nach oben

Erschienen in:

01.05.2011 | Neuro

Signal intensity in T2’ magnetic resonance imaging is related to brain glioma grade

verfasst von: Laura Saitta, Oliver Heese, Ann-Freya Förster, Jakob Matschke, Susanne Siemonsen, Lucio Castellan, Manfred Westphal, Jens Fiehler, Einar Goebell

Erschienen in: European Radiology | Ausgabe 5/2011

Einloggen, um Zugang zu erhalten

Abstract

Objectives

T2’ values reflect the presence of deoxyhaemoglobin related to high local oxygen extraction. We assessed the feasibility of T2’ imaging to display regions with high metabolic activity in brain gliomas.

Methods

MRI was performed in 25 patients (12 female; median age 46 years; range 2–69) with brain gliomas with additional T2 and T2* sequences. T2’ maps were derived from T2 and T2*. Dynamic susceptibility weighted contrast (DSC) perfusion was performed in 12/25 patients. Images were visually assessed by two readers and five ROIs were evaluated for each patient. Pearson correlation, Mann–Whitney and Kruskal–Wallis tests were applied for statistical analysis.

Results

Three patients were not further evaluated because of artefacts. Mean values of high-grade (III–IV) gliomas showed significantly lower T2’ values than low-grade (II) gliomas (p < 0.001). An inverse relationship was observed between rCBV and sqr (T2’) (r = −0.463, p < 0.001). No correlation was observed between T2’ and rCBV for grade II tumours (r = 0.038; p = 0.875).

Conclusions

High-grade tumours revealed lower T2’ values, presumably because of higher oxygen consumption in proliferating tissue. Our results indicate that T2’ imaging can be used as an alternative to DSC perfusion in the detection of subtle deviations in tumour metabolism.

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 191:41–51PubMed

Jackson RJ, Fuller GN, Abi-Said D, Lang FF, Gokaslan ZL, Shi WM, Wildrick DM, Sawaya R (2001) Limitations of stereotactic biopsy in the initial management of gliomas. Neuro Oncol 3:193–200PubMed

Mittler MA, Walters BC, Stopa EG (1996) Observer reliability in histological grading of astrocytoma stereotactic biopsies. J Neurosurg 85:1091–1094PubMedCrossRef

Prayson RA, Agamanolis DP, Cohen ML, Estes ML, Kleinschmidt-DeMasters BK, Abdul-Karim F, McClure SP, Sebek BA, Vinay R (2000) Interobserver reproducibility among neuropathologists and surgical pathologists in fibrillary astrocytoma grading. J Neurol Sci 175:33–39PubMedCrossRef

Lupo JM, Cha S, Chang SM, Nelson SJ (2005) Dynamic susceptibility-weighted perfusion imaging of high-grade gliomas: characterization of spatial heterogeneity. AJNR Am J Neuroradiol 26:1446–1454PubMed

Lupo JM, Cha S, Chang SM, Nelson SJ (2007) Analysis of metabolic indices in regions of abnormal perfusion in patients with high-grade glioma. AJNR Am J Neuroradiol 28:1455–1461PubMedCrossRef

Law M, Yang S, Wang H, Babb JS, Johnson G, Cha S, Knopp EA, Zagzag D (2003) Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging. AJNR Am J Neuroradiol 24:1989–1998PubMed

Majos C, Alonso J, Aguilera C, Serrallonga M, Perez-Martin J, Acebes JJ et al (2003) Proton magnetic resonance spectroscopy (H MRS) of human brain tumours: assessment of differences between tumour types and its applicability in brain tumour categorization. Eur Radiol 13:582–91PubMed

Tamiya T, Kinoshita K, Ono Y et al (2000) Proton magnetic resonance spectroscopy reflects cellular proliferative activity in astrocytomas. Neuroradiology 42:333–338PubMedCrossRef

10.

Law M, Yang S, Babb JS, Knopp EA, Golfinos JG, Zagzag D, Johnson G (2004) Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. AJNR Am J Neuroradiol 25:746–755PubMed

11.

Hakyemez B, Erdogan C, Bolca N, Yildirim N, Gokalp G, Parlak M (2006) Evaluation of different cerebral mass lesions by perfusion-weighted MR imaging. J Magn Reson Imaging 24:817–824PubMedCrossRef

12.

