Perfusion Imaging for Brain Tumor Characterization and Assessment of Treatment Response

Handbook of Neuro-Oncology Neuroimaging

Volumn , Issue , 2008, Pages 264-277

  Provenzale, James M ^a   Schmainda, Kathleen ^b  

^a DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b MEDICAL COLLEGE OF WISCONSIN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 78651310411     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1016/B978-012370863-2.50031-2     Document Type: Chapter

References (104)

1. Kaiser WA, Zeitler E MR imaging of the breast: fast imaging sequences with and without Gd-DTPA. Radiology 1989, 17:681-686.
2. Stack JP, et al. Breast disease: tissue characterization with Gd-DTPA enhancment profiles. Radiology 1990, 174:491-494.
3. Kelcz F, et al. Reducing the false positive gadolinium-enhanced breast MRI results through parameters analysis of the enhancement profile 1993.
4. Noseworthy MD, Morton G, Wright GA A comparison of normal and cancerous prostate using dynamic T1 and T2 weighted MRI 1999.
5. Hawihorst H, et al. Uterine cervical carcinoma: comparison of standard and pharmacokinetic analysis of timeintensity curves for assessment of tumor angiogenesis and patient survival. Cancer Res 1998, 58:3598-3602.
6. Buckley DL, et al. Microvessel disunity in invasive breast cancer assessed by dynamic Gd-DTPA enhanced MRI. J Magn Reson Imaging 1997, 7:461-464.
7. Tofts PS, Kermode AG Measurement of the blood-brain barrier permeability and leakage space using dynamic MR imaging: 1. Fundamental concepts. Magn Reson Med 1991, 17:357-367.
8. Tofts PS, et al. Estimating kinetic parameters from dynamic contrast-enhanced T1-weighted MRI of a diffusable tracer: standardized quantities and symbols. J Magn Reson Imaging 1999, 10:223-232.
9. StLawrence KS, Lee TY An adiabatic approximation to the tissue homogeneity model for water exchange in the brain: I. Theoretical derivation. J Cereb Blood Flow Metab 1998, 18:1365-1377.
10. Johnson JA, Wilson TA A model for capillary exchange. Am J Physiol 1966, 210:1299-1303.
11. Ludemann L, Hamm B, Zimmer C Pharmacokinetic analysis of glioma compartments with dynamic Gd-DTPA-enhanced magnetic resonance imaging. Magn Reson Imaging 2000, 18:1201-1214.
12. Harrer JU, et al. Comparative study of methods for determing vascular permeability and blood volume in human gliomas. J Magn Reson Imaging 2004, 20(5):748-757.
13. Ludemann L, et al. Quantitative measurement of leakage volume and permeability in gliomas, meningiomas and brain metastases with dynamic contrast-enhanced MRI. Magn Reson Imaging 2000, 23:833-841.
14. Henderson E, et al. Simultaneous MRI measurement of blood flow, blood volume, and capillary permeability in mammary tumors using two different contrast agents. J Magn Reson Imaging 2000, 12:991-1003.
15. Vajkoczy P, Menger MD Vascular microenvironment in gliomas. J Neuro-Oncol 2000, 50(1-2):99-108.
16. van Dijke CF, et al. Mammary carcinoma model: correlation of macromolecular contrast-enhanced MR imaging characterizations of tumor microvascultature and histologic capillary density. Radiology 1996, 198(3):813-818.
17. Daldrup H, et al. Correlation of dynamic contrast-enhanced MR imaging with histologic tumor grade: comparison of macromolecular and small-molecular contrast media. Am J Roentgenol 1998, 171(4):941-949.
18. Patlak CS, Blasberg RG, Fenstermacher JD Graphical evaluation of blood-to-brain transfer constants from multipletime uptake data. J Cerebr Blood Flow Metab 1983, 3:1-7.
19. Kenney J, et al. Measurement of blood-brain barrier permeability in a tumor model using magnetic resonance imaging with gadolinium-DTPA. Magn Reson Med 1992, 27:68-75.
