Anatomic, Physiologic and Metabolic Imaging in Neuro-Oncology

  • Sanjeev Chawla
  • Harish Poptani
  • Elias R. Melhem
Part of the Cancer Treatment and Research book series (CTAR, volume 143)

Primary brain tumors arise from various cell types of the brain, including glial cells, neurons, neuroglial precursor cells, pinealocytes, pericytes of the vessels, cells of the hypophysis, lymphocytes and the meninges [1, 2]. The incidence of primary brain tumors varies between subtypes, with the most common primary brain tumors in adults being gliomas and meningiomas.

Gliomas can be histologically classified into astrocytomas, oligodendrogliomas, mixed oligoastrocytomas, ependymal tumors and tumors of the choroid plexus. Tumor malignancy or grade is generally assessed according to the World Health Organization (WHO) criteria, taking into account the presence of nuclear changes, mitotic activity, endothelial proliferation and necrosis [1, 3]. The most fatal and common primary brain neoplasm is the glioblastoma multiforme (GBM), which corresponds to WHO grade IV. Despite aggressive multimodal treatment strategy (surgery, radiation and chemotherapy), median survival of patients with GBM is limited to less than 14 months. A complex series of molecular events occur during tumor growth resulting in dysregulation of the cell cycle, alterations in apoptosis and cell differentiation, neo-vascularization as well as tumor cell migration and invasion into the normal brain parenchyma. Genetic alterations also play an important role in the development of glioma, including a loss, mutation or hypermethylation of the tumor suppressor gene, such as p53 or other genes involved in the regulation of the cell cycle. During progression from low-grade to high-grade, step-wise accumulation of genetic alterations occurs. Growth of certain tumors seems to be related to the presence of viruses and familial diseases that accelerate the progression of molecular alterations, or exposure to environmental chemicals, pesticides, herbicides and fertilizers [4-6].


Positron Emission Tomography Brain Tumor Apparent Diffusion Coefficient Fractional Anisotropy Diffusion Tensor Imaging 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Kleihues P, Soylemezoglu F, Schauble B, Scheithauer BW, Burger PC. Histopathology, classification, and grading of gliomas. Glia 1995; 15:211–221.PubMedGoogle Scholar
  2. 2.
    Daumas-Duport C, Beuvon F, Varlet P, Fallet-Bianco C. [Gliomas: WHO and Sainte-Anne Hospital classifications]. Ann Pathol 2000; 20:413–428.PubMedGoogle Scholar
  3. 3.
    Louis DN, Holland EC, Cairncross JG. Glioma classification: a molecular reappraisal. Am J Pathol 2001; 159:779–786.PubMedGoogle Scholar
  4. 4.
    Furnari FB, Huang HJ, Cavenee WK. Genetics and malignant progression of human brain tumors. Cancer Surv 1995; 25:233–275.PubMedGoogle Scholar
  5. 5.
    Ichimura K, Bolin MB, Goike HM, Schmidt EE, Moshref A, Collins VP. Deregulation of the p14ARF/MDM2/p53 pathway is a prerequisite for human astrocytic gliomas with G1-S transition control gene abnormalities. Cancer Res 2000; 60:417–424.PubMedGoogle Scholar
  6. 6.
    Musicco M, Filippini G, Bordo BM, Melotto A, Morello G, Berrino F. Gliomas and occupational exposure to carcinogens: case-control study. Am J Epidemiol 1982; 116:782–790.PubMedGoogle Scholar
  7. 7.
    Negendank WG, Sauter R, Brown TR, et al. Proton magnetic resonance spectroscopy in patients with glial tumors: a multicenter study. J Neurosurg 1996; 84:449–458.PubMedGoogle Scholar
  8. 8.
    Al-Okaili RN, Krejza J, Wang S, Woo JH, Melhem ER. Advanced MRI Techniques in the Diagnosis of Intra-axial Brain Tumors in Adults. Radiographics 2006; 26 Suppl 1:S173–189PubMedGoogle Scholar
  9. 9.
