微创超声热消融技术的现状与挑战。

IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL
Shengrong Lin, Kang Chen, Jianming Wen
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引用次数: 0

摘要

图像引导的微创超声热消融由于其治疗量大、消融能量的适形传递等独特优势,在疾病治疗中得到了广泛的研究。本文介绍了该技术的最新进展,并强调了面临的挑战。首先总结了超声涂布器的设计、常用的图像引导方法和治疗部位。近十年来,尽管这项技术不断发展,但只有有限的临床转化成功。为了推动这项技术的发展,本文描述了应用器的进步、精确和实时的成像引导方法以及验证潜在治疗部位的临床有效性等方面的挑战。最后,对未来的发展方向进行了展望。展望未来,具有适形消融能力和多模态图像引导的先进涂抹器的发展将使外科医生能够进行精确、可见、可定制的治疗。 。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Current status and challenges of minimally invasive ultrasound thermal ablation technology.

Image-guided minimally invasive ultrasound thermal ablation has been widely studied for disease treatment due to its unique advantages, such as large treatment volumes and conformal delivery of ablation energy. This review presents the state-of-the-art of this technology and highlights the challenges. Ultrasound applicator designs, common image guidance methods, and treatment sites are first summarized. The recent decade has shown that despite the continuous development of this technology, only limited clinical translations have succeeded. To push this technology forward, challenges regarding the advancement of applicators, precise and real-time imaging guidance methods, and the validation of the clinical effectiveness of potential treatment sites are described. Finally, future directions are discussed. It is envisioned that future development of artificial intelligence-powered applicators with conformal ablation ability and multi-modal image guidance will enable surgeons to perform precise, visible, customizable treatment.

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来源期刊
Physics in medicine and biology
Physics in medicine and biology 医学-工程:生物医学
CiteScore
6.50
自引率
14.30%
发文量
409
审稿时长
2 months
期刊介绍: The development and application of theoretical, computational and experimental physics to medicine, physiology and biology. Topics covered are: therapy physics (including ionizing and non-ionizing radiation); biomedical imaging (e.g. x-ray, magnetic resonance, ultrasound, optical and nuclear imaging); image-guided interventions; image reconstruction and analysis (including kinetic modelling); artificial intelligence in biomedical physics and analysis; nanoparticles in imaging and therapy; radiobiology; radiation protection and patient dose monitoring; radiation dosimetry
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