通过基于放射学的定量成像分析，放射组学是一种强大的技术，可非侵入性地评估分子相关性并指导临床决策。鉴于治疗的复杂性，基于影像表型的分析对髓母细胞瘤越来越受到关注。本文对PubMed、Embase和Web of Science等数据库中发表的髓母细胞瘤放射组学分析进行了系统综述，截至2021年12月20日。我们编制了绩效数据，并使用Radiomics Quality Score（RQS）评估了文献质量。从170篇文章中，将放射组学应用于髓母细胞瘤的五个类别进行了分类：肿瘤检测和分割（21％）、跨神经系统疾病的分类（54％）、分级（14％）、特征相关性（3％）和预后（8％）。大部分研究聚焦于技术模型的开发（73％）而非临床应用（27％），并日益接受深度学习技术。研究使用私人机构（50％）或公共数据集（49％），但只有68％使用了验证数据集。对于检测和分割，放射组学模型的平均准确率为93.1±8.1％，Dice系数为88.8±7.9％。髓母细胞瘤分类的平均准确率为95.2±4.0％。肿瘤分级的平均AUC为0.85±0.08。髓母细胞瘤生物学特征的相关性平均AUC为0.89±0.07。临床过程的预后平均AUC为0.83±0.08。虽然临床研究的平均RQS高于技术研究，但总体质量较低，平均RQS为6.7±5.9（可能范围为-8至36）。由于数据的可访问性和新颖的计算方法，髓母细胞瘤放射组学已经在全球范围内得到增长。针对预后等复杂任务的可转化性需要改善质量，开发全面的患者数据集，并参与前瞻性试验。 ©作者2023。由牛津大学出版社代表神经肿瘤协会出版，版权所有。如需权限，请发送电子邮件至journals.permissions@oup.com。

Quantitative imaging analysis through radiomics is a powerful technology to non-invasively assess molecular correlates and guide clinical decision-making. There has been growing interest in image-based phenotyping for meningiomas given complexities in management.We systematically reviewed meningioma radiomics analyses published in PubMed, Embase, and Web of Science until 12/20/2021. We compiled performance data and assessed publication quality using the Radiomics Quality Score (RQS).170 publications were grouped into five categories of radiomics applications to meningiomas: tumor detection and segmentation (21%), classification across neurologic diseases (54%), grading (14%), feature correlation (3%), and prognostication (8%). A majority focused on technical model development (73%) versus clinical applications (27%), with increasing adoption of deep learning. Studies utilized either private institutional (50%) or public (49%) datasets, with only 68% using a validation dataset. For detection and segmentation, radiomic models had a mean accuracy of 93.1±8.1% and a dice coefficient of 88.8±7.9%. Meningioma classification had a mean accuracy of 95.2±4.0%. Tumor grading had a mean AUC of 0.85±0.08. Correlation with meningioma biological features had a mean AUC of 0.89±0.07.Prognostication of clinical course had a mean AUC of 0.83±0.08. While clinical studies had a higher mean RQS compared to technical studies, quality was low overall with a mean RQS of 6.7±5.9 (possible range -8 to 36).There has been global growth in meningioma radiomics, driven by data accessibility and novel computational methodology. Translatability toward complex tasks such as prognostication requires studies that improve quality, develop comprehensive patient datasets, and engage in prospective trials.© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.