‘EVALUATION OF EFFICACY OF PERFUSION MRI IN DIFFERENTIATING HIGH GRADE GLIOMAS FROM OTHER CNS LYMPHOMAS AND SOLITARY BRAIN METASTASIS: A SYSTEMATIC REVIEW’’
Main Article Content
Keywords
HGG, SBM, Perfusion MRI, DSC-MRI
Abstract
Background: Treatment evaluation of patients with tumor is crucial for clinical decision-making. Conventional contrast MRI struggles to distinguish between tumor progression and treatment effects. High-grade gliomas (HGGs), primary central nervous system lymphomas (PCNSLs), and solitary brain metastasis (SBMs) often exhibit similar enhancement patterns on MR imaging and complicating diagnosis. Perfusion MRI, which provides insights into tumor vascularity and microcirculation, may improve diagnostic accuracy. This systematic review aim to assess the effectiveness of perfusion MRI in differentiating HGGs from PCNSLs and SBMs.
Method: We performed this study based on the preferred reporting items for systematic review. The literature search was conducted using an electronic database for related articles published in English from PubMed, Scopus, the Web of Science, and Cochrane with periods from 2014 to 2023. Literature screening, data extraction, and risk of bias assessment were independently performed.
Results: A total of 765 articles were found, with 13 studies meeting the eligibility criteria. These studies included a total of 368 HGG patients, 131 SBM patients, and 102 PCNSL patients. Most of the studies included were retrospective studies. The mean age of the enrolled patients was 61.2 years. The majority of articles demonstrated low risk (62.82%), signifying reliability, while 19.23% of the studies were classified as 'unclear,' indicating some ambiguity without invalidating the results. Studies classified as 'high risk' (17.95%) indicated substantial bias and potential errors. For analysis, relative cerebral blood volume (rCBV) was a useful parameter for differentiating HGG from PCNSL and SBM, demonstrating significantly higher rCBV values for HGG.
Conclusion: Perfusion MRI is a promising non-invasive imaging method with good accuracy in diagnosing different types of brain tumors. The relative cerebral blood volume (rCBV) can facilitate the differentiation between HGG from PCNSLs and SBMs. Specifically, dynamic susceptibility contrast MRI (DSC-MRI) shows high diagnostic performance in stratifying gliomas.
Keywords: HGG, SBM, Perfusion MRI, DSC-MRI
Background: Treatment evaluation of patients with tumor is crucial for clinical decision-making. Conventional contrast MRI struggles to distinguish between tumor progression and treatment effects. High-grade gliomas (HGGs), primary central nervous system lymphomas (PCNSLs), and solitary brain metastasis (SBMs) often exhibit similar enhancement patterns on MR imaging and complicating diagnosis. Perfusion MRI, which provides insights into tumor vascularity and microcirculation, may improve diagnostic accuracy. This systematic review aim to assess the effectiveness of perfusion MRI in differentiating HGGs from PCNSLs and SBMs.
Method: We performed this study based on the preferred reporting items for systematic review. The literature search was conducted using an electronic database for related articles published in English from PubMed, Scopus, the Web of Science, and Cochrane with periods from 2014 to 2023. Literature screening, data extraction, and risk of bias assessment were independently performed.
Results: A total of 765 articles were found, with 13 studies meeting the eligibility criteria. These studies included a total of 368 HGG patients, 131 SBM patients, and 102 PCNSL patients. Most of the studies included were retrospective studies. The mean age of the enrolled patients was 61.2 years. The majority of articles demonstrated low risk (62.82%), signifying reliability, while 19.23% of the studies were classified as 'unclear,' indicating some ambiguity without invalidating the results. Studies classified as 'high risk' (17.95%) indicated substantial bias and potential errors. For analysis, relative cerebral blood volume (rCBV) was a useful parameter for differentiating HGG from PCNSL and SBM, demonstrating significantly higher rCBV values for HGG.
