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Research progress of multimodal magnetic resonance imaging in the diagnosis and differential diagnosis of glioblastoma and brain metastases
HAO Zhiyue  GAO Yang  WU Qiong 

Cite this article as: Hao ZY, Gao Y, Wu Q. Research progress of multimodal magnetic resonance imaging in the diagnosis and differential diagnosis of glioblastoma and brain metastases[J]. Chin J Magn Reson Imaging, 2022, 13(8): 125-129. DOI:10.12015/issn.1674-8034.2022.08.028.


[Abstract] Glioblastoma and brain metastases are two common malignant diseases of the central nervous system. The two diseases show similar image features in conventional image sequences, and conventional image examination can not differentiate them accurately, especially for single metastasis without medical history support. Correct preoperative differential diagnosis is of great significance for the formulation of clinical treatment and the analysis of survival prognosis. Multimodal MRI has shown high clinical value in differentiating glioblastoma from brain metastases. However, the accuracy and specificity of each MRI model in differentiating the two lesions are different. The combined use of multiple MRI models can effectively improve the diagnostic efficiency. Due to the difference of edema formation mechanism between the two diseases, the parameters of peritumoral edema area have higher diagnostic efficiency in differentiating the two diseases. This paper reviews the research progress of multimodal MRI techniques such as dynamic susceptibility contrast, dynamic contrast enhanced, diffusion tensor imaging and blood oxygen level dependent functional MRI in the differential diagnosis of glioblastoma and brain metastases, and extends some other magnetic resonance models that may be used to solve this clinical problem in the future, such as a mean apparent propagator-MRI, neurite orientation dispersion and density imaging and diffusion microstructure imaging, in order to provide reference ideas for follow-up research.
[Keywords] multimodal magnetic resonance imaging；perfusion imaging；diffusion magnetic resonance imaging；glioblastoma；brain metastasis

HAO Zhiyue   GAO Yang*   WU Qiong  

Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot 010050, China

Gao Y, E-mail: 1390903990@qq.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Inner Mongolia Autonomous Region Science and Technology Plan Project (No. 2019GG047).
Received  2022-04-08
Accepted  2022-06-02
DOI: 10.12015/issn.1674-8034.2022.08.028
Cite this article as: Hao ZY, Gao Y, Wu Q. Research progress of multimodal magnetic resonance imaging in the diagnosis and differential diagnosis of glioblastoma and brain metastases[J]. Chin J Magn Reson Imaging, 2022, 13(8): 125-129. DOI:10.12015/issn.1674-8034.2022.08.028.

[1]
GBD 2016 Brain and Other CNS Cancer Collaborators. Global, regional, and national burden of brain and other CNS cancer, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016[J]. Lancet Neurol, 2019, 18(4): 376-393. DOI: 10.1016/s1474-4422(18)30468-x.
[2]
Artzi M, Bressler I, Ben Bashat D. Differentiation between glioblastoma, brain metastasis and subtypes using radiomics analysis[J]. J Magn Reson Imaging, 2019, 50(2): 519-528. DOI: 10.1002/jmri.26643.
[3]
Askaner K, Rydelius A, Engelholm S, et al. Differentiation between glioblastomas and brain metastases and regarding their primary site of malignancy using dynamic susceptibility contrast MRI at 3 T[J]. J Neuroradiol, 2019, 46(6): 367-372. DOI: 10.1016/j.neurad.2018.09.006.
[4]
Lee MD, Baird GL, Bell LC, et al. Utility of Percentage Signal Recovery and Baseline Signal in DSC-MRI Optimized for Relative CBV Measurement for Differentiating Glioblastoma, Lymphoma, Metastasis, and Meningioma[J]. AJNR Am J Neuroradiol, 2019, 40(9): 1445-1450. DOI: 10.3174/ajnr.A6153.
[5]
Aparici-Robles F, Davidhi A, Carot-Sierra J, et al. Glioblastoma versus solitary brain metastasis: MRI differentiation using the edema perfusion gradient[J]. J Neuroimaging, 2022, 32(1): 127-133. DOI: 10.1111/jon.12920.
[6]
She D, Xing Z, Cao D. Differentiation of Glioblastoma and Solitary Brain Metastasis by Gradient of Relative Cerebral Blood Volume in the Peritumoral Brain Zone Derived from Dynamic Susceptibility Contrast Perfusion Magnetic Resonance Imaging[J]. J Comput Assist Tomo, 2019, 43(1): 13-17. DOI: 10.1097/rct.0000000000000771.
[7]
Fordham AJ, Hacherl CC, Patel N, et al. Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities[J]. Cancers, 2021, 13(12): 2960. DOI: 10.3390/cancers13122960.
[8]
Park JE, Kim HS, Lee J, et al. Deep-learned time-signal intensity pattern analysis using an autoencoder captures magnetic resonance perfusion heterogeneity for brain tumor differentiation[J/OL]. Sci Rep, 2020, 10(1) [2022-04-08]. https://www.nature.com/articles/s41598-020-78485-x. DOI: 10.1038/s41598-020-78485-x.
[9]
Pons-Escoda A, Garcia-Ruiz A, Naval-Baudin P, et al. Voxel-level analysis of normalized DSC-PWI time-intensity curves: a potential generalizable approach and its proof of concept in discriminating glioblastoma and metastasis[J]. Eur Radiol, 2022, 32(6): 3705-3715. DOI: 10.1007/s00330-021-08498-1.
[10]
Neska-Matuszewska M, Bladowska J, Sąsiadek M, et al. Differentiation of glioblastoma multiforme, metastases and primary central nervous system lymphomas using multiparametric perfusion and diffusion MR imaging of a tumor core and a peritumoral zone-Searching for a practical approach[J/OL]. PLoS One, 2018, 13(1) [2022-04-08]. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0191341. DOI: 10.1371/journal.pone.0191341.
[11]
Vallée A, Guillevin C, Wager M, et al. Added Value of Spectroscopy to Perfusion MRI in the Differential Diagnostic Performance of Common Malignant Brain Tumors[J]. AJNR Am J Neuroradiol, 2018, 39(8): 1423-1431. DOI: 10.3174/ajnr.A5725.
[12]
Mangla R, Kolar B, Zhu T, et al. Percentage signal recovery derived from MR dynamic susceptibility contrast imaging is useful to differentiate common enhancing malignant lesions of the brain[J]. AJNR Am J Neuroradiol, 2011, 32(6): 1004-1010. DOI: 10.3174/ajnr.A2441.
[13]
Novak J, Withey SB, Lateef S, et al. A comparison of pseudo-continuous arterial spin labelling and dynamic susceptibility contrast MRI with and without contrast agent leakage correction in paediatric brain tumours[J/OL]. Br J Radiol, 2019, 92(1094) [2022-04-08]. https://www.birpublications.org/doi/10.1259/bjr.20170872. DOI: 10.1259/bjr.20170872.
[14]
Leu K, Boxerman JL, Cloughesy TF, et al. Improved Leakage Correction for Single-Echo Dynamic Susceptibility Contrast Perfusion MRI Estimates of Relative Cerebral Blood Volume in High-Grade Gliomas by Accounting for Bidirectional Contrast Agent Exchange[J]. AJNR Am J Neuroradiol, 2016, 37(8): 1440-1446. DOI: 10.3174/ajnr.A4759.
[15]
Leu K, Boxerman JL, Ellingson BM. Effects of MRI Protocol Parameters, Preload Injection Dose, Fractionation Strategies, and Leakage Correction Algorithms on the Fidelity of Dynamic-Susceptibility Contrast MRI Estimates of Relative Cerebral Blood Volume in Gliomas[J]. AJNR Am J Neuroradiol, 2017, 38(3): 478-484. DOI: 10.3174/ajnr.A5027.
[16]
Bell LC, Hu LS, Stokes AM, et al. Characterizing the Influence of Preload Dosing on Percent Signal Recovery (PSR) and Cerebral Blood Volume (CBV) Measurements in a Patient Population With High-Grade Glioma Using Dynamic Susceptibility Contrast MRI[J]. Tomography, 2017, 3(2): 89-95. DOI: 10.18383/j.tom.2017.00004.
[17]
Lu S, Gao Q, Yu J, et al. Utility of dynamic contrast-enhanced magnetic resonance imaging for differentiating glioblastoma, primary central nervous system lymphoma and brain metastatic tumor[J]. Eur J Radiol, 2016, 85(10): 1722-1727. DOI: 10.1016/j.ejrad.2016.07.005.
[18]
Feng MW, Fang M, Wang GH. The application value of 3D arterial spin labeling and dynamic contrast-enhanced MRI in differential diagnosis of high-grade gliomas and brain metastatic tumors[J]. Chin J Clin Med Imaging, 2021, 32(8): 574-578. DOI: 10.12117/jccmi.2021.08.011.
[19]
Bazyar S, Ramalho J, Eldeniz C, et al. Comparison of Cerebral Blood Volume and Plasma Volume in Untreated Intracranial Tumors[J/OL]. PLoS One, 2016, 11(9) [2022-04-08]. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0161807. DOI: 10.1371/journal.pone.0161807.
[20]
Tupý R, Mírka H, Mraček J, et al. Tumor-related Perfusion Changes in White Matter Adjacent to Brain Tumors: Pharmacodynamic Analysis of Dynamic 3T Magnetic Resonance Imaging[J]. Anticancer Res, 2018, 38(7): 4149-4152. DOI: 10.21873/anticanres.12707.
[21]
Jung BC, Arevalo-Perez J, Lyo JK, et al. Comparison of Glioblastomas and Brain Metastases using Dynamic Contrast-Enhanced Perfusion MRI[J]. J Neuroimaging, 2016, 26(2): 240-246. DOI: 10.1111/jon.12281.
[22]
Holly KS, Barker BJ, Murcia D, et al. High-grade Gliomas Exhibit Higher Peritumoral Fractional Anisotropy and Lower Mean Diffusivity than Intracranial Metastases[J]. Front Surg, 2017, 4: 18. DOI: 10.3389/fsurg.2017.00018.
[23]
Abdel Razek A, Talaat M, El-Serougy L, et al. Differentiating Glioblastomas from Solitary Brain Metastases Using Arterial Spin Labeling Perfusion- and Diffusion Tensor Imaging-Derived Metrics[J/OL]. World Neurosurg, 2019, 127 [2022-04-08]. https://linkinghub.elsevier.com/retrieve/pii/S1878875019308939. DOI: 10.1016/j.wneu.2019.03.213.
[24]
Skogen K, Schulz A, Helseth E, et al. Texture analysis on diffusion tensor imaging: discriminating glioblastoma from single brain metastasis[J]. Acta Radiol, 2019, 60(3): 356-366. DOI: 10.1177/0284185118780889.
[25]
Wang S, Kim SJ, Poptani H, et al. Diagnostic utility of diffusion tensor imaging in differentiating glioblastomas from brain metastases[J]. AJNR Am J Neuroradiol, 2014, 35(5): 928-934. DOI: 10.3174/ajnr.A3871.
[26]
Yao Q, Jie PP, Liu Y, et al. Value of 3.0T Diffusion Tensor Imaging in Differential Diagnosis of High-Grade Gliomas and Brain Metastases[J]. J Clin Radiol, 2020, 354(1): 22-25. DOI: 10.13437/j.cnki.jcr.2020.01.004.
[27]
Samani ZR, Parker D, Wolf R, et al. Distinct tumor signatures using deep learning-based characterization of the peritumoral microenvironment in glioblastomas and brain metastases[J/OL]. Scientific Reports, 2021, 11 [2022-04-08]. https://www.nature.com/articles/s41598-021-93804-6. DOI: 10.1038/s41598-021-93804-6.
[28]
Holly KS, Fitz-Gerald JS, Barker BJ, et al. Differentiation of High-Grade Glioma and Intracranial Metastasis Using Volumetric Diffusion Tensor Imaging Tractography[J/OL]. World Neurosurg, 2018, 120 [2022-04-08]. https://linkinghub.elsevier.com/retrieve/pii/S1878875018317108. DOI: 10.1016/j.wneu.2018.07.230.
[29]
Heynold E, Zimmermann M, Hore N, et al. Physiological MRI Biomarkers in the Differentiation Between Glioblastomas and Solitary Brain Metastases[J]. Mol Imaging Biol, 2021, 23(5): 787-795. DOI: 10.1007/s11307-021-01604-1.
[30]
Treiber JM, Steed TC, Brandel MG, et al. Molecular physiology of contrast enhancement in glioblastomas: An analysis of The Cancer Imaging Archive (TCIA)[J]. J Clin Neurosci, 2018, 55: 86-92. DOI: 10.1016/j.jocn.2018.06.018.
[31]
Hossman KA, Blöink M. Blood flow and regulation of blood flow in experimental peritumoral edema[J]. Stroke, 1981, 12(2): 211-217. DOI: 10.1161/01.str.12.2.211.
[32]
Lüdemann L, Förschler A, Grieger W, et al. BOLD signal in the motor cortex shows a correlation with the blood volume of brain tumors[J]. J Magn Reson Imaging, 2006, 23(4): 435-443. DOI: 10.1002/jmri.20530.
[33]
Wedeen VJ, Hagmann P, Tseng WY, et al. Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging[J]. Magn Reson Med, 2005, 54(6): 1377-1386. DOI: 10.1002/mrm.20642.
[34]
Mao C, Jiang W, Huang J, et al. Quantitative Parameters of Diffusion Spectrum Imaging: HER2 Status Prediction in Patients With Breast Cancer[J/OL]. Front Ooncol, 2022, 12 [2022-04-08]. https://www.frontiersin.org/articles/10.3389/fonc.2022.817070/full. DOI: 10.3389/fonc.2022.817070.
[35]
Wang P, Weng L, Xie S, et al. Primary application of mean apparent propagator-MRI diffusion model in the grading of diffuse glioma[J/OL]. Eur J Radiol, 2021, 138 [2022-04-08]. https://linkinghub.elsevier.com/retrieve/pii/S0720048X21001029. DOI: 10.1016/j.ejrad.2021.109622.
[36]
Gao A, Zhang H, Yan X, et al. Whole-Tumor Histogram Analysis of Multiple Diffusion Metrics for Glioma Genotyping[J]. Radiology, 2022, 302(3): 652-661. DOI: 10.1148/radiol.210820.
[37]
Jiang R, Jiang S, Song S, et al. Laplacian-Regularized Mean Apparent Propagator-MRI in Evaluating Corticospinal Tract Injury in Patients with Brain Glioma[J]. Korean J Radiol, 2021, 22(5): 759-769. DOI: 10.3348/kjr.2020.0949.
[38]
Wang Y, Deng K, Sun Y, et al. Preserved microstructural integrity of the corticospinal tract in patients with glioma-induced motor epilepsy: a study using mean apparent propagator magnetic resonance imaging[J]. Quant Imag Med Surg, 2022, 12(2): 1415-1427. DOI: 10.21037/qims-21-679.
[39]
Sun Y, Su C, Deng K, et al. Mean apparent propagator-MRI in evaluation of glioma grade, cellular proliferation, and IDH-1 gene mutation status[J]. Eur Radiol, 2022, 32(6): 3744-3754. DOI: 10.1007/s00330-021-08522-4.
