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Clinical Article
Application of synthetic diffusion-weighted imaging in evaluating the grading of glioma
LÜ Ruirui  DANG Pei  GE Xin  LI Min  HUANG Xueying  WANG Minglei  YANG Xuhong  YONG Peng  WANG Xiaodong 

Cite this article as: Lü RR, Dang P, Ge X, et al. Application of synthetic diffusion-weighted imaging in evaluating the grading of glioma[J]. Chin J Magn Reson Imaging, 2022, 13(7): 12-16. DOI:10.12015/issn.1674-8034.2022.07.003.

[Abstract] Objective To evaluate the value of synthetic diffusion-weighted imaging (synthetic DWI) in the evaluation of high and low grade gliomas.Materials and Methods The patients with gliomas were analyzed retrospectively, who underwent brain MRI (GE Signa Architect 3.0 T) one week before operation. Finally, 72 patients were included according to the inclusion and exclusion criteria (30 low-grade gliomas and 42 high-grade gliomas). Two neuroimaging diagnostic physicians used the double-blind method to evaluate and outline the region of interest (ROI) of the lesions on synthetic DWI. The signal intensity of DWI images with different b values was analyzed and compared with the final pathological results. Independent sample t test was used to compare between the two groups. Logistic regression and area under the receiver operating characteristic curve (AUC) analysis were used to evaluate the diagnostic efficacy of high and low grade gliomas.Results For differentiating high and low grade gliomas, the synthetic DWI b values were 500, 800, 1000, 1200, 1500, 1800, 2000, 2200 and the signal intensity values corresponding to 2500 s/mm2 were statistically significant (P<0.001). When b value was 2500 s/mm2, the diagnostic efficiency of differentiating high and low grade gliomas was the highest, AUC was 0.935, the sensitivity was 98%, and the specificity was 87%.Conclusions A single scan of synthetic DWI can obtain the corresponding signal intensity value under any b values from 0 to 2500 s/mm2, and with the increasing of b values, the diagnostic efficiency of glioma grading is higher.
[Keywords] glioma;magnetic resonance imaging;synthetic diffusion weighted imaging;grading;diagnosis

LÜ Ruirui1   DANG Pei2   GE Xin1   LI Min3   HUANG Xueying2   WANG Minglei2   YANG Xuhong1   YONG Peng1   WANG Xiaodong2*  

1 School of Clinical Medicine, Ningxia Medical University, Yinchuan 750004, China

2 Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan 750004, China

3 GE Healthcare, MR Enhancement Application, Beijing 100176, China

Wang XD, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS Natural Science Foundation of Ningxia Hui Autonomous Region (No. 2022AAC03487); Science and Technology Key Research Program of Ningxia Hui Autonomous Region (No. 2019BEG03037).
Received  2022-02-28
Accepted  2022-07-06
DOI: 10.12015/issn.1674-8034.2022.07.003
Cite this article as: Lü RR, Dang P, Ge X, et al. Application of synthetic diffusion-weighted imaging in evaluating the grading of glioma[J]. Chin J Magn Reson Imaging, 2022, 13(7): 12-16. DOI:10.12015/issn.1674-8034.2022.07.003.

