Evidence map›Paper›PMID 38896238›Full record

ArticleNeuroradiology2024

Characterizing the relationship between MRI radiomics and AHR expression and deriving a predictive model for prognostic assessment in glioblastoma.

Chen Liu, Dingkang Xu, Limin Meng, Hongqi Li, Zhiguang Fu, Maohui Yan, Xiaolong Hu, Yingjie Wang

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Article in Neuroradiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Chen Liu *Department of Radiotherapy, Air Force Medical Center, The Fourth Military Medical University, PLA, No 30. Fucheng Road, Haidian District, Beijing, 100142, China.
Dingkang Xu *Department of Neurosurgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Limin MengDepartment of Radiology, Air Force Medical Center, The Fourth Military Medical University, PLA, Beijing, 100142, China.
Hongqi LiDepartment of Radiotherapy, Air Force Medical Center, The Fourth Military Medical University, PLA, No 30. Fucheng Road, Haidian District, Beijing, 100142, China.
Zhiguang FuDepartment of Radiotherapy, Air Force Medical Center, The Fourth Military Medical University, PLA, No 30. Fucheng Road, Haidian District, Beijing, 100142, China.
Maohui YanDepartment of Radiotherapy, Air Force Medical Center, The Fourth Military Medical University, PLA, No 30. Fucheng Road, Haidian District, Beijing, 100142, China.
Xiaolong HuDepartment of Radiation Oncology, Beijing Geriatric Hospital, Beijing, China.
Yingjie WangDepartment of Radiotherapy, Air Force Medical Center, The Fourth Military Medical University, PLA, No 30. Fucheng Road, Haidian District, Beijing, 100142, China. Wangyingjie666@fmmu.edu.cn.ORCID http://orcid.org/0009-0003-6287-0052

Funding

Youth PhD Advancement Project of Air Force Medical Center, PLA 21ZT07
6 · The paper itself

Abstract

purposeAryl hydrocarbon receptor (AHR), a crucial molecular marker associated with glioma, is a potential therapeutic target. We aimed to establish a non-invasive predictive model for AHR through radiomics.

methodsContrast-enhanced T1-weighted (T1W) MRI and the corresponding and clinical variables of glioblastoma patients from The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA) were obtained for analysis. KM curves and Cox regression analyses were used to assess the prognostic value of AHR expression. The radiomics features were screened by Max-Relevance and Min-Redundancy (mRMR) and recursive feature elimination (RFE), followed by the construction of two predictive models using logistic regression (LR) and a support vector machine (SVM).

resultsThe expression levels of AHR in tumour patients were significantly higher than those in the control group, and higher AHR expression was associated with worse prognosis (P<0.05). AHR remained a risk factor for poor prognosis in glioblastoma after multivariate adjustment (HR: 1.61, 95% CI: 1.085-2.39, P<0.05). The radiomics models constructed using LR and SVM based on three selected features achieved area under the curve (AUC) values of 0.887 and 0.872, respectively. Radiomics score emerged as a key factor influencing overall survival (OS) after multivariate adjustment in the Cox model (HR: 3.931, 95% CI: 1.272-12.148, P < 0.05).

conclusionThe radiomics models could effectively distinguish the expression levels of AHR and predict prognosis in patients with glioblastoma, which may serve as a powerful tool to assist clinical assessment and precision treatment.

Indexed as

Brain NeoplasmsGlioblastomaMagnetic Resonance ImagingReceptors, Aryl HydrocarbonAdultAgedBasic Helix-Loop-Helix ProteinsBiomarkers, TumorContrast MediaFemaleHumansMaleMiddle AgedPredictive Value of TestsPrognosisRadiomicsAHR protein, humanBasic Helix-Loop-Helix ProteinsBiomarkers, TumorContrast MediaReceptors, Aryl HydrocarbonAryl hydrocarbon receptorGlioblastomaImmune infiltration analysisMachine learningRadiomics score

Identifiers

PMID38896238

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