Impact of Spacing and Orientation on the Scar Threshold With a High-Density Grid Catheter.

BACKGROUND: Multipolar catheters are increasingly used for high-density mapping. However, the threshold to define scar areas has not been well described for each configuration. We sought to elucidate the impact of bipolar spacing and orientation on the optimal threshold to match magnetic resonance imaging-defined scar. METHOD: The HD-Grid catheter uniquely allows for different spatially stable bipolar configurations to be tested. We analyzed the electrograms with settings of HD-16 (3 mm spacing in both along and across bipoles) and HD-32 (1 mm spacing in along bipoles and 3 mm spacing in across bipoles) and determined the optimal cutoff for scar detection in 6 infarcted sheep. RESULTS: From 456 total acquisition sites (mean 76±12 per case), 14 750 points with the HD-16 and 32286 points with the HD-32 configuration for bipolar electrograms were analyzed. For bipolar voltages, the optimal cutoff value to detect the magnetic resonance imaging-defined scar based on the Youden's Index, and the area under the receiver operating characteristic curve (AUROC) differed depending on the spacing and orientation of bipoles; across 0.84 mV (AUROC, 0.920; 95% CI, 0.911-0.928), along 0.76 mV (AUROC, 0.903; 95% CI, 0.893-0.912), north-east direction 0.95 mV (AUROC, 0.923; 95% CI, 0.913-0.932), and south-east direction, 0.87 mV (AUROC, 0.906; 95% CI, 0.895-0.917) in HD-16; and across 0.83 mV (AUROC, 0.917; 95% CI, 0.911-0.924), along 0.46 mV (AUROC, 0.890; 95% CI, 0.883-0.897), north-east direction 0.89 mV (AUROC, 0.923; 95% CI, 0.917-0.929), and south-east direction 0.83 mV (AUROC, 0.913; 95% CI, 0.906-0.920) in HD-32. Significant differences in AUROC were seen between HD-16 along versus across (P=0.002), HD-16 north-east direction versus south-east direction (P=0.01), HD-32 north-east direction versus south-east direction (P<0.0001), and HD-16 along versus HD-32 along (P=0.006). The AUROC was significantly larger (P<0.01) when only the best points on each given site were selected for analysis, compared with when all points were used. CONCLUSIONS: Spacing and orientation of bipoles impacts the accuracy of scar detection. Optimal threshold specific to each bipolar configuration should be determined. Selecting one best voltage point among multiple points projected on the same surface is also critical on the Ensite-system to increase the accuracy of scar-mapping.

Detailed Analysis of the Relation Between Bipolar Electrode Spacing and Far- and Near-Field Electrograms.

OBJECTIVES: This study sought to evaluate the relation between bipolar electrode spacing and far- and near-field electrograms. BACKGROUND: The detailed effects of bipolar spacing on electrograms (EGMs) is not well described. METHODS: With a HD-Grid catheter, EGMs from different bipole pairs could be created in each acquisition. This study analyzed the effect of bipolar spacing on EGMs in 7 infarcted sheep. A segment was defined as a 2-mm center-to-center bipole. In total, 4,768 segments (2,020 healthy, 1,542 scar, and 1,206 in border areas, as defined by magnetic resonance imaging [MRI]) were covered with an electrode pair of spacing of 2 mm (Bi-2), 4 mm (Bi-4), and 8 mm (Bi-8). RESULTS: A total of 3,591 segments in Bi-2 were free from local abnormal ventricular activities (LAVAs); 1,630 segments were within the MRI-defined scar and/or border area. Among them, 172 (10.6%) segments in Bi-4 and 219 (13.4%) segments in Bi-8 showed LAVAs. In contrast, LAVAs were identified in 1,177 segments in Bi-2; 1,118 segments were within the MRI-defined scar and/or border area. Among them, LAVAs were missed in 161 (14.4%) segments in Bi-4 and in 409 (36.6%) segments in Bi-8. In segments with LAVAs, median far-field voltage increased from 0.09 mV (25th to 75th percentile: 0.06 to 0.14 mV) in Bi-2, to 0.16 mV (25th to 75th percentile: 0.10 to 0.24 mV) in Bi-4, and to 0.28 mV (25th to 75th percentile: 0.20 to 0.42 mV) in Bi-8 (p < 0.0001). Median near-field voltage increased from 0.14 mV (25th to 75th percentile: 0.08 to 0.25 mV) in Bi-2, to 0.21 mV (25th to 75th percentile: 0.12 to 0.35 mV) in Bi-4, and to 0.32 mV (25th to 75th percentile: 0.17 to 0.48 mV) in Bi-8 (p < 0.0001). The median near-/far-field voltage ratio decreased from 1.67 in Bi-2, to 1.43 in Bi-4, and 1.23 in Bi-8 (p < 0.0001). CONCLUSIONS: Closer spacing better discriminates surviving tissue from dead scar area. Although far-field voltage systematically increases with spacing, near-field voltages were more variable, depending on local surviving muscular bundles. Near-field EGMs are more easily observed with smaller spacing, largely due to the reduction of the far-field effect.

