1. Togao, O., Yoshiura, T., Keupp, J., Hiwatashi, A., & Yamashita, K. (2021). Perfusion-weighted techniques in MRI grading of pediatric cerebral tumors: Efficiency of dynamic susceptibility contrast and arterial spin labeling. *Neuroradiology, 63*(4), 561-570. https://doi.org/10.1007/s00234-021-02640-y
2. Purcell, E. M., Torrey, H. C., & Pound, R. V. (2020). Resonance absorption by nuclear magnetic moments in a solid. *Physical Review, 69*(1-2), 37–38.
3. Le Bihan, D., Breton, E., Lallemand, D., Grenier, P., Cabanis, E., & Laval-Jeantet, M. (2019). Dynamique de la diffusion des molécules d’eau. https://doi.org/10.1148/radiologie.161.2.3763909
4. Lauterbur, P. C. (2022). Image formation by induced local interactions: Examples employing nuclear magnetic resonance. *Nature, 242*(5394), 190–191.
5. Kumar, A., Welti, D., & Ernst, R. R. (2015). NMR Fourier zeugmatography. *Journal of Magnetic Resonance, 213*(2), 495–509. https://doi.org/10.1016/j.jmr.2011.09.019
6. Liu, T. T. (2019). MRI in systems medicine. *Wiley Interdisciplinary Reviews: Systems Biology and Medicine.* https://doi.org/10.1002/wsbm.1463
7. Cotton, F., Ongolo-Zogo, P., Louis-Tisserand, G., Streichenberger, N., Hermier, M., Jouvet, A., & Froment, J.C. (2006). IRM de diffusion-perfusion dans l’évaluation des lymphomes cérébraux. *Journal of Neuroradiology, 33*(4), 220-228. doi: 10.1016/s0150-9861(06)77267-4
8. Kastler, B., Vetter, D., Patay, Z., & Germain, P. (2011). Comprendre l’IRM – Manuel d’auto-apprentissage, Chapitre 2 : Le phénomène de résonance magnétique. 7ème édition. Issy-les-moulineaux : *Elsevier Masson*, 389p. ISBN 978-2-294-71044-5.
9. Currie, S., Hoggard, N., Craven, I. J., Hadjivassiliou, M., & Wilkinson, I. D. (2012). Understanding MRI: basic MR physics for physicians. *Postgraduate Medical Journal, 89*(1050), 209–223. https://doi.org/10.1136/postgradmedj-2012-131342
10. IRM made easy, Prof. Dr. Hans H. Schild Lt. Oberarzt im Institut für Klinische Strahlenkunde des Klinikums der Johann-Gutenberg-Universität. ISBN 3-921817-41-2
11. Kastler, B., Vetter, D., Patay, Z., & Germain, P. (2011). Comprendre l’IRM – Manuel d’auto-apprentissage, Chapitre 4 : La séquence de base : séquence d’écho de spin. 7ème édition. Issy-les-moulineaux : *Elsevier Masson*, 389p. ISBN 978-2-294-71044-5.
