Share：
Share this content in WeChat
X
[Chinese][PDF]78139
• Experience Exchang •
Value of enhanced MRI radiomics in predicting IDH-1 genotype in gliomas
TANG Wei  DUAN Junyan  YU Ziyi  ZHAI Zhaohua 

Cite this article as: Tang W, Duan JY, Yu ZY, et al. Value of enhanced MRI radiomics in predicting IDH-1 genotype in gliomas[J]. Chin J Magn Reson Imaging, 2022, 13(5): 111-114. DOI:10.12015/issn.1674-8034.2022.05.020.


[Abstract] Objective To explore the value of a radiomic model based on preoperative-enhanced MR images in the assessment of the IDH-1 genotype in patients with gliomas.Materials and Methods A retrospective analysis was performed on 102 patients with gliomas confirmed by surgical pathology in our hospital from 2017 to 2021 with complete preoperative brain-enhanced MRI images, including 73 patients with wild -type of IDH-1 (12 patients with WHO grade 2, 15 patients with grade 3, 46 patients with grade 4), 29 patients with an IDH-1 mutation (15 patients with WHO grade 2, 10 patients with grade 3, 4 patients with grade 4). All patients were randomly assigned to training group and validation group according to a ratio of 7∶3, 851 features were extracted using 3D-Slicer software. Least absolute shrinkage and selection operator was finally conducted to obtain 4 optimized subset of the feature to build the radiomic model, and the model was then tested with cross-validation. The area under the ROC curve was performed to evaluate the performance of the model.Results The combine model had the best performance, and the AUC of the training group and the validation group were respectively 0.886 (95% CI: 0.81-0.96) and 0.889 (95% CI: 0.77-1.00), the sensitivity were 0.90, 0.86, the specificity were 0.55, 0.55, and the accuracy were 80%, 77%. There was a statistically significant difference between the combine model and the clinic model (P＜0.05). The enhanced MR radiomics model had the similar predictive performance with the clinic model, and had no statistically significant between them.Conclusions The combine radiomics model based on the preoperative-enhanced MRI can effectively predict the IDH-1 genotype of gliomas.
[Keywords] gliomas；magnetic resonance imaging；enhanced；isocitrate dehydrogenase；genotype

TANG Wei   DUAN Junyan   YU Ziyi   ZHAI Zhaohua*  

Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China

Zhai ZH, E-mail: zhaizhaohuada@163.com

Conflicts of interest   None.

Received  2021-10-26
Accepted  2022-04-28
DOI: 10.12015/issn.1674-8034.2022.05.020
Cite this article as: Tang W, Duan JY, Yu ZY, et al. Value of enhanced MRI radiomics in predicting IDH-1 genotype in gliomas[J]. Chin J Magn Reson Imaging, 2022, 13(5): 111-114. DOI:10.12015/issn.1674-8034.2022.05.020.

