- 著者
- Hidehiro Iwakawa Masateru Takigawa Junji Yamaguchi Claire A Martin Masahiko Goya Tasuku Yamamoto Miki Amemiya Takashi Ikenouchi Miho Negishi Iwanari Kawamura Kentaro Goto Takatoshi Shigeta Takuro Nishimura Tomomasa Takamiya Susumu Tao Shinsuke Miyazaki Hiroyuki Watanabe Tetsuo Sasano
- 出版者
- The Japanese Circulation Society
- 雑誌
- Circulation Journal (ISSN:13469843)
- 巻号頁・発行日
- pp.CJ-23-0574, (Released:2023-10-27)
- 参考文献数
- 28
- 被引用文献数
- 1
Background: For lesion size prediction, each input parameter, including ablation energy (AE), and output parameter, such as impedance, is individually used. We hypothesize that using both parameters simultaneously may be more optimal.Methods and Results: Radiofrequency applications at a range of power (30–50 W), contact force (10 g and 20 g), duration (10–60 s), and catheter orientation with normal saline (NS)- or half-normal saline (HNS)-irrigation were performed in excised porcine hearts. The correlations, with lesion size of AE, absolute impedance drop (∆Imp-drop), relative impedance drop (%Imp-drop), and AE*%Imp-drop were examined. Lesion size was analyzed in 283 of 288 lesions (NS-irrigation, n=142; HNS-irrigation, n=141) without steam pops. AE*%Imp-drop consistently showed the strongest correlations with lesion maximum depth (NS-irrigation, ρ=0.91; HNS-irrigation, ρ=0.94), surface area (NS-irrigation, ρ=0.87; HNS-irrigation, ρ=0.86), and volume (NS-irrigation, ρ=0.94; HNS-irrigation, ρ=0.94) compared with the other parameters. Moreover, compared with AE alone, AE*%Imp-drop significantly improved the strength of correlation with lesion maximum depth (AE vs. AE*%Imp-drop, ρ=0.83 vs. 0.91, P<0.01), surface area (ρ=0.73 vs. 0.87, P<0.01), and volume (ρ=0.84 vs. 0.94, P<0.01) with NS-irrigation. This tendency was also observed with HNS-irrigation. Parallel catheter orientation showed a better correlation with lesion depth and volume using ∆Imp-drop, %Imp-drop, and AE*%Imp-drop than perpendicular orientation.Conclusions: The combination of input and output parameters is more optimal than each single parameter for lesion prediction.