12. IMAIOS. Formation médicale en ligne pour les professionnels de santé. L’IRM pas à pas : Cours interactif sur l’Imagerie par résonance magnétique. Disponible sur : http://www.imaios.com/fr/e-Cours/e-MRI
13. Filippi, M., & Agosta, F. (2016). Imagerie du tenseur de diffusion et IRM fonctionnelle. *Neuroimaging Part II*, 1065–1087. doi: 10.1016/b978-0-444-53486-6.00056-9
14. Ibrahim, M., Ghazi, T. U., Bapuraj, J. R., & Srinivasan, A. (2021b). Contrast pediatric brain perfusion. *Magnetic Resonance Imaging Clinics of North America, 29*(4), 515–526. https://doi.org/10.1016/j.mric.2021.06.004
15. Comprendre L’IRM. (2011). In *Elsevier eBooks.* https://doi.org/10.1016/b978-2-294-71044-5.x0001-2
16. Taso, M., & Alsop, D. C. (2023b). Arterial spin labeling perfusion imaging. *Magnetic Resonance Imaging Clinics of North America, 32*(1), 63–72. https://doi.org/10.1016/j.mric.2023.08.005
17. Hartkamp, N. S., Petersen, E. T., De Vis, J. B., Bokkers, R. P. H., & Hendrikse, J. (2012b). Mapping of cerebral perfusion territories using territorial arterial spin labeling: techniques and clinical application. *NMR in Biomedicine, 26*(8), 901–912. https://doi.org/10.1002/nbm.2836
18. Villanueva-Meyer, J. E., Mabray, M. C., & Cha, S. (2017c). Current clinical brain tumor imaging. *Neurosurgery, 81*(3), 397–415. https://doi.org/10.1093/neuros/nyx103
19. Essig, M., Nguyen, T. B., Shiroishi, M. S., Saake, M., Provenzale, J. M., Enterline, D. S., … Law, M. (2013). Perfusion MRI: The Five Most Frequently Asked Clinical Questions. *American Journal of Roentgenology, 201*(3), W495–W510. https://doi.org/10.2214/ajr.12.9544
20. She, D., Xing, Z., & Cao, D. (2018d). 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), 13–17. https://doi.org/10.1097/rct.0000000000000771
21. Caseiras, G. B., Chheang, S., Babb, J., et al. (2010). Relative cerebral blood volume measurements of low-grade gliomas predict patient outcome in a multi-institution setting. *Eur J Radiol, 73*, 215–220. doi: 10.1016/j.ejrad.2008.11.005.
22. Malhotra, H. S., Jain, K. K., Agarwal, A., et al. (2009). Characterization of tumefactive demyelinating lesions using MR imaging and in-vivo proton MR spectroscopy. *Mult Scler, 15*, 193–203. doi: 10.1177/1352458508097922.
23. Kurihara, N., Takahashi, S., Furuta, A., et al. (2018). MR imaging of multiple sclerosis simulating brain tumor. *Clin Imaging, 20*, 171–177. doi: 10.1016/0899-7071(95)00012-7.
24. Hourani, R., Brant, L. J., Rizk, T., Weingart, J. D., Barker, P. B., & Horska, A. (2008). Can proton MR spectroscopic and perfusion imaging differentiate between neoplastic and nonneoplastic brain lesions in adults? *AJNR, 29*, 366–372. doi: 10.3174/ajnr.A0810.
25. Kirk, J., Plumb, J., Mirakhur, M., & McQuaid, S. (2003). Tight junctional abnormality in multiple sclerosis white matter affects all calibres of vessel and is associated with blood-brain barrier leakage and active demyelination. *J Pathol, 201*, 319–327. doi: 10.1002/path.1434.
26. Blasel, S., Pfeilschifter, W., Jansen, V., Mueller, K., Zanella, F., & Hattingen, E. (2011). Metabolism and regional cerebral blood volume in autoimmune inflammatory demyelinating lesions mimicking malignant gliomas. *J Neurol, 258*, 113–122. doi: 10.1007/s00415-010-5703-4.
27. Bulakbasi, N., Guvenc, I., Onguru, O., et al. (2020). The added value of the apparent diffusion coefficient calculation to magnetic resonance imaging in the differentiation and grading of malignant brain tumors. *J Comput Assist Tomogr, 28
28. Price, S. J., Pena, A., Burnet, N. G., et al. (2004). Detecting glioma invasion of the corpus callosum using diffusion tensor imaging. *Br J Neurosurg, 18*, 391–395.
29. Sinha, S., Bastin, M. E., Whittle, I. R., et al. (2010). Diffusion tensor MR imaging of high-grade cerebral gliomas. *AJNR Am J Neuroradiol, 23*, 520–527.
30. Tropine, A., Vucurevic, G., Delani, P., et al. (2004). Contribution of diffusion tensor imaging to delineation of gliomas and glioblastomas. *J Magn Reson Imaging, 20*, 905–912.
31. Knopp, E. A., Cha, S., Johnson, G., et al. (1999). Glial neoplasms: dynamic contrast-enhanced T2*-weighted MR imaging. *Radiology, 211*, 791–798.
32. Aronen, H. J., Gazit, I. E., Louis, D. N., et al. (1994). Cerebral blood volume maps of gliomas: comparison with tumor grade and histologic findings. *Radiology, 191*, 41–51.