[1]
Niu L, Feng WH, Duan CF, et al. The value of enhanced MR radiomics in estimating the IDH1 genotype in high-grade gliomas[J]. Biomed Res Int, 2020, 2020: 4630218. DOI: 10.1155/2020/4630218.
[2]
Gritsch S, Batchelor TT, Gonzalez Castro LN. Diagnostic, therapeutic, and prognostic implications of the 2021 World Health Organization classification of tumors of the central nervous system[J]. Cancer, 2022, 128(1): 47-58. DOI: 10.1002/cncr.33918.
[3]
Komori T. The 2016 WHO classification of tumours of the central nervous system: the major points of revision[J]. Neurol Med Chir (Tokyo), 2017, 57(7): 301-311. DOI: 10.2176/nmc.ra.2017-0010.
[4]
Wang K, Zhang S, Shi L, et al. The 2016 World Health Organization classiifcation of tumors of the central nervous system: a summary[J]. Chin J Magn Reson Imaging, 2016, 7(12): 881-896. DOI: 10.12015/issn.1674-8034.2016.12.001.
[5]
Xu H, Ren J. Progress in imaging studies of IDH mutation and 1p/19q combined delection gioma[J]. Radiol Pract, 2020, 35(9): 1199-1202. DOI: 10.13609/j.cnki.1000-0313.2020.09.025.
[6]
Han SE, Liu Y, Cai SJ, et al. IDH mutation in glioma: molecular mechanisms and potential therapeutic targets[J]. Br J Cancer, 2020, 122(11): 1580-1589. DOI: 10.1038/s41416-020-0814-x.
[7]
Qin JB, Liu ZY, Zhang H, et al. Grading of gliomas by using radiomic features on multiple magnetic resonance imaging (MRI) sequences[J]. Med Sci Monit, 2017, 23: 2168-2178. DOI: 10.12659/msm.901270.
[8]
Tran AN, Lai A, Li SC, et al. Increased sensitivity to radiochemotherapy in IDH1 mutant glioblastoma as demonstrated by serial quantitative MR volumetry[J]. Neuro Oncol, 2014, 16(3): 414-420. DOI: 10.1093/neuonc/not198.
[9]
Rohle D, Popovici-Muller J, Palaskas N, et al. An inhibitor of mutant IDH1 delays growth and promotes differentiation of glioma cells[J]. Science, 2013, 340(6132): 626-630. DOI: 10.1126/science.1236062.
[10]
Kayabolen A, Yilmaz E, Bagci-Onder T. IDH mutations in glioma: double-edged sword in clinical applications?[J]. Biomedicines, 2021, 9(7): 799. DOI: 10.3390/biomedicines9070799.
[11]
Waitkus MS, Diplas BH, Yan H. Isocitrate dehydrogenase mutations in gliomas[J]. Neuro-oncology, 2016, 18(1): 16-26. DOI: 10.1093/neuonc/nov136.
[12]
Zhang LJ, Sorensen MD, Kristensen BW, et al. D-2-hydroxyglutarate is an intercellular mediator in IDH-mutant gliomas inhibiting complement and T cells[J]. Clin Cancer Res, 2018, 24(21): 5381-5391. DOI: 10.1158/1078-0432.CCR-17-3855.
[13]
Villanueva-Meyer JE, Wood MD, Choi BS, et al. MRI features and IDH mutational status of grade Ⅱ diffuse gliomas: impact on diagnosis and prognosis[J]. AJR Am J Roentgenol, 2018, 210(3): 621-628. DOI: 10.2214/AJR.17.18457.
[14]
Tan Y, Zhang ST, Wei JW, et al. A radiomics nomogram may improve the prediction of IDH genotype for astrocytoma before surgery[J]. Eur Radiol, 2019, 29(7): 3325-3337. DOI: 10.1007/s00330-019-06056-4.
[15]
Kim M, Jung SY, Park JE, et al. Diffusion- and perfusion-weighted MRI radiomics model may predict isocitrate dehydrogenase (IDH) mutation and tumor aggressiveness in diffuse lower grade glioma[J]. Eur Radiol, 2020, 30(4): 2142-2151. DOI: 10.1007/s00330-019-06548-3.
[16]
Manikis GC, Ioannidis GS, Siakallis L, et al. Multicenter DSC-MRI-based radiomics predict IDH mutation in gliomas[J]. Cancers (Basel), 2021, 13(16): 3965. DOI: 10.3390/cancers13163965.
[17]
Zhao J, Huang YQ, Song YK, et al. Diagnostic accuracy and potential covariates for machine learning to identify IDH mutations in glioma patients: evidence from a meta-analysis[J]. Eur Radiol, 2020, 30(8): 4664-4674. DOI: 10.1007/s00330-020-06717-9.
[18]
Liu N, Sui QL, Liu XJ, et al. The value of contrast enhanced MRI radiomics in predicting the IDH 1 genotype in high-grade gliomas[J]. Chin J Radiol, 2020, 54(5): 445-449. DOI: 10.3760/cma.j.cn112149-20190608-00257.
[19]
Park CJ, Choi YS, Park YW, et al. Diffusion tensor imaging radiomics in lower-grade glioma: improving subtyping of isocitrate dehydrogenase mutation status[J]. Neuroradiology, 2020, 62(3): 319-326. DOI: 10.1007/s00234-019-02312-y.
[20]
Li ZC, Bai HM, Sun QC, et al. Multiregional radiomics profiling from multiparametric MRI: identifying an imaging predictor of IDH1 mutation status in glioblastoma[J]. Cancer Med, 2018, 7(12): 5999-6009. DOI: 10.1002/cam4.1863.
[21]
Soni N, Priya S, Bathla G. Texture analysis in cerebral gliomas: a review of the literature[J]. AJNR Am J Neuroradiol, 2019, 40(6): 928-934. DOI: 10.3174/ajnr.A6075.
[22]
Hsieh KLC, Chen CY, Lo CM. Radiomic model for predicting mutations in the isocitrate dehydrogenase gene in glioblastomas[J]. Oncotarget, 2017, 8(28): 45888-45897. DOI: 10.18632/oncotarget.17585.
[23]
Han L, Wang SY, Miao YW, et al. MRI texture analysis based on 3D tumor measurement reflects the IDH1 mutations in gliomas——A preliminary study[J]. Eur J Radiol, 2019, 112: 169-179. DOI: 10.1016/j.ejrad.2019.01.025.
[24]
Sohn B, An C, Kim D, et al. Radiomics-based prediction of multiple gene alteration incorporating mutual genetic information in glioblastoma and grade 4 astrocytoma, IDH-mutant[J]. J Neurooncol, 2021, 155(3): 267-276. DOI: 10.1007/s11060-021-03870-z.

PREV The correlation between the characteristics of middle cerebral artery atherosclerotic plaque, cerebral perfusion and the occurrence of acute cerebral infarction
NEXT Therapeutic effects of radiofrequency ablation for hepatocellular carcinoma: Evaluated by magnetic resonance imaging
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn