• Experience Exchanges •
Comparison of value of three MRI perfusion techniques in the preoperative assessment of brain glioma grading
Cite this article as: Mei Z, Bi JY. Comparison of value of three MRI perfusion techniques in the preoperative assessment of brain glioma grading[J]. Chin J Magn Reson Imaging, 2022, 13(2): 83-86, 95. DOI:10.12015/issn.1674-8034.2022.02.017.
| [Abstract] Objective To analyze the value of three kinds of magnetic resonance imaging (MRI) perfusion techniques of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), dynamic susceptibility contrast-enhanced perfusion weighted imaging (DSC-PWI) and three-dimensional arterial spin labeling (3D-ASL) in the preoperative assessment of brain glioma (BG) grading.Materials and Methods The clinical data of patients with BG in the hospital were retrospectively analyzed, including 48 cases with preoperative DCE-MRI examination and 34 cases with preoperative DSC-PWI and 3D-ASL examinations. The diagnostic value of DCE-MRI parameters [volume transport constant (Ktrans), rate constant (Kep), extravascular extracellular space fraction (Ve), plasma volume fraction (Vp)], DSC-PWI parameter [relative cerebral blood flow (rCBF)] and 3D-ASL parameter (rCBF) on BG pathological grading was analyzed. The differences in rCBF of DSC-PWI parameter and rCBF of 3D-ASL parameter were compared.Results There were no significant differences in Kep and Vp among different BG pathological grades (P＞0.05). Ktrans and Ve of BG pathological grade Ⅱ were significantly lower than those of grades Ⅲ and Ⅳ (P＜0.05), but there were no statistically significant differences in Ktrans and Ve between grade Ⅲ and grade Ⅳ (P＞0.05). In DSC-PWI and 3D-ASL, there were significant differences in rCBF values between patients with different BG pathological grades and the contralateral hemisphere, gray matter, and white matter (P＜0.05), and the rCBF values of grade Ⅱ were lower than those of grade Ⅲ and Ⅳ (P＜0.05), and the values of grade Ⅲ were lower than those of grade Ⅳ (P＜0.05). ROC curve analysis showed that rCBF values measured by Ktrans, Ve, DSC-PWI and 3D-ASL had high diagnostic value on BG pathology grade Ⅳ (P＜0.05). There was no significant difference in rCBF measured by DSC-PWI and 3D-ASL (P＞0.05).Conclusions The effect of DCE-MRI in judging BG grading is not as good as DSC-PWI and 3D-ASL. DSC-PWI measures more parameters than 3D-ASL, but its safety and non-invasiveness are not as good as 3D-ASL. The three perfusion techniques have their own advantages and disadvantages, thus it is necessary to select the appropriate perfusion technique according to the actual situation in clincial practice. |
| [Keywords] brain glioma；grading；dynamic contrast-enhanced magnetic resonance imaging；dynamic susceptibility contrast-enhanced perfusion weighted imaging；three-dimensional arterial spin labeling |
MEI Zou1
BI Junying2*
1 Department of Radiology, the Third People's Hospital of Hubei Province, Jianghan University, Wuhan 430000, China
2 Department of Medical Imaging Interventional and Magnetic Resonance Imaging, the Third People's Hospital of Hubei Province, Jianghan University, Wuhan 430000, China
Bi JY, E-mail: bijunying123@163.com
Conflicts of interest None.
| Received 2021-05-21 |
| Accepted 2021-12-28 |
| DOI: 10.12015/issn.1674-8034.2022.02.017 |
| Cite this article as: Mei Z, Bi JY. Comparison of value of three MRI perfusion techniques in the preoperative assessment of brain glioma grading[J]. Chin J Magn Reson Imaging, 2022, 13(2): 83-86, 95. DOI:10.12015/issn.1674-8034.2022.02.017. |
[1]
Liu C, Li GH, Li X, et al. Research progress in the comprehensive treatment of brain glioma[J]. Chin J Minima Invasive Neurosurg, 2019, 24(4): 182-185.
DOI:
10.11850/j.issn.1009-122X.2019.04.013.
[2]
Li ZY, Liu BL, Liu BJ, et al. Short term effect of arsenic trioxide combined with brain tumor resection on brain glioma[J]. Pract J Cancer, 2019, 34(2): 231-234.
DOI:
10.3760/cma.j.issn.1001-2346.2020.02.023.
[3]
Kong LW, Li SW. Application of susceptibility weighted imaging in the diagnosis and treatment of brain glioma[J]. Chin J Neurosurg, 2020, 36(2): 214-216.
DOI:
10.3760/cma.j.issn.1001-2346.2020.02.023.
[4]
Xu C, Yu Q, Wang H. Application of multi-parameter magnetic resonance imaging in brain glioma[J]. Pract J Clin Med, 2019,16(4): 22-25.
DOI:
10.3969/j.issn.1672-6170.2019.04.007.
[5]
Brat DJ, Scheithauer BW, Fuller GN, et al. Newly Codified Glial Neoplasms of the 2007 WHO Classification of Tumours of the Central Nervous System: Angiocentric Glioma, Pilomyxoid Astrocytoma and Pituicytoma[J]. Brain Pathol, 2010, 17(3): 319-324.