33. Law, M., Yang, S., Wang, H., et al. (2003). Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging. *AJNR American Journal of Neuroradiology, 24*, 1989–1998.
34. Yamasaki, F., Kurisu, K., Satoh, K., et al. (2005). Apparent diffusion coefficient of human brain tumors at MR imaging. *Radiology, 235*, 985–991.
35. Rollin, N., Guyotat, J., Streichenberger, N., et al. (2006). Clinical relevance of diffusion and perfusion magnetic resonance imaging in assessing intra-axial brain tumors. *Neuroradiology, 48*, 150–159.
36. Guimaraes, M. D., Schuch, A., Hochhegger, B., Gross, J. L., Chojniak, R., & Marchiori, E. (2014). Imagerie par résonance magnétique fonctionnelle en oncologie: état de l’art. *Radiologia Brasileira, 47*(2), 101–111. https://doi.org/10.1590/s0100-39842014000200013
37. Ptak, T., Sheridan, R. L., Rhea, J. T., Gervasini, A. A., Yun, J. H., Curran, M. A., et al. (2003). Cerebral fractional anisotropy score in trauma patients: a new indicator of white matter injury after trauma. *AJR American Journal of Roentgenology, 181*, 1401–1406.
38. Siemonsen, S., Finsterbusch, J., Matschke, J., et al. (2008). Age-dependent normal values of T2* and T2 in brain parenchyma. *AJR American Journal of Neuroradiology, 29*, 950–955.
39. Cohen, Y., & Assaf, Y. (2022). High b-value q-space analyzed diffusion-weighted MRS and MRI in neuronal tissues – a technical review. *NMR in Biomedicine, 15*, 516–542. https://doi.org/10.1002/nbm.778
40. Krabbe, K., Gideon, P., Wagn, P., et al. (1997). MR diffusion imaging of human intracranial tumours. *Neuroradiology, 39*, 483–489.
41. Becker, R. L., Becker, A. D., & Sobel, D. F. (2015). Adult medulloblastoma: review of 13 cases with emphasis on MRI. *Neuroradiology, 37*, 104–108.
42. Lu, S., Ahn, D., Johnson, G., et al. (2003). Pertumoral diffusion tensor imaging of high-grade gliomas and metastatic brain tumors. *AJNR American Journal of Neuroradiology, 24*, 937–941.
43. Dangouloff-Ros, V., Varlet, P., Levy, R., Beccaria, K., Puget, S., Dufour, C., & Boddaert, N. (2018). Imaging features of medulloblastoma: Conventional imaging, diffusion-weighted imaging, perfusion-weighted imaging, and spectroscopy: From general features to subtypes and characteristics. *Neurochirurgie*. https://doi.org/10.1016/j.neuchi.2017.10.003
44. Koob M, Girard N. Cerebral tumors: specific features in children. *Diagn Interv Imaging* 2014;95:965–983. https://doi.org/10.1016/j.diii.2014.06.017.
45. Plaza MJ, Borja MJ, Altman N, Saigal G. Conventional and advanced MRI features of pediatric intracranial tumors: posterior fossa and suprasellar tumors. *AJR Am J Roentgenol* 2013;200:1115–1124. https://doi.org/10.2214/AJR.12.9725.
46. Law M, Kazmi K, Wetzel S, Wang E, Iacob C, Zagzag D, et al. Dynamic susceptibility contrast-enhanced perfusion and conventional MR imaging findings for adult patients with cerebral primitive neuroectodermal tumors. *AJNR Am J Neuroradiol* 2004;25:997–1005.
47. Thompson EM, Guillaume DJ, Dósa E, Li X, Nazemi KJ, Gahramanov S, et al. Dual contrast perfusion MRI in a single imaging session for assessment of pediatric brain tumors. *J Neurooncol* 2012;109:105–114. https://doi.org/10.1007/s11060-012-0872-x.
48. Theillac M, Meyronet D, Savatovsky J, Makris N, Hannoun S, Grand S, et al. Dynamic susceptibility contrast perfusion imaging in biopsy-proved adult medulloblastoma. *J Neuroradiol* 2016;43(5):317–324. https://doi.org/10.1016/j.neurad.2016.05.002.