Effect of bipolar electrode orientation on local electrogram properties.

BACKGROUND: The direct effect of bipolar orientation on electrograms (EGMs) remains unknown. OBJECTIVE: The purpose of this study was to examine the variation of EGMs with diagonally orthogonal bipoles. METHODS: The HD-32 Grid catheter (Abbott, Minneapolis, MN) can assess the effect of bipolar orientation while keeping the interelectrode distance and center unchanged. Seven sheep with anterior myocardial infarction were analyzed using diagonally orthogonal electrode pairs across splines by comparing local EGMs from each pair of opposing electrodes {eg. A1-B3 (southeast direction [SE]) vs A3-B1 (northeast direction [NE])}. RESULTS: A total of 4084 EGMs (1 in each direction) were analyzed for 2042 sites (544 in the infarcted area, 488 in the border area, and 1010 in the normal area). The higher and lower voltages measured using each pair of opposing electrodes significantly differed (1.10 mV [0.43-2.56 mV] vs 0.69 mV [0.28-1.58 mV]; P < .0001), and the median variation was 0.28 mV (0.11-0.80 mV) (31.7% [16.0%-48.9%]). The voltage variation was maximized to 48.7% (37.7%-61.6%) (P < .0001) on sites where the activation wavefront was perpendicular to the one bipolar direction and parallel to the other. A total of 594 of 719 (82.6%) sites with the voltage <0.5 mV and 539 of 699 (77.1%) sites with the voltage >1.5 mV in NE stayed in the same voltage range as those in SE. However, only 348 of 624 (55.8%) sites with the voltage 0.5-1.5 mV in NE stayed in the same range as those in SE. Local ventricular abnormal activities (LAVAs) were detected in 592 of 2042 (29.0%) sites in total, frequently distributed in the border area. A total of 177 (29.9%) LAVAs were missed in one direction and 180 (30.4%) in the other. When 415 (70.1%) LAVAs detected in NE are defined as the reference, 235 of 415 (56.6%) matched with those detected in SE. CONCLUSION: The bipolar voltage and distribution of LAVAs may differ significantly between diagonally orthogonal bipolar pairs at any given site.

Relationship Between Fibrosis Detected on Late Gadolinium-Enhanced Cardiac Magnetic Resonance and Re-Entrant Activity Assessed With Electrocardiographic Imaging in Human Persistent Atrial Fibrillation.

OBJECTIVES: This study sought to assess the relationship between fibrosis and re-entrant activity in persistent atrial fibrillation (AF). BACKGROUND: The mechanisms involved in sustaining re-entrant activity during AF are poorly understood. METHODS: Forty-one patients with persistent AF (age 56 ± 12 years; 6 women) were evaluated. High-resolution electrocardiographic imaging (ECGI) was performed during AF by using a 252-chest electrode array, and phase mapping was applied to locate re-entrant activity. Sites of high re-entrant activity were defined as re-entrant regions. Late gadolinium-enhanced (LGE) cardiac magnetic resonance (CMR) was performed at 1.25 × 1.25 × 2.5 mm resolution to characterize atrial fibrosis and measure atrial volumes. The relationship between LGE burden and the number of re-entrant regions was analyzed. Local LGE density was computed and characterized at re-entrant sites. All patients underwent catheter ablation targeting re-entrant regions, the procedural endpoint being AF termination. Clinical, CMR, and ECGI predictors of acute procedural success were then analyzed. RESULTS: Left atrial (LA) LGE burden was 22.1 ± 5.9% of the wall, and LA volume was 74 ± 21 ml/m2. The number of re-entrant regions was 4.3 ± 1.7 per patient. LA LGE imaging was significantly associated with the number of re-entrant regions (R = 0.52, p = 0.001), LA volume (R = 0.62, p < 0.0001), and AF duration (R = 0.54, p = 0.0007). Regional analysis demonstrated a clustering of re-entrant activity at LGE borders. Areas with high re-entrant activity showed higher local LGE density as compared with the remaining atrial areas (p < 0.0001). Failure to achieve AF termination during ablation was associated with higher LA LGE burden (p < 0.001), higher number of re-entrant regions (p < 0.001), and longer AF duration (p = 0.008). CONCLUSIONS: The number of re-entrant regions during AF relates to the extent of LGE on CMR, with the location of these regions clustering to LGE areas. These characteristics affect procedural outcomes of ablation.

