Evidence map›Paper›PMID 41081223›Full record

ArticleQuantitative imaging in medicine and surgery2025

Predicting glioma histo-molecular diagnosis and prognosis: preoperative dynamic contrast-enhanced magnetic resonance imaging insights.

Hui Ma, Shanmei Zeng, Yingqian Huang, Dingxiang Xie, Liwei Mazu, Nengjin Zhu, Jing Zhao, Zhiyun Yang, Jianping Chu

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Article in Quantitative imaging in medicine and surgery, 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

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Hui Ma *Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Shanmei Zeng *Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Yingqian Huang *Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Dingxiang XieDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Liwei MazuDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Nengjin ZhuDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Jing ZhaoDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Zhiyun YangDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Jianping ChuDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The preoperative prediction of glioma, integrated histological/molecular classification, and prognosis are critical for personalized patient management and treatment optimization. This study aimed to explore whether preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), an advanced MRI technique, can comprehensively and noninvasively evaluate gliomas. Methods: Adult patients (June 2013 to May 2021) with diffuse glioma, retrospectively reclassified by the 2021 World Health Organization (WHO) classification criteria in this cohort study, underwent conventional and DCE-MRI examinations at our institution. Quantitative measurements, including the volume transfer constant (Ktrans), volume of extravascular extracellular space per unit volume of tissue (Ve), and rate constant of backflux (Kep), were derived from the tumor parenchyma areas. The diagnostic efficacy of glioma grading and genotyping, such as isocitrate dehydrogenase ( Results: The study population consisted of 101 participants [mean age ± standard deviation (SD), 47.05±12.81 years (72 males and 29 females)]. Tumor.Kep.max emerged as the most crucial parameter, serving as an independent protective predictor of 1p/19q-codeletion [odds ratio (OR) and 95% confidence interval (CI): 0.98 (0.97-0.996), AUC: 0.71 (0.58-0.82)], whereas it was negatively associated with high-grade gliomas [OR: 0.972 (0.950-0.996), AUC: 0.87 (0.80-0.94)] and Conclusions: DCE-MRI technology holds significant value in glioma diagnosis, particularly in integrated molecular diagnostics, predicting grading, molecular genotype including

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genotypeGliomagradingmagnetic resonance imaging (MRI)prognosis

Identifiers

PMID41081223
PMCPMC12514690

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