    Meyerand ME, Pipas JM, Mamourian A, Tosteson TD, Dunn JF. Classification of biopsy-confirmed brain tumors using single-voxel MR spectroscopy. AJNR Am J Neuroradiol 1999; 20:117–123.PubMedGoogle Scholar
  10. 10.
    Haberg A, Kvistad KA, Unsgard G, Haraldseth O. Preoperative blood oxygen level-dependent functional magnetic resonance imaging in patients with primary brain tumors: clinical application and outcome. Neurosurgery 2004; 54:902–914; discussion 914–905PubMedGoogle Scholar
  11. 11.
    Pirzkall A, Li X, Oh J, et al. 3D MRSI for resected high-grade gliomas before RT: tumor extent according to metabolic activity in relation to MRI. Int J Radiat Oncol Biol Phys 2004; 59:126–137.PubMedGoogle Scholar
  12. 12.
    Dean BL, Drayer BP, Bird CR, et al. Gliomas: classification with MRI. Radiology 1990; 174:411–415.PubMedGoogle Scholar
  13. 13.
    Atlas SW, Thulborn KR. MR detection of hyperacute parenchymal hemorrhage of the brain. AJNR Am J Neuroradiol 1998; 19:1471–1477.PubMedGoogle Scholar
  14. 14.
    Gupta RK, Rao SB, Jain R, et al. Differentiation of calcification from chronic hemorrhage with corrected gradient echo phase imaging. J Comput Assist Tomogr 2001; 25:698–704.PubMedGoogle Scholar
  15. 15.
    Yamada N, Imakita S, Sakuma T, Takamiya M. Intracranial calcification on gradient-echo phase image: depiction of diamagnetic susceptibility. Radiology 1996; 198:171–178.PubMedGoogle Scholar
  16. 16.
    Atlas SW, Howard RS, 2nd, Maldjian J, et al. Functional magnetic resonance imaging of regional brain activity in patients with intracerebral gliomas: findings and implications for clinical management. Neurosurgery 1996; 38:329–338.PubMedGoogle Scholar
  17. 17.
    Knopp EA, Cha S, Johnson G, et al. Glial neoplasms: dynamic contrast-enhanced T2-weighted MRI. Radiology 1999; 211:791–798.PubMedGoogle Scholar
  18. 18.
    Fayed N, Morales H, Modrego PJ, Pina MA. Contrast/Noise ratio on conventional MRI and choline/creatine ratio on proton MRI spectroscopy accurately discriminate low-grade from high-grade cerebral gliomas. Acad Radiol 2006; 13:728–737.PubMedGoogle Scholar
  19. 19.
    Ricci PE. Imaging of adult brain tumors. Neuroimaging Clin N Am 1999; 9:651–669.PubMedGoogle Scholar
  20. 20.
    Cozad SC, Townsend P, Morantz RA, Jenny AB, Kepes JJ, Smalley SR. Gliomatosis cerebri. Results with radiation therapy. Cancer 1996; 78:1789–1793.PubMedGoogle Scholar
  21. 21.
    White ML, Zhang Y, Smoker WR, et al. Fluid-attenuated inversion-recovery MRI in assessment of intracranial oligodendrogliomas. Comput Med Imaging Graph 2005; 29:279–285.PubMedGoogle Scholar
  22. 22.
    Andreula CF, Recchia-Luciani AN. Rationale for the use of contrast media in MRI. Neuroimaging Clin N Am 1997; 7:461–498.PubMedGoogle Scholar
  23. 23.
    Posner JB, Chernik NL. Intracranial metastases from systemic cancer. Adv Neurol 1978; 19:579–592.PubMedGoogle Scholar
  24. 24.
    Sze G, Milano E, Johnson C, Heier L. Detection of brain metastases: comparison of contrast-enhanced MR with unenhanced MR and enhanced CT. AJNR Am J Neuroradiol 1990; 11:785–791.PubMedGoogle Scholar
  25. 25.
