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Abstract
ABSTRACT
Ventricular tachycardia (VT) is a severe arrhythmia commonly treated with implantable cardioverter defibrillators, antiarrhythmic drugs and catheter ablation (CA). Although CA is effective in reducing recurrent VT, its impact on survival remains uncertain, especially in patients with extensive scarring. Stereotactic arrhythmia radioablation (STAR) has emerged as a novel treatment for VT in patients unresponsive to CA, leveraging techniques from stereotactic body radiation therapy used in cancer treatments. Recent clinical trials and case series have demonstrated the short-term efficacy and safety of STAR, although long-term outcomes remain unclear. Imaging techniques, such as electroanatomical mapping, contrast-enhanced magnetic resonance imaging and nuclear imaging, play a crucial role in treatment planning by identifying VT substrates and guiding target delineation. However, challenges persist owing to the complex anatomy and variability in target volume definitions. Advances in imaging and artificial intelligence are expected to improve the precision and efficacy of STAR. The exact mechanisms underlying the antiarrhythmic effects of STAR, including potential fibrosis and improvement in cardiac conduction, are still being explored. Despite its potential, STAR should be cautiously applied in prospective clinical trials, with a focus on optimizing dose delivery and understanding long-term outcomes. Collaborative efforts are necessary to standardize treatment strategies and enhance the quality of life for patients with refractory VT.
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1 Department of Radiology, Nagoya University Graduate School of Medicine , 65 Tsurumaicho, Showa-ku, Nagoya, Aichi, 466-8550 , Japan
2 Department of Cardiology, Nagoya University Graduate School of Medicine , 65 Tsurumaicho, Showa-ku, Nagoya, Aichi, 466-8550 , Japan
3 Department of Diagnostic Radiology, Hiroshima University , 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551 , Japan
4 Department of Diagnostic Imaging , Faculty of Medicine, Hokkaido University , Kita15, Nishi7, Kita-Ku, Sapporo, Hokkaido, 060-8638 , Japan
5 Department of Radiology, University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655 , Japan
6 Department of Artificial Intelligence , Graduate School of Medicine, Osaka Metropolitan University , 1-4-3, Asahi-machi, Abeno-ku, Osaka, 545-8585 , Japan
7 Department of Radiology , Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University , 2-5-1 Shikata-cho, Kitaku, Okayama, 700-8558 , Japan
8 Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine , 54 Shogoin Kawaharacho, Sakyo-ku, Kyoto, 606-8507 , Japan
9 Department of Diagnostic Radiology, Tokyo Medical and Dental University , 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510 , Japan
10 Department of Radiology, Keio University School of Medicine , 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582 , Japan
11 Medical Data Science Course, Shinshu University School of Medicine , 3-1-1 Asahi, Matsumoto, Nagano, 390-8621 , Japan
12 Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital , Kita15, Nishi7, Kita-Ku, Sapporo, Hokkaido, 060-8638 , Japan
13 Department of Radiology, Osaka University Graduate School of Medicine , 2-2 Yamadaoka, Suita, Osaka, 565-0871 , Japan
14 Department of Diagnostic Radiology, Kumamoto University Graduate School of Medicine , 1-1-1 Honjo, Chuo-ku, Kumamoto, 860-8556 , Japan
15 Department of Radiology, Kobe University Graduate School of Medicine , 7-5-1 Kusunoki-cho,Chuo-ku, Kobe, Hyogo, 650-0017 , Japan
16 Department of Radiology, Juntendo University Graduate School of Medicine , 2-1-1 Hongo, Bunkyo-ku, Tokyo , Japan