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06.09.2017 | Original Article

Whole-tumor histogram analysis of the cerebral blood volume map: tumor volume defined by 11C-methionine positron emission tomography image improves the diagnostic accuracy of cerebral glioma grading

verfasst von: Rongli Wu, Yoshiyuki Watanabe, Atsuko Arisawa, Hiroto Takahashi, Hisashi Tanaka, Yasunori Fujimoto, Tadashi Watabe, Kayako Isohashi, Jun Hatazawa, Noriyuki Tomiyama

Erschienen in: Japanese Journal of Radiology | Ausgabe 10/2017

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Abstract

Purpose

This study aimed to compare the tumor volume definition using conventional magnetic resonance (MR) and 11C-methionine positron emission tomography (MET/PET) images in the differentiation of the pre-operative glioma grade by using whole-tumor histogram analysis of normalized cerebral blood volume (nCBV) maps.

Materials and methods

Thirty-four patients with histopathologically proven primary brain low-grade gliomas (n = 15) and high-grade gliomas (n = 19) underwent pre-operative or pre-biopsy MET/PET, fluid-attenuated inversion recovery, dynamic susceptibility contrast perfusion-weighted magnetic resonance imaging, and contrast-enhanced T1-weighted at 3.0 T. The histogram distribution derived from the nCBV maps was obtained by co-registering the whole tumor volume delineated on conventional MR or MET/PET images, and eight histogram parameters were assessed.

Results

The mean nCBV value had the highest AUC value (0.906) based on MET/PET images. Diagnostic accuracy significantly improved when the tumor volume was measured from MET/PET images compared with conventional MR images for the parameters of mean, 50th, and 75th percentile nCBV value (p = 0.0246, 0.0223, and 0.0150, respectively).

Conclusion

Whole-tumor histogram analysis of CBV map provides more valuable histogram parameters and increases diagnostic accuracy in the differentiation of pre-operative cerebral gliomas when the tumor volume is derived from MET/PET images.

Sadeghi N, Salmon I, Tang BN, Denolin V, Levivier M, Wikler D, et al. Correlation between dynamic susceptibility contrast perfusion MRI and methionine metabolism in brain gliomas: preliminary results. J Magnet Reson Imaging JMRI. 2006;24(5):989–94.CrossRef

Tietze A, Boldsen JK, Mouridsen K, Ribe L, Dyve S, Cortnum S, et al. Spatial distribution of malignant tissue in gliomas: correlations of 11C-l-methionine positron emission tomography and perfusion- and diffusion-weighted magnetic resonance imaging. Acta Radiol. 2015;56(9):1135–44.CrossRefPubMed

Law M, Yang S, Babb JS, Knopp EA, Golfinos JG, Zagzag D, et al. Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. Am J Neuroradiol. 2004;25(5):746–55.PubMed

Aronen HJ, Gazit IE, Louis DN, Buchbinder BR, Pardo FS, Weisskoff RM, et al. Cerebral blood volume maps of gliomas: comparison with tumor grade and histologic findings. Radiology. 1994;191(1):41–51.CrossRefPubMed

Lev MH, Rosen BR. Clinical applications of intracranial perfusion MR imaging. Neuroimaging Clin N Am. 1999;9(2):309–31.PubMed

Law M, Oh S, Babb JS, Wang E, Inglese M, Zagzag D, et al. Low-grade gliomas: dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging—prediction of patient clinical response. Radiology. 2006;238(2):658–67.CrossRefPubMed

Wang XC, Zhang H, Tan Y, Qin JB, Wu XF, Wang L, et al. Combined value of susceptibility-weighted and perfusion-weighted imaging in assessing WHO grade for brain astrocytomas. J Magn Reson Imaging. 2014;39(6):1569–74.CrossRefPubMed

Young R, Babb J, Law M, Pollack E, Johnson G. Comparison of region-of-interest analysis with three different histogram analysis methods in the determination of perfusion metrics in patients with brain gliomas. J Magn Reson Imaging JMRI. 2007;26(4):1053–63.CrossRefPubMed

Liu X, Tian W, Kolar B, Yeaney GA, Qiu X, Johnson MD, et al. MR diffusion tensor and perfusion-weighted imaging in preoperative grading of supratentorial nonenhancing gliomas. Neuro-oncology. 2011;13(4):447–55.CrossRefPubMedPubMedCentral

10.

