Impact of different activation wavefronts on ischemic myocardial scar electrophysiological properties during high-density ventricular tachycardia mapping and ablation.

INTRODUCTION: Scar-related ventricular tachycardia (VT) usually results from an underlying reentrant circuit facilitated by anatomical and functional barriers. The later are sensitive to the direction of ventricular activation wavefronts. We aim to evaluate the impact of different ventricular activation wavefronts on the functional electrophysiological properties of myocardial tissue. METHODS: Patients with ischemic heart disease referred for VT ablation underwent high-density mapping using Carto®3 (Biosense Webster). Maps were generated during sinus rhythm, right and left ventricular pacing, and analyzed using a new late potential map software, which allows to assess local conduction velocities and facilitates the delineation of intra-scar conduction corridors (ISCC); and for all stable VTs. RESULTS: In 16 patients, 31 high-resolution substrate maps from different ventricular activation wavefronts and 7 VT activation maps were obtained. Local abnormal ventricular activities (LAVAs) were found in VT isthmus, but also in noncritical areas. The VT isthmus was localized in areas of LAVAs overlapping surface between the different activation wavefronts. The deceleration zone location differed depending on activation wavefronts. Sixty-six percent of ISCCs were similarly identified in all activating wavefronts, but the one acting as VT isthmus was simultaneously identified in all activation wavefronts in all cases. CONCLUSION: Functional based substrate mapping may improve the specificity to localize the most arrhythmogenic regions within the scar, making the use of different activation wavefronts unnecessary in most cases.

Automatic identification of areas with low-voltage fragmented electrograms for the detection of the critical isthmus of atypical atrial flutters.

INTRODUCTION: Critical isthmuses of atypical atrial flutters (AAFLs) are usually located at slow conduction areas that exhibit fractionated electrograms. We tested a novel software, intended for integration with a commercially available navigation system, that automatically detects fractionated electrograms, to identify the critical isthmus in patients with AAFL ablation. METHODS AND RESULTS: All available patients were analyzed; 27 patients with 33 AAFLs were included. The PentaRay NAV catheter (Biosense Webster) was used for mapping. The novel software was retrospectively applied; fractionated points with duration ≥80 ms and bipolar voltage between 0.05 and 0.5 mV were highlighted on the surface of maps. In 10 randomly chosen AAFLs, an expert electrophysiologist evaluated the positive predictive value of the algorithm to detect true fractionation: 74.4%. We tested the capacity of the software to identify areas of fractionation (defined as clusters of ≥3 adjacent points with fractionation) at the critical isthmus of the AAFLs (defined using conventional mapping criteria). An area of fractionation was identified at the critical isthmus in 30 cases (91%). Globally, 144 areas of fractionation (median number per AAFL 4 [3-6]) were identified. Duration of the fractionation or the surface of the areas was not different between areas at critical isthmuses and the rest. Setting the fractionation score filter of the software in nine provided best performance. CONCLUSIONS: The novel software detected areas of fractionation at the critical isthmus in most AAFLs, which may help identify the critical isthmus in clinical practice.

Novel "late potential map" algorithm: Abnormal potentials and scar channels detection for ventricular tachycardia ablation.

BACKGROUND: Automated systems for substrate mapping in the context of ventricular tachycardia (VT) ablation may annotate far-field rather than near-field signals, rendering the resulting maps hard to interpret. Additionally, quantitative assessment of local conduction velocity (LCV) remains an unmet need in clinical practice. We evaluate whether a new late potential map (LPM) algorithm can provide an automatic and reliable annotation and localized bipolar voltage measurement of ventricular electrograms (EGMs) and if LCV analysis allows recognizing intrascar conduction corridors acting as VT isthmuses. METHODS: In 16 patients referred for scar-related VT ablation, 8 VT activation maps and 29 high-resolution substrate maps from different activation wavefronts were obtained. In offline analysis, the LPM algorithm was compared to manually annotated substrate maps. Locations of the VT isthmuses were compared with the corresponding substrate maps in regard to LCV. RESULTS: The LPM algorithm had an overall/local abnormal ventricular activity (LAVA) annotation accuracy of 94.5%/81.1%, which compares to 83.7%/23.9% for the previous wavefront algorithm. The resultant maps presented a spatial concordance of 88.1% in delineating regions displaying LAVA. LAVA median localized bipolar voltage was 0.22 mV, but voltage amplitude assessment had modest accuracy in distinguishing LAVA from other abnormal EGMs (area under the curve: 0.676; p < .001). LCV analysis in high-density substrate maps identified a median of two intrascar conduction corridors per patient (interquartile range: 2-3), including the one acting as VT isthmus in all cases. CONCLUSION: The new LPM algorithm and LCV analysis may enhance substrate characterization in scar-related VT.

Activation Mapping With Integration of Vector and Velocity Information Improves the Ability to Identify the Mechanism and Location of Complex Scar-Related Atrial Tachycardias.

BACKGROUND: Activation mapping of scar-related atrial tachycardias (ATs) can be difficult to interpret because of inaccurate time annotation of complex electrograms and passive diastolic activity. We examined whether integration of a vector map can help to describe patterns of propagation to better explain the mechanism and location of ATs. METHODS: The investigational mapping algorithm calculates vectors and applies physiological constraints of electrical excitation in human atrial tissue to determine the arrhythmia source and circuit. Phase I consisted of retrospective evaluation in 35 patients with ATs. Phase II consisted of prospective validation in 20 patients with ATs. Macroreentry was defined as a continuous propagation in a circular path >30 mm; localized reentry was defined as a circular path ≤30 mm; a focal source had a centrifugal spread from a point source. RESULTS: In phase I, standard activation mapping identified 28 of 40 ATs (70%): 25 macroreentry and 3 focal tachycardias. In the remaining 12 ATs, the mechanism and location could not be identified by activation and required entrainment or empirical ablation for termination (radiofrequency time, 17.3±6.6 minutes). In comparison, the investigational algorithm identified 37 of 40 (92.5%) ATs, including 5 macroreentry, 3 localized reentry, and 1 focal AT not identified by standard mapping. It also predicted the successful termination site of all 37 of 40 ATs. In phase II, the investigational algorithm identified 12 macroreentry, 6 localized reentry, and 2 focal tachycardias that all terminated with limited ablation (3.2±1.7 minutes). It identified 3 macroreentry, 3 localized reentry, and 1 focal AT not well characterized by standard mapping. The diagnosis of localized reentry was supported by highly curved vectors, resetting with increasing curve and termination with limited ablation (22±6 s). CONCLUSIONS: Activation mapping integrating vectors can help determine the arrhythmia mechanism and identify its critical components. It has particular value for identifying complex macroreentrant circuits and for differentiating a focal source from a localized reentry.