Multielectrode Unipolar Voltage Mapping and Electrogram Morphology to Identify Post-Infarct Scar Geometry: Validation by Histology

VT ablation based on CT imaging substrate visualization: results from a large cohort of ischemic and non-ischemic cardiomyopathy patients

INTRODUCTION

The eradication of ventricular tachycardia (VT) isthmus sites constitutes the minimal procedural endpoint for VT ablation procedures. Contemporary high-resolution computed tomography (CT) imaging, in combination with computer-assisted analysis and segmentation of CT data, facilitates targeted elimination of VT isthmi. In this context, inHEART offers digitally rendered three-dimensional (3D) cardiac models which allow preoperative planning for VT ablations in ischemic and non-ischemic cardiomyopathies. To date, almost no data have been collected to compare the outcomes of VT ablations utilizing inHEART with those of traditional ablation approaches.

METHODS

The presented data are derived from a retrospective analysis of n = 108 patients, with one cohort undergoing VT ablation aided by late-enhancement CT and subsequent analysis and segmentation by inHEART, while the other cohort received ablation through conventional methods like substrate mapping and activation mapping. The ablations were executed utilizing a 3D mapping system (Carto3), with the mapping generated via the CARTO® PENTARAY™ NAV catheter and subsequently merged with the inHEART model, if available.

RESULTS

Results showed more successful outcome of ablations for the inHEART group with lower VT recurrence (27% vs. 42%, p < 0.06). Subsequent analyses revealed that patients with ischemic cardiomyopathies appeared to derive a significant benefit from inHEART-assisted VT ablation procedures, with a higher rate of successful ablation (p = 0.05).

CONCLUSION

Our findings indicate that inHEART-guided ablation is associated with reduced VT recurrence compared to conventional procedures. This suggests that employing advanced imaging and computational modeling in VT ablation may be valuable for VT recurrences.

Whole-Heart Histological and Electroanatomic Assessment of Postinfarction Cardiac Magnetic Resonance Imaging Scar and Conducting Channels

BACKGROUND

Cardiac magnetic resonance imaging (CMR)-defined ventricular scar and anatomic conduction channels (CMR-CCs) offer promise in delineating ventricular tachycardia substrate. No studies have validated channels with coregistered histology, nor have they ascertained the histological characteristics of deceleration zones (DZs) within these channels. We aimed to validate CMR scar and CMR-CCs with whole-heart histology and electroanatomic mapping in a postinfarction model.

METHODS

Five sheep underwent anteroseptal infarction. CMR (116±20 days post infarct) was postprocessed using ADAS-3D, varying pixel intensity thresholds (5545, 6040, 6535, and 7030). DZs were identified by electroanatomic mapping (129±12 days post infarct). Explanted hearts were sectioned and stained with Picrosirius red, and whole-heart histopathologic shells were generated. Scar topography as well as percentage fibrosis, adiposity, and remaining viable myocardium within 3 mm histological biopsies and within CMR-CCs were determined.

RESULTS

Using the standard 6040 thresholding, CMR had 83.8% accuracy for identifying histological scar in the endocardium (κ, 0.666) and 61.4% in the epicardium (κ, 0.276). Thirty-seven CMR-CCs were identified by varying thresholding; 23 (62%) were unique. DZs colocalized to 19 of 23 (83%) CMR-CCs. Twenty (87%) CMR-CCs were histologically confirmed. Within-channel histological fibrosis did not differ by the presence of DZs (P=0.242). Within-channel histological adiposity was significantly higher at sites with versus without DZs (24.1% versus 8.3%; P<0.001).

CONCLUSIONS

Postprocessed CMR-derived scars and channels were validated by histology and electroanatomic mapping. Regions of CMR-CCs at sites of DZs had higher adiposity but similar fibrosis than regions without DZs, suggesting that lipomatous metaplasia may contribute to arrhythmogenicity of postinfarction scar.