49. Dangouloff-Ros V, Deroulers C, Foissac F, Badoual M, Shotar E, Grévent D, et al. Arterial spin labeling to predict brain tumor grading in children: correlations between histopathologic vascular density and perfusion MR imaging. *Radiology* 2016;281(2):553–566. https://doi.org/10.1148/radiol.20161522.
50. Yeom KW, Mitchell LA, Lober RM, Barnes PD, Vogel H, Fisher PG, et al. Arterial spin-labeled perfusion of pediatric brain tumors. *AJNR Am J Neuroradiol* 2014;35:395–401. https://doi.org/10.3174/ajnr.A3670.
51. Eberhart CG, Cohen KJ, Tihan T, Goldthwaite PT, Burger PC. Medulloblastomas
with systemic metastases: evaluation of tumor histopathology and clinical
behavior in 23 patients. J Pediatr Hematol Oncol 2003;25:198–203. Mahajan A, Paul P, Sridhar E, Rangarajan V, Gupta T, Chinnaswamy
G, et al. Extraneural metastases from desmoplastic medulloblastoma masquerading as lymphoma. Clin Nucl Med 2017;42:354–7,
http://dx.doi.org/10.1097/RLU.0000000000001610.
52.Kumar AJ, Leeds NE, Fuller GN, et al. Malignant gliomas: MR imaging spectrum of radiation therapy- and chemotherapy-induced necrosis of the brain after treatment. Radiology. 2000;217:377–384. doi: 10.1148/radiology.217.2.r00nv36377.
53.Barajas RF, Chang JS, Sneed PK, Segal MR, Mc-Dermott MW, Cha S. Distinguishing recurrent intra-axial metastatic tumor from radiation necrosis following gamma knife radiosurgery using dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. AJNR. 2009;30:367–372. doi: 10.3174/ajnr.A1362.
54.Oh BC, Pagnini PG, Wang MY, et al. Stereotactic radiosurgery: adjacent tissue injury and response after high-dose single fraction radiation. Part 1. Histology, imaging, and molecular events. Neurosurgery. 2007;60:31–44. doi: 10.1227/01.NEU.0000249191.23162.D2.
55.Barajas RF, Jr, Chang JS, Segal MR, et al. Differentiation of recurrent glioblastoma multiforme from radiation necrosis after external beam radiation therapy with dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology. 2009;253:486–496. doi: 10.1148/radiol.2532090007.
56.Lacerda S, Law M. Magnetic resonance perfusion and permeability imaging in brain tumors. Neuroimaging Clin N Am. 2009;19:527–557. doi: 10.1016/j.nic.2009.08.007
57.Bisdas S, Naegele T, Ritz R, et al. Distinguishing recurrent high-grade gliomas from radiation injury: a pilot study using dynamic contrast-enhanced MR imaging. Acad Radiol. 2011;18:575–583. doi: 10.1016/j.acra.2011.01.018.
58. Demir MK, Yapıcıer O, Onat E, et al. Rare and challenging extra-axial brain lesions : CT and MRI findings with clinico-radiological differential diagnosis and pathological correlation. Diagn Interv Radiol2014 ; 20 : 448–52.
59. Filippi CG, Edgar MA, Ulug AM, et al. Appearance of meningiomas on diffusion-weighted images : correlating diffusion constants with histopathologic findings. AJNR Am J Neuroradiol 2001 ; 22 : 65–72.
60. Nagar VA, Ye JR, Ng WH, et al. Diffusion-weighted MR imaging : diagnosing atypical or malignant meningiomas and detecting tumor dedifferentiation. AJNR Am J Neuroradiol 2008 ; 29 : 1147–52.
61. Surov A, Ginat DT, Sanverdi E, et al. Use of diffusion weighted imaging in differentiating between maligant and benign meningiomas. A multicenter analysis. World Neurosurg 2016 ; 88 : 598–602.