Atrial tachycardias: Cause or effect with ablation of persistent atrial fibrillation?

INTRODUCTION: It is largely believed that atrial tachycardias (ATs) encountered during ablation of persistent atrial fibrillation (PsAF) are a byproduct of ablative lesions. We aimed to explore the alternative hypothesis that they may be a priori drivers of AF remaining masked until other AF sources are reduced or eliminated. METHODS AND RESULTS: Radiofrequency ablation of fibrillatory drivers mapped by electrocardiographic imaging (ECGI; ECVUE™, Cardioinsight Technologies, Cleveland, OH, USA) terminated PsAF in 198 (73%) out of 270 patients (61 ± 10 years, 9 ± 9 m). Two hundred and six ATs in 158 patients were subsequently mapped. Their anatomic relationship to the fibrillatory drivers prospectively identified by ECGI was then established. There were 26 (13%), 52 (25%), and 128 (62%) focal, localized, and macrore-entrant ATs, respectively. In focal/localized re-entrant ATs, 64 (82%) were terminated within an AF-driver region, in which 26 (81%) among 32 focal/localized ATs analyzed with 3-D-mapping system merged to driver map occurred from AF-driver regions in 1.0 ± 1.0 cm distance from the driver core. Importantly, there was no attempt at ablation of the associated AF-driver region in 25 of 64 (39%) of focal/localized re-entrant ATs. The sites of ATs origin generally had low-voltage, fractionated, and long-duration electrograms in AF. All but two focal/localized re-entrant ATs were successfully ablated. CONCLUSION: The majority of post-AF-ablation focal and localized re-entrant ATs originate from the region of prospectively established AF-driver regions. A third of these are localized to regions not subsequently submitted to ablation. These data suggest that many ATs exist, although not necessarily manifest independently, prior to ablation. They may have a role in the maintenance of PsAF in these individuals.

ECG imaging of ventricular tachycardia: evaluation against simultaneous non-contact mapping and CMR-derived grey zone.

ECG imaging is an emerging technology for the reconstruction of cardiac electric activity from non-invasively measured body surface potential maps. In this case report, we present the first evaluation of transmurally imaged activation times against endocardially reconstructed isochrones for a case of sustained monomorphic ventricular tachycardia (VT). Computer models of the thorax and whole heart were produced from MR images. A recently published approach was applied to facilitate electrode localization in the catheter laboratory, which allows for the acquisition of body surface potential maps while performing non-contact mapping for the reconstruction of local activation times. ECG imaging was then realized using Tikhonov regularization with spatio-temporal smoothing as proposed by Huiskamp and Greensite and further with the spline-based approach by Erem et al. Activation times were computed from transmurally reconstructed transmembrane voltages. The results showed good qualitative agreement between the non-invasively and invasively reconstructed activation times. Also, low amplitudes in the imaged transmembrane voltages were found to correlate with volumes of scar and grey zone in delayed gadolinium enhancement cardiac MR. The study underlines the ability of ECG imaging to produce activation times of ventricular electric activity-and to represent effects of scar tissue in the imaged transmembrane voltages.

Biophysical Modeling Predicts Ventricular Tachycardia Inducibility and Circuit Morphology: A Combined Clinical Validation and Computer Modeling Approach.

INTRODUCTION: Computational modeling of cardiac arrhythmogenesis and arrhythmia maintenance has made a significant contribution to the understanding of the underlying mechanisms of arrhythmia. We hypothesized that a cardiac model using personalized electro-anatomical parameters could define the underlying ventricular tachycardia (VT) substrate and predict reentrant VT circuits. We used a combined modeling and clinical approach in order to validate the concept. METHODS AND RESULTS: Non-contact electroanatomic mapping studies were performed in 7 patients (5 ischemics, 2 non-ischemics). Three ischemic cardiomyopathy patients underwent a clinical VT stimulation study. Anatomical information was obtained from cardiac magnetic resonance imaging (CMR) including high-resolution scar imaging. A simplified biophysical mono-domain action potential model personalized with the patients' anatomical and electrical information was used to perform in silico VT stimulation studies for comparison. The personalized in silico VT stimulations were able to predict VT inducibility as well as the macroscopic characteristics of the VT circuits in patients who had clinical VT stimulation studies. The patients with positive clinical VT stimulation studies had wider distribution of action potential duration restitution curve (APD-RC) slopes and APDs than the patient with a negative VT stimulation study. The exit points of reentrant VT circuits encompassed a higher percentage of the maximum APD-RC slope compared to the scar and non-scar areas, 32%, 4%, and 0.2%, respectively. CONCLUSIONS: VT stimulation studies can be simulated in silico using a personalized biophysical cardiac model. Myocardial spatial heterogeneity of APD restitution properties and conductivity may help predict the location of crucial entry/exit points of reentrant VT circuits.

