Iranian Journal of Medical Physics

Iranian Journal of Medical Physics

Quantitative Dynamic Susceptibility Contrast MRI for Non-Invasive Glioma Grading: The Role of rCBV and rCBF

Document Type : Original Paper

Authors
Fateme Shahedi 1
Hoda Zare 2
1 Department of Radiology Technology, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran
2 Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
10.22038/ijmp.2026.95343.2690
Abstract
Introduction: Accurate preoperative grading of gliomas is essential for personalized treatment planning; however, conventional MRI often fails to reliably differentiate low-grade gliomas from high-grade gliomas due to overlapping imaging characteristics. Dynamic susceptibility contrast (DSC) MRI provides quantitative perfusion biomarkers that more directly reflect tumor vascularity and biological aggressiveness. This study aimed to evaluate the diagnostic utility of relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) for non-invasive glioma grading and to characterize regional perfusion patterns across distinct tumor compartments.
Material and Methods: Thirty patients with histopathologically confirmed gliomas underwent preoperative structural and DSC-MRI. Quantitative rCBV and rCBF maps were generated using standardized acquisition and post-processing protocols. Regions of interest were placed within the contrast-enhancing tumor, peritumoral edema, tumor core, and contralateral normal-appearing white matter. Perfusion metrics were compared across tumor subregions and between glioma grades. Diagnostic performance was assessed using receiver operating characteristic (ROC) analysis.
Results: High-grade gliomas exhibited significantly higher rCBV and rCBF than low-grade gliomas (p <0.05). In high-grade gliomas, the enhancing region exhibited markedly increased perfusion relative to the contralateral hemisphere, whereas the tumor core showed significantly reduced values. No significant perfusion differences were observed within the edema region. ROC analysis demonstrated strong diagnostic performance for both biomarkers, with rCBV achieving the best diagnostic performance (AUC=0.941, 95% CI: 0.821, 0.992, p<0.05).
Conclusion: Quantitative rCBV and rCBF show promising potential as biologically meaningful indicators of glioma grade, reflecting vascularity-related tumor biology. These metrics enhance non-invasive tumor characterization and may assist in optimizing surgical planning and individualized therapeutic strategies.
Keywords
Magnetic Resonance Imaging
Dynamic Susceptibility Contrast
Glioma
Subjects
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2.        Nowacka A, Śniegocki M, Smuczyński W, Bożiłow D, Ziółkowska E. Angiogenesis in glioblastoma—treatment approaches. Cells. 2025;14(6):407.
3.        Ahmed R, Oborski MJ, Hwang M, Lieberman FS, Mountz JM. Malignant gliomas: current perspectives in diagnosis, treatment, and early response assessment using advanced quantitative imaging methods. Cancer management and research. 2014:149-70.
4.        Setyawan NH, Choridah L, Nugroho HA, Malueka RG, Dwianingsih EK. Beyond invasive biopsies: using VASARI MRI features to predict grade and molecular parameters in gliomas. Cancer Imaging. 2024;24(1):3.
5.        Davidson C, Woodford S, Valle D, Parker G, Derias A-M, Copley C, et al. Diffuse intrinsic pontine gliomas in pediatric patients: management updates. Egyptian Journal of Neurosurgery. 2023;38(1):64.
6.        Elsheikh M, Bridgman E, Lavrador JP, Lammy S, Poon MTC. Association of extent of resection and functional outcomes in diffuse low-grade glioma: systematic review & meta-analysis. Journal of Neuro-oncology. 2022;160(3):717-24.
7.        Kang X-w, Xi Y-b, Liu T-t, Wang N, Zhu Y-q, Wang X-r, et al. Grading of Glioma: combined diagnostic value of amide proton transfer weighted, arterial spin labeling and diffusion weighted magnetic resonance imaging. BMC Medical Imaging. 2020;20(1):50.
8.        Henriksen OM, del Mar Álvarez-Torres M, Figueiredo P, Hangel G, Keil VC, Nechifor RE, et al. High-grade glioma treatment response monitoring biomarkers: a position statement on the evidence supporting the use of advanced MRI techniques in the clinic, and the latest bench-to-bedside developments. Part 1: perfusion and diffusion techniques. Frontiers in oncology. 2022;12:810263.
9.        Wang Y-L, Yao J, Chakhoyan A, Raymond C, Salamon N, Liau LM, et al. Association between tumor acidity and hypervascularity in human gliomas using pH-weighted amine chemical exchange saturation transfer echo-planar imaging and dynamic susceptibility contrast perfusion MRI at 3T. American Journal of Neuroradiology. 2019;40(6):979-86.