[40]
Le H, Zeng W, Zhang H, et al. Mean Apparent Propagator MRI Is Better Than Conventional Diffusion Tensor Imaging for the Evaluation of Parkinson's Disease: A Prospective Pilot Study[J/OL]. Front Aging Neurosci, 2020, 12 [2022-04-08]. https://www.frontiersin.org/articles/10.3389/fnagi.2020.563595/full. DOI: 10.3389/fnagi.2020.563595.
[41]
Corr F, Grimm D, Saß B, et al. Radiogenomic Predictors of Recurrence in Glioblastoma-A Systematic Review[J]. Journal of personalized medicine, 2022, 12(3): 402. DOI: 10.3390/jpm12030402.
[42]
Jiang J, Zhang XL, Zhou JL. Research progress on isocitrate dehydrogenase genotype and imaging of glioma[J]. Chin J Magn Reson Imaging, 2021, 107(5): 103-106. DOI: 10.12015/issn.1674-8034.2021.05.025.
[43]
Mao J, Zeng W, Zhang Q, et al. Differentiation between high-grade gliomas and solitary brain metastases: a comparison of five diffusion-weighted MRI models[J]. BMC Med Imaging, 2020, 20(1): 124. DOI: 10.1186/s12880-020-00524-w.
[44]
Zhang H, Schneider T, Wheeler-Kingshott CA, et al. NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain[J]. Neuroimage, 2012, 61(4): 1000-1016. DOI: 10.1016/j.neuroimage.2012.03.072.
[45]
Chong ST, Liu X, Kao H-W, et al. Exploring Peritumoral Neural Tracts by Using Neurite Orientation Dispersion and Density Imaging[J/OL]. Front Neurosci, 2021, 15 [2022-04-08]. https://www.frontiersin.org/articles/10.3389/fnins.2021.702353/full. DOI: 10.3389/fnins.2021.702353.
[46]
Kadota Y, Hirai T, Azuma M, et al. Differentiation between glioblastoma and solitary brain metastasis using neurite orientation dispersion and density imaging[J]. J Neuroradiol, 2020, 47(3): 197-202. DOI: 10.1016/j.neurad.2018.10.005.
[47]
Reisert M, Kellner E, Dhital B, et al. Disentangling micro from mesostructure by diffusion MRI: A Bayesian approach[J]. NeuroImage, 2017, 147: 964-975. DOI: 10.1016/j.neuroimage.2016.09.058.
[48]
Rau A, Reisert M, Kellner E, et al. Increased interstitial fluid in periventricular and deep white matter hyperintensities in patients with suspected idiopathic normal pressure hydrocephalus[J/OL]. Sci Rep, 2021, 11(1) [2022-04-08]. https://www.nature.com/articles/s41598-021-98054-0. DOI: 10.1038/s41598-021-98054-0.
[49]
Demerath T, Donkels C, Reisert M, et al. Gray-White Matter Blurring of the Temporal Pole Associated With Hippocampal Sclerosis: A Microstructural Study Involving 3 T MRI and Ultrastructural Histopathology[J]. Cereb Cortex, 2021, 32(9): 1882-1893. DOI: 10.1093/cercor/bhab320.
[50]
Würtemberger U, Diebold M, Erny D, et al. Diffusion Microstructure Imaging to Analyze Perilesional T2 Signal Changes in Brain Metastases and Glioblastomas[J]. Cancers (Basel), 2022, 14(5): 1155. DOI: 10.3390/cancers14051155.
[51]
Martín-Noguerol T, Mohan S, Santos-Armentia E, et al. Advanced MRI assessment of non-enhancing peritumoral signal abnormality in brain lesions[J/OL]. Eur J Radiol, 2021, 143 [2022-04-08]. https://linkinghub.elsevier.com/retrieve/pii/S0720048X21003818. DOI: 10.1016/j.ejrad.2021.109900.

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