Top

Published in:

Open Access 01-12-2016 | Functional Neuroradiology

Prognostic value of preoperative dynamic contrast-enhanced MRI perfusion parameters for high-grade glioma patients

Authors: Agne Ulyte, Vasileios K. Katsaros, Evangelia Liouta, Georgios Stranjalis, Christos Boskos, Nickolas Papanikolaou, Jurgita Usinskiene, Sotirios Bisdas

Published in: Neuroradiology | Issue 12/2016

Abstract

Introduction

The prognostic value of the dynamic contrast-enhanced (DCE) MRI perfusion and its histogram analysis-derived metrics is not well established for high-grade glioma (HGG) patients. The aim of this prospective study was to investigate DCE perfusion transfer coefficient (K^trans), vascular plasma volume fraction (v_p), extracellular volume fraction (v_e), reverse transfer constant (k_ep), and initial area under gadolinium concentration time curve (IAUGC) as predictors of progression-free (PFS) and overall survival (OS) in HGG patients.

Methods

Sixty-nine patients with suspected anaplastic astrocytoma or glioblastoma underwent preoperative DCE-MRI scans. DCE perfusion whole tumor region histogram parameters, clinical details, and PFS and OS data were obtained. Univariate, multivariate, and Kaplan–Meier survival analyses were conducted. Receiver operating characteristic (ROC) curve analysis was employed to identify perfusion parameters with the best differentiation performance.

Results

On univariate analysis, v_e and skewness of v_p had significant negative impacts, while k_ep had significant positive impact on OS (P < 0.05). v_e was also a negative predictor of PFS (P < 0.05). Patients with lower v_e and IAUGC had longer median PFS and OS on Kaplan–Meier analysis (P < 0.05). K^trans and v_e could also differentiate grade III from IV gliomas (area under the curve 0.819 and 0.791, respectively).

Conclusions

High v_e is a consistent predictor of worse PFS and OS in HGG glioma patients. v_p skewness and k_ep are also predictive for OS. K^trans and v_e demonstrated the best diagnostic performance for differentiating grade III from IV gliomas.

Wen PY, Kesari S (2008) Malignant gliomas in adults. N Engl J Med 359(5):492–507. doi:10.1056/NEJMra0708126 CrossRefPubMed

Smoll NR, Schaller K, Gautschi OP (2013) Long-term survival of patients with glioblastoma multiforme (GBM). Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia 20(5):670–675. doi:10.1016/j.jocn.2012.05.040 CrossRef

Theeler BJ, Yung WK, Fuller GN, De Groot JF (2012) Moving toward molecular classification of diffuse gliomas in adults. Neurology 79(18):1917–1926. doi:10.1212/WNL.0b013e318271f7cb CrossRefPubMedPubMedCentral

Hirai T, Murakami R, Nakamura H, Kitajima M, Fukuoka H, Sasao A, Akter M, Hayashida Y, Toya R, Oya N, Awai K, Iyama K, Kuratsu JI, Yamashita Y (2008) Prognostic value of perfusion MR imaging of high-grade astrocytomas: long-term follow-up study. AJNR Am J Neuroradiol 29(8):1505–1510. doi:10.3174/ajnr.A1121 CrossRefPubMed

Ducray F, El Hallani S, Idbaih A (2009) Diagnostic and prognostic markers in gliomas. Curr Opin Oncol 21(6):537–542. doi:10.1097/CCO.0b013e32833065a7 CrossRefPubMed

Saraswathy S, Crawford FW, Lamborn KR, Pirzkall A, Chang S, Cha S, Nelson SJ (2009) Evaluation of MR markers that predict survival in patients with newly diagnosed GBM prior to adjuvant therapy. J Neuro-Oncol 91(1):69–81. doi:10.1007/s11060-008-9685-3 CrossRef

Law M, Young RJ, Babb JS, Peccerelli N, Chheang S, Gruber ML, Miller DC, Golfinos JG, Zagzag D, Johnson G (2008) Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology 247(2):490–498. doi:10.1148/radiol.2472070898 CrossRefPubMedPubMedCentral