    Yuh WT, Tali ET, Nguyen HD, Simonson TM, Mayr NA, Fisher DJ. The effect of contrast dose, imaging time, and lesion size in the MR detection of intracerebral metastasis. AJNR Am J Neuroradiol 1995; 16:373–380.PubMedGoogle Scholar
  26. 26.
    Sze G, Johnson C, Kawamura Y, et al. Comparison of single- and triple-dose contrast material in the MR screening of brain metastases. AJNR Am J Neuroradiol 1998; 19:821–828.PubMedGoogle Scholar
  27. 27.
    Tang YM, Ngai S, Stuckey S. The solitary enhancing cerebral lesion: can FLAIR aid the differentiation between glioma and metastasis? AJNR Am J Neuroradiol 2006; 27:609–611.PubMedGoogle Scholar
  28. 28.
    Tokumaru A, O’Uchi T, Eguchi T, et al. Prominent meningeal enhancement adjacent to meningioma on Gd-DTPA-enhanced MR images: histopathologic correlation. Radiology 1990; 175:431–433.PubMedGoogle Scholar
  29. 29.
    Nagele T, Petersen D, Klose U, Grodd W, Opitz H, Voigt K. The “dural tail” adjacent to meningiomas studied by dynamic contrast-enhanced MRI: a comparison with histopathology. Neuroradiology 1994; 36:303–307.PubMedGoogle Scholar
  30. 30.
    Kremer P, Forsting M, Hamer J, Sartor K. MR enhancement of the internal auditory canal induced by tissue implant after resection of acoustic neurinoma. AJNR Am J Neuroradiol 1998; 19:115–118.PubMedGoogle Scholar
  31. 31.
    Johnson BA, Fram EK, Johnson PC, Jacobowitz R. The variable MR appearance of primary lymphoma of the central nervous system: comparison with histopathologic features. AJNR Am J Neuroradiol 1997; 18:563–572.PubMedGoogle Scholar
  32. 32.
    Kleihues P, Burger PC, Scheithauer BW. The new WHO classification of brain tumors. Brain Pathol 1993; 3:255–268.PubMedGoogle Scholar
  33. 33.
    Ikushima I, Korogi Y, Hirai T, et al. MR of epidermoids with a variety of pulse sequences. AJNR Am J Neuroradiol 1997; 18:1359–1363.PubMedGoogle Scholar
  34. 34.
    Ernemann U, Rieger J, Tatagiba M, Weller M. An MRI view of a ruptured dermoid cyst. Neurology 2006; 66:270.PubMedGoogle Scholar
  35. 35.
    Plate KH, Risau W. Angiogenesis in malignant gliomas. Glia 1995; 15:339–347.PubMedGoogle Scholar
  36. 36.
    Zagzag D, Zhong H, Scalzitti JM, Laughner E, Simons JW, Semenza GL. Expression of hypoxia-inducible factor 1alpha in brain tumors: association with angiogenesis, invasion, and progression. Cancer 2000; 88:2606–2618.PubMedGoogle Scholar
  37. 37.
    Boxerman JL, 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. AJNR Am J Neuroradiol 2006; 27:859–867.PubMedGoogle Scholar
  38. 38.
    Aronen HJ, Perkio J. Dynamic susceptibility contrast MRI of gliomas. Neuroimaging Clin N Am 2002; 12:501–523.PubMedGoogle Scholar
  39. 39.
    Donahue KM, Krouwer HG, Rand SD, 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.PubMedGoogle Scholar
  40. 40.
    Tofts PS, Kermode AG. Measurement of the blood-brain barrier permeability and leakage space using dynamic MRI. 1. Fundamental concepts. Magn Reson Med 1991; 17:357–367.PubMedGoogle Scholar
  41. 41.