Louis D N, Perry A, Wesseling P, et al. The 2021 WHO Classification of Tumors of the Central Nervous System: a summary[J]. Neuro-Oncology, 2021, 23(8): 1231-1251. DOI: 10.1093/neuonc/noab106.
Chang TJ, Shen HC, Yu MM, et al. The diagnostic value of IVIM in glioma grading and its correlation with Ki-67 labeling index[J]. Chin J Magn Reson Imaging, 2021, 12(2): 19-23. DOI: 10.12015/issn.1674-8034.2021.02.005.
Batalov AI, Zakharova NE, Pronin IN, et al. 3D pCASL-perfusion in preoperative assessment of brain gliomas in large cohort of patients[J/OL]. Scientific Reports, 2022, 12(1) [2022-02-28]. DOI: 10.1038/s41598-022-05992-4.
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]. European Radiology, 2020, 30(4): 2142-2151. DOI: 10.1007/s00330-019-06548-3.
Zeng Q, Dong F, Shi F, et al. Apparent diffusion coefficient maps obtained from high b value diffusion-weighted imaging in the preoperative evaluation of gliomas at 3T: comparison with standard b value diffusion-weighted imaging[J]. Eur Radiol, 2017, 27(12): 5309-5315. DOI: 10.1007/s00330-017-4910-0.
Kang X, Xi Y, Liu T, et al. Grading of Glioma: combined diagnostic value of amide proton transfer weighted, arterial spin labeling and diffusion weighted magnetic resonance imaging[J/OL]. BMC Med Imaging, 2020, 20(1) [2022-02-28]. DOI: 10.1186/s12880-020-00450-x.
Cao H, Xiao X, Hua J, et al. The Added Value of Inflow-Based Vascular-Space-Occupancy and Diffusion-Weighted Imaging in Preoperative Grading of Gliomas[J]. Neurodegenerative Diseases, 2021, 20(4): 123-130. DOI: 10.1159/000512545.
Fukukura Y, Kumagae Y, Hakamada H, et al. Computed diffusion-weighted MR imaging for visualization of pancreatic adenocarcinoma: Comparison with acquired diffusion-weighted imaging[J]. Eur J Radiol, 2017, 95: 39-45. DOI: 10.1016/j.ejrad.2017.07.022.
Daimiel Naranjo I, Lo Gullo R, Saccarelli C, et al. Diagnostic value of diffusion-weighted imaging with synthetic b-values in breast tumors: comparison with dynamic contrast-enhanced and multiparametric MRI[J]. Eur Radiol, 2021, 31(1): 356-367. DOI: 10.1007/s00330-020-07094-z.
Verma S, Sarkar S, Young J, et al. Evaluation of the impact of computed high b-value diffusion-weighted imaging on prostate cancer detection[J]. Abdom Radiol, 2016, 41(5): 934-945. DOI: 10.1007/s00261-015-0619-1.
Moribata Y, Kido A, Fujimoto K, et al. Feasibility of Computed Diffusion Weighted Imaging and Optimization of b-value in Cervical Cancer[J]. Magn Reson Med Sci, 2017, 16(1): 66-72. DOI: 10.2463/
Li Y, Kim M, Lawrence TS, et al. Microstructure Modeling of High b-Value Diffusion-Weighted Images in Glioblastoma[J]. Tomography, 2020, 6(1): 34-43. DOI: 10.18383/j.tom.2020.00018.
Blackledge MD, Leach MO, Collins DJ, et al. Computed diffusion-weighted MR imaging may improve tumor detection [J]. Radiology, 2011, 261: 573-581. DOI: 10.1148/radiol.11101919/-/DC1.
Al-Agha M, Abushab K, Quffa K, et al. Efficiency of High and Standardb Value Diffusion-Weighted Magnetic Resonance Imaging in Grading of Gliomas[J]. J Oncol, 2020, 2020: 1-9. DOI: 10.1155/2020/6942406.
Doskaliyev A, Yamasaki F, Ohtaki M, et al. Lymphomas and glioblastomas: Differences in the apparent diffusion coefficient evaluated with high b-value diffusion-weighted magnetic resonance imaging at 3T[J]. Eur J Radiol, 2012, 81(2): 339-344. DOI: 10.1016/j.ejrad.2010.11.005.
Mardor Y, Pfeffer R, Spiegelmann R, et al. Early Detection of Response to Radiation Therapy in Patients With Brain Malignancies Using Conventional and High b-Value Diffusion-Weighted Magnetic Resonance Imaging[J]. J Clin Oncol, 2003, 21(6): 1094-1100. DOI: 10.1200/JCO.2003.05.069.