62. Cha S, Knopp EA, Johnson G, Wetzel SG, Litt AW, Zagzag D. Intracranial mass lesions: dynamic contrast-enhanced susceptibility-weighted echo-planar perfusion MR imaging. Radiology 2002; 223:11–29
63. Saloner D, Uzelac A, Hetts S, Martin A, Dillon W. Modern meningioma imaging techniques. J Neurooncol 2010; 99:333–340
64. Austin BP, Nair VA, Meier TB, et al. Effects of hypoperfusion in Alzheimer’s disease. J Alzheimers Dis 2018; 26(suppl 3):123–133
65.Calli C, Kitis O, Yunten N, Yurtseven T, Islekel S, Akalin T. Perfusion and diffusion MR imaging in enhancing malignant cerebral tumors. Eur J Radiol. 2006;58:394–403. doi: 10.1016/j.ejrad.2005.12.032.
66. -Zakaria R, Das K, Bhojak M, et al. The role of magnetic resonance imaging in the management of brainmetastases : diagnosis to prognosis. Cancer Imaging 2014 ;14 : 8.
67. Chiang IC, Kuo YT, Lu CY. Distinction between high-grade gliomas and solitary metastases using peritumoral 3-T magnetic resonance spectroscopy, diffusion, and perfusion imagings. Neuroradiol 2004 ; 46 : 619–27.
68. Zhang, J., Liu, H., Tong, H., Wang, S., Yang, Y., Liu, G., & Zhang, W. (2017). Clinical Applications of Contrast-Enhanced Perfusion MRI Techniques in Gliomas: Recent Advances and Current Challenges. Contrast Media & Molecular Imaging, 2017, 1–27. doi:10.1155/2017/7064120
69. Essig M, Shiroishi MS, Nguyen TB, Saake M, Provenzale JM, Enterline D, et al. Perfusion MRI: the five most frequently asked technical questions. American Journal of Roentgenology 2013; 200: 24–34. https://doi.org/10.2214/AJR.12.9543
70. Petersen ET, Zimine I, Ho YCL, Golay X.Non-invasive measurement of perfusion:a critical review of arterial spin labelling techniques. Br J Radiol 2006; 79: 688–701.https://doi.org/10.1259/bjr/67705974
71. Petcharunpaisan S, Ramalho J, Castillo M. Arterial spin labeling in neuroimaging.World J Radiol 2010; 2: 384–98. https://doi.org/10.4329/wjr.v2.i10.38433. Thompson G, Mills SJ, Stivaros SM, JacksonA. Imaging of brain tumors: perfusion/permeability. Neuroimaging Clin N Am 2010;20: 337–53. https://doi.org/10.1016/j.nic.2010.04.008
72. Jung BC, Arevalo-PerezJ, Lyo JK, HolodnyAI, Karimi S, Young RJ, et al. Comparison of Glioblastomas and brain metastases using dynamic contrast-enhanced perfusion MRI. J Neuroimaging 2016; 26: 240–46. https://doi. org/10.1111/jon.12281
73. Chakhoyan A, Raymond C, Chen J,Goldman J, Yao J, Kaprealian TB, et al.Probabilistic independent component analysis of dynamic susceptibility contrast perfusion MRI in metastatic brain tumors. Cancer Imaging 2019; 19(1): 14. https://doi.org/10.1186/s40644-019-0201-0
74. Dobeson, C. B., Birkbeck, M., Bhatnagar, P., Hall, J., Pearson, R., West, S., English, P.,
Butteriss, D., Perthen, J., & Lewis, J. (2023). Perfusion MRI in the evaluation of brain
metastases: current practice review and rationale for study of baseline MR perfusion imaging
prior to stereotactic radiosurgery (STARBEAM-X). British Journal of Radiology, 96(1152).