Impact of Electrode Type on Mapping of Scar-Related VT.

BACKGROUND: Substrate-based VT ablation is mostly based on maps acquired with ablation catheters. We hypothesized that multipolar mapping catheters are more effective for identification of scar and local abnormal ventricular activity (LAVA). METHODS AND RESULTS: Phase1: In a sheep infarction model (2 months postinfarction), substrate mapping and LAVA tagging (CARTO® 3) was performed, using a Navistar (NAV) versus a PentaRay (PR) catheter (Biosense Webster). Phase2: Consecutive VT ablation patients from a single center underwent NAV versus PR mapping. Point pairs were defined as a PR and a NAV point located within a 3D-distance of ≤3 mm. Agreement was defined as both points in a pair being manually tagged as normal or LAVA. Four sheep (4 years, 50 ± 4.8 kg) and 9 patients were included (53 ± 14 years, 8 male, 6 ischemic cardiomyopathy). Mapping density was higher within the scar with PR versus NAV (3.2 vs. 0.7 points/cm2 , P = 0.001) with larger bipolar scar area (68 ± 55 cm2 vs. 58 ± 48 cm2 , P = 0.001). In total, 818 point pairs were analyzed. Using PR, far-field voltages were smaller (PR vs. NAV; bipolar: 1.43 ± 1.84 mV vs. 1.64 ± 2.04 mV, P = 0.001; unipolar; 4.28 ± 3.02 mV vs. 4.59 ± 3.67 mV, P < 0.001). More LAVA were also detected with PR (PR vs. NAV; 126 ± 113 vs. 36 ± 29, P = 0.001). When agreement on LAVA was reached (overall: 72%; both LAVA, 40%; both normal, 82%) higher LAVA voltages were recorded on PR (0.48 ± 0.33 mV vs. 0.31 ± 0.21 mV, P = 0.0001). CONCLUSION: Multipolar mapping catheters with small electrodes provide more accurate and higher density maps, with a higher sensitivity to near-field signals. Agreement between PR and NAV is low.

Age, atrial fibrillation, and structural heart disease are the main determinants of left atrial fibrosis detected by delayed-enhanced magnetic resonance imaging in a general cardiology population.

INTRODUCTION: We studied the extent and distribution of left atrial (LA) fibrosis on delayed-enhanced (DE) MRI in a general cardiology population. METHODS AND RESULTS: One hundred ninety consecutive patients referred for cardiac MRI underwent DE imaging using a free breathing method. The population comprised 60 AF patients and 130 patients without AF, including 75 with structural heart disease (SHD). DE was quantified using histogram thresholding, expressed in % of the wall. Regression analysis was performed to identify predictors of DE. Additionally, DE was registered on a template to study its distribution in subpopulations. In the total population, age, AF, and SHD were independently associated with DE. DE was increasingly observed from 11.1 ± 4.7% in patients with no SHD nor AF, 18.8 ± 7.8% in SHD and no AF history, 22.9 ± 7.8% in paroxysmal AF, to 27.8 ± 7.7% in persistent AF. Among non-AF patients, age and SHD were independently associated with DE. Among AF patients, female gender and AF persistence were independently associated with DE. DE was variably distributed but more frequently detected in the posterior wall. CONCLUSION: Age, history of AF, and SHD are the most powerful predictors of atrial fibrosis, as detected by MRI, in a general cardiology population. Atrial fibrosis predominates in the posterior LA wall.

Automated Quantification of Right Ventricular Fat at Contrast-enhanced Cardiac Multidetector CT in Arrhythmogenic Right Ventricular Cardiomyopathy.