Conclusion: Perfusion MRI is a promising non-invasive imaging method with good accuracy in diagnosing different types of brain tumors. The relative cerebral blood volume (rCBV) can facilitate the differentiation between HGG from PCNSLs and SBMs. Specifically, dynamic susceptibility contrast MRI (DSC-MRI) shows high diagnostic performance in stratifying gliomas.
References
2. Zheng X, Li P, Dong Q, Duan Y, Yang S, Cai Z, Chen F, Li W. MicroRNAs as Diagnostic Biomarkers in Primary Central Nervous System Lymphoma: A Systematic Review and Meta-Analysis. Front Oncol. 2021 Sep 17;11:743542. doi: 10.3389/fonc.2021.743542. PMID: 34604087; PMCID: PMC8484918.
3. Omuro A, DeAngelis LM. Glioblastoma and other malignant gliomas: a clinical review. JAMA. 2013;310:1842–1850. doi: 10.1001/jama.2013.280319
4. Ding Y, Xing Z, Liu B, Lin X, Cao D. Differentiation of primary central nervous system lymphoma from high-grade glioma and brain metastases using susceptibility-weighted imaging. Brain Behav. 2014;4(6):841-9. doi: 10.1002/brb3.288. Epub 2014 Oct 10. PMID: 25365807; PMCID: PMC4212111.
5. Neska-Matuszewska M, Bladowska J, Sąsiadek M, Zimny A. Differentiation of glioblastoma multiforme, metastases and primary central nervous system lymphomas using multiparametric perfusion and diffusion MR imaging of a tumor core and a peritumoral zone-Searching for a practical approach. PLoS One. 2018 Jan 17;13(1):e0191341. doi: 10.1371/journal.pone.0191341. PMID: 29342201; PMCID: PMC5771619.
6. Munir S, Khan SA, Hanif H, Khan M. Diagnostic accuracy of magnetic resonance imaging in detection of intra-axial gliomas. Pak J Med Sci. 2021 Jan-Feb;37(1):125-130. doi: 10.12669/pjms.37.1.2489. PMID: 33437263; PMCID: PMC7794124.
7. Rahmathulla G, Hovey EJ, Hashemi-Sadraei N, Ahluwalia MS. Bevacizumab in high-grade gliomas: a review of its uses, toxicity assessment, and future treatment challenges. Onco Targets Ther. 2013 Apr 15;6:371-89. doi: 10.2147/OTT.S38628. PMID: 23620671; PMCID: PMC3633547.
8. Munir S, Khan SA, Hanif H, Khan M. Diagnostic accuracy of magnetic resonance imaging in detection of intra-axial gliomas. Pak J Med Sci. 2021 Jan-Feb;37(1):125-130. doi: 10.12669/pjms.37.1.2489. PMID: 33437263; PMCID: PMC7794124.
9. Grochans S, Cybulska AM, Simińska D, Korbecki J, Kojder K, Chlubek D, Baranowska-Bosiacka I. Epidemiology of Glioblastoma Multiforme-Literature Review. Cancers (Basel). 2022;14(10):2412.
10. Salari, N., Ghasemi, H., Fatahian, R. et al. The global prevalence of primary central nervous system tumors: a systematic review and meta-analysis. Eur J Med Res 28, 39 (2023). https://doi.org/10.1186/s40001-023-01011-y
11. Kaichi Y, Tatsugami F, Nakamura Y, Baba Y, Iida M, Higaki T, Kiguchi M, Tsushima S, Yamasaki F, Amatya VJ, Takeshima Y, Kurisu K, Awai K. Improved differentiation between high- and low-grade gliomas by combining dual-energy CT analysis and perfusion CT. Medicine (Baltimore). 2018 Aug;97(32):e11670. doi: 10.1097/MD.0000000000011670. PMID: 30095624; PMCID: PMC6133561.
12. Law M, Yang S, Babb JS, et al. Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. AJNR Am J Neuroradiol 2004;25:746–55.]