https://doi.org/10.1259/bjr.20220462
75. Ata, E. S., Turgut, M., Eraslan, C., & Dayanır, Y. Ö. (2016). Comparison between dynamic susceptibility contrast magnetic resonance imaging and arterial spin labeling techniques in distinguishing malignant from benign brain tumors. European Journal of Radiology, 85(9), 1545–1553. doi:10.1016/j.ejrad.2016.05.015
76. Cha, S., Knopp, E. A., Johnson, G., Wetzel, S. G., Litt, A. W., & Zagzag, D. (2002). Intracranial mass lesions: dynamic contrast-enhanced susceptibility-weighted echo-planar perfusion MR imaging. Radiology, 223(1), 11–29. https://doi.org/10.1148/radiol.2231010594
77. Ferré, J., Shiroishi, M. S., & Law, M. (2012). Advanced techniques using contrast media in neuroimaging. Magnetic Resonance Imaging Clinics of North America, 20(4), 699–713. https://doi.org/10.1016/j.mric.2012.07.007
78. Pollock, J. M., Tan, H., Kraft, R. A., Whitlow, C. T., Burdette, J. H., & Maldjian, J. A. (2009). Arterial Spin-Labeled MR Perfusion Imaging: Clinical Applications. Magnetic Resonance Imaging Clinics of North America, 17(2), 315–338. https://doi.org/10.1016/j.mric.2009.01.008
79. Ozsunar, Y., Mullins, M. E., Kwong, K., Hochberg, F. H., Ament, C., Schaefer, P. W., Gonzalez, R. G., & Lev, M. H. (2010). Glioma recurrence versus radiation necrosis? Academic Radiology, 17(3), 282–290. https://doi.org/10.1016/j.acra.2009.10.024
80. Metellus, P., Dutertre, G., Mekkaoui, C., Nanni, I., Fuentes, S., Ait-Ameur, A., Chinot, O., Dufour, H., Figarella-Branger, D., Cordoliani, Y., & Grisoli, F. (2008). Intérêt de la mesure du volume sanguin régional cérébral relatif par IRM de perfusion dans la prise en charge des gliomes. Neurochirurgie, 54(4), 503–511. https://doi.org/10.1016/j.neuchi.2008.03.007
81. :@newrei.company & newrei.company. (n.d.). Société Marocaine de Radiologie – Fiche Apport de l’irm de perfusion dans le diagnostic des tumeurs cérébrales (Cours). Société Marocaine De Radiologie – Fiche Apport De L’irm De Perfusion Dans Le Diagnostic Des Tumeurs Cérébrales (Cours). https://www.smradiologie.org/Fiche-apport-de-lirm-de-perfusion-dans-le-diagnostic-des-tumeurs-cerebrales-448
82. Razek, A. a. K. A., Talaat, M., El-Serougy, L., Gaballa, G., & Abdelsalam, M. (2019). Clinical applications of arterial spin labeling in brain tumors. Journal of Computer Assisted Tomography, 43(4), 525–532. https://doi.org/10.1097/rct.0000000000000873 \
83.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 [PMC free article] [PubMed] [Google Scholar];
84. Law M, Cha S, Knopp EA, et al. High-grade gliomas and solitary metastases: differentiation by using perfusion and proton spectroscopic MR imaging. Radiology 2002;222:715–21 [DOI] [PubMed] [Google Scholar]
85. Aronen HJ, Gazit IE, Louis DN, et al. Cerebral blood volume maps of gliomas: comparison with tumour grade and histologic findings. Radiology 1994;191:41–51 [DOI] [PubMed] [Google Scholar]
86. Nugent LJ, Jain RK. Extravascular diffusion in normal and neoplastic tissues. Cancer Res 1984;44:238–44 [PubMed] [Google Scholar]
87. Jain RK, Gerlowski LE. Extravascular transport in normal and tumor tissues. Crit Rev Oncol Hematol 1986;5:115–70 [DOI] [PubMed] [Google Scholar]
88. Wesseling P, Ruiter DJ, Burger PC. Angiogenesis in brain tumors: pathobiological and clinical aspects. J Neurooncol 1997;32:253–65 [DOI] [PubMed] [Google Scholar]
89. Johnson JP, Bruce JN. Angiogenesis in human gliomas: prognostic and therapeutic implications. In: Rosen EM, Goldberg D, eds. Regulation of Angiogenesis. Basel, Switzerland: Birkhauser;1997. :29–46 [DOI] [PubMed]
