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人工智能(AI)在改进调强放疗和容积旋转调强放疗治疗计划流程中的应用:系统评价。

Artificial intelligence (AI) applications in improvement of IMRT and VMAT radiotherapy treatment planning processes: A systematic review.

机构信息

Department of Physics, University of Guilan, Rasht, Iran.

Physics Department, Imam Khomeini International University, Qazvin, Iran.

出版信息

Radiography (Lond). 2024 Oct;30(6):1530-1535. doi: 10.1016/j.radi.2024.09.049. Epub 2024 Sep 24.

Abstract

INTRODUCTION

Radiotherapy is a common option in the treatment of many types of cancer. Intensity-Modulated Radiation Therapy (IMRT) and Volumetric-Modulated Arc Therapy (VMAT) are the latest radiotherapy techniques. However, clinicians face problems due to these techniques' complexity and time-consuming planning. Various studies have pointed out the importance and role of artificial intelligence (AI) in radiotherapy and accelerating and improving its quality. This research explores different AI methods in different fields of IMRT and VMAT. This study evaluated both quantitative and qualitative methods used within the reviewed articles.

METHODS

Various articles were reviewed from Google Scholar, Science Direct, and PubMed databases between 2018 and 2024. According to PRISMA 2020 guidelines, study selection processes, screening, and inclusion and exclusion criteria were defined. The critical Appraisal Skill Program qualitative checklist tool was used for the qualitative evaluation of articles.

RESULTS

26 articles met the inclusion among the 33 articles obtained. The search procedure was displayed using the PRISMA flow diagram. The evaluation of the articles shows the automation of various treatment planning processes by AI methods and their better performance than traditional methods. The qualitative evaluation of studies has demonstrated the high quality of all studies. The lowest score obtained from the qualitative evaluation of the article is 7 out of 9.

CONCLUSION

AI methods used in radiotherapy reduce time and increase prediction accuracy. They also work better than other methods in different areas, such as dose prediction, treatment design, and dose delivery.

IMPLICATIONS FOR PRACTICE

Healthcare providers should consider integrating artificial intelligence technologies into their practice to optimize treatment planning and enhance patient care in radiation therapy. Additionally, fostering collaboration between radiotherapy experts and artificial intelligence specialists can significantly improve the development and application of AI technologies in this field.

摘要

引言

放射治疗是治疗多种癌症的常用方法。强度调制放射治疗(IMRT)和容积调制弧形治疗(VMAT)是最新的放射治疗技术。然而,由于这些技术的复杂性和耗时的规划,临床医生面临着问题。许多研究都指出了人工智能(AI)在放射治疗中的重要性和作用,它可以加速和提高放射治疗的质量。本研究探讨了 IMRT 和 VMAT 不同领域中的不同 AI 方法。本研究评估了综述文章中使用的定量和定性方法。

方法

从 Google Scholar、Science Direct 和 PubMed 数据库中回顾了 2018 年至 2024 年的各种文章。根据 PRISMA 2020 指南,定义了研究选择过程、筛选以及纳入和排除标准。使用批判性评估技能计划定性清单工具对文章进行定性评估。

结果

在 33 篇获得的文章中,有 26 篇符合纳入标准。PRISMA 流程图显示了搜索过程。对文章的评估表明,人工智能方法可实现各种治疗计划过程的自动化,并且比传统方法表现更好。对研究的定性评估表明,所有研究的质量都很高。文章定性评估的最低得分为 9 分中的 7 分。

结论

放射治疗中使用的人工智能方法可以减少时间并提高预测准确性。它们在剂量预测、治疗设计和剂量输送等不同领域的表现也优于其他方法。

意义

医疗保健提供者应考虑将人工智能技术整合到他们的实践中,以优化治疗计划并在放射治疗中增强患者护理。此外,促进放射治疗专家和人工智能专家之间的合作,可以显著改善人工智能技术在该领域的开发和应用。

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