20. Ewing JR, et al. Patlak plots of Gd-DTPA MRI data yield blood-brain transfer constants concordant with those of 14Csucrose in areas of blood-brain opening. Magn Reson Med 2003, 50(2):283-292.
21. Choyke PL, Dwyer AJ, Knopp MV Functional tumor imaging with dynamic contrast enhanced magnetic resonance imaging. J Magn Reson Imaging 2003, 17:509-520.
22. Evelhoch J, et al. Expanding the use of magnetic resonance in the assessment of tumor response to therapy: workshop report. Cancer Res 2005, 65(16):7041-7044.
23. Henderson E, RuttBK, Lee TY Temporal sampling requirements for the tracer kinetics modeling of breast disease. Magn Reson Imag 1998, 16:1057-1073.
24. Rijpkema M, et al. Method for quantitative mapping of dynamic MRI contrast agent uptake in human tumors. J Magn Reson Imaging 2001, 14(4):457-463.
25. Degani H, et al. Mapping of patholophysiologic features of breast tumors by MRI at high spatial resolution. Nat Med 1997, 3:780-782.
26. Mayr NA, et al. MR microcirculation assessment in cervical cancer: correlations with histomorphological tumor markers and clinical outcome. J Magn Reson Imaging 1999, 10:267-276.
27. Padhani AR Dynamic contrast-enhanced MRI in clinical oncology: current status and future directions. J Magn Reson Imaging 2002, 16:407-422.
28. Gossmann A, et al. Dynamic contrast-enhanced magnetic resonance imaging as a surrogate marker of tumor response to anti-angiogenic therapy in a xenograft model of glioblastoma multiforme. J Magn Reson Imaging 2002, 15:223-240.
29. Knopp MV, et al. Pathophysiologic basis of contrast enhancement in breast tumors. J Magn Reson Imaging 1999, 10:260-266.
30. Hulka CA, et al. Dynamic echo-planar imaging of the breast: experience in diagnosing breast carcinoma and correlation with tumor angiogenesis. Radiology 1997, 205(3):837-842.
31. Yang S, et al. Dynamic contrast-enhanced perfusion MR imaging measurements of endothelial permeability: differentiation between atypical and typical meningiomas. Am J Neuroradiol 2003, 24:1554-1559.
32. Lund R, et al. Using rCBV to Distinguish Radiation Necrosis from Tumor Recurrence in Malignant Gliomas 2005.
33. Roberts HC, et al. Correlation of microvascular permeability derived from dynamic contrast-enhanced MR imaging with histologic grade and tumor labeling index: a study in human brain tumors. Acad Radiol 2001, 8:384-391.
34. Rosen BR, et al. Perfusion imaging with NMR contrast agents. Magn Reson Med 1990, 14:249-265.
35. Ostergaard L, et al. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis. Magn Reson Med 1996, 36:715-725.
36. Hacklander T, et al. Cerebral blood volume maps with dynamic contrast-enhanced T1-weighted FLASH imaging: normal values and preliminary clinical results. J Comput Assist Tomogr 1996, 20(4):532-539.
37. Hacklander T, Reichenbach JR, Modder U Comparison of cerebral blood volume measurements using the T1 and T2 methods in normal human brains and brain tumors. J Comput Assist Tomogr 1997, 21(6):857-866.
38. Bruening R, et al. Echo-planar MR determination of relative cerebral blood volume in human brain tumors: T1 versus T2 weighting. Am J Neuroradiol 1996, 17:831-840.
39. Siegal T, et al. Utility of relative cerebral blood volume mapping derived from perfusion magnetic resonance imaging in the routine follow up of brain tumors. J Neurosurg 1997, 86:22-27.
40. Donahue KM, et al. Utility of simultaneously acquired gradient-echo and spin-echo cerebral blood volume and morphology maps in brain tumor patients. Magn Reson Med 2000, 43:845-853.
41. Schmainda KM, et al. Characterization of a first-pass gradient-echo spin-echo method to predict brain tumor grade and angiogenesis. Am J Neuroradiol 2004, 25:1524-1532.
