Differentiation between recurrent gliomas and radiation necrosis using arterial spin labeling perfusion imaging

Ye,Jing; Bhagat,Santosh Kumar; Li,Hongmei; Luo,Xianfu; Wang,Buhai; Liu,Liqin; Yang,Guomei

doi:10.3892/etm.2016.3225

Differentiation between recurrent gliomas and radiation necrosis using arterial spin labeling perfusion imaging

Authors:
- Jing Ye
- Santosh Kumar Bhagat
- Hongmei Li
- Xianfu Luo
- Buhai Wang
- Liqin Liu
- Guomei Yang
View Affiliations

Affiliations: Department of Radiology, Northern Jiangsu People's Hospital, Yangzhou, Jiangsu 225001, P.R. China, Department of Oncology, Northern Jiangsu People's Hospital, Yangzhou, Jiangsu 225001, P.R. China
Published online on: April 4, 2016 https://doi.org/10.3892/etm.2016.3225
Pages: 2432-2436

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )

Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )

Cited By (CrossRef): 0 citations Loading Articles...

Abstract

Arterial spin labeling (ASL) magnetic resonance (MR) perfusion imaging has been proposed as an effective method to measure brain tumor perfusion. The aim of the present study was to evaluate the utility of this technique in the differentiation of recurrent gliomas from radiation necrosis. Twenty‑one patients with surgically treated primary gliomas, including 16 cases of recurrent glioma and 5 of radiation necrosis were examined using 3.0T MR imaging (MRI). ASL and dynamic susceptibility contrast‑weighted (DSC) perfusion MRI scans were performed. Maps of normalized cerebral blood ﬂow (CBF) in ASL imaging and cerebral blood volume (CBV) in DSC imaging were computed and analyzed in the regions of interest. In cases of glioma recurrence, the normalized ASL‑CBF ratio (4.45±2.72) was higher than that in cases of radiation injury (1.22±0.61) (P<0.01). The normalized DSC‑relative CBV ratio was also significantly higher in glioma recurrence (3.38±2.08) than it was in radiation injury (1.09±0.55) (P<0.05). A close linear correlation was found between the ASL and DSC MRI techniques (linear regression coefﬁcient, R=0.85; P=0.005) in the differentiation of recurrent glioma from radiation injury. The results indicate that ASL perfusion is an accurate method of distinguishing between glioma recurrence and radiation necrosis.

