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Abstract

Background

Since oligodendroglial tumors are sensitive to chemotherapy and have a better prognosis, the differentiation of oligodendroglial tumors (OT) from astrocytic tumors (AT) is important.

Purpose

To investigate the perfusion and permeability parameters that differentiate grade II and III OT from AT, using dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI).

Material and Methods

We retrospectively reviewed the DCE and DSC MRIs of 39 patients with OT (OTs, n = 19; grade II, n = 12 and grade III, n = 7) and AT (ATs, n = 20; grade II, n = 7 and grade III, n = 13). Glioblastomas were not included. Various histogram parameters of relative cerebral blood volume, volume transfer constant (Ktrans), flux rate constant (Kep), plasma volume fraction (Vp), and extravascular extracellular volume fraction (Ve) from DSC and DCE MRI, were compared between the two groups. Univariable and multivariable logistic regression were used to distinguish OT from AT. Receiver operating characteristic (ROC) curve analysis was performed.

Results

On the results of DCE MRI, most of the histogram parameters of Ktrans, Kep, and Ve showed tendencies toward higher values in OT than AT. Multivariable logistic regression revealed that the 50th Kep and 95th Ktrans were the most significant parameters predictive of OT, with an odds ratio of 3.7 and 2.5, respectively (P = 0.004 and 0.03). The area under the curve from the ROC curve analysis for the 50th Kep and the 95th Ktrans were 0.81 and 0.80, respectively.

Conclusion

The DCE MRI-derived parameters of Ktrans and Kep could facilitate differentiation of OT from AT.

Keywords

Oligodendroglial tumors astrocytomas dynamic susceptibility contrast MRI dynamic contrast-enhanced MRI magnetic resonance imaging (MRI)

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References

Louis

Perry

Reifenberger

et al.

The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathol 2016; 131: 803–820.

Narang

Jain

Scarpace

et al.

Tumor vascular leakiness and blood volume estimates in oligodendrogliomas using perfusion CT: an analysis of perfusion parameters helping further characterize genetic subtypes as well as differentiate from astroglial tumors. J Neurooncol 2011; 102: 287–293.

Saito

Yamasaki

Kajiwara

et al.

Role of perfusion-weighted imaging at 3T in the histopathological differentiation between astrocytic and oligodendroglial tumors. Eur J Radiol 2012; 81: 1863–1869.

Jia

Geng

Liu

et al.

Low-grade and anaplastic oligodendrogliomas: differences in tumour microvascular permeability evaluated with dynamic contrast-enhanced magnetic resonance imaging. J Clin Neurosci 2013; 20: 1110–1113.

Netto

Bleil

Hilbig

et al.

Immunohistochemical evaluation of the microvascular density through the expression of TGF-beta (CD 105/endoglin) and CD 34 receptors and expression of the vascular endothelial growth factor (VEGF) in oligodendrogliomas. Neuropathology 2008; 28: 17–23.

Ricard

Idbaih

Ducray

et al.

Primary brain tumours in adults. Lancet 2012; 379: 1984–1996.

Smith

Chang

Lamborn

et al.

Role of extent of resection in the long-term outcome of low-grade hemispheric gliomas. J Clin Oncol 2008; 26: 1338–1345.

Yun

Park

Kim

et al.

Glioblastoma treated with concurrent radiation therapy and temozolomide chemotherapy: differentiation of true progression from pseudoprogression with quantitative dynamic contrast-enhanced MR imaging. Radiology 2015; 274: 830–840.

Yamaguchi

Kobayashi

Terasaka

et al.

The impact of extent of resection and histological subtype on the outcome of adult patients with high-grade gliomas. Jpn J Clin Oncol 2012; 42: 270–277.

10.

Lecavalier-Barsoum

Quon

Abdulkarim

. Adjuvant treatment of anaplastic oligodendrogliomas and oligoastrocytomas. Cochrane Database Syst Rev 2014; 5: CD007104–CD007104.

11.

Jenkinson

Smith

Joyce

et al.

Cerebral blood volume, genotype and chemosensitivity in oligodendroglial tumours. Neuroradiology 2006; 48: 703–713.

12.

Khalid

Carone

Dumrongpisutikul

et al.

Imaging characteristics of oligodendrogliomas that predict grade. Am J Neuroradiol 2012; 33: 852–857.

13.

Zulfiqar

Dumrongpisutikul

Intrapiromkul

et al.

Detection of intratumoral calcification in oligodendrogliomas by susceptibility-weighted MR imaging. Am J Neuroradiol 2012; 33: 858–864.

14.

Zhou

Yang

et al.

Vascular patterns of brain tumors. Int J Surg Pathol 2011; 19: 709–717.

15.

Cha

Tihan

Crawford

et al.