Knopp EA, Cha S, Johnson G, Mazumdar A, Golfinos JG, Zagzag D, Miller DC, Kelly PJ, Kricheff II (1999) Glial neoplasms: dynamic contrast-enhanced T2*-weighted MR imaging. Radiology 211:791–798PubMed

13.

Ludemann L, Grieger W, Wurm R, Budzisch M, Hamm B, Zimmer C (2001) Comparison of dynamic contrast-enhanced MRI with WHO tumour grading for gliomas. Eur Radiol 11:1231–1241PubMedCrossRef

14.

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 27:853–858PubMed

15.

Shin JH, Lee HK, Kwun BD, Kim JS, Kang W, Choi CG, Suh DC (2002) Using relative cerebral blood flow and volume to evaluate the histopathologic grade of cerebral gliomas: preliminary results. AJR Am J Roentgenol 179:783–789PubMed

16.

Zonari P, Baraldi P, Crisi G (2007) Multimodal MRI in the characterization of glial neoplasms: the combined role of single-voxel MR spectroscopy, diffusion imaging and echo-planar perfusion imaging. Neuroradiology 49:795–803PubMedCrossRef

17.

Haris M, Gupta RK, Singh A, Husain N, Husain M, Pandey CM, Srivastava C, Behari S, Rathore RK (2008) Differentiation of infective from neoplastic brain lesions by dynamic contrast-enhanced MRI. Neuroradiology 50:531–540PubMedCrossRef

18.

Sugahara T, Korogi Y, Kochi M, Ikushima I, Hirai T, Okuda T, Shigematsu Y, Liang L, Ge Y, Ushio Y et al (1998) Correlation of MR imaging-determined cerebral blood volume maps with histologic and angiographic determination of vascularity of gliomas. AJR Am J Roentgenol 171:1479–1486PubMed

19.

Danchaivijitr N, Waldman AD, Tozer DJ, Benton CE, Brasil Caseiras G, Tofts PS, Rees JH, Jager HR (2008) Low-grade gliomas: do changes in rCBV measurements at longitudinal perfusion-weighted MR imaging predict malignant transformation? Radiology 247:170–178PubMedCrossRef

20.

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 247:490–498PubMedCrossRef

21.

Law M, Oh S, Babb JS, Wang E, Inglese M, Zagzag D, Knopp EA, Johnson G (2006) Low-grade gliomas: dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging—prediction of patient clinical response. Radiology 238:658–667PubMedCrossRef

22.

Kato T, Shinoda J, Oka N, Miwa K, Nakayama N, Yano H, Maruyama T, Muragaki Y, Iwama T (2008) Analysis of 11C-methionine uptake in low-grade gliomas and correlation with proliferative activity. AJNR Am J Neuroradiol 29:1867–1871PubMedCrossRef

23.

Siemonsen S, Fitting T, Thomalla G, Horn P, Finsterbusch J, Summers P, Saager C, Kucinski T, Fiehler J (2008) T2’ imaging predicts infarct growth beyond the acute diffusion-weighted imaging lesion in acute stroke. Radiology 248:979–986PubMedCrossRef

24.

Brooks DJ, Luthert P, Gadian D, Marsden CD (1989) Does signal-attenuation on high-field T2-weighted MRI of the brain reflect regional cerebral iron deposition? Observations on the relationship between regional cerebral water proton T2 values and iron levels. J Neurol Neurosurg Psychiatry 52:108–111PubMedCrossRef

25.

Ding XQ, Kucinski T, Wittkugel O, Goebell E, Grzyska U, Gorg M, Kohlschutter A, Zeumer H (2004) Normal brain maturation characterized with age-related T2 relaxation times: an attempt to develop a quantitative imaging measure for clinical use. Invest Radiol 39:740–746PubMedCrossRef

26.

Geisler BS, Brandhoff F, Fiehler J, Saager C, Speck O, Rother J, Zeumer H, Kucinski T (2006) Blood-oxygen-level-dependent MRI allows metabolic description of tissue at risk in acute stroke patients. Stroke 37:1778–1784PubMedCrossRef

27.

Moenninghoff C, Maderwald S, Theysohn JM, Kraff O, Ladd ME, El Hindy N, van de Nes J, Forsting M, Wanke I (2010) Imaging of adult astrocytic brain tumours with 7 T MRI: preliminary results. Eur Radiol 20:704–713PubMedCrossRef

28.