    Dixon WT, Du LN, Faul DD, Gado M, Rossnick S. Projection angiograms of blood labeled by adiabatic fast passage. Magn Reson Med 1986; 3:454–462.PubMedGoogle Scholar
  42. 42.
    Sardashti M, Schwartzberg DG, Stomp GP, Dixon WT. Spin-labeling angiography of the carotids by presaturation and simplified adiabatic inversion. Magn Reson Med 1990; 15:192–200.PubMedGoogle Scholar
  43. 43.
    St Lawrence KS, Frank JA, McLaughlin AC. Effect of restricted water exchange on cerebral blood flow values calculated with arterial spin tagging: a theoretical investigation. Magn Reson Med 2000; 44:440–449.PubMedGoogle Scholar
  44. 44.
    Aronen HJ, Gazit IE, Louis DN, et al. Cerebral blood volume maps of gliomas: comparison with tumor grade and histologic findings. Radiology 1994; 191:41–51.PubMedGoogle Scholar
  45. 45.
    Sugahara T, Korogi Y, Kochi M, et al. Correlation of MRI-determined cerebral blood volume maps with histologic and angiographic determination of vascularity of gliomas. AJR Am J Roentgenol 1998; 171:1479–1486.PubMedGoogle Scholar
  46. 46.
    Daumas-Duport C, Tucker ML, Kolles H, et al. Oligodendrogliomas. Part II: A new grading system based on morphological and imaging criteria. J Neurooncol 1997; 34:61–78.PubMedGoogle Scholar
  47. 47.
    Cha S, Tihan T, Crawford F, et al. Differentiation of low-grade oligodendrogliomas from low-grade astrocytomas by using quantitative blood-volume measurements derived from dynamic susceptibility contrast-enhanced MRI. AJNR Am J Neuroradiol 2005; 26:266–273.PubMedGoogle Scholar
  48. 48.
    Gelabert-Gonzalez M, Fernandez-Villa JM, Lopez-Garcia E, Gonzalez-Garcia J, Garcia-Allut A. [Choroid plexus tumors]. Rev Neurol 2001; 33:177–183.PubMedGoogle Scholar
  49. 49.
    Patankar TF, Haroon HA, Mills SJ, et al. Is volume transfer coefficient (K(trans)) related to histologic grade in human gliomas? AJNR Am J Neuroradiol 2005; 26:2455–2465.PubMedGoogle Scholar
  50. 50.
    Pollack IF, Lunsford LD, Flickinger JC, Dameshek HL. Prognostic factors in the diagnosis and treatment of primary central nervous system lymphoma. Cancer 1989; 63:939–947.PubMedGoogle Scholar
  51. 51.
    Cotton F, Ongolo-Zogo P, Louis-Tisserand G, et al. [Diffusion and perfusion MRI in cerebral lymphomas]. J Neuroradiol 2006; 33:220–228.PubMedGoogle Scholar
  52. 52.
    Posner JB. Management of brain metastases. Rev Neurol (Paris) 1992; 148:477–487.Google Scholar
  53. 53.
    Long DM. Capillary ultrastructure in human metastatic brain tumors. J Neurosurg 1979; 51:53–58.PubMedGoogle Scholar
  54. 54.
    Law M, Cha S, Knopp EA, Johnson G, Arnett J, Litt AW. High-grade gliomas and solitary metastases: differentiation by using perfusion and proton spectroscopic MRI. Radiology 2002; 222:715–721.PubMedGoogle Scholar
  55. 55.
    Stewart PA, Hayakawa K, Farrell CL, Del Maestro RF. Quantitative study of microvessel ultrastructure in human peritumoral brain tissue. Evidence for a blood-brain barrier defect. J Neurosurg 1987; 67:697–705.PubMedGoogle Scholar
  56. 56.
    Provenzale JM, Wang GR, Brenner T, Petrella JR, Sorensen AG. Comparison of permeability in high-grade and low-grade brain tumors using dynamic susceptibility contrast MRI. AJR Am J Roentgenol 2002; 178:711–716.PubMedGoogle Scholar
  57. 57.
