Perfusion Magnetic Resonance Imaging to Assess Brain Tumor - Responses to New Therapies

Perfusion Magnetic Resonance Imaging to Assess Brain Tumor - Responses to New Therapies

Published: US Neurological Disease 2006
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Neuroimaging has become a means to display both normal and abnormal brain physiology and function. Magnetic resonance imaging (MRI) techniques have been optimized to provide measures of change within and around primary and metastatic brain tumors, including peri-tumoral cerebral edema, deformation of contiguous white matter tracts, volumetric and anatomic features of inhomogeneous areas within tumors, and spectroscopic evaluations of tumor chemistry. Diffusion imaging techniques measure the diffusion characteristics of water molecules. Understanding that brain tumors contain areas of necrosis, reactive cells, cyst formation, and live tumor infiltrates, clinicians make use of advanced MRI analyses to delineate tumor as distinct from normal brain. This distinction serves as the basis for MRIguided operative intervention, MR-based provision of radiation treatment fields, and the separation of therapeutic responses and tumor necrosis, calcification, and reduced blood supply.

Recently available biological therapies mandate further refinements in MRI images. Basic to tumor growth in the brain is the recruitment of new vessels, which investigators have attempted to prevent with a plethora of angiogenesis inhibitors provided in phase I/II clinical trials.1 Similarly, conventional therapies like radiotherapy are at least partly mediated by microvascular damage.2 Of newer MRI modalities, perfusion MRI has emerged as a unique marker of tumor-induced blood vessels and their function. MRIbased perfusion measures the vascularity within a tumor, as well as its component heterogeneous parts. In this review, we will present the principles of perfusion MRI, its application in brain tumor imaging, and the areas of translational application.

Perfusion MRI
At initiation, tumors in a pre-vascular phase are supplied by oxygen and nutrients that diffuse from pre-existing normal vessels.When the tumor reaches a critical size of approximately 1-4mm diameter,3,4 the resultant ischemia leads to the secretion of angiogenic factors, which in turn leads to proliferation of new vessels. These factors, such as vascular endothelial growth factor (VEGF), recruit and maintain tumor vessels, which are characterized by a tortuous and branched structure.5,6 Both in vitro and in vivo, ‘new’ vessels (neovasculature) exhibit increased blood volume and permeability compared with normal vessels.

Vascular imaging provides a visual correlate of vessel dilatation, increased blood vessel volume, and permeability. To evaluate these changes as well as the effects of vessel-specific therapies, neuroradiologists provide research-based measures of cerebral blood volume (CBV), cerebral blood flow (CBF), the mean transit time of contrast (MTT), and transfer constants of contrast agents leaving and re-entering these blood vessels (k1, k2). Of these parameters, blood volume and permeability are commonly applied in patient studies. Blood volume measures the aggregate size of the vascular space within designated areas, while the permeability function informs about the integrity of vessels and their ‘leakiness’ to contrast agents. Each function is derived from the analysis of signal changes over time of contrast agents that are injected into the vein and subsequently reach the area of interest. If no contrast flows to the imaged areas or the molecular size of the contrast agent is extremely large, permeability estimates cannot be made. In general, measurements of vascular images assume two compartments of contrast flow:(k1) describes contrast that initially moves out of the vessel into the extravascular space and (k2) the contrast that moves from the extravascular space back into the vessel.7 The rate of change of contrast in the extravascular space is described by the following formula:

Rate of change of contrast = k1 x Cb – k2 x Ae

where Cb = contrast concentration in blood and Ae = amount of contrast in the extravascular space.

In clinical settings, two different contrast-based MRI techniques are used: T2*-weighted dynamic susceptibility MRI and T1-weighted dynamic contrastenhanced perfusion imaging. Both measure the pharmacokinetics of contrast that passes through a predefined volume. In general, T2*-weighted images,obtained during ultrafast scans, reflect contrast in the vascular bed, while T1-weighted dynamic contrast images measure the intravascular contrast and the resulting leakage from the vessels.