Cha S, Knopp EA, Johnson G, Wetzel SG, Litt AW, Zagzag D (2002) Intracranial mass lesions: dynamic contrast-enhanced susceptibility-weighted echo-planar perfusion MR imaging. Radiology 223:11–29PubMedCrossRef

29.

Kassner A, Annesley DJ, Zhu XP, Li KL, Kamaly-Asl ID, Watson Y, Jackson A (2000) Abnormalities of the contrast re-circulation phase in cerebral tumors demonstrated using dynamic susceptibility contrast-enhanced imaging: a possible marker of vascular tortuosity. J Magn Reson Imaging 11:103–113PubMedCrossRef

30.

Calamante F, Lythgoe MF, Pell GS, Thomas DL, King MD, Busza AL, Sotak CH, Williams SR, Ordidge RJ, Gadian DG (1999) Early changes in water diffusion, perfusion, T1, and T2 during focal cerebral ischemia in the rat studied at 8.5 T. Magn Reson Med 41:479–485PubMedCrossRef

31.

Caseiras GB, Thornton JS, Yousry T, Benton C, Rees J, Waldman AD, Jager HR (2008) Inclusion or exclusion of intratumoral vessels in relative cerebral blood volume characterization in low-grade gliomas: does it make a difference? AJNR Am J Neuroradiol 29:1140–1141PubMedCrossRef

32.

Adamson AJ, Rand SD, Prost RW, Kim TA, Schultz C, Haughton VM (1998) Focal brain lesions: effect of single-voxel proton MR spectroscopic findings on treatment decisions. Radiology 209:73–78PubMed

33.

Barker PB, Glickson JD, Bryan N (1993) In vivo magnetic resonance spectroscopy of human brain tumours. Top Magn Reson Imaging 5:32–45PubMedCrossRef

34.

Castillo M, Kwock L, Scatliff J, Mukherji SK (1998) Proton MR spectroscopy in neoplastic and non-neoplastic brain disorders. Magn Reson Imaging Clin N Am 6:1–20PubMed

35.

Dowling C, Bollen AW, Noworolski SM, McDermott MW, Barbaro NM, Day MR, Henry RG, Chang SM, Dillon WP, Nelson SJ et al (2001) Preoperative proton MR spectroscopic imaging of brain tumors: correlation with histopathologic analysis of resection specimens. AJNR Am J Neuroradiol 22:604–612PubMed

36.

Minn H (2005) PET and SPECT in low-grade glioma. Eur J Radiol 56:171–8PubMedCrossRef

37.

Popperl G, Kreth FW, Herms J, Koch W, Mehrkens JH, Gildehaus FJ et al (2006) Analysis of 18F-FET PET for grading of recurrent gliomas: is evaluation of uptake kinetics superior to standard methods? J Nucl Med 47:393–403PubMed

38.

Rachinger W, Goetz C, Popperl G, Gildehaus FJ, Kreth FW, Holtmannspotter M et al (2005) Positron emission tomography with O-(2-[18F]fluoroethyl)-l-tyrosine versus magnetic resonance imaging in the diagnosis of recurrent gliomas. Neurosurgery 57:505–511, discussion 505–511PubMedCrossRef

39.

Jain R, Scarpace LM, Ellika S, Torcuator R, Schultz LR, Hearshen D et al (2010) Imaging response criteria for recurrent gliomas treated with bevacizumab: role of diffusion weighted imaging as an imaging biomarker. J Neurooncol 96:423–31PubMedCrossRef

40.

Koeller KK, Rushing EJ (2005) From the archives of the AFIP: oligodendroglioma and its variants: radiologic-pathologic correlation. Radiographics 25:1669–88PubMedCrossRef

Titel: Signal intensity in T2’ magnetic resonance imaging is related to brain glioma grade
verfasst von: Laura Saitta
Oliver Heese
Ann-Freya Förster
Jakob Matschke
Susanne Siemonsen
Lucio Castellan
Manfred Westphal
Jens Fiehler
Einar Goebell
Publikationsdatum: 01.05.2011
Verlag: Springer-Verlag
Erschienen in: European Radiology / Ausgabe 5/2011
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-010-2004-3

Update Radiologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen

Die Highlights vom Kongress des American College of Cardiology 2024

Springer Medizin

Signal intensity in T2’ magnetic resonance imaging is related to brain glioma grade