Directed Graph Mapping for Ventricular Tachycardia: A Comparison to Established Mapping Techniques.

BACKGROUND: Understanding underlying mechanism(s) and identifying critical circuit components are fundamental to successful ventricular tachycardia (VT) ablation. Directed graph mapping (DGM) offers a novel technique to identify the mechanism and critical components of a VT circuit. OBJECTIVES: This study sought to evaluate the accuracy of DGM in VT ablation compared with traditional mapping techniques and a commercially available automated conduction velocity mapping (ACVM) tool. METHODS: Patients with structural heart disease who had undergone a VT ablation with entrainment-proven critical isthmus and a high-density electroanatomical activation map were included. Traditional mapping (TM) consisted of a combination of local activation time and entrainment mapping and was considered the gold standard for determining the VT mechanism, circuit, and isthmus location. The same local activation time values were then processed using DGM and a commercially available ACVM (Coherent Mapping, Biosense Webster) tool. The aim of this study was to compare TM vs DGM and ACVM in their ability to identify the VT mechanism, characterize the VT circuit, and locate the critical isthmus. RESULTS: Thirty-five cases were identified. TM classified the VT mechanism as focal in 7 patients and re-entrant in 28 patients. TM classified 11 VTs as single-loop re-entry, 15 as dual-loop re-entry, 1 as complex, and 1 case was indeterminant. The overall agreement between DGM and TM for determining VT mechanism and circuit type was strong (kappa value = 0.79; P < 0.01), as was the agreement between ACVM and TM (kappa value = 0.66; P < 0.01). Both DGM and ACVM identified the putative VT isthmus in 25 (89%) of the re-entrant cases. Focal activation was correctly identified by both techniques in all cases. CONCLUSIONS: DGM is a rapid automated algorithm that has a strong level of agreement with TM for manually re-annotated VT maps.

Retrospective Window of Interest Annotation Provides New Insights Into Functional Channels in Ventricular Tachycardia Substrate.

BACKGROUND: Accurate annotation of local activation time is crucial in the functional assessment of ventricular tachycardia (VT) substrate. A major limitation of modern mapping systems is the standard prospective window of interest (sWOI) is limited to 490 to 500 milliseconds, preventing annotation of very late potentials (LPs). A novel retrospective window of interest (rWOI), which allows annotation of all diastolic potentials, was used to assess the functional VT substrate. OBJECTIVES: This study sought to investigate the utility of a novel rWOI, which allows accurate visualization and annotation of all LPs during VT substrate mapping. METHODS: Patients with high-density VT substrate maps and a defined isthmus were included. All electrograms were manually annotated to latest activation using a novel rWOI. Reannotated substrate maps were correlated to critical sites, with areas of late activation examined. Propagation patterns were examined to assess the functional aspects of the VT substrate. RESULTS: Forty-eight cases were identified with 1,820 ± 826 points per map. Using the novel rWOI, 31 maps (65%) demonstrated LPs beyond the sWOI limit. Two distinct patterns of channel activation were seen during substrate mapping: 1) functional block with unidirectional conduction into the channel (76%); and 2) wave front collision within the channel (24%). In addition, a novel marker termed the zone of early and late crowding was studied in the rWOI substrate maps and found to have a higher positive predictive value (85%) than traditional deceleration zones (69%) for detecting critical sites of re-entry. CONCLUSIONS: The standard WOI of contemporary mapping systems is arbitrarily limited and results in important very late potentials being excluded from annotation. Future versions of electroanatomical mapping systems should provide longer WOIs for accurate local activation time annotation.

Functional Assessment of Ventricular Tachycardia Circuits and Their Underlying Substrate Using Automated Conduction Velocity Mapping.

OBJECTIVES: This study sought to describe the utility of automated conduction velocity mapping (ACVM) in ventricular tachycardia (VT) ablation. BACKGROUND: Identification of areas of slowed conduction velocity (CV) is critical to our understanding of VT circuits and their underlying substrate. Recently, an ACVM called Coherent Mapping (Biosense Webster Inc) has been developed for atrial mapping. However, its utility in VT mapping has not been described. METHODS: Patients with paired high-density VT activation and substrate maps were included. ACVM was applied to paired VT activation and substrate maps to assess regional CV and activation patterns. A combination of ACVM, traditional local activation time maps, electrogram analysis, and off-line calculated CV using triangulation were used to characterize zones of slowed conduction during VT and in substrate mapping. RESULTS: Fifteen patients were included in the study. In all cases, ACVM identified slow CV within the putative VT isthmus, which colocalized to the VT isthmus identified with entrainment. The dimensions of the VT isthmus with local activation time mapping were 37.8 ± 13.7 mm long and 8.7 ± 4.2 mm wide. In comparison, ACVM produced an isthmus that was shorter (length: 25.1 ± 10.6 mm; mean difference: 12.8; 95% CI: 7.5-18.0; P < 0.01) and wider (width: 18.8 ± 8.1 mm; mean difference: 10.1; 95% CI: 6.1-14.2; P < 0.01). In VT, the CV using triangulation at the entrance (8.0 ± 3.6 cm/s) and midisthmus (8.1 ± 4.3 cm/s) was not significantly different (P = 0.92) but was significantly faster at the exit (16.2 ± 9.7 cm/s; P < 0.01). In the paired substrate analysis, traditional local activation time isochronal mapping identified 6.3 ± 2.0 deceleration zones. In contrast, ACVM identified a median of 0 deceleration zones (IQR: 0-1; P < 0.01). CONCLUSIONS: ACVM is a novel complementary tool that can be used to accurately resolve complex VT circuits and identify slow conduction zones in VT but has limited accuracy in identifying slowed conduction during substrate-based mapping.