Mind the gap: quantification of incomplete ablation patterns after pulmonary vein isolation using minimum path search

TL;DR

This paper introduces a semi-automatic method to quantify ablation gaps after pulmonary vein isolation using minimum path search, providing a more objective assessment of lesion completeness to improve atrial fibrillation treatment.

Contribution

The paper presents a novel gap quantification technique using minimum path search and introduces the Relative Gap Measure (RGM), enhancing accuracy and consistency over existing methods.

Findings

Left superior pulmonary vein has more gaps than the left inferior PV.

The method was validated on synthetic and clinical data from 50 patients.

Regional analysis revealed significant differences in gap distribution.

Abstract

Pulmonary vein isolation (PVI) is a common procedure for the treatment of atrial fibrillation (AF). A successful isolation produces a continuous lesion (scar) completely encircling the veins that stops activation waves from propagating to the atrial body. Unfortunately, the encircling lesion is often incomplete, becoming a combination of scar and gaps of healthy tissue. These gaps are potential causes of AF recurrence, which requires a redo of the isolation procedure. Late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) is a non-invasive method that may also be used to detect gaps, but it is currently a time-consuming process, prone to high inter-observer variability. In this paper, we present a method to semi-automatically identify and quantify ablation gaps. Gap quantification is performed through minimum path search in a graph where every node is a scar patch and the edges are the geodesic distances between patches. We propose the Relative Gap Measure (RGM) to estimate the percentage of gap around a vein, which is defined as the ratio of the overall gap length and the total length of the path that encircles the vein. Additionally, an advanced version of the RGM has been developed to integrate gap quantification estimates from different scar segmentation techniques into a single figure-of-merit. Population-based statistical and regional analysis of gap distribution was performed using a standardised parcellation of the left atrium. We have evaluated our method on synthetic and clinical data from 50 AF patients who underwent PVI with radiofrequency ablation. The population-based analysis concluded that the left superior PV is more prone to lesion gaps while the left inferior PV tends to have less gaps (p<0.05 in both cases), in the processed data. This type of information can be very useful for the optimization and objective assessment of PVI interventions.