PURPOSE: To evaluate an automated method for the quantification of fat in the right ventricular (RV) free wall on multidetector computed tomography (CT) images and assess its diagnostic value in arrhythmogenic RV cardiomyopathy (ARVC). MATERIALS AND METHODS: This study was approved by the institutional review board, and all patients gave informed consent. Thirty-six patients with ARVC (mean age ± standard deviation, 46 years ± 15; seven women) were compared with 36 age- and sex-matched subjects with no structural heart disease (control group), as well as 36 patients with ischemic cardiomyopathy (ischemic group). Patients underwent contrast material-enhanced electrocardiography-gated cardiac multidetector CT. A 2-mm-thick RV free wall layer was automatically segmented and myocardial fat, expressed as percentage of RV free wall, was quantified as pixels with attenuation less than -10 HU. Patient-specific segmentations were registered to a template to study fat distribution. Receiver operating characteristic (ROC) analysis was performed to assess the diagnostic value of fat quantification by using task force criteria as a reference. RESULTS: Fat extent was 16.5% ± 6.1 in ARVC and 4.6% ± 2.7 in non-ARVC (P < .0001). No significant difference was observed between control and ischemic groups (P = .23). A fat extent threshold of 8.5% of RV free wall was used to diagnose ARVC with 94% sensitivity (95% confidence interval [CI]: 82%, 98%) and 92% specificity (95% CI: 83%, 96%). This diagnostic performance was higher than the one for RV volume (mean area under the ROC curve, 0.96 ± 0.02 vs 0.88 ± 0.04; P = .009). In patients with ARVC, fat correlated to RV volume (R = 0.63, P < .0001), RV function (R = -0.67, P = .001), epsilon waves (R = 0.39, P = .02), inverted T waves in V1-V3 (R = 0.38, P = .02), and presence of PKP2 mutations (R = 0.59, P = .02). Fat distribution differed between patients with ARVC and those without, with posterolateral RV wall being the most ARVC-specific area. CONCLUSION: Automated quantification of RV myocardial fat on multidetector CT images is feasible and performs better than RV volume in the diagnosis of ARVC. Online supplemental material is available for this article.

Relationship between MDCT-imaged myocardial fat and ventricular tachycardia substrate in arrhythmogenic right ventricular cardiomyopathy.

BACKGROUND: Myocardial fibrofatty infiltration is a milieu for ventricular tachycardia (VT) in arrhythmogenic right ventricular cardiomyopathy (ARVC) and can be depicted as myocardial hypodensity on contrast-enhanced multidetector computed tomography (MDCT) with high spatial and temporal resolution. This study aimed to assess the relationship between MDCT-imaged myocardial fat and VT substrate in ARVC. METHODS AND RESULTS: We studied 16 patients with ARVC who underwent ablation and preprocedural MDCT. High-resolution imaging data were processed and registered to high-density endocardial and epicardial maps in sinus rhythm on 3-dimensional electroanatomic mapping (3D-EAM) (626±335 and 575±279 points/map, respectively). Analysis of the locations of low-voltage and fat segmentation included the following endocardial and epicardial regions: apex, mid (anterior, lateral, inferior), and basal (anterior, lateral, inferior). The location of local abnormal ventricular activities (LAVA) was compared with fat distribution. RV myocardial fat was successfully segmented and integrated with 3D-EAM in all patients. The κ agreement test demonstrated a good concordance between the epicardial low voltage and fat (κ=0.69, 95% CI 0.54 to 0.84), but fair concordance with the endocardium (κ=0.41, 95% CI 0.27 to 0.56). The majority of LAVA (520/653 [80%]) were located within the RV fat segmentation, of which 90% were not farther than 20 mm from its border. Registration of MDCT allowed direct visualization of the coronary arteries, thus avoiding coronary damage during epicardial radiofrequency delivery. CONCLUSIONS: The integration of MDCT-imaged myocardial fat with 3D-EAM provides valuable information on the extent and localization of VT substrate and demonstrates ablation targets clustering in its border region.

Spatial correlation of action potential duration and diastolic dysfunction in transgenic and drug-induced LQT2 rabbits.