    Law M, Yang S, Babb JS, et al. Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MRI with glioma grade. AJNR Am J Neuroradiol 2004; 25:746–755.PubMedGoogle Scholar
  58. 58.
    Roberts HC, Roberts TP, Brasch RC, Dillon WP. Quantitative measurement of microvascular permeability in human brain tumors achieved using dynamic contrast-enhanced MRI: correlation with histologic grade. AJNR Am J Neuroradiol 2000; 21:891–899.PubMedGoogle Scholar
  59. 59.
    George ML, Dzik-Jurasz AS, Padhani AR, et al. Non-invasive methods of assessing angiogenesis and their value in predicting response to treatment in colorectal cancer. Br J Surg 2001; 88:1628–1636.PubMedGoogle Scholar
  60. 60.
    Roberts HC, Roberts TP, Bollen AW, Ley S, Brasch RC, Dillon WP. Correlation of microvascular permeability derived from dynamic contrast-enhanced MRI with histologic grade and tumor labeling index: a study in human brain tumors. Acad Radiol 2001; 8:384–391.PubMedGoogle Scholar
  61. 61.
    Ludemann L, Grieger W, Wurm R, Budzisch M, Hamm B, Zimmer C. Comparison of dynamic contrast-enhanced MRI with WHO tumor grading for gliomas. Eur Radiol 2001; 11:1231–1241.PubMedGoogle Scholar
  62. 62.
    Johnson G, Wetzel SG, Cha S, Babb J, Tofts PS. Measuring blood volume and vascular transfer constant from dynamic, T(2)*-weighted contrast-enhanced MRI. Magn Reson Med 2004; 51:961–968.PubMedGoogle Scholar
  63. 63.
    Wolf RL, Wang J, Wang S, et al. Grading of CNS neoplasms using continuous arterial spin labeled perfusion MRI at 3 Tesla. J Magn Reson Imaging 2005; 22:475–482.PubMedGoogle Scholar
  64. 64.
    Warmuth C, Gunther M, Zimmer C. Quantification of blood flow in brain tumors: comparison of arterial spin labeling and dynamic susceptibility-weighted contrast-enhanced MRI. Radiology 2003; 228:523–532.PubMedGoogle Scholar
  65. 65.
    Chiang IC, Kuo YT, Lu CY, et al. Distinction between high-grade gliomas and solitary metastases using peritumoral 3-T magnetic resonance spectroscopy, diffusion, and perfusion imagings. Neuroradiology 2004; 46:619–627.PubMedGoogle Scholar
  66. 66.
    Burger PC. Morphologic correlates in gliomas: where do we stand? Monogr Pathol 1990:16–29Google Scholar
  67. 67.
    Muir KW, Buchan A, von Kummer R, Rother J, Baron JC. Imaging of acute stroke. Lancet Neurol 2006; 5:755–768.PubMedGoogle Scholar
  68. 68.
    Bulakbasi N, Kocaoglu M, Ors F, Tayfun C, Ucoz T. Combination of single-voxel proton MR spectroscopy and apparent diffusion coefficient calculation in the evaluation of common brain tumors. AJNR Am J Neuroradiol 2003; 24:225–233.PubMedGoogle Scholar
  69. 69.
    Sundgren PC, Dong Q, Gomez-Hassan D, Mukherji SK, Maly P, Welsh R. Diffusion tensor imaging of the brain: review of clinical applications. Neuroradiology 2004; 46:339–350.PubMedGoogle Scholar
  70. 70.
    Bulakbasi N, Guvenc I, Onguru O, Erdogan E, Tayfun C, Ucoz T. 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 2004; 28:735–746.PubMedGoogle Scholar
  71. 71.
    Gupta RK, Sinha U, Cloughesy TF, Alger JR. Inverse correlation between choline magnetic resonance spectroscopy signal intensity and the apparent diffusion coefficient in human glioma. Magn Reson Med 1999; 41:2–7.PubMedGoogle Scholar
  72. 72.