Takayasu T, Yamasaki F, Akiyama Y, et al. Advantages of high b-value diffusion-weighted imaging for preoperative differential diagnosis between embryonal and ependymal tumors at 3 T MRI[J]. Eur J Radiol, 2018, 101: 136-143. DOI: 10.1016/j.ejrad.2018.02.013.
Glaister J, Cameron A, Wong A, et al. Quantitative investigative analysis of tumour separability in the prostate gland using ultra-high b-value computed diffusion imaging[J]. Annu Int Conf IEEE Eng Med Biol Soc, 2012, 2012: 420-423. DOI: 10.1109/EMBC.2012.6345957.
Zhang L, Min Z, Tang M, et al. The utility of diffusion MRI with quantitative ADC measurements for differentiating high-grade from low-grade cerebral gliomas: Evidence from a meta-analysis[J]. J Neurol Sci, 2017, 373: 9-15. DOI: 10.1016/j.jns.2016.12.008.
Brabec J, Durmo F, Szczepankiewicz F, et al. Separating Glioma Hyperintensities From White Matter by Diffusion-Weighted Imaging With Spherical Tensor Encoding[J/OL]. Frontiers in Neuroscience, 2022, 16 [2022-02-28]. DOI: 10.3389/fnins.2022.842242.
Zhu W, Gao Y, Wang PJ. The Research of Multimodal Functional MRI in the Evaluation of IDH1 mutation Status of Glioma[J]. Chin Comput Med Imag, 2021, 27(3): 179-184. DOI: 10.3969/j.issn.1006-5741.2021.03.001.
Cihangiroglu MM, Ozturk-Isik E, Firat Z, et al. Preoperative grading of supratentorial gliomas using high or standard b-value diffusion-weighted MR imaging at 3T[J]. Diagnostic and Interventional Imaging, 2017, 98(3): 261-268. DOI: 10.1016/j.diii.2016.11.005.
Wang QR, Wang DY, Zhao S, et al. Application of diffusion-weighted magnetic resonance imaging with different b-values in the puncture of lung space-occupying lesions[J]. Chin J Magn Reson Imaging, 2021, 12(8): 75-78. DOI: 10.12015/issn.1674-8034.2021.08.015.
Harder FN, Jung E, McTavish S, et al. High-Resolution, High b-Value Computed Diffusion-Weighted Imaging Improves Detection of Pancreatic Ductal Adenocarcinoma[J]. Cancers, 2022, 14(3): 470. DOI: 10.3390/cancers14030470.
DelPriore MR, Biswas D, Hippe DS, et al. Breast Cancer Conspicuity on Computed Versus Acquired High b-Value Diffusion-Weighted MRI[J]. Academic Radiology, 2021, 28(8): 1108-1117. DOI: 10.1016/j.acra.2020.03.011.
Cha SY, Kim E, Park SY. Why Is a b-value Range of 1500-2000 s/mm2 Optimal for Evaluating Prostatic Index Lesions on Synthetic Diffusion-Weighted Imaging?[J]. Korean J Radiol, 2021, 22(6): 922. DOI: 10.3348/kjr.2020.0836.
Bickel H, Polanec SH, Wengert G, et al. Diffusion‐Weighted MRI of Breast Cancer: Improved Lesion Visibility and Image Quality Using Synthetic b‐Values[J]. J Magn Reson Imaging, 2019, 50(6): 1754-1761. DOI: 10.1002/jmri.26809.
Choi BH, Baek HJ, Ha JY, et al. Feasibility Study of Synthetic Diffusion-Weighted MRI in Patients with Breast Cancer in Comparison with Conventional Diffusion-Weighted MRI[J]. Korean J Radiol, 2020, 21(9): 1036. DOI: 10.3348/kjr.2019.0568.
Sartoretti T, Sartoretti E, Wyss M, et al. Diffusion-weighted MRI of ischemic stroke at 3T: Value of synthetic b-values[J/OL]. Brit J Radiol, 2021, 94(1121) [2022-02-28]. DOI: 10.1259/bjr.20200869.
Gatidis S, Schmidt H, Martirosian P, et al. Apparent diffusion coefficient-dependent voxelwise computed diffusion-weighted imaging: An approach for improving SNR and reducing T2 shine-through effects[J]. J Magn Reson Imaging, 2016, 43(4): 824-832. DOI: 10.1002/jmri.25044.

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