Background/Objectives: Radiomics is a powerful and emerging tool in oncology, with many potential applications in predicting therapy response and prognosis. To assess the current state of radiomics in melanoma, we conducted a systematic review of its various clinical uses.Methods: We searched three databases: PubMed, Web of Science and Scopus. Each study was classified based on multiple variables, including patient number, metastasis number, therapy, imaging modality, clinical endpoints and analysis methods. The risk of bias in the systematic review was assessed with QUADAS-2, and the certainty of evidence in the meta-analysis with GRADE.Results: Forty studies involving 4673 patients and 24,561 lesions were included in the analysis. Metastatic disease was the most frequently studied clinical setting (85%). Immunotherapy was the most commonly investigated treatment, featured in half of the studies. Computed tomography (CT) was the preferred imaging modality, appearing in 17 studies (42.5%). Radiomic features were most often extracted using three-dimensional (3D) analysis (72.5%). Across 24 studies investigating the prediction of treatment response and survival, only 9 provided sufficient data (Area Under the Curve, AUC, and standard error, SE) for inclusion. A random-effects model estimated a pooled AUC of 0.83 (95% CI: 0.74 to 0.92), indicating strong discriminative performance of the radiomic models included. Low to moderate heterogeneity was observed (I2= 28.6%,p= 0.4741). No evidence of publication bias was detected (p= 0.470).Conclusions: Radiomics is increasingly being explored in the context of melanoma, particularly in advanced disease settings and in relation to immunotherapy. Most studies rely on CT imaging and 3D feature extraction, while molecular integration remains limited. Despite promising findings with strong discriminative performance in predicting therapy response, further prospective, standardized studies with higher methodological rigor are needed to validate radiomic biomarkers and integrate them into clinical decision-making.
背景/目的：影像组学是肿瘤学领域一种强大且新兴的工具，在预测治疗反应和预后方面具有诸多潜在应用。为评估影像组学在黑色素瘤研究中的现状，我们对其各类临床应用进行了系统性综述。 方法：我们检索了PubMed、Web of Science和Scopus三个数据库。每项研究根据患者数量、转移灶数量、治疗方案、成像方式、临床终点和分析方法等多个变量进行分类。系统综述的偏倚风险采用QUADAS-2工具评估，荟萃分析的证据确定性采用GRADE标准评定。 结果：共纳入40项研究，涉及4673名患者和24561个病灶。转移性疾病是最常研究的临床场景（85%）。免疫治疗是最常研究的治疗方案，出现在半数研究中。计算机断层扫描（CT）是首选的成像方式，见于17项研究（42.5%）。影像组学特征最常通过三维（3D）分析提取（72.5%）。在24项关于治疗反应和生存预测的研究中，仅9项提供了足够数据（曲线下面积AUC及标准误SE）可供纳入分析。随机效应模型估计合并AUC为0.83（95% CI：0.74-0.92），表明所纳入的影像组学模型具有强大的判别性能。观察到低至中度异质性（I²=28.6%，p=0.4741），未发现发表偏倚证据（p=0.470）。 结论：影像组学在黑色素瘤领域的研究日益增多，特别是在晚期疾病和免疫治疗相关场景中。多数研究依赖CT成像和3D特征提取，而分子整合研究仍然有限。尽管在预测治疗反应方面显示出强大的判别性能且前景可观，但仍需开展方法学更严谨的前瞻性标准化研究，以验证影像组学生物标志物并将其整合到临床决策中。
Application of Radiomics in Melanoma: A Systematic Review and Meta-Analysis
肿瘤(癌症)患者之家