90. Jackson A, Kassner A, Annesley-Williams D, et al. Abnormalities in the recirculation phase of contrast agent bolus passage in cerebral gliomas: comparison with relative blood volume and tumor grade. AJNR Am J Neuroradiol 2002;23:7–14 [PMC free article] [PubMed] [Google Scholar]
91. Covarrubias DJ, Rosen BR, Lev MH. Dynamic magnetic resonance perfusion imaging of brain tumors. Oncologist 2004;9:528–37 [DOI] [PubMed] [Google Scholar]
92. Grand, S., Tahon, F., Attye, A., Lefournier, V., Bas, J. L., & Krainik, A. (2013). Perfusion imaging in brain disease. Diagnostic and Interventional Imaging, 94(12), 1241–1257. https://doi.org/10.1016/j.diii.2013.06.009
93. Van Dijken, B. R. J., van Laar, P. J., Smits, M., Dankbaar, J. W., Enting, R. H., & van der Hoorn, A. (2018). Perfusion MRI in treatment evaluation of glioblastomas: Clinical relevance of current and future techniques. Journal of Magnetic Resonance Imaging, 49(1), 11–22. doi:10.1002/jmri.26306
94. Hakyemez B, Erdogan C, Ercan I, et al. High-grade and low-grade gliomas: differentiation by using perfusion MR imaging. Clin Radiol 2005;60:493–502 [DOI] [PubMed] [Google Scholar]
95. Calli C, Kitis O, Yunten N, Yurtseven T, Islekel S, Akalin T. Perfusion and diffusion MR imaging in enhancing malignant cerebral tumors. Eur J Radiol. 2006;58:394–403. doi: 10.1016/j.ejrad.2005.12.032. [DOI] [PubMed] [Google Scholar]
96. Covarrubias DJ, Rosen BR, Lev MH. Dynamic magnetic resonance perfusion imaging of brain tumors. Oncologist. 2004;9(5):528-37.
97. Zhang H, Rodiger LA, Shen T, Miao J, Oudkerk M. Preoperative subtyping of meningiomas by perfusion MR imaging. Neuroradiology 2008;50(10):835—40.
98. Zimny A, Sasiadek M. Contribution of perfusion-weighted magnetic resonance imaging in the differentiation of meningiomas and other extra-axial tumors: case reports and literature review. J Neurooncol 2011;103(3):777—83
99. Kremer S, Grand S, Remy C, Pasquier B, Benabid AL, Bracard S, et al. Contribution of dynamic contrast MR imaging to the differentiation between dural metastasis and meningioma.
100. Mangla R, Kolar B, Zhu T, Zhong J, Almast J, Ekholm S. Percentage signal recovery derived from MR dynamic susceptibility contrast imaging is useful to differentiate common enhancing malignant lesions of the brain. AJNR Am J Neuroradiol 2011;32(6):1004—10.
101. Kwee, R. M., & Kwee, T. C. (2019). Dynamic susceptibility MR perfusion in diagnosing recurrent brain metastases after radiotherapy: A systematic review and meta‐analysis. Journal of Magnetic Resonance Imaging. doi:10.1002/jmri.26812
102. Ata, E. S., Turgut, M., Eraslan, C., & Dayanır, Y. Ö. (2016). Comparison between dynamic susceptibility contrast magnetic resonance imaging and arterial spin labeling techniques in distinguishing malignant from benign brain tumors. European Journal of Radiology, 85(9), 1545–1553. doi:10.1016/j.ejrad.2016.05.015
103. Soni, N., Srindharan, K., Kumar, S., Mishra, P., Bathla, G., Kalita, J., & Behari, S. (2018). Arterial spin labeling perfusion: Prospective MR imaging in differentiating neoplastic from non-neoplastic intra-axial brain lesions. The Neuroradiology Journal, 197140091878305. doi:10.1177/1971400918783058
104. Housni, A., Boujraf, S., Maaroufi, M., Benzagmout, M., Ezzaher, K., & Tizniti, S. (2014). Le diagnostic et le suivi thérapeutique des tumeurs cérébrales intra-parenchymateuses par l’imagerie par résonance magnétique multimodale. Médecine Nucléaire, 38(6), 469–477. doi:10.1016/j.mednuc.2014.05.002
105. Ellika, S., Jain, R., Patel, S., Scarpace, L., Schultz, L., Rock, J., & Mikkelsen, T. (2007). Role of Perfusion CT in Glioma Grading and Comparison with Conventional MR Imaging Features. American Journal of Neuroradiology, 28(10), 1981–1987. https://doi.org/10.3174/ajnr.a0688