Radiomic Analysis of Contrast-Enhanced MRI Predicts DNA Copy-Number Subtype and Outcome in Lower-Grade Gliomas

Published:December 13, 2021DOI:

      Rationale and Objectives

      DNA copy-number (CN)2-subtype impairs outcomes in patients with lower-grade gliomas (LGG). We aimed to determine the value of preoperative nomograms integrating radiomic and radiographic (RR) features in predicting DNA copy-number subtype.


      Data of 153 consecutive patients were retrospectively analyzed. A total of 1167 radiomics features were extracted from contrast-enhanced MR images. LASSO logistic regression was performed to choose the key features and construct a radiomics signature. Three CN-related RR model were built with multivariate logistic regression.


      CN2-subtype was associated with shortest median PFS(p <0.001) and OS (p <0.001). The radiomics nomogram, which incorporated the signature (AUC:0.891, OR: 2.345; p = 0.001), extranodular growth (OR: 14.413; p <0.001) and width (OR: 0.194; p = 0.027), distinguished CN2-subtype with an AUC of 0.924(95%CI: 0.869–0.979).The radiomics nomogram, which incorporated the signature (AUC:0.730, OR: 2.408; p = 0.001), hemorrhage (OR: 0.100; p <0.001), poorly-defined margin (OR:4.433; p = 0.001) and volume>=60cm3 (OR: 4.195; p = 0.002) were associated with CN1-subtype (AUC:0.829,95%CI:0.765–0.892).The radiomics nomogram, which incorporated the signature (AUC:0.660, OR: 2.518; p = 0.003), necrosis/cystic(OR:6.975; p = 0.008), hemorrhage (OR:3.723; p = 0.024), poorly-defined margin (OR:0.124; p <0.001) and frontal lobe tumors (OR: 4.870; p <0.001) were associated with CN3-subtype (AUC: 0.837,95%CI: 0.767–0.909).All three RR models showed good discrimination and calibration. Decision curve analysis indicated that all RR models were clinically useful. The average accuracy of the ten-fold cross validation was 92.8% for CN2-subtype, 72.6% for CN1-subtype and 79.0% for CN3-subtype.


      The shortest PFS and OS was observed in LGG patients with CN2-subtype. The RR models, integrating radiomic and radiographic features, demonstrates good performance for predicting DNA copy-number subtype and clinical outcomes.

      Key Words

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'


      Subscribe to Academic Radiology
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


