Pulmonary veins anatomical determinants of cooling kinetics during second‐generation cryoballoon ablation

Abstract

Aim The aim of the study was to investigate the role of anatomical characteristics of the pulmonary veins (PVs) determining cooling kinetics during second‐generation cryoballoon ablation (CbA). Methods and Results we enrolled all consecutive patients who underwent CbA for symptomatic atrial fibrillation in our center from January 2019 to March 2019. All patients had complete computed tomography scans of the heart before the ablation. Anatomical characteristics were tested for prediction of a nadir temperature (NT) ≤ −48°C. Significant differences were noted among PV max diameter (20.8 ± 2.8 vs 18.5 ± 2.5 mm; P < .001); PV minimum diameter (15.2 ± 3.0 vs 13.0 ± 3.1 mm; P < .001); PV area (268.1 ± 71.9 vs 206.2 ± 58.7 mm2; P < .001); PV ovality (1.4 ± 0.3 vs 1.5 ± 0.3; P = .005); and PV trunk length (27.4 ± 7.4 vs 21.3 ± 6.5 mm; P < .001). A scoring system was created by assigning one point each ranging from 0 (best anatomical combination) to 5. In the group with a score of 0, 94.0% of the CbA could reach a NT ≤ −48°C whereas with a score of 5, only 29.0% (P < .001). Left superior pulmonary vein with short trunk length and acute angle of PV branch was significantly associated with warmer NT (11.8% satisfactory CbA; P = .003). Regarding right inferior pulmonary vein, trunk length (P = .004), maximum diameter (P = .044), and transverse angle (P = .008) were independently associated with good NT. Conclusion Anatomical PV features are associated with cooling kinetics and an anatomical score could predict lower NT during second‐generation CbA. Specific characteristics were identified for inferior PV. Although heart imaging is not mandatory prior CbA, it can be a useful tool to predict cooling kinetics.

Procedural performance between two cryoballoon systems for ablation of atrial fibrillation depends on pulmonary vein anatomy

“…It was defined as the distance between PV ostium and the first branch leaving the vein and was expressed in millimeter. Using these parameters, an anatomical performance score was evaluated for each vein as described earlier 14 . Briefly, the score was calculated by assigning one point for each of the following anatomical characteristics: PVd max ≤19.5 mm; PVd min ≤14.0; PV area ≤ 240 mm 2 ; PV trunk length ≤ 24.0 mm; and PV ovality ≥1.45.…”

“…The aim of the present study was to compare the biophysical parameters as well as complications and outcome to the established Arctic Front Advance Pro™ (AFAP, Medtronic) ablation system. Pulmonary vein (PV) anatomy can affect cooling kinetics and CB ablation outcome 14–17 . A recent study demonstrated an association between cross‐sectional orifice area of the superior PVs and outcome after CB ablation in patients with paroxysmal AF 9 .…”

“…Normal PV anatomy was associated with a significantly improved outcome for both catheter systems 9 . We addressed the influence of various PV anatomical characteristics on the cooling kinetics of both cryoablation systems by applying an established PV anatomy scoring system to preprocedural magnetic resonance (MR) angiography data 14 …”

Impact of pulmonary vein ovality index on cooling kinetics and acute success of atrial fibrillation ablation with the third-generation cryoballoon catheter

“…Borio et al confirmed that PV diameters, area of the ostium, ovality and trunk length were associated with temperatures achieved during CBA. They emphasize the cumulative role of these parameters (put together in a score) to predict satisfactory cryokinetics [34]. Some of these observations were confirmed in the study published by Chen et al, who reported an association between the lowest temperature achieved (T nadir ) and PV ostial diameter, but not shape [35].…”

Variations in human pulmonary vein ostia morphology: A systematic review with meta‐analysis

“…Data on ostial area were extracted from 18 studies that matched the inclusion criteria (Borio et al, 2020; Choi et al, 2005; Chu et al, 2011; Clarke et al, 2021; Fodi et al, 2013; Hamdan et al, 2009; Hauser et al, 2015; Kajiyama et al, 2017; Kim et al, 2005; Krum et al, 2013; Lambert et al, 2018; Manghat et al, 2012; McLellan et al, 2014; Polaczek et al, 2019; Pontone et al, 2015; Rustogi et al, 2015; Shi et al, 2017; Tsao et al, 2005). The baseline characteristics of each analyzed study are collected in Table 6.…”