{"title":"Prediction of MYCN amplification status in neuroblastoma using radiomics: a systematic review and meta-analysis.","authors":"Xinru Kuang, Xiaoquan Xu, Fei Teng, Dapeng Li, Feiyun Wu","doi":"10.1177/02841851251403127","DOIUrl":null,"url":null,"abstract":"<p><p>BackgroundMYCN gene amplification is associated with poor prognosis in neuroblastoma (NB) patients; however, its detection relies on the invasive fluorescence in situ hybridization technique. Radiomics can non-invasively predict MYCN gene amplification by extracting high-dimensional features from medical images.PurposeTo systematically review and meta-analyze the performance of radiomics models in predicting MYCN gene amplification status in NB patients.Material and MethodsAs of 18 March 2025, a systematic search was performed for original literature on the prediction of MYCN amplification in NB patients using radiomics models in the following databases: PubMed, Embase, Web of Science, and Cochrane Library. The quality of the literature was assessed using the QUADAS-2 and Radiomics Quality Score (RQS) tools. The meta-analysis was performed using the random-effects model.ResultsThis research ultimately included nine articles (899 patients), from which data could be extracted for both radiomics-only models and combined models that integrate radiomic features with other predictors. The radiomics-only model demonstrated pooled sensitivity of 0.85 (95% confidence interval [CI] = 0.77-0.91) and specificity of 0.86 (95% CI = 0.79-0.90), while the combined model showed a sensitivity of 0.81 (95% CI = 0.75-0.87) and specificity of 0.92 (95% CI = 0.87-0.95). Summary receiver operating characteristic (SROC) curve yielded an area under ROC curve of 0.92 ± 0.02 for the radiomics-only model and 0.94 ± 0.02 for the combined model. No evidence of publication bias was found.ConclusionsRadiomics might be one promising approach for predicting MYCN gene amplification in patients with NB.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"217-226"},"PeriodicalIF":1.2000,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta radiologica","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/02841851251403127","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/12/18 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
BackgroundMYCN gene amplification is associated with poor prognosis in neuroblastoma (NB) patients; however, its detection relies on the invasive fluorescence in situ hybridization technique. Radiomics can non-invasively predict MYCN gene amplification by extracting high-dimensional features from medical images.PurposeTo systematically review and meta-analyze the performance of radiomics models in predicting MYCN gene amplification status in NB patients.Material and MethodsAs of 18 March 2025, a systematic search was performed for original literature on the prediction of MYCN amplification in NB patients using radiomics models in the following databases: PubMed, Embase, Web of Science, and Cochrane Library. The quality of the literature was assessed using the QUADAS-2 and Radiomics Quality Score (RQS) tools. The meta-analysis was performed using the random-effects model.ResultsThis research ultimately included nine articles (899 patients), from which data could be extracted for both radiomics-only models and combined models that integrate radiomic features with other predictors. The radiomics-only model demonstrated pooled sensitivity of 0.85 (95% confidence interval [CI] = 0.77-0.91) and specificity of 0.86 (95% CI = 0.79-0.90), while the combined model showed a sensitivity of 0.81 (95% CI = 0.75-0.87) and specificity of 0.92 (95% CI = 0.87-0.95). Summary receiver operating characteristic (SROC) curve yielded an area under ROC curve of 0.92 ± 0.02 for the radiomics-only model and 0.94 ± 0.02 for the combined model. No evidence of publication bias was found.ConclusionsRadiomics might be one promising approach for predicting MYCN gene amplification in patients with NB.
mycn基因扩增与神经母细胞瘤(NB)患者预后不良相关;然而,其检测依赖于侵入性荧光原位杂交技术。放射组学可以通过从医学图像中提取高维特征,无创地预测MYCN基因扩增。目的系统回顾和荟萃分析放射组学模型在预测NB患者MYCN基因扩增状态方面的表现。材料与方法于2025年3月18日,系统检索了利用放射组学模型预测NB患者MYCN扩增的原始文献,检索数据库包括PubMed、Embase、Web of Science和Cochrane Library。使用QUADAS-2和放射组学质量评分(RQS)工具评估文献的质量。meta分析采用随机效应模型。该研究最终纳入了9篇文章(899例患者),从中可以提取仅放射组学模型和将放射组学特征与其他预测因子相结合的组合模型的数据。单纯放射组学模型的敏感性为0.85(95%可信区间[CI] = 0.77-0.91),特异性为0.86 (95% CI = 0.79-0.90),而联合模型的敏感性为0.81 (95% CI = 0.75-0.87),特异性为0.92 (95% CI = 0.87-0.95)。综合受试者工作特征(SROC)曲线显示,放射组学单一模型的ROC曲线下面积为0.92±0.02,联合模型为0.94±0.02。未发现发表偏倚的证据。结论放射组学可能是预测NB患者MYCN基因扩增的一种有前景的方法。
期刊介绍:
Acta Radiologica publishes articles on all aspects of radiology, from clinical radiology to experimental work. It is known for articles based on experimental work and contrast media research, giving priority to scientific original papers. The distinguished international editorial board also invite review articles, short communications and technical and instrumental notes.