Abstract：
BACKGROUND: The advent of image-guided radiation therapy (IGRT) has recently changed the workflow of radiation treatments by ensuring highly collimated treatments. Artificial intelligence (AI) and radiomics are tools that have shown promising results for diagnosis, treatment optimization and outcome prediction. This review aims to assess the impact of AI and radiomics on modern IGRT modalities in RT.
METHODS: A PubMed/MEDLINE and Embase systematic review was conducted to investigate the impact of radiomics and AI to modern IGRT modalities. The search strategy was \"Radiomics\" AND \"Cone Beam Computed Tomography\"; \"Radiomics\" AND \"Magnetic Resonance guided Radiotherapy\"; \"Radiomics\" AND \"on board Magnetic Resonance Radiotherapy\"; \"Artificial Intelligence\" AND \"Cone Beam Computed Tomography\"; \"Artificial Intelligence\" AND \"Magnetic Resonance guided Radiotherapy\"; \"Artificial Intelligence\" AND \"on board Magnetic Resonance Radiotherapy\" and only original articles up to 01.11.2022 were considered.
RESULTS: A total of 402 studies were obtained using the previously mentioned search strategy on PubMed and Embase. The analysis was performed on a total of 84 papers obtained following the complete selection process. Radiomics application to IGRT was analyzed in 23 papers, while a total 61 papers were focused on the impact of AI on IGRT techniques.
CONCLUSIONS: AI and radiomics seem to significantly impact IGRT in all the phases of RT workflow, even if the evidence in the literature is based on retrospective data. Further studies are needed to confirm these tools\' potential and provide a stronger correlation with clinical outcomes and gold-standard treatment strategies.
METHODS: A PubMed/MEDLINE and Embase systematic review was conducted to investigate the impact of radiomics and AI to modern IGRT modalities. The search strategy was \"Radiomics\" AND \"Cone Beam Computed Tomography\"; \"Radiomics\" AND \"Magnetic Resonance guided Radiotherapy\"; \"Radiomics\" AND \"on board Magnetic Resonance Radiotherapy\"; \"Artificial Intelligence\" AND \"Cone Beam Computed Tomography\"; \"Artificial Intelligence\" AND \"Magnetic Resonance guided Radiotherapy\"; \"Artificial Intelligence\" AND \"on board Magnetic Resonance Radiotherapy\" and only original articles up to 01.11.2022 were considered.
RESULTS: A total of 402 studies were obtained using the previously mentioned search strategy on PubMed and Embase. The analysis was performed on a total of 84 papers obtained following the complete selection process. Radiomics application to IGRT was analyzed in 23 papers, while a total 61 papers were focused on the impact of AI on IGRT techniques.
CONCLUSIONS: AI and radiomics seem to significantly impact IGRT in all the phases of RT workflow, even if the evidence in the literature is based on retrospective data. Further studies are needed to confirm these tools\' potential and provide a stronger correlation with clinical outcomes and gold-standard treatment strategies.
摘要：
背景：图像引导放射治疗（IGRT）的出现最近通过确保高度准直的治疗改变了放射治疗的工作流程。人工智能（AI）和影像组学是已经显示出有希望的诊断结果的工具，治疗优化和结果预测。这篇综述旨在评估AI和影像组学对RT中现代IGRT模式的影响。
方法：进行了PubMed/MEDLINE和Embase系统综述，以研究影像组学和AI对现代IGRT模式的影响。搜索策略为“放射组学”和“锥束计算机断层扫描”；“放射组学”和“磁共振引导放射治疗”；“放射组学”和“磁共振放射治疗”；“人工智能”和“机载磁共振放射治疗”；“人工智能”和“锥束计算机断层扫描”；“人工智能”和“磁共振引导的文章”仅被认为是2022年的“磁共振辐射成像”和“磁共振成像”。
结果：使用先前提到的在PubMed和Embase上的搜索策略，共获得了402项研究。对完整选择过程后获得的总共84篇论文进行分析。23篇论文分析了影像组学在IGRT中的应用，共有61篇论文集中在人工智能对IGRT技术的影响上。
结论：AI和影像组学似乎在RT工作流程的所有阶段对IGRT产生了重大影响，即使文献中的证据是基于回顾性数据。需要进一步的研究来证实这些工具的潜力，并提供与临床结果和金标准治疗策略的更强相关性。
方法：进行了PubMed/MEDLINE和Embase系统综述，以研究影像组学和AI对现代IGRT模式的影响。搜索策略为“放射组学”和“锥束计算机断层扫描”；“放射组学”和“磁共振引导放射治疗”；“放射组学”和“磁共振放射治疗”；“人工智能”和“机载磁共振放射治疗”；“人工智能”和“锥束计算机断层扫描”；“人工智能”和“磁共振引导的文章”仅被认为是2022年的“磁共振辐射成像”和“磁共振成像”。
结果：使用先前提到的在PubMed和Embase上的搜索策略，共获得了402项研究。对完整选择过程后获得的总共84篇论文进行分析。23篇论文分析了影像组学在IGRT中的应用，共有61篇论文集中在人工智能对IGRT技术的影响上。
结论：AI和影像组学似乎在RT工作流程的所有阶段对IGRT产生了重大影响，即使文献中的证据是基于回顾性数据。需要进一步的研究来证实这些工具的潜力，并提供与临床结果和金标准治疗策略的更强相关性。
