Evidence map›Paper›PMID 40150669›Full record

ArticleChildren (Basel, Switzerland)2025

Application of Radiomics in Predicting the Prognosis of Medulloblastoma in Children.

Jiashu Chen, Wei Yang, Zesheng Ying, Ping Yang, Yuting Liang, Chen Liang, Baojin Shang, Hong Zhang, Yingjie Cai, Xiaojiao Peng and 3 more

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In one paragraph

Article in Children (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Jiashu ChenDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
Wei YangDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
Zesheng YingDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
Ping YangDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
Yuting LiangDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
Chen LiangDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
Baojin ShangDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
Hong ZhangImage Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
Yingjie CaiDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
Xiaojiao PengDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
Hailang SunDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
Wenping MaDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
Ming GeDepartment of Neurosurgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.ORCID 0000-0002-4476-4331

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeMedulloblastoma (MB) represents the predominant intracranial neoplasm observed in pediatric populations, characterized by a five-year survival rate ranging from 60% to 80%. Anticipating the prognostic outcome of medulloblastoma in children prior to surgical intervention holds paramount significance for informing treatment modalities effectively. Radiomics has emerged as a pervasive tool in both prognostic anticipation and therapeutic management across diverse tumor spectra. This study aims to develop a radiomics-based prediction model for the prognosis of children with MB and to validate the contribution of radiomic features in predicting the prognosis of MB when combined with clinical features. MATERIALS AND

methodsPatients diagnosed with medulloblastoma at our hospital from December 2012 to March 2022 were randomly divided into a training cohort (

resultsA total of 81 children were included in this study. A total of five prognostic radiomic features were selected. The radiomics model could discriminate different risk hierarchies with good performance power in the training and testing datasets (training set

conclusionsRadiomic features based on T1-weighted imaging have predictive value for pediatric medulloblastoma. Radiomics has incremental value in predicting the prognosis of MB, and clinical-radiomics models have a better predictive effect than clinical models.

Indexed as

clinical-radiomics modelmedulloblastomaprognosisradiomics features

Identifiers

PMID40150669
PMCPMC11940979

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