13. The Role of CT Perfusion Parameters in Grading of Brain Gliomas in Correlation with Histopathology Satheesh Kumar E1 , D. Ramesh2 , N. Kailasanathan
14. Hung ND, Anh NN, Minh ND, Huyen DK, Duc NM. Differentiation of glioblastoma and primary central nervous system lymphomas using multiparametric diffusion and perfusion magnetic resonance imaging. Biomed Rep. 2023;19(5):82. doi: 10.3892/br.2023.1664. PMID: 37881606; PMCID: PMC10594071.
15. Cindil E, Sendur HN, Cerit MN, Dag N, Erdogan N, Celebi FE, Oner Y, Tali T. Validation of combined use of DWI and percentage signal recovery-optimized protocol of DSC-MRI in differentiation of high-grade glioma, metastasis, and lymphoma. Neuroradiology. 2021 Mar;63(3):331-342. doi: 10.1007/s00234-020-02522-9. Epub 2020 Aug 21. PMID: 32821962.
16. Aparici-Robles F, Davidhi A, Carot-Sierra JM, Perez-Girbes A, Carreres-Polo J, Momparler MM, et al. Glioblastoma versus solitary brain metastasis: MRI differentiation using the edema perfusion gradient. J Neuroimaging. 2021;1–7.
17. She, Dejun MD; Xing, Zhen MD; Cao, Dairong MD. Differentiation of Glioblastoma and Solitary Brain Metastasis by Gradient of Relative Cerebral Blood Volume in the Peritumoral Brain Zone Derived from Dynamic Susceptibility Contrast Perfusion Magnetic Resonance Imaging. Journal of Computer Assisted Tomography 43(1):p 13-17, 1/2 2019. | DOI: 10.1097/RCT.0000000000000771
18. Aslan K, Gunbey HP, Tomak L, Incesu L. Multiparametric MRI in differentiating solitary brain metastasis from high-grade glioma: diagnostic value of the combined use of diffusion-weighted imaging, dynamic susceptibility contrast imaging, and magnetic resonance spectroscopy parameters. Neurol Neurochir Pol. 2019;53(3):227-237. doi: 10.5603/PJNNS.a2019.0024. Epub 2019 Jun 10. PMID: 31180131.
19. Ghodsi S M, Khoshnevisan A, Arjipour M, Ghanaati H, Firouznia K, et al. Diagnostic Efficacy of Perfusion Magnetic Resonance Imaging in Supratentorial Glioma Grading. I J Radiol. 2018;15(2):e13696. https://doi.org/10.5812/iranjradiol.13696
20. Makino K, Hirai T, Nakamura H, Kuroda JI, Shinojima N, Uetani H, Kitajima M, Yano S. Differentiating Between Primary Central Nervous System Lymphomas and Glioblastomas: Combined Use of Perfusion-Weighted and Diffusion-Weighted Magnetic Resonance Imaging. World Neurosurg. 2018 Apr;112:e1-e6. doi: 10.1016/j.wneu.2017.10.141. Epub 2018 Feb 13. PMID: 29104150.
21. Neska-Matuszewska M, Bladowska J, Sąsiadek M, Zimny A. Differentiation of glioblastoma multiforme, metastases and primary central nervous system lymphomas using multiparametric perfusion and diffusion MR imaging of a tumor core and a peritumoral zone-Searching for a practical approach. PLoS One. 2018 Jan 17;13(1):e0191341. doi: 10.1371/journal.pone.0191341. PMID: 29342201; PMCID: PMC5771619.
22. Murayama K, Nishiyama Y, Hirose Y, Abe M, Ohyu S, Ninomiya A, Fukuba T, Katada K, Toyama H. Differentiating between Central Nervous System Lymphoma and High-grade Glioma Using Dynamic Susceptibility Contrast and Dynamic Contrast-enhanced MR Imaging with Histogram Analysis. Magn Reson Med Sci. 2018 Jan 10;17(1):42-49. doi: 10.2463/mrms.mp.2016-0113. Epub 2017 May 18. PMID: 28515410; PMCID: PMC5760232.