BACKGROUND: Enhanced dispersion of action potential duration (APD) is a major contributor to long QT syndrome (LQTS)-related arrhythmias. OBJECTIVE: To investigate spatial correlations of regional heterogeneities in cardiac repolarization and mechanical function in LQTS. METHODS: Female transgenic LQTS type 2 (LQT2; n = 11) and wild-type littermate control (LMC) rabbits (n = 9 without E4031 and n = 10 with E4031) were subjected to phase contrast magnetic resonance imaging to assess regional myocardial velocities. In the same rabbits' hearts, monophasic APDs were assessed in corresponding segments. RESULTS: In LQT2 and E4031-treated rabbits, APD was longer in all left ventricular segments (P < .01) and APD dispersion was greater than that in LMC rabbits (P < .01). In diastole, peak radial velocities (Vr) were reduced in LQT2 and E4031-treated compared to LMC rabbits in LV base and mid (LQT2: -3.36 ± 0.4 cm/s, P < .01; E4031-treated: -3.24 ± 0.6 cm/s, P < .0001; LMC: -4.42 ± 0.5 cm/s), indicating an impaired diastolic function. Regionally heterogeneous diastolic Vr correlated with APD (LQT2: correlation coefficient [CC] 0.38, P = .01; E4031-treated: CC 0.42, P < .05). Time-to-diastolic peak Vr were prolonged in LQT2 rabbits (LQT2: 196.8 ± 2.9 ms, P < .001; E4031-treated: 199.5 ± 2.2 ms, P < .0001, LMC 183.1 ± 1.5), indicating a prolonged contraction duration. Moreover, in transgenic LQT2 rabbits, diastolic time-to-diastolic peak Vr correlated with APD (CC 0.47, P = .001). In systole, peak Vr were reduced in LQT2 and E4031-treated rabbits (P < .01) but longitudinal velocities or ejection fraction did not differ. Finally, random forest machine learning algorithms enabled a differentiation between LQT2, E4031-treated, and LMC rabbits solely based on "mechanical" magnetic resonance imaging data. CONCLUSIONS: The prolongation of APD led to impaired diastolic and systolic function in transgenic and drug-induced LQT2 rabbits. APD correlated with regional diastolic dysfunction, indicating that LQTS is not purely an electrical but an electromechanical disorder.

Regional myocardial wall thinning at multidetector computed tomography correlates to arrhythmogenic substrate in postinfarction ventricular tachycardia: assessment of structural and electrical substrate.

BACKGROUND: A majority of patients undergoing ablation of ventricular tachycardia have implanted devices precluding substrate imaging with delayed-enhancement MRI. Contrast-enhanced multidetector computed tomography (MDCT) can depict myocardial wall thickness with submillimetric resolution. We evaluated the relationship between regional myocardial wall thinning (WT) imaged by MDCT and arrhythmogenic substrate in postinfarction ventricular tachycardia. METHODS AND RESULTS: We studied 13 consecutive postinfarction patients undergoing MDCT before ablation. MDCT data were integrated with high-density 3-dimensional electroanatomic maps acquired during sinus rhythm (endocardium, 509±291 points/map; epicardium, 716±323 points/map). Low-voltage areas (<1.5 mV) and local abnormal ventricular activities (LAVA) during sinus rhythm were assessed with regard to the WT. A significant correlation was found between the areas of WT <5 mm and endocardial low voltage (correlation-R=0.82; P=0.001), but no such correlation was found in the epicardium. The WT <5 mm area was smaller than the endocardial low-voltage area (54 cm(2) [Q1-Q3, 46-92] versus 71 cm(2) [Q1-Q3, 59-124]; P=0.001). Among a total of 13 060 electrograms reviewed in the whole study population, 538 LAVA were detected and analyzed. LAVA were located within the WT <5 mm (469/538 [87%]) or at its border (100% within 23 mm). Very late LAVA (>100 ms after QRS complex) were almost exclusively detected within the thinnest area (93% in the WT<3 mm). CONCLUSIONS: Regional myocardial WT correlates to low-voltage regions and distribution of LAVA critical for the generation and maintenance of postinfarction ventricular tachycardia. The integration of MDCT WT with 3-dimensional electroanatomic maps can help focus mapping and ablation on the culprit regions, even when MRI is precluded by the presence of implanted devices.

Integration of merged delayed-enhanced magnetic resonance imaging and multidetector computed tomography for the guidance of ventricular tachycardia ablation: a pilot study.