View Figures

View References

1	Tsuruda JS, Kortman KE, Bradley WG, Wheeler DC, Van Dalsem W and Bradley TP: Radiation effects on cerebral white matter: MR evaluation. AJR Am J Roentgenol. 149:165–171. 1987. View Article : Google Scholar : PubMed/NCBI
2	Remler MP, Marcussen WH and Tiller-Borsich J: The late effects of radiation on the blood brain barrier. Int J Radiat Oncol Biol Phys. 12:1965–1969. 1986. View Article : Google Scholar : PubMed/NCBI
3	Leon SP, Folkerth RD and Black PM: Microvessel density is a prognostic indicator for patients with astroglial brain tumors. Cancer. 77:362–372. 1996. View Article : Google Scholar : PubMed/NCBI
4	Huang AP, Tsai JC, Kuo LT, Lee CW, Lai HS, Tsai LK, Huang SJ, Chen CM, Chen YS, Chuang HY and Wintermark M: Clinical application of perfusion computed tomography in neurosurgery. J Neurosurg. 120:473–488. 2014. View Article : Google Scholar : PubMed/NCBI
5	Mullins ME, Barest GD, Schaefer PW, Hochberg FH, Gonzalez RG and Lev MH: Radiation necrosis versus glioma recurrence: Conventional MR imaging clues to diagnosis. AJNR Am J Neuroradiol. 26:1967–1972. 2005.PubMed/NCBI
6	Brandes AA, Tosoni A, Spagnolli F, Frezza G, Leonardi M, Calbucci F and Franceschi E: Disease progression or pseudoprogression after concomitant radiochemotherapy treatment: Pitfalls in neurooncology. Neuro Oncol. 10:361–367. 2008. View Article : Google Scholar : PubMed/NCBI
7	Kumar AJ, Leeds NE, Fuller GN, Van Tassel P, Maor MH, Sawaya RE and Levin VA: Malignant gliomas: MR imaging spectrum of radiation therapy- and chemotherapy-induced necrosis of the brain after treatment. Radiology. 217:377–384. 2000. View Article : Google Scholar : PubMed/NCBI
8	Cha S, Knopp EA, Johnson G, Wetzel SG, Litt AW and Zagzag D: Intracranial mass lesions: Dynamic contrast-enhanced susceptibility-weighted echo-planar perfusion MR imaging. Radiology. 223:11–29. 2002. View Article : Google Scholar : PubMed/NCBI
9	Paulson ES and Schmainda KM: Comparison of dynamic susceptibility-weighted contrast-enhanced MR methods: Recommendations for measuring relative cerebral blood volume in brain tumors. Radiology. 249:601–613. 2008. View Article : Google Scholar : PubMed/NCBI
10	Thomsen H, Steffensen E and Larsson EM: Perfusion MRI (dynamic susceptibility contrast imaging) with different measurement approaches for the evaluation of blood flow and blood volume in human gliomas. Acta Radiol. 53:95–101. 2012. View Article : Google Scholar : PubMed/NCBI
11	Barajas RF Jr, Chang JS, Segal MR, Parsa AT, McDermott MW, Berger MS and Cha S: Differentiation of recurrent glioblastoma multiforme from radiation necrosis after external beam radiation therapy with dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology. 253:486–496. 2009. View Article : Google Scholar : PubMed/NCBI
12	Matsumura T, Hayakawa M, Shimada F, Yabuki M, Dohanish S, Palkowitsch P and Yoshikawa K: Safety of gadopentetate dimeglumine after 120 million administrations over 25 years of clinical use. Magn Reson Med Sci. 12:297–304. 2013. View Article : Google Scholar : PubMed/NCBI
13	Yang L, Krefting I, Gorovets A, Marzella L, Kaiser J, Boucher R and Rieves D: Nephrogenic systemic fibrosis and class labeling of gadolinium-based contrast agents by the food and drug administration. Radiology. 265:248–253. 2012. View Article : Google Scholar : PubMed/NCBI
14	Bjornerud A and Emblem KE: A fully automated method for quantitative cerebral hemodynamic analysis using DSC-MRI. J Cereb Blood Flow Metab. 30:1066–1078. 2010. View Article : Google Scholar : PubMed/NCBI
15	Carlsson A, Starck G, Ljungberg M, Ekholm S and Forssell-Aronsson E: Accurate and sensitive measurements of magnetic susceptibility using echo planar imaging. Magn Reson Imaging. 24:1179–1185. 2006. View Article : Google Scholar : PubMed/NCBI
16	Detre JA, Rao H, Wang DJ, Chen YF and Wang Z: Applications of arterial spin labeled MRI in the brain. J Magn Reson Imaging. 35:1026–1037. 2012. View Article : Google Scholar : PubMed/NCBI
17	Detre JA, Wang J, Wang Z and Rao H: Arterial spin-labeled perfusion MRI in basic and clinical neuroscience. Curr Opin Neuro. 22:348–355. 2009. View Article : Google Scholar
18	Chawla S, Wang S, Wolf RL, Woo JH, Wang J, O'Rourke DM, Judy KD, Grady MS, Melhem ER and Poptani H: Arterial spin-labeling and MR spectroscopy in the differentiation of gliomas. AJNR Am J Neuroradiol. 28:1683–1689. 2007. View Article : Google Scholar : PubMed/NCBI
19	Macdonald DR, Cascino TL, Schold SC Jr and Cairncross JG: Response criteria for phase II studies of supratentorial malignant glioma. J Clin Oncol. 8:1277–1280. 1990.PubMed/NCBI
20	Tan H, Chen L, Guan Y and Lin X: Comparison of MRI, F-18 FDG and 11C-choline PET/CT for their potentials in differentiating brain tumor recurrence from brain tumor necrosis following radiotherapy. Clin Nucl Med. 36:978–981. 2011. View Article : Google Scholar : PubMed/NCBI
21	Sugahara T, Korogi Y, Tomiguchi S, Shigematsu Y, Ikushima I, Kira T, Liang L, Ushio Y and Takahashi M: Posttherapeutic intraaxial brain tumor: The value of perfusion-sensitive contrast-enhanced MR imaging for differentiating tumor recurrence from nonneoplastic contrast-enhancing tissue. AJNR Am J Neuroradiol. 21:901–909. 2000.PubMed/NCBI
22	Warmuth C, Gunther M and Zimmer C: Quantification of blood flow in brain tumors: Comparison of arterial spin labeling and dynamic susceptibility-weighted contrast-enhanced MR imaging. Radiology. 228:523–532. 2003. View Article : Google Scholar : PubMed/NCBI
23	White CM, Pope WB, Zaw T, Qiao J, Naeini KM, Lai A, Nghiemphu PL, Wang JJ, Cloughesy TF and Ellingson BM: Regional and voxel-wise comparisons of blood flow measurements between dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) and arterial spin labeling (ASL) in brain tumors. J Neuroimaging. 24:23–30. 2014. View Article : Google Scholar : PubMed/NCBI
24	Ozsunar Y, Mullins ME, Kwong K, Hochberg FH, Ament C, Schaefer PW, Gonzalez RG and Lev MH: Glioma recurrence versus radiation necrosis? A pilot comparison of arterial spin-labeled, dynamic susceptibility contrast enhanced MRI and FDG-PET imaging. Acad Radiol. 17:282–290. 2010. View Article : Google Scholar : PubMed/NCBI
25	Choi YJ, Kim HS, Jahng GH, Kim SJ and Suh DC: Pseudoprogression in patients with glioblastoma: Added value of arterial spin labeling to dynamic susceptibility contrast perfusion MR imaging. Acta Radiol. 54:448–454. 2013. View Article : Google Scholar : PubMed/NCBI
26	Hu LS, Baxter LC, Smith KA, Feuerstein BG, Karis JP, Eschbacher JM, Coons SW, Nakaji P, Yeh RF, Debbins J and Heiserman JE: Relative cerebral blood volume values to differentiate high-grade glioma recurrence from posttreatment radiation effect: Direct correlation between image-guided tissue histopathology and localized dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging measurements. AJNR Am J Neuroradiol. 30:552–558. 2009. View Article : Google Scholar : PubMed/NCBI
27	Larsen VA, Simonsen HJ, Law I, Larsson HB and Hansen AE: Evaluation of dynamic contrast-enhanced T1-weighted perfusion MRI in the differentiation of tumor recurrence from radiation necrosis. Neuroradiology. 55:361–369. 2013. View Article : Google Scholar : PubMed/NCBI