Aronen HJ, Gazit IE, Louis DN, Buchbinder BR, Pardo FS, Weisskoff RM, Harsh GR, Cosgrove GR, Halpern EF, Hochberg FH, et al. (1994) Cerebral blood volume maps of gliomas: comparison with tumor grade and histologic findings. Radiology 191(1):41–51. doi:10.1148/radiology.191.1.8134596 CrossRefPubMed

Russell SM, Elliott R, Forshaw D, Golfinos JG, Nelson PK, Kelly PJ (2009) Glioma vascularity correlates with reduced patient survival and increased malignancy. Surg Neurol 72(3):242–246 . doi:10.1016/j.surneu.2008.11.012discussion 246-247CrossRefPubMed

10.

Bonekamp D, Deike K, Wiestler B, Wick W, Bendszus M, Radbruch A, Heiland S (2015) Association of overall survival in patients with newly diagnosed glioblastoma with contrast-enhanced perfusion MRI: comparison of intraindividually matched T1- and T2 (*)-based bolus techniques. Journal of magnetic resonance imaging : JMRI 42(1):87–96. doi:10.1002/jmri.24756 CrossRefPubMed

11.

Mills SJ, Soh C, Rose CJ, Cheung S, Zhao S, Parker GJ, Jackson A (2010) Candidate biomarkers of extravascular extracellular space: a direct comparison of apparent diffusion coefficient and dynamic contrast-enhanced MR imaging—derived measurement of the volume of the extravascular extracellular space in glioblastoma multiforme. AJNR Am J Neuroradiol 31(3):549–553. doi:10.3174/ajnr.A1844 CrossRefPubMed

12.

Li X, Zhu Y, Kang H, Zhang Y, Liang H, Wang S, Zhang W (2015) Glioma grading by microvascular permeability parameters derived from dynamic contrast-enhanced MRI and intratumoral susceptibility signal on susceptibility weighted imaging. Cancer imaging : the official publication of the International Cancer Imaging Society 15:4. doi:10.1186/s40644-015-0039-z CrossRef

13.

Cha S, Yang L, Johnson G, Lai A, Chen MH, Tihan T, Wendland M, Dillon WP (2006) Comparison of microvascular permeability measurements, K(trans), determined with conventional steady-state T1-weighted and first-pass T2*-weighted MR imaging methods in gliomas and meningiomas. AJNR Am J Neuroradiol 27(2):409–417PubMed

14.

Zhang N, Zhang L, Qiu B, Meng L, Wang X, Hou BL (2012) Correlation of volume transfer coefficient Ktrans with histopathologic grades of gliomas. Journal of magnetic resonance imaging : JMRI 36(2):355–363. doi:10.1002/jmri.23675 CrossRefPubMedPubMedCentral

15.

Awasthi R, Rathore RK, Soni P, Sahoo P, Awasthi A, Husain N, Behari S, Singh RK, Pandey CM, Gupta RK (2012) Discriminant analysis to classify glioma grading using dynamic contrast-enhanced MRI and immunohistochemical markers. Neuroradiology 54(3):205–213. doi:10.1007/s00234-011-0874-y CrossRefPubMed

16.

Arevalo-Perez J, Peck KK, Young RJ, Holodny AI, Karimi S, Lyo JK (2015) Dynamic contrast-enhanced perfusion MRI and diffusion-weighted imaging in grading of gliomas. Journal of neuroimaging : official journal of the American Society of Neuroimaging. doi:10.1111/jon.12239

17.

Jain KK, Sahoo P, Tyagi R, Mehta A, Patir R, Vaishya S, Prakash N, Vasudev N, Gupta RK (2015) Prospective glioma grading using single-dose dynamic contrast-enhanced perfusion MRI. Clin Radiol 70(10):1128–1135. doi:10.1016/j.crad.2015.06.076 CrossRefPubMed

18.

Jia ZZ, Gu HM, Zhou XJ, Shi JL, Li MD, Zhou GF, Wu XH (2015) The assessment of immature microvascular density in brain gliomas with dynamic contrast-enhanced magnetic resonance imaging. Eur J Radiol 84(9):1805–1809. doi:10.1016/j.ejrad.2015.05.035 CrossRefPubMed

19.