BACKGROUND: Delayed enhancement (DE) MRI can assess the fibrotic substrate of scar-related VT. MDCT has the advantage of inframillimetric spatial resolution and better 3D reconstructions. We sought to evaluate the feasibility and usefulness of integrating merged MDCT/MRI data in 3D-mapping systems for structure-function assessment and multimodal guidance of VT mapping and ablation. METHODS: Nine patients, including 3 ischemic cardiomyopathy (ICM), 3 nonischemic cardiomyopathy (NICM), 2 myocarditis, and 1 redo procedure for idiopathic VT, underwent MRI and MDCT before VT ablation. Merged MRI/MDCT data were integrated in 3D-mapping systems and registered to high-density endocardial and epicardial maps. Low-voltage areas (<1.5 mV) and local abnormal ventricular activities (LAVA) during sinus rhythm were correlated to DE at MRI, and wall-thinning (WT) at MDCT. RESULTS: Endocardium and epicardium were mapped with 391 ± 388 and 1098 ± 734 points per map, respectively. Registration of MDCT allowed visualization of coronary arteries during epicardial mapping/ablation. In the idiopathic patient, integration of MRI data identified previously ablated regions. In ICM patients, both DE at MRI and WT at MDCT matched areas of low voltage (overlap 94 ± 6% and 79 ± 5%, respectively). In NICM patients, wall-thinning areas matched areas of low voltage (overlap 63 ± 21%). In patients with myocarditis, subepicardial DE matched areas of epicardial low voltage (overlap 92 ± 12%). A total number of 266 LAVA sites were found in 7/9 patients. All LAVA sites were associated to structural substrate at imaging (90% inside, 100% within 18 mm). CONCLUSION: The integration of merged MDCT and DEMRI data is feasible and allows combining substrate assessment with high-spatial resolution to better define structure-function relationship in scar-related VT.

Construction of 3D MR image-based computer models of pathologic hearts, augmented with histology and optical fluorescence imaging to characterize action potential propagation.

Cardiac computer models can help us understand and predict the propagation of excitation waves (i.e., action potential, AP) in healthy and pathologic hearts. Our broad aim is to develop accurate 3D MR image-based computer models of electrophysiology in large hearts (translatable to clinical applications) and to validate them experimentally. The specific goals of this paper were to match models with maps of the propagation of optical AP on the epicardial surface using large porcine hearts with scars, estimating several parameters relevant to macroscopic reaction-diffusion electrophysiological models. We used voltage-sensitive dyes to image AP in large porcine hearts with scars (three specimens had chronic myocardial infarct, and three had radiofrequency RF acute scars). We first analyzed the main AP waves' characteristics: duration (APD) and propagation under controlled pacing locations and frequencies as recorded from 2D optical images. We further built 3D MR image-based computer models that have information derived from the optical measures, as well as morphologic MRI data (i.e., myocardial anatomy, fiber directions and scar definition). The scar morphology from MR images was validated against corresponding whole-mount histology. We also compared the measured 3D isochronal maps of depolarization to simulated isochrones (the latter replicating precisely the experimental conditions), performing model customization and 3D volumetric adjustments of the local conductivity. Our results demonstrated that mean APD in the border zone (BZ) of the infarct scars was reduced by ~13% (compared to ~318 ms measured in normal zone, NZ), but APD did not change significantly in the thin BZ of the ablation scars. A generic value for velocity ratio (1:2.7) in healthy myocardial tissue was derived from measured values of transverse and longitudinal conduction velocities relative to fibers direction (22 cm/s and 60 cm/s, respectively). The model customization and 3D volumetric adjustment reduced the differences between measurements and simulations; for example, from one pacing location, the adjustment reduced the absolute error in local depolarization times by a factor of 5 (i.e., from 58 ms to 11 ms) in the infarcted heart, and by a factor of 6 (i.e., from 60 ms to 9 ms) in the heart with the RF scar. Moreover, the sensitivity of adjusted conductivity maps to different pacing locations was tested, and the errors in activation times were found to be of approximately 10-12 ms independent of pacing location used to adjust model parameters, suggesting that any location can be used for model predictions.

Strain-based regional nonlinear cardiac material properties estimation from medical images.

Model personalization is essential for model-based surgical planning and treatment assessment. As alteration in material elasticity is a fundamental cause to various cardiac pathologies, estimation of material properties is important to model personalization. Although the myocardium is heterogeneous, hyperelastic, and orthotropic, existing image-based estimation frameworks treat the tissue as either heterogeneous but linear, or hyperelastic but homogeneous. In view of these, we present a physiology-based framework for estimating regional, hyperelastic, and orthotropic material properties. A cardiac physiological model is adopted to describe the macroscopic cardiac physiology. By using a strain-based objective function which properly reflects the change of material constants, the regional material properties of a hyperelastic and orthotropic constitutive law are estimated using derivative-free optimization. Experiments were performed on synthetic and real data to show the characteristics of the framework.

Efficient probabilistic model personalization integrating uncertainty on data and parameters: Application to eikonal-diffusion models in cardiac electrophysiology.

