Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Surgery, Cancer Center Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands.
Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Surgery, Cancer Center Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands.
Surg Oncol. 2021 Sep;38:101578. doi: 10.1016/j.suronc.2021.101578. Epub 2021 Apr 15.
To better select patients with colorectal liver metastases (CRLM) for an optimal selection of treatment strategy (i.e. local, systemic or combined treatment) new prognostic models are warranted. In the last decade, radiomics has emerged as a field to create predictive models based on imaging features. This systematic review aims to investigate the current state and potential of radiomics to predict clinical outcomes in patients with CRLM.
A comprehensive literature search was conducted in the electronic databases of PubMed, Embase, and Cochrane Library, according to PRISMA guidelines. Original studies reporting on radiomics predicting clinical outcome in patients diagnosed with CRLM were included. Clinical outcomes were defined as response to systemic treatment, recurrence of disease, and survival (overall, progression-free, disease-free). Primary outcome was the predictive performance of radiomics. A narrative synthesis of the results was made. Methodological quality was assessed using the radiomics quality score.
In 11 out of 14 included studies, radiomics was predictive for response to treatment, recurrence of disease, survival, or a combination of outcomes. Combining clinical parameters and radiomic features in multivariate modelling often improved the predictive performance. Different types of individual features were found prognostic. Noticeable were the contrary levels of heterogeneous and homogeneous features in patients with good response. The methodological quality as assessed by the radiomics quality score varied considerably between studies.
Radiomics appears a promising non-invasive method to predict clinical outcome and improve personalized decision-making in patients with CRLM. However, results were contradictory and difficult to compare. Standardized prospective studies are warranted to establish the added value of radiomics in patients with CRLM.
为了更好地选择结直肠癌肝转移（CRLM）患者，以优化治疗策略的选择（即局部、全身或联合治疗），需要新的预后模型。在过去十年中，放射组学已成为一种基于影像学特征创建预测模型的领域。本系统评价旨在调查放射组学预测 CRLM 患者临床结局的现状和潜力。
根据 PRISMA 指南，在 PubMed、Embase 和 Cochrane 图书馆的电子数据库中进行了全面的文献检索。纳入了报告放射组学预测 CRLM 患者临床结局的原始研究。临床结局定义为系统治疗反应、疾病复发和生存（总生存、无进展生存、无疾病生存）。主要结局是放射组学的预测性能。对结果进行了叙述性综合。使用放射组学质量评分评估方法学质量。
在纳入的 14 项研究中有 11 项研究表明，放射组学可预测治疗反应、疾病复发、生存或多种结局。在多变量建模中结合临床参数和放射组学特征通常可以提高预测性能。发现了不同类型的个体特征具有预后意义。值得注意的是，在反应良好的患者中，异质性和同质性特征的水平相反。根据放射组学质量评分评估的方法学质量在研究之间差异很大。
放射组学似乎是一种很有前途的非侵入性方法，可以预测 CRLM 患者的临床结局，并改善个体化决策。然而，结果存在矛盾，难以比较。需要进行标准化的前瞻性研究，以确定放射组学在 CRLM 患者中的附加价值。