DOI:
10.1111/j.1750-3639.2007.00082.x.
[6]
Wang DK, Zhu JZ, Liu H, et al. The correlation between Ktrans,Ve value measured by DCE-MRI combined with ADC value and MVD, pathological stage in glioma patients[J]. J Chin Clin Med Imag, 2020, 31(11): 12-15.
DOI:
10.12117/jccmi.2020.11.002.
[7]
Inglese M, Ordidge KL, Honeyfield L, et al. Reliability of dynamic contrast-enhanced magnetic resonance imaging data in primary brain tumours: a comparison of Tofts and shutter speed models[J]. Neuroradiology, 2019, 61(12): 1375-1386.
DOI:
10.1007/s00234-019-02265-2.
[8]
Bai SJ, Qin LJ, Pan HL, et al. Research on the value of quantitative imaging characteristics of MRI in diagnosing preoperative grading of brain glioma[J]. Chin Med Equip, 2019, 16(9): 75-79.
DOI:
10.3969/J.ISSN.1672-8270.2019.09.020.
[9]
Conte GM, Altabella L, Castellano A, et al. Comparison of T1 mapping and fixed T1 method for dynamic contrast-enhanced MRI perfusion in brain gliomas[J]. Eur Radiol, 2019, 29(7): 3467-3479.
DOI:
10.1007/s00330-019-06122-x.
[10]
Wang N, Yin H, Kang XW, et al. Correlation of Ki-67 labeling index with quantitative dynamic contrast-enhanced MRI in glioma[J]. Radiol Prac, 2019, 34(4): 417-421.
DOI:
10.13609/j.cnki.1000-0313.2019.04.010.
[11]
Yu LB, Xu GL. Application of 3D-ASL and DCE-MRI in preoperative grading diagnosis of glioma[J]. Neural Injury and Functional Reconstruction, 2020, 15(1): 62-64.
DOI:
10.16780/j.cnki.sjssgncj.2020.01.018.
[12]
Zhang S, Chiang CY, Magge RS, et al. Texture analysis on conventional MRI images accurately predicts early malignant transformation of low-grade gliomas[J]. Eur Radiol, 2019, 29(6): 2751-2759.
DOI:
10.1007/s00330-018-5921-1.
[13]
Wang Q, Lei D, Yuan Y, et al. Accuracy of magnetic resonance imaging texture analysis in differentiating low-grade from high-grade gliomas: Systematic review and meta-analysis[J]. BMJ Open, 2019, 9(9): e027144.
DOI:
10.1136/bmjopen-2018-027144.
[14]
Karlberg A, Berntsen EM, Johansen H, et al. 18F-FACBC PET/MRI in diagnostic assessment and neurosurgery of gliomas[J]. Clin Nucl Med, 2019, 44(7): 550-559.
DOI:
10.1097/RLU.0000000000002610.
[15]
Hwz A, Gwl A, Wjh A, et al. DSC and DCE Histogram Analyses of Glioma Biomarkers, Including IDH, MGMT, and TERT, on Differentiation and Survival[J]. Acad Radiol, 2020, 27(12): 263-271.
DOI:
10.1016/j.acra.2019.12.010.
[16]
Smits M, Bendszus M, Collette S, et al. Repeatability and reproducibility of relative cerebral blood volume measurement of recurrent glioma in a multicentre trial setting[J]. Eur J Cancer, 2019, 114(6): 89-96.
DOI:
10.1016/j.ejca.2019.03.007.
[17]
Tang F, Liang S, Zhong T, et al. Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs[J]. Eur Radiol, 2019, 30(12): 823-832.
DOI:
10.1007/s00330-019-06441-z.
[18]
Yang Y, Yang Y, Wu X, et al. Adding DSC PWI and DWI to BT-RADS can help identify postoperative recurrence in patients with high-grade gliomas[J]. J Neurooncol, 2020, 146(2): 363-371.
DOI:
10.1007/s11060-019-03387-6.
[19]
Pang H, Dang X, Ren Y, et al. 3D-ASL perfusion correlates with VEGF expression and overall survival in glioma patients: Comparison of quantitative perfusion and pathology on accurate spatial location-matched basis[J]. J Magn Reson Imaging, 2019, 50(1): 209-220.
DOI:
10.1002/jmri.26562.
[20]
Alsaedi A, Doniselli F, Jger HR, et al. The value of arterial spin labelling in adults glioma grading: systematic review and meta-analysis[J]. Oncotarget, 2019, 10(16): 1589-1601.
DOI:
10.18632/oncotarget.26674.
[21]
Xi YB, Kang XW, Wang N, et al. Differentiation of primary central nervous system lymphoma from high-grade glioma and brain metastasis using arterial spin labeling and dynamic contrast-enhanced magnetic resonance imaging[J]. Eur J Radiol, 2019, 112(3): 59-64.
DOI:
10.1016/j.ejrad.2019.01.008.
[22]
Bell LC, Stokes AM, Quarles CC. Analysis of postprocessing steps for residue function dependent dynamic susceptibility contrast (DSC)-MRI biomarkers and their clinical impact on glioma grading for both 1.5 and 3T[J]. J Magn Reson Imaging, 2020, 51(2): 547-553.
DOI:
10.1002/jmri.26837.