References:
  1. Kerbel R, Folkman J, Clinical translation of angiogenesis inhibitors, Nat Rev Cancer (2002); 2: pp. 727 739.
  2. Garcia-Barros M, Paris F, Cordon-Cardo C, et al., Tumor response to radiotherapy regulated by endothelial cell apoptosis,Science (2003); 300: pp. 1,155 1,159.
  3. Kerbel R S, Tumor angiogenesis: past, present and the near future, Carcinogenesis (2000); 21: pp. 505 515.
  4. Folkman J, Tumor angiogenesis: therapeutic implications, N Engl J Med (1971); 285: pp. 1,182 1,186.
  5. Jain R K, Munn L L, Fukumura D, Dissecting tumour pathophysiology using intravital microscopy. Nat Rev Cancer (2002);2: pp. 266 276.
  6. Bullitt E, Zeng D, Gerig G, et al., Vessel tortuosity and brain tumor malignancy: a blinded study, Acad Radiol (2005); 12:pp. 1,232 1,240.
  7. Groothuis D R, Lapin G D,Vriesendorp F J, Mikhael M A, Patlak C S, A method to quantitatively measure transcapillary transport of iodinated compounds in canine brain tumors with computed tomography, J Cereb Blood Flow Metab (1991); 11: pp. 939 948.
  8. Covarrubias D J, Rosen B R, Lev M H, Dynamic magnetic resonance perfusion imaging of brain tumors, Oncologist (2004); 9: pp. 528 537.
  9. Boxerman J L, Hamberg L M, Rosen B R, Weisskoff R M, MR contrast due to intravascular magnetic susceptibility perturbations, Magn Reson Med (1995); 34: pp. 555 566.
  10. Roberts H C, Roberts T P, Brasch R C, Dillon W P, Quantitative measurement of microvascular permeability in human brain tumors achieved using dynamic contrast-enhanced MR imaging: correlation with histologic grade. Am J Neuroradiol (2000); 21: pp. 891 899.
  11. Detre J A, Leigh J S,Williams D S, Koretsky A P, Perfusion imaging, Magn Reson Med (1992); 23: pp. 37 45.
  12. Edelman R R, Siewert B, Darby D G, et al., Qualitative mapping of cerebral blood flow and functional localization with echoplanar MR imaging and signal targeting with alternating radio frequency, Radiology (1994); 192: pp. 513 520.
  13. Lev M H, Hochberg F, Perfusion magnetic resonance imaging to assess brain tumor responses to new therapies, Cancer Control (1998); 5: pp. 115 123.
  14. Niermann K J, Fleischer A C, Donnelly E F, et al., Sonographic depiction of changes of tumor vascularity in response to various therapies, Ultrasound Q (2005); 21: pp. 61 67.
  15. Drevs J, Muller-Driver R,Wittig C, et al., PTK787/ZK 222584, a specific vascular endothelial growth factor-receptor tyrosine kinase inhibitor, affects the anatomy of the tumor vascular bed and the functional vascular properties as detected by dynamic enhanced magnetic resonance imaging, Cancer Res (2002); 62: pp. 4,015 4,022.
  16. Gossmann A, Helbich T H, Kuriyama N, 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: pp. 233 240.
  17. Cha S, Johnson G,Wadghiri Y Z, et al., Dynamic, contrast-enhanced perfusion MRI in mouse gliomas: correlation with histopathology, Magn Reson Med (2003); 49: pp. 848 855.
  18. Jackson A, Jayson G C, Li K L, et al., Reproducibility of quantitative dynamic contrast-enhanced MRI in newly presenting glioma, Br J Radiol (2003); 76: pp. 153 162.
  19. Cobleigh M A, Langmuir V K, Sledge G W, et al., A phase I/II dose-escalation trial of bevacizumab in previously treated metastatic breast cancer, Semin Oncol (2003); 30: pp. 117 124.
  20. Yang J C, Haworth L, Sherry R M et al., A randomized trial of bevacizumab, an anti-vascular endothelial growth factor antibody, for metastatic renal cancer, N Engl J Med (2003); 349: pp. 427 434.
  21. Wedam S B, Low J A,Yang S X, et al., Antiangiogenic and antitumor effects of bevacizumab in inflammatory and locally advanced breast cancer patients, J Clin Oncol (2006); 24: pp. 769 777.