20.

Jensen RL, Mumert ML, Gillespie DL, Kinney AY, Schabel MC, Salzman KL (2014) Preoperative dynamic contrast-enhanced MRI correlates with molecular markers of hypoxia and vascularity in specific areas of intratumoral microenvironment and is predictive of patient outcome. Neuro-Oncology 16(2):280–291. doi:10.1093/neuonc/not148 CrossRefPubMed

21.

Kickingereder P, Wiestler B, Graf M, Heiland S, Schlemmer HP, Wick W, Wick A, Bendszus M, Radbruch A (2015) Evaluation of dynamic contrast-enhanced MRI derived microvascular permeability in recurrent glioblastoma treated with bevacizumab. J Neuro-Oncol 121(2):373–380. doi:10.1007/s11060-014-1644-6 CrossRef

22.

Verhoeff JJ, Lavini C, van Linde ME, Stalpers LJ, Majoie CB, Reijneveld JC, van Furth WR, Richel DJ (2010) Bevacizumab and dose-intense temozolomide in recurrent high-grade glioma. Annals of oncology : official journal of the European Society for Medical Oncology / ESMO 21(8):1723–1727. doi:10.1093/annonc/mdp591 CrossRef

23.

Bisdas S, Smrdel U, Bajrovic FF, Surlan-Popovic K (2014) Assessment of progression-free-survival in glioblastomas by intratreatment dynamic contrast-enhanced MRI. Clin Neuroradiol. doi:10.1007/s00062-014-0328-0 PubMed

24.

Choi YS, Kim DW, Lee SK, Chang JH, Kang SG, Kim EH, Kim SH, Rim TH, Ahn SS (2015) The added prognostic value of preoperative dynamic contrast-enhanced MRI histogram analysis in patients with glioblastoma: analysis of overall and progression-free survival. AJNR Am J Neuroradiol 36(12):2235–2241. doi:10.3174/ajnr.A4449 CrossRefPubMed

25.

Burth S, Kickingereder P, Eidel O, Tichy D, Bonekamp D, Weberling L, Wick A, Low S, Hertenstein A, Nowosielski M, Schlemmer HP, Wick W, Bendszus M, Radbruch A (2016) Clinical parameters outweigh diffusion- and perfusion-derived MRI parameters in predicting survival in newly diagnosed glioblastoma. Neuro-Oncology. doi:10.1093/neuonc/now122 PubMed

26.

Nguyen TB, Cron GO, Mercier JF, Foottit C, Torres CH, Chakraborty S, Woulfe J, Jansen GH, Caudrelier JM, Sinclair J, Hogan MJ, Thornhill RE, Cameron IG (2015) Preoperative prognostic value of dynamic contrast-enhanced MRI-derived contrast transfer coefficient and plasma volume in patients with cerebral gliomas. AJNR Am J Neuroradiol 36(1):63–69. doi:10.3174/ajnr.A4006 CrossRefPubMed

27.

Mills SJ, Patankar TA, Haroon HA, Baleriaux D, Swindell R, Jackson A (2006) Do cerebral blood volume and contrast transfer coefficient predict prognosis in human glioma? AJNR Am J Neuroradiol 27(4):853–858PubMed

28.

Stupp R, Brada M, van den Bent MJ, Tonn JC, Pentheroudakis G, Group EGW (2014) High-grade glioma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Annals of oncology : official journal of the European Society for Medical Oncology / ESMO 25(Suppl 3):iii93–ii101. doi:10.1093/annonc/mdu050 CrossRef

29.

Stupp R, Roila F (2008) Malignant glioma: ESMO clinical recommendations for diagnosis, treatment and follow-up. Annals of oncology : official journal of the European Society for Medical Oncology / ESMO 19(Suppl 2):ii83–ii85. doi:10.1093/annonc/mdn099

30.

Stupp R, Tonn J-C, Brada M, Pentheroudakis G, Group ObotEGW (2010) High-grade malignant glioma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol 21(suppl 5):v190–v193. doi:10.1093/annonc/mdq187 CrossRefPubMed

31.

