3D ⫹ time anatomical model of RA, using the 7 external reference marker positions. After acquiring the catheter map, these
Fig. 4. (A) Epicardial and (B) endocardial WPW-sinus rhythm AT map for patient B. The accessory pathway was localized at the left posterior site of the ventricle.
reference points were digitized in the CARTO device coordinate system. This information was then used to transform the catheter map to the MRI frame. The first endocardial breakthroughs determined in the eletroanatomical catheter map and in the reconstructed AT map of RA were compared in order to obtain a quantitative localization criterion. The mean geometrical error between the modeled RA and the points of the catheter map was determined to be 6.4 mm. The localization error of the first endocardial breakthrough was 6 mm. The global AT pattern was in good qualitatively agreement with the electroanatomical map. Patient B suffered from a WPW syndrome. Surface ECG data suggested the accessory pathway of the WPW to be somewhere in the left posterior or left anterior region of the ventricle. Figure 4 depicts the reconstructed WPW-sinus rhythm AT map in ms from a posterior view. As can be clearly seen in Figure 4 the accessory pathway was at the posterior region of the left ventricle. Successful radio-frequency
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Discussion
Fig. 5. Movie frames for the RV pacing propagation pattern for patient C from an anterior-posterior view. The numbers indicate the times during ventricular depolarization. Epicardium is depicted in a transparent style.
catheter ablation was performed at this site. A comparison between reconstructed and invasive data (radio frequency ablation sites) could be done only qualitatively. From the results we concluded a localization accuracy smaller than 15 mm. The right panel of Figure 4 depicts the AT map only on the endocardium of RV and LV. The epicardium is indicated in a transparent style. Patient C also suffered from a WPW syndrome. For this patient a RV pacing protocol was performed. The stimulation catheter was positioned at the right lateral wall of RV. Pacing was done during the ventricular enddiastolic phase. Figure 5 depicts the reconstructed spread of excitation on the endocardium of RV and LV at different times (30, 40, 50, 60, 70, 80, 90, 100, 110 ms) from an anterior-posterior view. The epicardium again is depicted in a transparent style. Movie frames beginning at the left upper panel are shown at 9 subsequent times. Black indicates electrically activated myocardium. White indicates the resting phase. Again, the localization accuracy could be verified only qualitatively. As can be seen in Figure 5, the first endocardial breakthrough was reconstructed at 28 ms on the right wall of RV. The first endocardial breakthrough on LV occurred at 48 ms, suggesting electrical conduction from RV to LV also through the Purkinje fibre network. The interval of the entire ventricular depolarization was 116 ms.
We presented a method for the imaging of the AT map on the surface of the atrium and ventricle from ECG mapping data. The individual thorax models of the patients were constructed from 3D⫹time MRI data. ECG and MRI data were coupled in time and space. Results were presented for sinus and paced rhythms. The bidomain theory based surface heart model AT imaging approach constitutes an excellent basis for the electrocardiographic inverse problem formulation. As long as we are dealing with cardiac excitation it not only allows to image the isochrones on the endocardium and epicardium, it also enables the incorporation of a mathematical and physically based model for the relationship between the AT map and the surface ECG mapping data. One of the advantages of the presented AT imaging approach is its non-sensitivity with regard to (relatively small) changes in the amplitudes of the surface ECG mapping data. The absolute values of the a priori conductivities of the different compartments in the patient’s thorax do, therefore, not play that important role in the modeling process. This circumstance dramatically improves the stability of the AT imaging approach with respect to modeling errors belonging to changes in the amplitudes. On the contrary, we convincingly found that errors related to the temporal information of the data are of significant importance for the stability of the AT imaging approach. The consideration of an accurate source-containing surface model for the atrium or the ventricle, and their coupling in time and space to the ECG mapping data is one of the critical aspects. This surface modeling together with the coupling of the data influences the temporal information and the associated numerical stability. In this study we tried to perform this heart surface modeling and data coupling as accurately as possible. We demonstrated that AT imaging within the human atrium and ventricle from paced and sinus rhythm ECG mapping data is feasible under clinical conditions. Of course, the imaging of spontaneous rhythms, like the onset of flutter or spontaneous foci from the pulmonary veins, will be another important milestone in the development and clinical establishment of this novel diagnostic imaging technique. To the extent to which this method may be applicable at the present development stage and to our experience attained up to now, there are some important aspects for a successful imaging of the target activation pattern. First, not surprisingly, an accurate model of the target source-containing surface coupled as exactly as possible in time and space with the ECG mapping data is of utmost
Imaging of Cardiac Electrical Excitation •
importance. Second, the target ECG wave for which imaging has to be performed should uniquely represent the underlying activation process. In clinical situations this often is not the case and signalsubtraction techniques will therefore have a huge methodical impact. Third, the applied inverse approach must show a good numerical performance to extract a unique and stable inverse solution in the presence of a noisy environment. In summary, the atrial and ventricular AT imaging results are very promising and give hope that further research will bring this new diagnostic tool closer to clinical applications. From the current point of view, it can be expected that this novel model-based imaging technique will have a significant impact on cardiac MRI, in particular on interventional MRI.
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Conclusion 10.
We demonstrated that the surface heart AT inverse formulation and the applied inverse approach are able to image sinus and coronary sinus paced atrial activation sequences with sufficient accuracy. The inverse solutions displayed good numerical stability. It turned out that an accurate ECG-gated modeling of the atrial surfaces and a coupling of this model, as accurately as possible, to the ECG mapping data is of utmost importance. Also, the coupling of the CARTO maps with the geometrical models of the target chambers has to be done very carefully in order to allow a quantitative validation. Further clinical validation studies will be focused on more complex pacing protocols and on atrial and ventricular arrhythmias. Of course, the imaging of spontaneous abnormal rhythms, eg, foci from the pulmonary veins or a flutter circuit in the right atrium, will be the next very important milestone in the clinical establishment and in the process of clinical validation of inverse electrocardiography.
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