10.     Boxerman J, Schmainda K, Weisskoff R. Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not. American Journal of neuroradiology. 2006;27(4):859-67.
11.     Paulson ES, Schmainda KM. Comparison of dynamic susceptibility-weighted contrast-enhanced MR methods: recommendations for measuring relative cerebral blood volume in brain tumors. Radiology. 2008;249(2):601-13.
12.     Arevalo‐Perez J, Peck KK, Young RJ, Holodny AI, Karimi S, Lyo JK. Dynamic contrast‐enhanced perfusion MRI and diffusion‐weighted imaging in grading of gliomas. Journal of Neuroimaging. 2015;25(5):792-8.
13.     Ma L, Song ZJ. Differentiation between low-grade and high-grade glioma using combined diffusion tensor imaging metrics. Clinical neurology and neurosurgery. 2013;115(12):2489-95.
14.     Aydin S, Fatihoğlu E, Koşar PN, Ergün E. Perfusion and permeability MRI in glioma grading. Egyptian Journal of Radiology and Nuclear Medicine. 2020;51(1):2.
15.     Song D, Chen B, Li Z, Li Y, Zhao L, Wang L, et al. Role of dynamic contrast-enhanced and dynamic susceptibility contrast imaging in evaluating the biological features of glioma. Quantitative Imaging in Medicine and Surgery. 2025;15(8):7030-45.
16.     Falk A, Fahlström 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.
17.     Ballato M, Germanà E, Ricciardi G, Giordano WG, Tralongo P, Buccarelli M, et al. Understanding neovascularization in glioblastoma: insights from the current literature. International Journal of Molecular Sciences. 2025;26(6):2763.
18.     Guo H, Kang H, Tong H, Du X, Liu H, Tan Y, et al. Microvascular characteristics of lower-grade diffuse gliomas: investigating vessel size imaging for differentiating grades and subtypes. European radiology. 2019;29(4):1893-902.
19.     Ma H, Wang Z, Xu K, Shao Z, Yang C, Xu P, et al. Three-dimensional arterial spin labeling imaging and dynamic susceptibility contrast perfusion-weighted imaging value in diagnosing glioma grade prior to surgery. Experimental and therapeutic medicine. 2017;13(6):2691-8.
20.     Shin JH, Lee HK, Kwun BD, Kim J-S, Kang W, Choi CG, et al. Using relative cerebral blood flow and volume to evaluate the histopathologic grade of cerebral gliomas: preliminary results. American Journal of Roentgenology. 2002;179(3):783-9.
21.     Ghodsi SM, Khoshnevisan A, Arjipour M, Ghanaati H, Firouznia K, Jalali AH, et al. Diagnostic efficacy of perfusion magnetic resonance imaging in supratentorial glioma grading. Iran J Radiol. 2018;15(2):e13696.
22.     Waqar M, Lewis D, Agushi E, Gittins M, Jackson A, Coope D. Cerebral and tumoral blood flow in adult gliomas: a systematic review of results from magnetic resonance imaging. The British journal of radiology. 2021;94(1125):20201450.
23.     Kaur G, Roy B. Decoding tumor angiogenesis for therapeutic advancements: mechanistic insights. Biomedicines. 2024;12(4):827.
24.     Stenberg L, Englund E, Wirestam R, Siesjö P, Salford L, Larsson E-M. Dynamic susceptibility contrast-enhanced perfusion magnetic resonance (MR) imaging combined with contrast-enhanced MR imaging in the follow-up of immunogene-treated glioblastoma multiforme. Acta Radiologica. 2006;47(8):852-61.
25.     Englund E. Brain Tumor Characterization Using Multibiometric Evaluation of MRI. Tomography (Ann Arbor, Mich). 2018.
26.     Zakharova NE, Batalov AI, Pogosbekian EL, Chekhonin IV, Goryaynov SA, Bykanov AE, et al. Perifocal zone of brain gliomas: application of diffusion kurtosis and perfusion MRI values for tumor invasion border determination. Cancers. 2023;15(10):2760.
27.     Varakis L, Rologis D, Grivas A, Vretakos G, Papanikolaou N, editors. Pearls and pitfalls of physiology based MR imaging in brain tumors2010: European Congress of Radiology-ECR 2010.
28.     Chelebian E, Fuster-Garcia E, Álvarez-Torres MdM, Juan-Albarracín J, Garcia-Gomez JM. Higher vascularity at infiltrated peripheral edema differentiates proneural glioblastoma subtype. PLoS One. 2020;15(10):e0232500.
29.     Senturk S, Oguz KK, Cila A. Dynamic contrast-enhanced susceptibility-weighted perfusion imaging of intracranial tumors: a study using a 3T MR scanner. Diagn Interv Radiol. 2009;15(1):3-12.
30.     Pries AR, Höpfner M, Le Noble F, Dewhirst MW, Secomb TW. The shunt problem: control of functional shunting in normal and tumour vasculature. Nature Reviews Cancer. 2010;10(8):587-93.
 