42. Boxerman J, et al. The intravascular contribution to fMRI signal change: Monte Carlo modeling and diffusionweighted studies in vivo. Magn Reson Med 1995, 34:4-10.
43. Dennie J, et al. NMR imaging of changes in vascular morphology due to tumor angiogenesis. Magn Reson Med 1998, 40:793-799.
44. Tropres I, et al. Vessel size imaging. Magn Reson Med 2001, 45:397-408.
45. Boxerman JL, Rosen BR, Weisskoff RM Signal-to-noise analysis of cerebral blood volume maps from dynamic NMR imaging studies. J Magn Reson Imaging 1997, 7(3):528-537.
46. Hou L, et al. Optimization of fast acquisition methods for whole-brain relative cerebral blood volume (rCBV) mapping with susceptibility contrast agents. J Magn Reson Imaging 1999, 9:233-239.
47. Perkio J, et al. Evaluation of four postprocessing methods for determination of cerebral blood volume and mean transit time by dynamic susceptibility contrast imaging. Magn Reson Med 2002, 47:973-981.
48. Aronen HJ, et al. Ultrafast imaging of brain tumors. Top Magn Reson Imaging 1993, 5:14-24.
49. Aronen H, et al. Cerebral blood volume maps of gliomas: comparison with tumor grade and histologic findings. Radiology 1994, 191:41-51.
50. Aronen HJ, et al. High microvascular blood volume is associated with high glucose uptake and tumor angiogenesis in human gliomas. Clin Cancer Res 2000, 6(6):2189-2200.
51. Fuss M, et al. Tumor angiogenesis of low-grade astrocytomas measured by dynamic susceptibility contrastenhanced MRI (DSC-MRI) is predictive of local tumor control after radiation therapy. Int J Radiat Oncol Biol Phys 2001, 51(2):478-482.
52. Maeda M, et al. Tumor vascularity in the brain: evaluation with dynamic susceptibility-contrast MR imaging. Radiology 1993, 189:233-238.
53. Cha S Perfusion imaging of brain tumors. Top Magn Reson Imaging 2004, 15(5):279-289.
54. Knopp EA, et al. Glial neoplasms: dynamic contrastenhanced T2-weighted MR imaging. Radiology 1999, 211(3):791-798.
55. Heiland S, et al. Simultaneous assessment of cerebral hemodynamics and contrast agent uptake in lesions with disrupted blood-brain barrier. Magn Reson Imaging 1999, 17(1):21-27.
56. Weisskoff RM, et al. Simultaneous blood volume and permeability mapping using a single Gd-based contrast injection 1994.
57. Boxerman J, Schmainda KM, Weisskoff RM Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade whereas uncorrected maps do not. Am J Neuroradiol 2006, 27:859-867.
58. Quarles CC, Ward BD, Schmainda KM Improving the reliability of obtaining tumor hemodynamic parameters in the presence of contrast agent extravasation. Magn Reson Med 2005, 53:1307-1316.
59. Quarles CC, et al. Dexamethasone normalizes brain tumor hemodynamics as indicated by dynamic susceptibility contrast MRI perfusion parameters. Technol Cancer Res Treat 2005, 4(3):245-249.
60. Guckel F, et al. Assessment of cerebral blood volume with dynamic susceptibility contrast enhanced gradient-echo imaging. J Comput Assist Tomogr 1994, 18(3):344-351.
61. Zhu XP, et al. Quantification of endothelial permeability, leakage space, and blood volume in brain tumors using combined T1 and T2 contrast-enhanced dynamic MR imaging. J Magn Reson Imaging 2000, 11:575-585.
62. Sugahara T, et al. Posttherapeutic intraaxial brain tumor: the value of perfusion-sensitive contrast-enhanced MR imaging for differentiating tumor recurrence from nonneoplastic contrast-enhancing tissue. Am J Neuroradiol 2000, 21:901-909.