Electroanatomical Conduction Characteristics of Pig Myocardial Tissue Derived from High-Density Mapping

BACKGROUND

Ultra-high-density mapping systems allow more precise measurement of the heart chambers at corresponding conduction velocities (CVs) and voltage amplitudes (VAs). Our aim for this study was to define and compare a basic value set for unipolar CV and VA in all four heart chambers and their separate walls in healthy, juvenile porcine hearts using ultra-high-density mapping.

METHODS

We used the Rhythmia Mapping System to create electroanatomical maps of four pig hearts in sinus rhythm. CVs and VAs were calculated for chambers and wall segments with overlapping circular areas (radius of 5 mm).

RESULTS

We analysed 21 maps with a resolution of 1.4 points/mm2. CVs were highest in the left atrium (LA), followed by the left ventricle (LV), right ventricle (RV), and right atrium (RA). As for VA, LV was highest, followed by RV, LA, and RA. The left chambers had a higher overall CV and VA than the right. Within the chambers, CV varied more in the right than in the left chambers, and VA varied in the ventricles but not in the atria. There was a slightly positive correlation between CVs and VAs at velocity values of <1.5 m/s.

CONCLUSIONS

In healthy porcine hearts, the left chambers showed higher VAs and CVs than the right. CV differs mainly within the right chambers and VA differs only within the ventricles. A slightly positive linear correlation was found between slow CVs and low VAs.

Differences in atrial substrate localization using late gadolinium enhancement-magnetic resonance imaging, electrogram voltage, and conduction velocity: a cohort study using a consistent anatomical reference frame in patients with persistent atrial fibrillation

AIMS

Electro-anatomical voltage, conduction velocity (CV) mapping, and late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) have been correlated with atrial cardiomyopathy (ACM). However, the comparability between these modalities remains unclear. This study aims to (i) compare pathological substrate extent and location between current modalities, (ii) establish spatial histograms in a cohort, (iii) develop a new estimated optimized image intensity threshold (EOIIT) for LGE-MRI identifying patients with ACM, (iv) predict rhythm outcome after pulmonary vein isolation (PVI) for persistent atrial fibrillation (AF).

METHODS AND RESULTS

Thirty-six ablation-naive persistent AF patients underwent LGE-MRI and high-definition electro-anatomical mapping in sinus rhythm. Late gadolinium enhancement areas were classified using the UTAH, image intensity ratio (IIR >1.20), and new EOIIT method for comparison to low-voltage substrate (LVS) and slow conduction areas <0.2 m/s. Receiver operating characteristic analysis was used to determine LGE thresholds optimally matching LVS. Atrial cardiomyopathy was defined as LVS extent ≥5% of the left atrium (LA) surface at <0.5 mV. The degree and distribution of detected pathological substrate (percentage of individual LA surface are) varied significantly (P < 0.001) across the mapping modalities: 10% (interquartile range 0-14%) of the LA displayed LVS <0.5 mV vs. 7% (0-12%) slow conduction areas <0.2 m/s vs. 15% (8-23%) LGE with the UTAH method vs. 13% (2-23%) using IIR >1.20, with most discrepancies on the posterior LA. Optimized image intensity thresholds and each patient's mean blood pool intensity correlated linearly (R2 = 0.89, P < 0.001). Concordance between LGE-MRI-based and LVS-based ACM diagnosis improved with the novel EOIIT applied at the anterior LA [83% sensitivity, 79% specificity, area under the curve (AUC): 0.89] in comparison to the UTAH method (67% sensitivity, 75% specificity, AUC: 0.81) and IIR >1.20 (75% sensitivity, 62% specificity, AUC: 0.67).

CONCLUSION

Discordances in detected pathological substrate exist between LVS, CV, and LGE-MRI in the LA, irrespective of the LGE detection method. The new EOIIT method improves concordance of LGE-MRI-based ACM diagnosis with LVS in ablation-naive AF patients but discrepancy remains particularly on the posterior wall. All methods may enable the prediction of rhythm outcomes after PVI in patients with persistent AF.