Wen PY, Macdonald DR, Reardon DA, Cloughesy TF, Sorensen AG, Galanis E, Degroot J, Wick W, Gilbert MR, Lassman AB, Tsien C, Mikkelsen T, Wong ET, Chamberlain MC, Stupp R, Lamborn KR, Vogelbaum MA, van den Bent MJ, Chang SM (2010) Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 28(11):1963–1972. doi:10.1200/jco.2009.26.3541 CrossRef

32.

Tofts PS, Kermode AG (1991) Measurement of the blood-brain barrier permeability and leakage space using dynamic MR imaging. 1. Fundamental concepts. Magn Reson Med 17(2):357–367CrossRefPubMed

33.

Orton MR, d'Arcy JA, Walker-Samuel S, Hawkes DJ, Atkinson D, Collins DJ, Leach MO (2008) Computationally efficient vascular input function models for quantitative kinetic modelling using DCE-MRI. Phys Med Biol 53(5):1225–1239. doi:10.1088/0031-9155/53/5/005 CrossRefPubMed

34.

Parker GJ, Roberts C, Macdonald A, Buonaccorsi GA, Cheung S, Buckley DL, Jackson A, Watson Y, Davies K, Jayson GC (2006) Experimentally-derived functional form for a population-averaged high-temporal-resolution arterial input function for dynamic contrast-enhanced MRI. Magn Reson Med 56(5):993–1000. doi:10.1002/mrm.21066 CrossRefPubMed

35.

Leach MO, Morgan B, Tofts PS, Buckley DL, Huang W, Horsfield MA, Chenevert TL, Collins DJ, Jackson A, Lomas D, Whitcher B, Clarke L, Plummer R, Judson I, Jones R, Alonzi R, Brunner T, Koh DM, Murphy P, Waterton JC, Parker G, Graves MJ, Scheenen TW, Redpath TW, Orton M, Karczmar G, Huisman H, Barentsz J, Padhani A, Experimental Cancer Medicine Centres Imaging Network Steering C (2012) Imaging vascular function for early stage clinical trials using dynamic contrast-enhanced magnetic resonance imaging. Eur Radiol 22(7):1451–1464. doi:10.1007/s00330-012-2446-x CrossRefPubMed

36.

Spampinato MV, Schiarelli C, Cianfoni A, Giglio P, Welsh CT, Bisdas S, Rumboldt Z (2013) Correlation between cerebral blood volume measurements by perfusion-weighted magnetic resonance imaging and two-year progression-free survival in gliomas. Neuroradiol J 26(4):385–395CrossRefPubMedPubMedCentral

37.

Mangla R, Ginat DT, Kamalian S, Milano MT, Korones DN, Walter KA, Ekholm S (2014) Correlation between progression free survival and dynamic susceptibility contrast MRI perfusion in WHO grade III glioma subtypes. J Neuro-Oncol 116(2):325–331. doi:10.1007/s11060-013-1298-9 CrossRef

38.

Heye T, Merkle EM, Reiner CS, Davenport MS, Horvath JJ, Feuerlein S, Breault SR, Gall P, Bashir MR, Dale BM, Kiraly AP, Boll DT (2013) Reproducibility of dynamic contrast-enhanced MR imaging. Part II. Comparison of intra- and interobserver variability with manual region of interest placement versus semiautomatic lesion segmentation and histogram analysis. Radiology 266(3):812–821. doi:10.1148/radiol.12120255 CrossRefPubMed

39.

Leach MO, Brindle KM, Evelhoch JL, Griffiths JR, Horsman MR, Jackson A, Jayson GC, Judson IR, Knopp MV, Maxwell RJ, McIntyre D, Padhani AR, Price P, Rathbone R, Rustin GJ, Tofts PS, Tozer GM, Vennart W, Waterton JC, Williams SR, Workman P (2005) The assessment of antiangiogenic and antivascular therapies in early-stage clinical trials using magnetic resonance imaging: issues and recommendations. Br J Cancer 92(9):1599–1610. doi:10.1038/sj.bjc.6602550 CrossRefPubMedPubMedCentral

40.