Biophysical models are increasingly used for medical applications at the organ scale. However, model predictions are rarely associated with a confidence measure although there are important sources of uncertainty in computational physiology methods. For instance, the sparsity and noise of the clinical data used to adjust the model parameters (personalization), and the difficulty in modeling accurately soft tissue physiology. The recent theoretical progresses in stochastic models make their use computationally tractable, but there is still a challenge in estimating patient-specific parameters with such models. In this work we propose an efficient Bayesian inference method for model personalization using polynomial chaos and compressed sensing. This method makes Bayesian inference feasible in real 3D modeling problems. We demonstrate our method on cardiac electrophysiology. We first present validation results on synthetic data, then we apply the proposed method to clinical data. We demonstrate how this can help in quantifying the impact of the data characteristics on the personalization (and thus prediction) results. Described method can be beneficial for the clinical use of personalized models as it explicitly takes into account the uncertainties on the data and the model parameters while still enabling simulations that can be used to optimize treatment. Such uncertainty handling can be pivotal for the proper use of modeling as a clinical tool, because there is a crucial requirement to know the confidence one can have in personalized models.

Personalization of a cardiac electrophysiology model using optical mapping and MRI for prediction of changes with pacing.

Computer models of cardiac electrophysiology (EP) can be a very efficient tool to better understand the mechanisms of arrhythmias. Quantitative adjustment of such models to experimental data (personalization) is needed in order to test their realism and predictive power, but it remains challenging at the organ scale. In this paper, we propose a framework for the personalization of a 3-D cardiac EP model, the Mitchell-Schaeffer (MS) model, and evaluate its volumetric predictive power under various pacing scenarios. The personalization was performed on ex vivo large porcine healthy hearts using diffusion tensor MRI (DT-MRI) and optical mapping data. The MS model was simulated on a 3-D mesh incorporating local fiber orientations, built from DT-MRI. The 3-D model parameters were optimized using features such as 2-D epicardial depolarization and repolarization maps, extracted from the optical mapping. We also evaluated the sensitivity of our personalization framework to different pacing locations and showed results on its robustness. Further, we evaluated volumetric model predictions for various epi- and endocardial pacing scenarios. We demonstrated promising results with a mean personalization error around 5 ms and a mean prediction error around 10 ms (5% of the total depolarization time). Finally, we discussed the potential translation of such work to clinical data and pathological hearts.

euHeart: personalized and integrated cardiac care using patient-specific cardiovascular modelling.

The loss of cardiac pump function accounts for a significant increase in both mortality and morbidity in Western society, where there is currently a one in four lifetime risk, and costs associated with acute and long-term hospital treatments are accelerating. The significance of cardiac disease has motivated the application of state-of-the-art clinical imaging techniques and functional signal analysis to aid diagnosis and clinical planning. Measurements of cardiac function currently provide high-resolution datasets for characterizing cardiac patients. However, the clinical practice of using population-based metrics derived from separate image or signal-based datasets often indicates contradictory treatments plans owing to inter-individual variability in pathophysiology. To address this issue, the goal of our work, demonstrated in this study through four specific clinical applications, is to integrate multiple types of functional data into a consistent framework using multi-scale computational modelling.

Coupled personalization of cardiac electrophysiology models for prediction of ischaemic ventricular tachycardia.

In order to translate the important progress in cardiac electrophysiology modelling of the last decades into clinical applications, there is a requirement to make macroscopic models that can be used for the planning and performance of the clinical procedures. This requires model personalization, i.e. estimation of patient-specific model parameters and computations compatible with clinical constraints. Simplified macroscopic models can allow a rapid estimation of the tissue conductivity, but are often unreliable to predict arrhythmias. Conversely, complex biophysical models are more complete and have mechanisms of arrhythmogenesis and arrhythmia sustainibility, but are computationally expensive and their predictions at the organ scale still have to be validated. We present a coupled personalization framework that combines the power of the two kinds of models while keeping the computational complexity tractable. A simple eikonal model is used to estimate the conductivity parameters, which are then used to set the parameters of a biophysical model, the Mitchell-Schaeffer (MS) model. Additional parameters related to action potential duration restitution curves for the tissue are further estimated for the MS model. This framework is applied to a clinical dataset derived from a hybrid X-ray/magnetic resonance imaging and non-contact mapping procedure on a patient with heart failure. This personalized MS model is then used to perform an in silico simulation of a ventricular tachycardia (VT) stimulation protocol to predict the induction of VT. This proof of concept opens up possibilities of using VT induction modelling in order to both assess the risk of VT for a given patient and also to plan a potential subsequent radio-frequency ablation strategy to treat VT.