Evidence map›Paper›PMID 42037585›Full record

Observational studyCNS neuroscience & therapeutics2026

Feasibility and Tumor Dynamics of Daily MRI-Guided Online Adaptive Radiotherapy for Brain Glioma.

Shouliang Ding, Xiumao Yin, Mengqi Sun, Hongdong Liu, Ying Wang, Biaoshui Liu, Mengke Qi, Yuchuan Zhou, Xiaojing Du, Meiling Deng and 5 more

Abstract readObservational Study
In one paragraph

Observational study in CNS neuroscience & therapeutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Trial
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Shouliang DingDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Xiumao YinCancer Center, The Tenth Affiliated Hospital, Southern Medical University (Dongguan People's Hospital), Dongguan, China.
Mengqi SunDepartment of Radiation Oncology, Shenzhen People's Hospital, Shenzhen, China.ORCID https://orcid.org/0009-0008-6543-173X
Hongdong LiuDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Ying WangDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Biaoshui LiuDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Mengke QiDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Yuchuan ZhouDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Xiaojing DuDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Meiling DengDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Wanming HuDepartment of Pathology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.ORCID https://orcid.org/0000-0002-3632-1258
Xiaoyan HuangDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Zihuang LiDepartment of Radiation Oncology, Shenzhen People's Hospital, Shenzhen, China.
Yonggao MouDepartment of Neurosurgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Yuanyuan ChenDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.ORCID https://orcid.org/0000-0002-1611-0111

Funding

Fundamental Research Funds for the Central Universities, Clinical Research 5010 Program, Sun Yat-sen University 2022008National Natural Science Foundation of China 12405409National Natural Science Foundation of China 62271475National Natural Science Foundation of China 82102877
6 · The paper itself

Abstract

backgroundMagnetic resonance image (MRI)-guided radiotherapy can optimize the therapeutic outcomes of brain glioma patients, as it adjusts to tumor changes in the course of radiation treatment. This study evaluates the dynamic changes of tumors and the feasibility of implementing MRI-guided online adaptive radiotherapy (MRIgOART) for the treatment of brain glioma. PATIENTS &

methodsThis observational prospective cohort study involved patients with brain glioma treated using 1.5 T MR-Linac from 2021 to 2023. MRIgOART can correct treatment errors and evaluate treatment response through adapt-to-position (ATP) and adapt-to-shape (ATS) strategies. Dice similarity coefficient (DSC), absolute/relative volume (Vrel), and Hausdorff distance (HD) metrics were used to quantify tumor changes. The covariables subjected to evaluation included: surgical resection extent, 1p/19q status, telomerase reverse transcriptase (TERT) mutation status, O6-methylguanine-DNA-methyltransferase (MGMT) methylation status, and isocitrate dehydrogenase (IDH) mutation status. ART and non-ART treatment plans were comparatively analyzed based on target coverage and dose constraints for normal brain tissue. The pattern of failure, as the primary endpoint, was evaluated in this study. Secondary endpoints of the study consisted of overall survival (OS) and progression-free survival (PFS), assessed according to treatment schedules.

resultsThe cohort comprised 57 patients. The patients with an interval longer than 10 days from simulation to the Fx1 exhibited more significant tumor changes (p < 0.001). The tumor volume showed a gradual reduction during the treatment, whereas the alterations in its location and shape became increasingly evident over time. Multivariate analyses identified associations between prognosis and HD, in addition to a relationship between the extent of surgical resection and DSC. ATS was utilized in 52.6% of patients at least once during treatment, with a higher frequency in TERT wild-type patients (p = 0.013). MRIgOART treatment plans achieved superior target conformality, adequate coverage, and effective sparing of OARs. High-grade glioma (HGG) patients exhibited median PFS of 13 months (95% CI, 10.2-15.8 months) and OS of 28 months (95% CI, 23.3-32.7 months). Failure analysis revealed 58.9% in-field, 17.6% marginal, and 23.5% distant recurrences, with IDH mutation status associated with failure patterns.

conclusionPreliminary findings in patients with HGG suggest a lower incidence of recurrences within the radiation field and indicate promising outcomes associated with MRIgOART. However, these observations require further validation through comparative studies.

Indexed as

Brain NeoplasmsGliomaMagnetic Resonance ImagingRadiotherapy, Image-GuidedAdultAgedCohort StudiesFeasibility StudiesFemaleHumansMaleMiddle AgedProspective StudiesTreatment Outcomeadaptive radiotherapybrain gliomafeasibilityMR‐Linactumor dynamics

Identifiers

PMID42037585
PMCPMC13112182

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.