63. Sugahara T, et al. Perfusion-sensitive MR imaging of gliomas: comparison between gradient-echo and spinecho echo-planar imaging techniques. Am J Neuroradiol 2001, 22(7):1306-1315.
64. Sugahara T, Korogi Y, Kochi M Correlation of MR imaging-determined cerebral blood volume maps with histologic and angiographic determination of vascularity in gliomas. Am J Roentgenol 1998, 171:1479-1486.
65. Warmuth C, Gunther M, Zimmer C Quantification of blood flow in brain tumors: comparison of arterial spin labeling and dynamic susceptibility-weighted contrast-enhanced MR imaging. Radiology 2003, 228:523-532.
66. Aronen HJ, et al. Echo-planar MR cerebral blood volume mapping of gliomas. Clinical utility. Acta Radiol 1995, 36(5):520-528.
67. Bulakbasi N, et al. Assessment of diagnostic accuracy of perfusion MR imaging in primary and metastatic solitary malignant brain tumors. Am J Neuroradiol 2005, 26:2187-2199.
68. Lev MH, et al. Glial tumor grading and outcome prediction using dynamic spin-echo MR susceptibility mapping compared with conventional contrast-enhanced MR: confounding effect of elevated rCBV of oligodendrogliomas. Am J Neuroradiol 2004, 25:214-221.
69. Hartmann M, et al. Distinguishing of primary cerebral lymphoma from high-grade glioma with perfusion-weighted magnetic resonance imaging. Neurosci Lett2003, 338(2):119-122.
70. Wong JC, Provenzale JM, Petrella JR Perfusion MR imaging of brain neoplasms. Am J Neuroradiol 2000, 174:1147-1157.
71. Kremer S, et al. Contribution of dynamic contrast MR imaging to the differentiation between dural metastasis and meningioma. Neuroradiology 2004, 46(8):642-648.
72. Gillies RJ, et al. Causes and effects of heterogeneous perfusion in tumors. Neoplasia 1999, 1(3):197-207.
73. Jain RK Determinants of tumor blood flow: a review. Cancer Res 1988, 48:2641-2658.
74. Hamberg LM, et al. Spatial heterogeneity in tumor perfusion measured with functional computed tomography at 0.05 μl resolution. Cancer Res 1994, 54:6032-6036.
75. Eskey CJ, et al. 2H-Nuclear magnetic resonance imaging of tumor blood flow: spatial and temporal heterogeneity in a tissue-isolated mammary adenocarcinoma. Cancer Res 1992, 52:6010-6019.
76. Jain RK Physiological resistance to the treatment of solid tumors. Drug Resistance in Oncology 1993, 87-105. Marcel Dekker, Inc., New York. B.A. Teicher (Ed.).
77. Durand RE, LePard NE Modulaton of tumor hypoxia by conventional chemotherapeutic agents. Int J Radiat Oncol 1994, 29(3):481-486.
78. Gee MS, et al. Doppler ultrasound imaging detects changes in tumor perfusion during antivascular therapy associated with vascular anatomic alterations. Cancer Res 2001, 61:2974-2982.
79. Tozer GM, et al. Combretastatin A-4 phosphate as a tumor vascular-targeting agent: early effects in tumors and normal tissues. Cancer Res 1999, 59:1626-1634.
80. Dark GG, et al. Combretastatin A-4, an agent that displays potent and selective toxicity toward tumor vasculature. Cancer Res 1997, 57:1829-1834.
81. Holash J, et al. Vessel cooption, regression, and growth in tumors mediated by angiopoietins and VEGF. Science 1999, 284:1994-1998.
82. Bernsen HJ, et al. Suramin treatment of human glioma xenografts; effects on tumor vasculature and oxygenation status. J Neuro-Oncol 1999, 44:129-136.
83. Badruddoja MA, et al. Antiangiogenic effects of dexa methasone in 9L gliosarcoma assessed by MRI cerebral blood volume maps. Neuro-Oncology 2003, 5(4):235-243.