O'Connor JP, Jayson GC (2012) Do imaging biomarkers relate to outcome in patients treated with VEGF inhibitors? Clinical cancer research : an official journal of the American Association for Cancer Research 18(24):6588–6598. doi:10.1158/1078-0432.ccr-12-1501 CrossRef

41.

Bernstein JM, Homer JJ, West CM (2014) Dynamic contrast-enhanced magnetic resonance imaging biomarkers in head and neck cancer: potential to guide treatment? A systematic review. Oral Oncol 50(10):963–970. doi:10.1016/j.oraloncology.2014.07.011 CrossRefPubMed

42.

Peng SL, Chen CF, Liu HL, Lui CC, Huang YJ, Lee TH, Chang CC, Wang FN (2013) Analysis of parametric histogram from dynamic contrast-enhanced MRI: application in evaluating brain tumor response to radiotherapy. NMR Biomed 26(4):443–450. doi:10.1002/nbm.2882 CrossRefPubMed

43.

Kreisl TN, Zhang W, Odia Y, Shih JH, Butman JA, Hammoud D, Iwamoto FM, Sul J, Fine HA (2011) A phase II trial of single-agent bevacizumab in patients with recurrent anaplastic glioma. Neuro-Oncology 13(10):1143–1150. doi:10.1093/neuonc/nor091 CrossRefPubMedPubMedCentral

44.

Tofts PS, Brix G, Buckley DL, Evelhoch JL, Henderson E, Knopp MV, Larsson HB, Lee TY, Mayr NA, Parker GJ, Port RE, Taylor J, Weisskoff RM (1999) Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols. Journal of magnetic resonance imaging : JMRI 10(3):223–232CrossRefPubMed

45.

Aref M, Chaudhari AR, Bailey KL, Aref S, Wiener EC (2008) Comparison of tumor histology to dynamic contrast enhanced magnetic resonance imaging-based physiological estimates. Magn Reson Imaging 26(9):1279–1293. doi:10.1016/j.mri.2008.02.015 CrossRefPubMed

46.

Pike MM, Stoops CN, Langford CP, Akella NS, Nabors LB, Gillespie GY (2009) High-resolution longitudinal assessment of flow and permeability in mouse glioma vasculature: sequential small molecule and SPIO dynamic contrast agent MRI. Magn Reson Med 61(3):615–625. doi:10.1002/mrm.21931 CrossRefPubMedPubMedCentral

47.

Aryal MP, Nagaraja TN, Keenan KA, Bagher-Ebadian H, Panda S, Brown SL, Cabral G, Fenstermacher JD, Ewing JR (2014) Dynamic contrast enhanced MRI parameters and tumor cellularity in a rat model of cerebral glioma at 7 T. Magn Reson Med 71(6):2206–2214. doi:10.1002/mrm.24873 CrossRefPubMed

48.

Koh TS, Shi W, Thng CH, Kwek JW, Bisdas S, Khoo JB (2012) Interpretation and applicability of empirical tissue enhancement metrics in dynamic contrast-enhanced MRI based on a multiple pathway model. Phys Med Biol 57(15):N279–N294. doi:10.1088/0031-9155/57/15/N279 CrossRefPubMed

49.

Mills SJ, du Plessis D, Pal P, Thompson G, Buonacorrsi G, Soh C, Parker GJ, Jackson A (2016) Mitotic activity in glioblastoma correlates with estimated extravascular extracellular space derived from dynamic contrast-enhanced MR imaging. AJNR Am J Neuroradiol 37(5):811–817. doi:10.3174/ajnr.A4623 CrossRefPubMed

50.

Jia Z, Geng D, Liu Y, Chen X, Zhang J (2013) Low-grade and anaplastic oligodendrogliomas: differences in tumour microvascular permeability evaluated with dynamic contrast-enhanced magnetic resonance imaging. Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia 20(8):1110–1113. doi:10.1016/j.jocn.2012.09.019 CrossRef

51.