        • Siegel RL
        • Miller KD
        • Fuchs HE
        • Jemal A
        Cancer statistics, 2021.
        CA Cancer J Clin. 2021; 71: 7-33
        • Silantyev AS
        • Falzone L
        • Libra M
        • et al.
        Current and future trends on diagnosis and prognosis of glioblastoma: from molecular biology to proteomics.
        Cells. 2019; 8: 863
        • Chang SM
        • Cahill DP
        • Aldape KD
        • Mehta MP
        Treatment of adult lower-grade glioma in the era of genomic medicine.
        Am Soc Clin Oncol Educ Book. 2016; 35: 75-81
        • Chen R
        • Cohen AL
        • Colman H
        Targeted therapeutics in patients with high-grade gliomas: past, present, and future.
        Curr Treat Options Oncol. 2016; 17: 42
        • Weller M
        • Weber RG
        • Willscher E
        • et al.
        Molecular classification of diffuse cerebral WHO grade II/III gliomas using genome- and transcriptome-wide profiling improves stratification of prognostically distinct patient groups.
        Acta Neuropathol. 2015; 129: 679-693
        • Siegal T
        Clinical relevance of prognostic and predictive molecular markers in gliomas.
        Adv Tech Stand Neurosurg. 2016; 43: 91-108
        • Nowakowska B
        Clinical interpretation of copy number variants in the human genome.
        J Appl Genet. 2017; 58: 449-457
        • Lauer S
        • Gresham D
        An evolving view of copy number variants.
        Curr Genet. 2019; 65: 1287-1295
        • Cancer Genome Atlas Research N
        • Brat DJ
        • Verhaak RG
        • et al.
        Comprehensive, integrative genomic analysis of diffuse lower-grade gliomas.
        N Engl J Med. 2015; 372: 2481-2498
        • Zhang S
        • Wu S
        • Wan Y
        • et al.
        Development of MR-based preoperative nomograms predicting DNA copy number subtype in lower grade gliomas with prognostic implication.
        Eur Radiol. 2021; 31: 2094-2105
        • Chai RC
        • Zhang KN
        • Chang YZ
        • et al.
        Systematically characterize the clinical and biological significances of 1p19q genes in 1p/19q non-codeletion glioma.
        Carcinogenesis. 2019; 40: 1229-1239
        • Zhang Y
        • Cheng C
        • Liu Z
        • et al.
        Radiomics analysis for the differentiation of autoimmune pancreatitis and pancreatic ductal adenocarcinoma in (18) F-FDG PET/CT.
        Med Phys. 2019; 46: 4520-4530
        • Wang X
        • Wan Q
        • Chen H
        • Li Y
        • Li X
        Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.
        Eur Radiol. 2020; 30: 4595-4605
        • Avanzo M
        • Stancanello J
        • El Naqa I
        Beyond imaging: The promise of radiomics.
        Phys Med. 2017; 38: 122-139
        • Wong CW
        • Chaudhry A
        Radiogenomics of lung cancer.
        J Thorac Dis. 2020; 12: 5104-5109
        • Wu J
        • Tha KK
        • Xing L
        • Li R
        Radiomics and radiogenomics for precision radiotherapy.
        J Radiat Res. 2018;; 59: i25-i31
        • Di Noto T
        • von Spiczak J
        • Mannil M
        • et al.
        Radiomics for distinguishing myocardial infarction from myocarditis at late gadolinium enhancement at mri: comparison with subjective visual analysis.
        Radiol Cardiothorac Imaging. 2019; 1e180026
        • Gore S
        • Chougule T
        • Jagtap J
        • Saini J
        • Ingalhalikar M
        A review of radiomics and deep predictive modeling in glioma characterization.
        Acad Radiol. 2020; 28: 1599-1621
        • Liu Z
        • Zhang T
        • Jiang H
        • Xu W
        • Zhang J
        Conventional MR-based Preoperative Nomograms for Prediction of IDH/1p19q Subtype in Low-Grade Glioma.
        Acad Radiol. 2019; 26: 1062-1070
        • Zhang H
        • Xu L
        • Zhong Z
        • Liu Y
        • Long Y
        • Zhou S
        Lower-grade gliomas: predicting DNA methylation subtyping and its consequences on survival with MR features.
        Acad Radiol. 2021; 28: e199-e208
        • Zhang L
        • Yang LQ
        • Wen L
        • et al.
        Noninvasively evaluating the grading of glioma by multiparametric magnetic resonance imaging.
        Acad Radiol. 2021; 28: e137-e146
        • Abecasis GR
        • Altshuler D
        • Auton A
        • et al.
        • Genomes Project C
        A map of human genome variation from population-scale sequencing.
        Nature. 2010; 467: 1061-1073
        • Butchbach ME
        Copy number variations in the survival motor neuron genes: implications for spinal muscular atrophy and other neurodegenerative diseases.
        Front Mol Biosci. 2016; 3: 7
        • Munoz-Hidalgo L
        • San-Miguel T
        • Megias J
        • et al.
        Somatic copy number alterations are associated with EGFR amplification and shortened survival in patients with primary glioblastoma.
        Neoplasia. 2020; 22: 10-21
        • Chen YP
        • Wang YQ
        • Lv JW
        • et al.
        Identification and validation of novel microenvironment-based immune molecular subgroups of head and neck squamous cell carcinoma: implications for immunotherapy.
        Ann Oncol. 2019; 30: 68-75
        • Khoury MJ
        • Coates RJ
        • Fennell ML
        • et al.
        Multilevel research and the challenges of implementing genomic medicine.
        J Natl Cancer Inst Monogr. 2012; 44: 112-120
        • Goetz LH
        • Schork NJ
        Personalized medicine: motivation, challenges, and progress.
        Fertil Steril. 2018; 109: 952-963
        • Liu Z
        • Wang S
        • Dong D
        The applications of radiomics in precision diagnosis and treatment of oncology: opportunities and challenges.
        Theranostics. 2019; 9: 1303-1322
        • Thawani R
        • McLane M
        • Beig N
        • et al.
        Radiomics and radiogenomics in lung cancer: a review for the clinician.
        Lung Cancer. 2018; 115: 34-41
        • van Timmeren JE
        • Cester D
        • Tanadini-Lang S
        • Alkadhi H
        • Baessler B
        Radiomics in medical imaging-"how-to" guide and critical reflection.
        Insights Imaging. 2020; 11: 91
        • Zhou H
        • Vallieres M
        • Bai HX
        • et al.
        MRI features predict survival and molecular markers in diffuse lower-grade gliomas.
        Neuro Oncol. 2017; 19: 862-870
        • Gong J
        • Liu J
        • Hao W
        • Nie S
        • Wang S
        • Peng W
        Computer-aided diagnosis of ground-glass opacity pulmonary nodules using radiomic features analysis.
        Phys Med Biol. 2019; 6135015
        • Yip SS
        • Aerts HJ
        Applications and limitations of radiomics.
        Phys Med Biol. 2016; 61: R150-R166
        • Chen Z
        • Xiong S
        • Li J
        • et al.
        DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model.
        Transl Lung Cancer Res. 2020; 9: 280-287
        • van der Gaag M
        • Hoffman T
        • Remijsen M
        • et al.
        The five-factor model of the Positive and Negative Syndrome Scale II: a ten-fold cross-validation of a revised model.
        Schizophr Res. 2006; 85: 280-287
        • Gross F
        • MacLeod M
        Prospects and problems for standardizing model validation in systems biology.
        Prog Biophys Mol Biol. 2017; 129: 3-12
        • Wang S
        • Yang L
        • Ci B
        • et al.
        Development and validation of a nomogram prognostic model for SCLC Patients.
        J Thorac Oncol. 2018; 13: 1338-1348