 
 
 
 
 
1.        Antonelli M, Poliani PL. Adult type diffuse gliomas in the new 2021 WHO Classification. Pathologica. 2022;114(6):397.
2.        Nowacka A, Śniegocki M, Smuczyński W, Bożiłow D, Ziółkowska E. Angiogenesis in glioblastoma—treatment approaches. Cells. 2025;14(6):407.
3.        Ahmed R, Oborski MJ, Hwang M, Lieberman FS, Mountz JM. Malignant gliomas: current perspectives in diagnosis, treatment, and early response assessment using advanced quantitative imaging methods. Cancer management and research. 2014:149-70.
4.        Setyawan NH, Choridah L, Nugroho HA, Malueka RG, Dwianingsih EK. Beyond invasive biopsies: using VASARI MRI features to predict grade and molecular parameters in gliomas. Cancer Imaging. 2024;24(1):3.
5.        Davidson C, Woodford S, Valle D, Parker G, Derias A-M, Copley C, et al. Diffuse intrinsic pontine gliomas in pediatric patients: management updates. Egyptian Journal of Neurosurgery. 2023;38(1):64.
6.        Elsheikh M, Bridgman E, Lavrador JP, Lammy S, Poon MTC. Association of extent of resection and functional outcomes in diffuse low-grade glioma: systematic review & meta-analysis. Journal of Neuro-oncology. 2022;160(3):717-24.
7.        Kang X-w, Xi Y-b, Liu T-t, Wang N, Zhu Y-q, Wang X-r, et al. Grading of Glioma: combined diagnostic value of amide proton transfer weighted, arterial spin labeling and diffusion weighted magnetic resonance imaging. BMC Medical Imaging. 2020;20(1):50.
8.        Henriksen OM, del Mar Álvarez-Torres M, Figueiredo P, Hangel G, Keil VC, Nechifor RE, et al. High-grade glioma treatment response monitoring biomarkers: a position statement on the evidence supporting the use of advanced MRI techniques in the clinic, and the latest bench-to-bedside developments. Part 1: perfusion and diffusion techniques. Frontiers in oncology. 2022;12:810263.
9.        Wang Y-L, Yao J, Chakhoyan A, Raymond C, Salamon N, Liau LM, et al. Association between tumor acidity and hypervascularity in human gliomas using pH-weighted amine chemical exchange saturation transfer echo-planar imaging and dynamic susceptibility contrast perfusion MRI at 3T. American Journal of Neuroradiology. 2019;40(6):979-86.
10.     Boxerman J, Schmainda K, Weisskoff R. Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not. American Journal of neuroradiology. 2006;27(4):859-67.
11.     Paulson ES, Schmainda KM. Comparison of dynamic susceptibility-weighted contrast-enhanced MR methods: recommendations for measuring relative cerebral blood volume in brain tumors. Radiology. 2008;249(2):601-13.
12.     Arevalo‐Perez J, Peck KK, Young RJ, Holodny AI, Karimi S, Lyo JK. Dynamic contrast‐enhanced perfusion MRI and diffusion‐weighted imaging in grading of gliomas. Journal of Neuroimaging. 2015;25(5):792-8.
13.     Ma L, Song ZJ. Differentiation between low-grade and high-grade glioma using combined diffusion tensor imaging metrics. Clinical neurology and neurosurgery. 2013;115(12):2489-95.
14.     Aydin S, Fatihoğlu E, Koşar PN, Ergün E. Perfusion and permeability MRI in glioma grading. Egyptian Journal of Radiology and Nuclear Medicine. 2020;51(1):2.
15.     Song D, Chen B, Li Z, Li Y, Zhao L, Wang L, et al. Role of dynamic contrast-enhanced and dynamic susceptibility contrast imaging in evaluating the biological features of glioma. Quantitative Imaging in Medicine and Surgery. 2025;15(8):7030-45.