Differentiation of low-grade oligodendrogliomas from low-grade astrocytomas by using quantitative blood-volume measurements derived from dynamic susceptibility contrast-enhanced MR imaging. Am J Neuroradiol 2005; 26: 266–273.

16.

Kapoor

Gocke

Chawla

et al.

Magnetic resonance perfusion-weighted imaging defines angiogenic subtypes of oligodendroglioma according to 1p19q and EGFR status. J Neurooncol 2009; 92: 373–386.

17.

Kickingereder

Sahm

Wiestler

et al.

Evaluation of microvascular permeability with dynamic contrast-enhanced MRI for the differentiation of primary CNS lymphoma and glioblastoma: radiologic-pathologic correlation. Am J Neuroradiol 2014; 35: 1503–1508.

18.

Lev

Ozsunar

Henson

et al.

Glial tumor grading and outcome prediction using dynamic spin-echo MR susceptibility mapping compared with conventional contrast-enhanced MR: confounding effect of elevated rCBV of oligodendrogliomas [corrected]. Am J Neuroradiol 2004; 25: 214–221.

19.

Emblem

Scheie

Due-Tonnessen

et al.

Histogram analysis of MR imaging-derived cerebral blood volume maps: combined glioma grading and identification of low-grade oligodendroglial subtypes. Am J Neuroradiol 2008; 29: 1664–1670.

20.

Yoon

Ahn

Lee

et al.

Differential diagnosis of oligodendroglial and astrocytic tumors using imaging results: the added value of perfusion MR imaging. Neuroradiology 2017; 59: 665–675.

21.

Tofts

Brix

Buckley

et al.

Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols. J Magn Reson Imaging 1999; 10: 223–232.

22.

Paldino

Barboriak

. Fundamentals of quantitative dynamic contrast-enhanced MR imaging. Magn Reson Imaging Clin N Am 2009; 17: 277–289.

23.

Boxerman

Schmainda

Weisskoff

. Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not. Am J Neuroradiol 2006; 27: 859–867.

24.

Welker

Boxerman

Kalnin

. ASFNR recommendations for clinical performance of MR dynamic susceptibility contrast perfusion imaging of the brain. Am J Neuroradiol 2015; 36: E41–51.

25.

Paulson

Schmainda

. Comparison of dynamic susceptibility-weighted contrast-enhanced MR methods: recommendations for measuring relative cerebral blood volume in brain tumors. Radiology 2008; 249: 601–613.

26.

Jung

Yeom

Kim

et al.

Glioma: Application of histogram analysis of pharmacokinetic parameters from T1-weighted dynamic contrast-enhanced MR imaging to tumor grading. Am J Neuroradiol 2014; 35: 1103–1110.

27.

Tietze

Mouridsen

Mikkelsen

. The impact of reliable prebolus T 1 measurements or a fixed T 1 value in the assessment of glioma patients with dynamic contrast enhancing MRI. Neuroradiology 2015; 57: 561–572.

28.

Essig

Nguyen

Shiroishi

et al.

Perfusion MRI: the five most frequently asked clinical questions. Am J Roentgenol 2013; 201: W495–510.

29.

Choi

Kim

Lee

et al.

The added prognostic value of preoperative dynamic contrast-enhanced MRI histogram analysis in patients with glioblastoma: analysis of overall and progression-free survival. Am J Neuroradiol 2015; 36: 2235–2241.

30.

Christov

Adle-Biassette

Le Guerinel

et al.

Immunohistochemical detection of vascular endothelial growth factor (VEGF) in the vasculature of oligodendrogliomas. Neuropathol Appl Neurobiol 1998; 24: 29–35.

31.

Maia

Jr Malheiros

da Rocha

et al.

MR cerebral blood volume maps correlated with vascular endothelial growth factor expression and tumor grade in nonenhancing gliomas. Am J Neuroradiol 2005; 26: 777–783.

32.

Mills

Patankar

Haroon

et al.

Do cerebral blood volume and contrast transfer coefficient predict prognosis in human glioma?

Am J Neuroradiol 2006; 27: 853–858.

33.

Chan

Leung

Wong

et al.

Expression of vascular endothelial growth factor and its receptors in the anaplastic progression of astrocytoma, oligodendroglioma, and ependymoma. Am J Surg Pathol 1998; 22: 816–826.

34.

Nguyen

Cron

Mercier

et al.

Preoperative prognostic value of dynamic contrast-enhanced MRI-derived contrast transfer coefficient and plasma volume in patients with cerebral gliomas. Am J Neuroradiol 2015; 36: 63–69.

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Differentiation of grade II and III oligodendrogliomas from grade II and III astrocytomas: a histogram analysis of perfusion parameters derived from dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) MRI

Abstract

Background

Purpose

Material and Methods

Results

Conclusion

Keywords

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References

Supplementary Material