  22. Morgan B, Thomas A L, Drevs J, et al., Dynamic contrast-enhanced magnetic resonance imaging as a biomarker for the pharmacological response of PTK787/ZK 222584, an inhibitor of the vascular endothelial growth factor receptor tyrosine kinases, in patients with advanced colorectal cancer and liver metastases: results from two phase I studies, J Clin Oncol (2003); 21: pp. 3,955 3,964.
  23. Cha S, Knopp E A, Johnson G,et al., Dynamic contrast-enhanced T2-weighted MR imaging of recurrent malignant gliomas treated with thalidomide and carboplatin, Am J Neuroradiol (2000); 21: pp. 881 890.
  24. Akella N S,Twieg D B, Mikkelsen T, et al., Assessment of brain tumor angiogenesis inhibitors using perfusion magnetic resonance imaging: quality and analysis results of a phase I trial, J Magn Reson Imaging (2004); 20: pp. 913 922.
  25. Cao Y,Tsien C I, Nagesh V, et al., Clinical investigation survival prediction in high-grade gliomas by MRI perfusion before and during early stage of RT, Int J Radiat Oncol Biol Phys (2006); 64: pp. 876 885.
  26. Law M, Oh S, Babb J S, et al., Low-grade gliomas: dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging prediction of patient clinical response, Radiology (2006); 238: pp. 658 667.
  27. Weber M A,Thilmann C, Lichy M P, et al., Assessment of irradiated brain metastases by means of arterial spin-labeling and dynamic susceptibility-weighted contrast-enhanced perfusion MRI: initial results, Invest Radiol (2004); 39: pp. 277 287.
  28. Ostergaard L, Hochberg F H, Rabinov J D, et al., Early changes measured by magnetic resonance imaging in cerebral blood flow, blood volume, and blood brain barrier permeability following dexamethasone treatment in patients with brain tumors, J Neurosurg (1999); 90: pp. 300 305.
  29. Lev M H, Ozsunar Y, Henson J W, 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 [corrected], Am J Neuroradiol (2004); 25: pp. 214 221.
  30. Provenzale J M,Wang G R, Brenner T, Petrella J R, Sorensen A G, Comparison of permeability in high-grade and low-grade brain tumors using dynamic susceptibility contrast MR imaging, Am J Roentgenol (2002); 178: pp. 711 716.
  31. Law M,Yang S, Babb J S, et al., Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade, Am J Neuroradiol (2004); 25: pp. 746 755.
  32. Hazle J D, Jackson E F, Schomer D F, et al., Dynamic imaging of intracranial lesions using fast spin-echo imaging: differentiation of brain tumors and treatment effects, J Magn Reson Imaging (1997);7: pp. 1,084 1,093.
  33. Wenz F, Rempp K, Hess T, 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: pp. 187 93.
  34. Schonberg T, Pianka P, Hendler T, Pasternak O, Assaf Y, Characterization of displaced white matter by brain tumors using combined DTI and fMRI, Neuroimage (2006); E-pub ahead of print.
  35. Holodny A I,Watts R, Korneinko V N, et al., Diffusion tensor tractography of the motor white matter tracts in man: current controversies and future directions, Ann NY Acad Sci (2005);1064: pp. 88 97.
  36. Partridge S C, Vigneron D B, Charlton N N, et al., Pyramidal tract maturation after brain injury in newborns with heart disease, Ann Neurol (2006);59: pp. 640 651.
  37. Jang S H, Kim Y H, Kwon Y H, et al., Restoration of the corticospinal tract compressed by hematoma: a tractography study using diffusion tensor imaging, Arch Neurol (2006);63: pp. 140 141.
  38. Ge Y, Law M, Grossman R I, Applications of diffusion tensor MR imaging in multiple sclerosis, Ann N. Acad Sci (2005);1064: pp. 202 219.
  39. Shimony J S, Burton H, Epstein A A, et al., Diffusion tensor imaging reveals white matter reorganization in early blind humans, Cereb Cortex (2005); E-pub ahead of print.

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