16.     Falk A, Fahlström 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.
17.     Ballato M, Germanà E, Ricciardi G, Giordano WG, Tralongo P, Buccarelli M, et al. Understanding neovascularization in glioblastoma: insights from the current literature. International Journal of Molecular Sciences. 2025;26(6):2763.
18.     Guo H, Kang H, Tong H, Du X, Liu H, Tan Y, et al. Microvascular characteristics of lower-grade diffuse gliomas: investigating vessel size imaging for differentiating grades and subtypes. European radiology. 2019;29(4):1893-902.
19.     Ma H, Wang Z, Xu K, Shao Z, Yang C, Xu P, et al. Three-dimensional arterial spin labeling imaging and dynamic susceptibility contrast perfusion-weighted imaging value in diagnosing glioma grade prior to surgery. Experimental and therapeutic medicine. 2017;13(6):2691-8.
20.     Shin JH, Lee HK, Kwun BD, Kim J-S, Kang W, Choi CG, et al. Using relative cerebral blood flow and volume to evaluate the histopathologic grade of cerebral gliomas: preliminary results. American Journal of Roentgenology. 2002;179(3):783-9.
21.     Ghodsi SM, Khoshnevisan A, Arjipour M, Ghanaati H, Firouznia K, Jalali AH, et al. Diagnostic efficacy of perfusion magnetic resonance imaging in supratentorial glioma grading. Iran J Radiol. 2018;15(2):e13696.
22.     Waqar M, Lewis D, Agushi E, Gittins M, Jackson A, Coope D. Cerebral and tumoral blood flow in adult gliomas: a systematic review of results from magnetic resonance imaging. The British journal of radiology. 2021;94(1125):20201450.
23.     Kaur G, Roy B. Decoding tumor angiogenesis for therapeutic advancements: mechanistic insights. Biomedicines. 2024;12(4):827.
24.     Stenberg L, Englund E, Wirestam R, Siesjö P, Salford L, Larsson E-M. Dynamic susceptibility contrast-enhanced perfusion magnetic resonance (MR) imaging combined with contrast-enhanced MR imaging in the follow-up of immunogene-treated glioblastoma multiforme. Acta Radiologica. 2006;47(8):852-61.
25.     Englund E. Brain Tumor Characterization Using Multibiometric Evaluation of MRI. Tomography (Ann Arbor, Mich). 2018.
26.     Zakharova NE, Batalov AI, Pogosbekian EL, Chekhonin IV, Goryaynov SA, Bykanov AE, et al. Perifocal zone of brain gliomas: application of diffusion kurtosis and perfusion MRI values for tumor invasion border determination. Cancers. 2023;15(10):2760.
27.     Varakis L, Rologis D, Grivas A, Vretakos G, Papanikolaou N, editors. Pearls and pitfalls of physiology based MR imaging in brain tumors2010: European Congress of Radiology-ECR 2010.
28.     Chelebian E, Fuster-Garcia E, Álvarez-Torres MdM, Juan-Albarracín J, Garcia-Gomez JM. Higher vascularity at infiltrated peripheral edema differentiates proneural glioblastoma subtype. PLoS One. 2020;15(10):e0232500.
29.     Senturk S, Oguz KK, Cila A. Dynamic contrast-enhanced susceptibility-weighted perfusion imaging of intracranial tumors: a study using a 3T MR scanner. Diagn Interv Radiol. 2009;15(1):3-12.
30.     Pries AR, Höpfner M, Le Noble F, Dewhirst MW, Secomb TW. The shunt problem: control of functional shunting in normal and tumour vasculature. Nature Reviews Cancer. 2010;10(8):587-93.
 
 
 
 
 
 
Iranian Journal of Medical Physics
Volume 23, Issue 2 - Serial Number 2
March and April 2026
Pages 124-131

  • Receive Date 29 April 2026
  • Revise Date 13 May 2026
  • Accept Date 04 July 2026