23. Jiang S, Yu H, Wang X, Lu S, Li Y, Feng L, Zhang Y, Heo HY, Lee DH, Zhou J, Wen Z. Molecular MRI differentiation between primary central nervous system lymphomas and high-grade gliomas using endogenous protein-based amide proton transfer MR imaging at 3 Tesla. Eur Radiol. 2016 Jan;26(1):64-71. doi: 10.1007/s00330-015-3805-1. Epub 2015 Apr 30. PMID: 25925361; PMCID: PMC4627862.
24. Bauer AH, Erly W, Moser FG, Maya M, Nael K. Differentiation of solitary brain metastasis from glioblastoma multiforme: a predictive multiparametric approach using combined MR diffusion and perfusion. Neuroradiology. 2015 Jul;57(7):697-703. doi: 10.1007/s00234-015-1524-6. Epub 2015 Apr 7. PMID: 25845813.
25. Nakajima S, et al., Differentiation between primary central nervous system lymphoma and glioblastoma: a comparative study of parameters derived from dynamic susceptibility contrast-enhanced perfusion-weighted MRI, Clinical Radiology (2015), http://dx.doi.org/10.1016/j.crad.2015.08.004.
26. Svolos P, et al, Investigating brain tumor differentiation with diffusion and perfusion metrics at 3T MRI using pattern recognition techniques, Magn Reson Imaging (2013), http://dx.doi.org/10.1016/j.mri.2013.06.010.
27. McGahan BG, Neilsen BK, Kelly DL, McComb RD, Kazmi SA, White ML, Zhang Y, Aizenberg MR. Assessment of vascularity in glioblastoma and its implications on patient outcomes. J Neurooncol. 2017 Mar;132(1):35-44. doi: 10.1007/s11060-016-2350-3. Epub 2017 Jan 19. PMID: 28102487; PMCID: PMC5479489.
28. Das S and Marsden PA: Angiogenesis in glioblastoma. N Engl J Med. 369:1561–1563. 2013.PubMed/NCBI View Article : Google Scholar
29. Okuchi S, Rojas-Garcia A, Ulyte A, Lopez I, Ušinskienė J, Lewis M, Hassanein SM, Sanverdi E, Golay X, Thust S, Panovska-Griffiths J, Bisdas S. Diagnostic accuracy of dynamic contrast-enhanced perfusion MRI in stratifying gliomas: A systematic review and meta-analysis. Cancer Med. 2019 Sep;8(12):5564-5573. doi: 10.1002/cam4.2369. Epub 2019 Aug 7. PMID: 31389669; PMCID: PMC6745862
30. Xu W, Wang Q, Shao A, Xu B, Zhang J. The performance of MR perfusion-weighted imaging for the differentiation of high-grade glioma from primary central nervous system lymphoma: A systematic review and meta-analysis. PLoS One. 2017 Mar 16;12(3):e0173430. doi: 10.1371/journal.pone.0173430. PMID: 28301491; PMCID: PMC5354292.
31. Toh CH, Wei KC, Chang CN, Ng SH, Wong HF. Differentiation of primary central nervous system lymphomas and glioblastomas: comparisons of diagnostic performance of dynamic susceptibility contrast-enhanced perfusion MR imaging without and with contrast-leakage correction. AJNR Am J Neuroradiol. 2013 Jun-Jul;34(6):1145-9. doi: 10.3174/ajnr.A3383. Epub 2013 Jan 24. PMID: 23348763; PMCID: PMC7964581..
Article Sidebar
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
All articles published in JPTCP are licensed under Copyright Creative Commons Attribution-NonCommercial 4.0 International License.
Dr. Mounika Sathi
Junior resident at Department of Radiology, MGM Medical College and Hospital, Aurangabad
Dr.Shivaji Pole
Associate Professor at Department of Radiology, MGM Medical College and Hospital, Aurangabad
Dr. Devidas Dahiphale
HOD at Department of Radiology, MGM Medical College and Hospital, Aurangabad
Dr. P. S. Mishrikotkar
Professor at Department of Radiology, MGM Medical College and Hospital, Aurangabad