Papadakos Stavros P, Argyrou Alexandra, Karniadakis Ioannis, Theocharopoulos Charalampos, Katsaros Ioannis, Machairas Nikolaos, Vlachogiannakos Jiannis, Theocharis Stamatios
First Department of Pathology, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.
First Academic Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Laiko", 11527 Athens, Greece.
Cancers (Basel). 2025 Aug 30;17(17):2855. doi: 10.3390/cancers17172855.
: Computed tomography (CT)-based radiomic analysis is an emerging technique that enables non-invasive assessment of tumor characteristics. In gastrointestinal stromal tumors (GISTs), radiomics may reflect biological behavior such as proliferative activity, often indicated by Ki-67 expression. To our knowledge, this is the first systematic review and meta-analysis synthesizing evidence on the ability of CT radiomics to predict the Ki-67 index in GISTs, addressing an important gap in the literature. : A systematic review and meta-analysis were conducted following PRISMA guidelines to evaluate the predictive performance of CT radiomics for Ki-67 expression in GISTs. A literature search of PubMed, Scopus, Science Direct, and the Cochrane Library was performed up to December 2024 using predefined terms. Extracted data included study design, patient demographics, imaging protocols, radiomic features, and diagnostic performance. Study quality was assessed using the QUADAS-2 tool. A random-effects meta-analysis summarized the pooled area under the ROC curve (AUC), sensitivity, and specificity. Subgroup and sensitivity analyses explored heterogeneity sources. Publication bias was assessed using Egger's test and funnel plots. : Six studies involving 1632 patients were included. The pooled sensitivity and specificity for predicting Ki-67 expression were 0.71 and 0.76, respectively, with a summary AUC of 0.79. Subgroup analyses showed consistent results across different imaging protocols and radiomic feature sets, though the Ki-67 cutoff (8% vs. 10%) affected diagnostic performance. Moderate heterogeneity and potential publication bias in specificity were observed. : CT-based radiomics demonstrates moderate accuracy for non-invasively predicting Ki-67 index in GISTs. While not a substitute for histology, it may support personalized preoperative planning and guide future immunotherapy strategies. In the future, radiomic signatures-particularly when integrated with molecular or immune-related biomarkers-could help refine patient selection and monitoring strategies for emerging therapies, including immunotherapy.
基于计算机断层扫描（CT）的放射组学分析是一种新兴技术，能够对肿瘤特征进行非侵入性评估。在胃肠道间质瘤（GIST）中，放射组学可能反映诸如增殖活性等生物学行为，通常由Ki-67表达来指示。据我们所知，这是第一项系统评价和荟萃分析，综合了关于CT放射组学预测GIST中Ki-67指数能力的证据，填补了文献中的一个重要空白。
按照PRISMA指南进行了系统评价和荟萃分析，以评估CT放射组学对GIST中Ki-67表达的预测性能。截至2024年12月，使用预定义术语在PubMed、Scopus、Science Direct和Cochrane图书馆进行了文献检索。提取的数据包括研究设计、患者人口统计学、成像方案、放射组学特征和诊断性能。使用QUADAS-2工具评估研究质量。随机效应荟萃分析总结了汇总的ROC曲线下面积（AUC）、敏感性和特异性。亚组分析和敏感性分析探讨了异质性来源。使用Egger检验和漏斗图评估发表偏倚。
纳入了六项涉及1632例患者的研究。预测Ki-67表达的汇总敏感性和特异性分别为0.71和0.76，汇总AUC为0.79。亚组分析显示，尽管Ki-67临界值（8%对10%）影响诊断性能，但在不同成像方案和放射组学特征集之间结果一致。观察到中度异质性和特异性方面的潜在发表偏倚。
基于CT的放射组学在非侵入性预测GIST中Ki-67指数方面显示出中等准确性。虽然不能替代组织学，但它可能支持个性化的术前规划并指导未来的免疫治疗策略。未来，放射组学特征——特别是与分子或免疫相关生物标志物整合时——可能有助于优化患者选择和新兴疗法（包括免疫治疗）的监测策略。