    Sugahara T, Korogi Y, Kochi M, et al. Usefulness of diffusion-weighted MRI with echo-planar technique in the evaluation of cellularity in gliomas. J Magn Reson Imaging 1999; 9:53–60.PubMedGoogle Scholar
  73. 73.
    Kitis O, Altay H, Calli C, Yunten N, Akalin T, Yurtseven T. Minimum apparent diffusion coefficients in the evaluation of brain tumors. Eur J Radiol 2005; 55:393–400.PubMedGoogle Scholar
  74. 74.
    Kono K, Inoue Y, Nakayama K, et al. The role of diffusion-weighted imaging in patients with brain tumors. AJNR Am J Neuroradiol 2001; 22:1081–1088.PubMedGoogle Scholar
  75. 75.
    Yang D, Korogi Y, Sugahara T, et al. Cerebral gliomas: prospective comparison of multivoxel 2D chemical-shift imaging proton MR spectroscopy, echoplanar perfusion and diffusion-weighted MRI. Neuroradiology 2002; 44:656–666.PubMedGoogle Scholar
  76. 76.
    Lam WW, Poon WS, Metreweli C. Diffusion MRI in glioma: does it have any role in the pre-operation determination of grading of glioma? Clin Radiol 2002; 57:219–225.PubMedGoogle Scholar
  77. 77.
    Rollin N, Guyotat J, Streichenberger N, Honnorat J, Tran Minh VA, Cotton F. Clinical relevance of diffusion and perfusion magnetic resonance imaging in assessing intra-axial brain tumors. Neuroradiology 2006; 48:150–159.PubMedGoogle Scholar
  78. 78.
    Fan GG, Deng QL, Wu ZH, Guo QY. Usefulness of diffusion/perfusion-weighted MRI in patients with non-enhancing supratentorial brain gliomas: a valuable tool to predict tumor grading? Br J Radiol 2006; 79:652–658.PubMedGoogle Scholar
  79. 79.
    Lu S, Ahn D, Johnson G, Law M, Zagzag D, Grossman RI. Diffusion-tensor MRI of intracranial neoplasia and associated peritumoral edema: introduction of the tumor infiltration index. Radiology 2004; 232:221–228.PubMedGoogle Scholar
  80. 80.
    Roberts TP, Liu F, Kassner A, Mori S, Guha A. Fiber density index correlates with reduced fractional anisotropy in white matter of patients with glioblastoma. AJNR Am J Neuroradiol 2005; 26:2183–2186.PubMedGoogle Scholar
  81. 81.
    Beppu T, Inoue T, Shibata Y, et al. Fractional anisotropy value by diffusion tensor magnetic resonance imaging as a predictor of cell density and proliferation activity of glioblastomas. Surg Neurol 2005; 63:56–61; discussion 61PubMedGoogle Scholar
  82. 82.
    Krabbe K, Gideon P, Wagn P, Hansen U, Thomsen C, Madsen F. MR diffusion imaging of human intracranial tumors. Neuroradiology 1997; 39:483–489.PubMedGoogle Scholar
  83. 83.
    Lu S, Ahn D, Johnson G, Cha S. Peritumoral diffusion tensor imaging of high-grade gliomas and metastatic brain tumors. AJNR Am J Neuroradiol 2003; 24:937–941.PubMedGoogle Scholar
  84. 84.
    Yamasaki F, Kurisu K, Satoh K, et al. Apparent diffusion coefficient of human brain tumors at MRI. Radiology 2005; 235:985–991.PubMedGoogle Scholar
  85. 85.
    Guo AC, Cummings TJ, Dash RC, Provenzale JM. Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology 2002; 224:177–183.PubMedGoogle Scholar
  86. 86.