Yun TJ, Park CK, Kim TM, Lee SH, Kim JH, Sohn CH, Park SH, Kim IH, Choi SH (2015) Glioblastoma treated with concurrent radiation therapy and temozolomide chemotherapy: differentiation of true progression from pseudoprogression with quantitative dynamic contrast-enhanced MR imaging. Radiology 274(3):830–840. doi:10.1148/radiol.14132632 CrossRefPubMed

52.

Just N (2014) Improving tumour heterogeneity MRI assessment with histograms. Br J Cancer 111(12):2205–2213. doi:10.1038/bjc.2014.512 CrossRefPubMedPubMedCentral

53.

Tofts PS, Wicks DA, Barker GJ (1991) The MRI measurement of NMR and physiological parameters in tissue to study disease process. Prog Clin Biol Res 363:313–325PubMed

54.

Arevalo-Perez J, Kebede AA, Peck KK, Diamond E, Holodny AI, Rosenblum M, Rubel J, Gaal J, Hatzoglou V (2015) Dynamic contrast-enhanced MRI in low-grade versus anaplastic oligodendrogliomas. Journal of neuroimaging : official journal of the American Society of Neuroimaging. doi:10.1111/jon.12320

55.

Falk A, Fahlstrom M, Rostrup E, Berntsson S, Zetterling M, Morell A, Larsson HB, Smits A, Larsson EM (2014) Discrimination between glioma grades II and III in suspected low-grade gliomas using dynamic contrast-enhanced and dynamic susceptibility contrast perfusion MR imaging: a histogram analysis approach. Neuroradiology 56(12):1031–1038. doi:10.1007/s00234-014-1426-z CrossRefPubMed

56.

Cohen AL, Holmen SL, Colman H (2013) IDH1 and IDH2 mutations in gliomas. Current neurology and neuroscience reports 13(5):345. doi:10.1007/s11910-013-0345-4 CrossRefPubMedPubMedCentral

57.

Zou P, Xu H, Chen P, Yan Q, Zhao L, Zhao P, Gu A (2013) IDH1/IDH2 mutations define the prognosis and molecular profiles of patients with gliomas: a meta-analysis. PLoS One 8(7):e68782. doi:10.1371/journal.pone.0068782 CrossRefPubMedPubMedCentral

58.

Lee S, Choi SH, Ryoo I, Yoon TJ, Kim TM, Lee SH, Park CK, Kim JH, Sohn CH, Park SH, Kim IH (2015) Evaluation of the microenvironmental heterogeneity in high-grade gliomas with IDH1/2 gene mutation using histogram analysis of diffusion-weighted imaging and dynamic-susceptibility contrast perfusion imaging. J Neuro-Oncol 121(1):141–150. doi:10.1007/s11060-014-1614-z CrossRef

Title: Prognostic value of preoperative dynamic contrast-enhanced MRI perfusion parameters for high-grade glioma patients
Authors: Agne Ulyte
Vasileios K. Katsaros
Evangelia Liouta
Georgios Stranjalis
Christos Boskos
Nickolas Papanikolaou
Jurgita Usinskiene
Sotirios Bisdas
Publication date: 01-12-2016
Publisher: Springer Berlin Heidelberg
Published in: Neuroradiology / Issue 12/2016
Print ISSN: 0028-3940
Electronic ISSN: 1432-1920
DOI: https://doi.org/10.1007/s00234-016-1741-7

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Prognostic value of preoperative dynamic contrast-enhanced MRI perfusion parameters for high-grade glioma patients

Abstract

Introduction

Methods

Results

Conclusions

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Introduction

Methods

Results

Conclusions

Please log in to get access to this content

Other articles of this Issue 12/2016

Annual Report 2016

Erratum to: 38th EUROPEAN SOCIETY OF NEURORADIOLOGY Diagnostic and Interventional ANNUAL MEETING

Endovascular treatment of acute internal carotid artery dissections: technical considerations, clinical and angiographic outcome

Editorial: Founding members of the ESNR

Fractional anisotropy and diffusivity changes in thyroid-associated orbitopathy

Micro-structural white matter abnormalities in type 2 diabetic patients: a DTI study using TBSS analysis