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Research progress on multimodal MRI and radiomics for predicting postoperative recurrence/progression in meningioma
SI Yihua  HAN Tao  SUN Jiachen  ZHOU Junlin 

Cite this article as: SI Y H, HAN T, SUN J C, et al. Research progress on multimodal MRI and radiomics for predicting postoperative recurrence/progression in meningioma[J]. Chin J Magn Reson Imaging, 2026, 17(10): 188-194, 224. DOI:10.12015/issn.1674-8034.2026.10.023.


[Abstract] Meningioma is one of the most common primary central nervous system tumors. Although the majority are benign, a considerable proportion of patients still experience postoperative recurrence/progression (R/P), which significantly impacts long-term surveillance, prognostic assessment, and decisions regarding adjuvant radiotherapy and subsequent treatment strategies. Multimodal magnetic resonance imaging (MRI) can capture the biological characteristics and microenvironmental information of tumors from multiple perspectives, including morphology, water diffusion, perfusion, metabolism, and protein content. In recent years, radiomics—a representative artificial intelligence technique in medical imaging—has enabled the extraction of high-dimensional, quantitative features from routine imaging data, opening new avenues for noninvasive prediction of meningioma R/P. In this review, we summarize recent advances in the application of conventional MRI features, multimodal MRI, and radiomics for predicting postoperative R/P in meningiomas. Additionally, we explore the emerging potential of deep learning and habitat analysis as complementary approaches in this field. We also critically evaluate the achievements and limitations of existing studies and discuss future directions. This review is intended to provide a reference for individualized postoperative risk stratification and precision therapeutic decision-making in meningioma patients.
[Keywords] meningioma；recurrence/progression；multimodal magnetic resonance imaging；radiomics；prognosis

SI Yihua1, 2, 3, 4   HAN Tao1, 2, 3, 4   SUN Jiachen1, 2, 3, 4   ZHOU Junlin1, 3, 4*  

1 Department of Radiology, the Second Hospital of Lanzhou University, Lanzhou 730000, China

2 Second Clinical School of Lanzhou University, Lanzhou 730000, China

3 Key Laboratory of Medical Imaging of Gansu Province Lanzhou 730000, China

4 Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730030, China

Corresponding author: ZHOU J L, E-mail: ery_zhoujl@lzu.edu.cn.

Conflicts of interest   None.

Received  2026-05-13
Accepted  2026-09-20
DOI: 10.12015/issn.1674-8034.2026.10.023
Cite this article as: SI Y H, HAN T, SUN J C, et al. Research progress on multimodal MRI and radiomics for predicting postoperative recurrence/progression in meningioma[J]. Chin J Magn Reson Imaging, 2026, 17(10): 188-194, 224. DOI:10.12015/issn.1674-8034.2026.10.023.

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