Emblem KE, Nedregaard B, Nome T, Due-Tonnessen P, Hald JK, Scheie D, et al. Glioma grading by using histogram analysis of blood volume heterogeneity from MR-derived cerebral blood volume maps. Radiology. 2008;247(3):808–17.CrossRefPubMed

11.

Lev MH, Ozsunar Y, Henson JW, Rasheed AA, Barest GD, Harsh GRT, 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(2):214–21.PubMed

12.

Filss CP, Galldiks N, Stoffels G, Sabel M, Wittsack HJ, Turowski B, et al. Comparison of 18F-FET PET and perfusion-weighted MR imaging: a PET/MR imaging hybrid study in patients with brain tumors. J Nucl Med Off Publ Soc Nucl Med. 2014;55(4):540–5.

13.

Ma JH, Kim HS, Rim NJ, Kim SH, Cho KG. Differentiation among glioblastoma multiforme, solitary metastatic tumor, and lymphoma using whole-tumor histogram analysis of the normalized cerebral blood volume in enhancing and perienhancing lesions. Am J Neuroradiol. 2010;31(9):1699–706.CrossRefPubMed

14.

Falk A, Fahlstrom M, Rostrup E, Berntsson S, Zetterling M, Morell A, et al. 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. 2014;56(12):1031–8.CrossRefPubMed

15.

Kim H, Choi SH, Kim JH, Ryoo I, Kim SC, Yeom JA, et al. Gliomas: application of cumulative histogram analysis of normalized cerebral blood volume on 3 T MRI to tumor grading. PLoS One. 2013;8(5):e63462.CrossRefPubMedPubMedCentral

16.

Emblem KE, Scheie D, Due-Tonnessen P, Nedregaard B, Nome T, Hald JK, 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(9):1664–70.CrossRefPubMed

17.

Law M, Young R, Babb J, Pollack E, Johnson G. Histogram analysis versus region of interest analysis of dynamic susceptibility contrast perfusion MR imaging data in the grading of cerebral gliomas. Am J Neuroradiol. 2007;28(4):761–6.PubMed

18.

Sato N, Suzuki M, Kuwata N, Kuroda K, Wada T, Beppu T, et al. Evaluation of the malignancy of glioma using 11C-methionine positron emission tomography and proliferating cell nuclear antigen staining. Neurosurg Rev. 1999;22(4):210–4.CrossRefPubMed

19.

Hatakeyama T, Kawai N, Nishiyama Y, Yamamoto Y, Sasakawa Y, Ichikawa T, et al. 11C-methionine (MET) and 18F-fluorothymidine (FLT) PET in patients with newly diagnosed glioma. Eur J Nucl Med Mol Imaging. 2008;35(11):2009–17.CrossRefPubMed

20.

Ogawa T, Inugami A, Hatazawa J, Kanno I, Murakami M, Yasui N, et al. Clinical positron emission tomography for brain tumors: comparison of fludeoxyglucose F 18 and l-methyl-11C-methionine. Am J Neuroradiol. 1996;17(2):345–53.PubMed

21.

Van Laere K, Ceyssens S, Van Calenbergh F, de Groot T, Menten J, Flamen P, et al. Direct comparison of 18F-FDG and 11C-methionine PET in suspected recurrence of glioma: sensitivity, inter-observer variability and prognostic value. Eur J Nucl Med Mol Imaging. 2005;32(1):39–51.CrossRefPubMed

22.

Borbely K, Nyary I, Toth M, Ericson K, Gulyas B. Optimization of semi-quantification in metabolic PET studies with 18F-fluorodeoxyglucose and 11C-methionine in the determination of malignancy of gliomas. J Neurol Sci. 2006;246(1–2):85–94.CrossRefPubMed

23.

Susheela SP, Revannasiddaiah S, Madhusudhan N, Bijjawara M. The demonstration of extension of high-grade glioma beyond magnetic resonance imaging defined edema by the use of (11) C-methionine positron emission tomography. J Cancer Res Ther. 2013;9(4):715–7.CrossRefPubMed

24.

Whitfield GA, Kennedy SR, Djoukhadar IK, Jackson A. Imaging and target volume delineation in glioma. Clin Oncol (Royal College of Radiologists (Great Britain)). 2014;26(7):364–76.CrossRef

25.

Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, Burger PC, Jouvet A, et al. The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol. 2007;114(2):97–109.CrossRefPubMedPubMedCentral

26.

Berger G, Maziere M, Knipper R, Prenant C, Comar D. Automated synthesis of 11C-labelled radiopharmaceuticals: imipramine, chlorpromazine, nicotine and methionine. Int J Appl Radiat Isot. 1979;30(7):393–9.CrossRefPubMed

27.

Kinoshita M, Goto T, Arita H, Okita Y, Isohashi K, Kagawa N, et al. Imaging ¹⁸F-fluorodeoxy glucose/¹¹C-methionine uptake decoupling for identification of tumor cell infiltration in peritumoral brain edema. J Neurooncol. 2012;106(2):417–25.CrossRefPubMed

28.

Chiba Y, Kinoshita M, Okita Y, Tsuboi A, Isohashi K, Kagawa N, et al. Use of ¹¹C-methionine PET parametric response map for monitoring WT1 immunotherapy response in recurrent malignant glioma. J Neurosurg. 2012;116(4):835–42.CrossRefPubMed

29.

Berntsson SG, Falk A, Savitcheva I, Godau A, Zetterling M, Hesselager G, et al. Perfusion and diffusion MRI combined with ¹¹C-methionine PET in the preoperative evaluation of suspected adult low-grade gliomas. J Neurooncol. 2013;114(2):241–9.CrossRefPubMedPubMedCentral

30.

Saito T, Yamasaki F, Kajiwara Y, Abe N, Akiyama Y, Kakuda T, et al. Role of perfusion-weighted imaging at 3T in the histopathological differentiation between astrocytic and oligodendroglial tumors. Eur J Radiol. 2012;81(8):1863–9.CrossRefPubMed

31.

Boxerman JL, Schmainda KM, Weisskoff RM. 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(4):859–67.PubMed

32.

Tofts PS. Modeling tracer kinetics in dynamic Gd-DTPA MR imaging. J Magn Reson Imaging JMRI. 1997;7(1):91–101.CrossRefPubMed

33.

Yamada S, Ishikawa M, Yamamoto K. Optimal diagnostic indices for idiopathic normal pressure hydrocephalus based on the 3D quantitative volumetric analysis for the cerebral ventricle and subarachnoid space. Am J Neuroradiol. 2015;36(12):2262–9.CrossRefPubMed

34.

Pauleit D, Floeth F, Hamacher K, Riemenschneider MJ, Reifenberger G, Muller HW, et al. O-(2-[18F]fluoroethyl)-l-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain J Neurol. 2005;128(Pt 3):678–87.CrossRef

35.

Stall B, Zach L, Ning H, Ondos J, Arora B, Shankavaram U, et al. Comparison of T2 and FLAIR imaging for target delineation in high grade gliomas. Radiat Oncol (London, England). 2010;5:5.CrossRefPubMedCentral

36.

Floeth FW, Pauleit D, Sabel M, Stoffels G, Reifenberger G, Riemenschneider MJ, et al. Prognostic value of O-(2-18F-fluoroethyl)-l-tyrosine PET and MRI in low-grade glioma. J Nucl Med Off Publ Soc Nucl Med. 2007;48(4):519–27.

Titel: Whole-tumor histogram analysis of the cerebral blood volume map: tumor volume defined by 11C-methionine positron emission tomography image improves the diagnostic accuracy of cerebral glioma grading
verfasst von: Rongli Wu
Yoshiyuki Watanabe
Atsuko Arisawa
Hiroto Takahashi
Hisashi Tanaka
Yasunori Fujimoto
Tadashi Watabe
Kayako Isohashi
Jun Hatazawa
Noriyuki Tomiyama
Publikationsdatum: 06.09.2017
Verlag: Springer Japan
Erschienen in: Japanese Journal of Radiology / Ausgabe 10/2017
Print ISSN: 1867-1071
Elektronische ISSN: 1867-108X
DOI: https://doi.org/10.1007/s11604-017-0675-2

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Whole-tumor histogram analysis of the cerebral blood volume map: tumor volume defined by 11C-methionine positron emission tomography image improves the diagnostic accuracy of cerebral glioma grading

Abstract

Purpose

Materials and methods

Results

Conclusion

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