84. Heiss JD, et al. Mechanism of dexamethasone suppression of brain tumor-associated vascular permeability in rats. J Clin Invest 1996, 98:1400-1408.
85. Machein MR, et al. Differential downregulation of vascular endothelial growth factor by dexamethasone in normoxic and hypoxic rat glioma cells. Neuropathol Appl Neurobiol 1999, 25:104-112.
86. Chiang IC, Kuo YT, Lu CY Distinction between highgrade gliomas and solitary metastases using peritumoral 3T magnetic resonance spectroscopy, diffusion, and perfusion imaging. Neuroradiology 2004, 46:619-627.
87. Law M, et al. High-grade gliomas and solitary metastases: differentiation by using perfusion and proton spectroscopic MR imaging. Radiology 2002, 222:715-721.
88. Pham CD, et al. Magnetic resonance imaging detects suppression of tumor vascular permeability after administration of antibody to vascular endothelial growth factor. Cancer Invest 1998, 16(4):225-230.
89. Brasch R, et al. Assessing tumor angiogenesis using macromolecular MR imaging contrast agents. J Magn Reson Imaging 1997, 7(1):68-74.
90. Gossmann A, et al. Dynamic contrast-enhanced magnetic resonance imaging as a surrogate marker of tumor response to anti-angiogenic therapy in xenograft model of glioblastoma multiforme. J Magn Reson Imaging 2002, 15:233-240.
91. Provenzale JM, Galvez Moya M, Leeds NE, et al. MR imaging evaluation of a novel anti-angiogenesis agent, PTK787 2002.
92. Essig M, et al. Assessment of brain metastases with dynamic susceptibility-weighted contrast-enhanced MR imaging: inital results. Radiology 2003, 228:193-199.
93. Rock JP, et al. Associations among magnetic resonance spectroscopy, apparent diffusion coefficients, and imageguided histopathology with special attention to radiation necrosis. Neurosurgery 2004, 54(5):1111-1117.
94. Cha S, et al. Dynamic, contrast-enhanced perfusion MRI in mouse gliomas: correlation with histopathology. Magn Reson Med 2003, 49:848-855.
95. Hazle JD, Jackson EF, Schomer DF, Leeds NE Dynamic imaging of intracranial lesions using fast spain-echo imaging: differentiation of brain tumors and treatment effects. J Magn Reson Imaging 1997, 7:1084-1093.
96. Wenz F, et al. Effect of radiation on blood volume in low-grade astrocytomas and normal brain tissue: quantification with dynamic susceptibility contrast MR imaging. Am J Roentgenol 1996, 166(1):187-193.
97. Silva AC, Kim SG, Garwood M Imaging blood flow in brain tumors using arterial spin labeling. Magn Reson Med 2000, 44:169-173.
98. Provenzale JM, et al. Comparison of permeability in high-grade and low-grade brain tumors using dynamic susceptibililty contrast MR imaging. Am J Neuroradiol 2002, 178:711-716.
99. Cenic A, et al. A CT method to measure hemodynamics in brain tumors: validation and application to cerebral blood flow maps. Am J Neuroradiol 2000, 21:462-470.
100. Brix G, et al. Regional blood flow, capillary permeability, and compartmental volumes: measurement with dynamic CT-initial experience. Radiology 1999, 210:269-276.
101. LeggettD, Miles KA, Kelly BB Blood-brain barrier and blood volume imaging of cerebral glioma using functional CT: a pictorial review. Eur J Radiol 1999, 30:185-190.
102. Nabavi DG, et al. CT assessment of cerebral perfusion: experimental validation and initial clinical experience. Radiology 1999, 213:141-149.
103. Eastwood JD, Provenzale JM Cerebral blood flow, blood voume, and vascular permeability of cerebral glioma assessed with dynamic CT perfusion imaging. Neuroradiology 2003, 45:373-376.
104. Roberts HC, et al. Dyanmic, contrast-enhanced CT of human brain tumors: quantitative asessment of blood volume, blood flow, and microvascular permeability: report of two cases. Am J Neuroradiol 2002, 23:828-832.