Aldawsari Abeer M, Al-Qaisieh Bashar, Broadbent David A, Bird David, Murray Louise, Speight Richard
Leeds Institute of Cardiovascular & Metabolic Medicine (LICAMM), University of Leeds, Woodhouse, Leeds LS2 9JT, United Kingdom.
Radiological Sciences Department, College of Applied Medical Sciences, King Saud University, Riyadh 12371, Saudi Arabia.
Phys Imaging Radiat Oncol. 2023 Jul 25;27:100476. doi: 10.1016/j.phro.2023.100476. eCollection 2023 Jul.
Improving the accuracy of brain tumour radiotherapy (RT) treatment planning is important to optimise patient outcomes. This systematic review investigates primary studies providing clinical evidence for the integration of quantitative magnetic resonance imaging (qMRI) biomarkers and MRI radiomics to optimise brain tumour RT planning.
PubMed, Scopus, Embase and Web of Science databases were searched for all years until June 21, 2022. The search identified original articles demonstrating clinical evidence for the use of qMRI biomarkers and MRI radiomics for the optimization of brain cancer RT planning. Relevant information was extracted and tabulated, including qMRI metrics and techniques, impact on RT plan optimization and changes in target and normal tissue contouring and dose distribution.
Nineteen articles met the inclusion criteria. Studies were grouped according to the qMRI biomarkers into: 1) diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI; five studies); 2) diffusion tensor imaging (DTI; seven studies); and 3) MR spectroscopic imaging (MRSI; seven studies). No relevant MRI-based radiomics studies were identified. Integration of DTI maps offers the potential for improved organs at risk (OAR) sparing. MRSI metabolic maps are a promising technique for improving delineation accuracy in terms of heterogeneity and infiltration, with OAR sparing. No firm conclusions could be drawn regarding the integration of DWI metrics and PWI maps.
Integration of qMRI metrics into RT planning offers the potential to improve delineation and OAR sparing. Clinical trials and consensus guidelines are required to demonstrate the clinical benefits of such approaches.
提高脑肿瘤放射治疗（RT）治疗计划的准确性对于优化患者治疗效果至关重要。本系统评价调查了提供定量磁共振成像（qMRI）生物标志物与MRI放射组学相结合以优化脑肿瘤RT计划的临床证据的原始研究。
检索了截至2022年6月21日的PubMed、Scopus、Embase和Web of Science数据库的历年文献。检索确定了证明使用qMRI生物标志物和MRI放射组学优化脑癌RT计划的临床证据的原始文章。提取了相关信息并制成表格，包括qMRI指标和技术、对RT计划优化的影响以及靶区和正常组织轮廓及剂量分布的变化。
19篇文章符合纳入标准。根据qMRI生物标志物将研究分为：1）扩散加权成像（DWI）和灌注加权成像（PWI；5项研究）；2）扩散张量成像（DTI；7项研究）；3）磁共振波谱成像（MRSI；7项研究）。未发现相关的基于MRI的放射组学研究。DTI图的整合为改善危及器官（OAR）的保护提供了潜力。MRSI代谢图是一种有前景的技术，可在考虑异质性和浸润的情况下提高勾画准确性，并保护OAR。关于DWI指标和PWI图的整合无法得出明确结论。
将qMRI指标整合到RT计划中有可能改善勾画并保护OAR。需要进行临床试验和制定共识指南来证明这些方法的临床益处。