    Filippi CG, Edgar MA, Ulug AM, Prowda JC, Heier LA, Zimmerman RD. Appearance of meningiomas on diffusion-weighted images: correlating diffusion constants with histopathologic findings. AJNR Am J Neuroradiol 2001; 22:65–72.PubMedGoogle Scholar
  87. 87.
    Mori S, van Zijl PC. Fiber tracking: principles and strategies - a technical review. NMR Biomed 2002; 15:468–480.PubMedGoogle Scholar
  88. 88.
    Wakana S, Jiang H, Nagae-Poetscher LM, van Zijl PC, Mori S. Fiber tract-based atlas of human white matter anatomy. Radiology 2004; 230:77–87.PubMedGoogle Scholar
  89. 89.
    Catani M, Howard RJ, Pajevic S, Jones DK. Virtual in vivo interactive dissection of white matter fasciculi in the human brain. Neuroimage 2002; 17:77–94.PubMedGoogle Scholar
  90. 90.
    Yu CS, Li KC, Xuan Y, Ji XM, Qin W. Diffusion tensor tractography in patients with cerebral tumors: a helpful technique for neurosurgical planning and postoperative assessment. Eur J Radiol 2005; 56:197–204.PubMedGoogle Scholar
  91. 91.
    Witwer BP, Moftakhar R, Hasan KM, et al. Diffusion-tensor imaging of white matter tracts in patients with cerebral neoplasm. J Neurosurg 2002; 97:568–575.PubMedGoogle Scholar
  92. 92.
    Price SJ, Burnet NG, Donovan T, et al. Diffusion tensor imaging of brain tumors at 3T: a potential tool for assessing white matter tract invasion? Clin Radiol 2003; 58:455–462.PubMedGoogle Scholar
  93. 93.
    Sinha S, Bastin ME, Whittle IR, Wardlaw JM. Diffusion tensor MRI of high-grade cerebral gliomas. AJNR Am J Neuroradiol 2002; 23:520–527.PubMedGoogle Scholar
  94. 94.
    Burlina AP, Aureli T, Bracco F, Conti F, Battistin L. MR spectroscopy: a powerful tool for investigating brain function and neurological diseases. Neurochem Res 2000; 25:1365–1372.PubMedGoogle Scholar
  95. 95.
    Bhakoo KK, Williams IT, Williams SR, Gadian DG, Noble MD. Proton nuclear magnetic resonance spectroscopy of primary cells derived from nervous tissue. J Neurochem 1996; 66:1254–1263.PubMedGoogle Scholar
  96. 96.
    Birken DL, Oldendorf WH. N-acetyl-L-aspartic acid: a literature review of a compound prominent in 1H-NMR spectroscopic studies of brain. Neurosci Biobehav Rev 1989; 13:23–31.PubMedGoogle Scholar
  97. 97.
    Ross B, Michaelis T. Clinical applications of magnetic resonance spectroscopy. Magn Reson Q 1994; 10:191–247.PubMedGoogle Scholar
  98. 98.
    Howe FA, Barton SJ, Cudlip SA, et al. Metabolic profiles of human brain tumors using quantitative in vivo 1H magnetic resonance spectroscopy. Magn Reson Med 2003; 49:223–232.PubMedGoogle Scholar
  99. 99.
    Shimizu H, Kumabe T, Shirane R, Yoshimoto T. Correlation between choline level measured by proton MR spectroscopy and Ki-67 labeling index in gliomas. AJNR Am J Neuroradiol 2000; 21:659–665.PubMedGoogle Scholar
  100. 100.
    Shino A, Nakasu S, Matsuda M, Handa J, Morikawa S, Inubushi T. Noninvasive evaluation of the malignant potential of intracranial meningiomas performed using proton magnetic resonance spectroscopy. J Neurosurg 1999; 91:928–934.PubMedGoogle Scholar
  101. 101.
    Manton DJ, Lowry M, Blackband SJ, Horsman A. Determination of proton metabolite concentrations and relaxation parameters in normal human brain and intracranial tumors. NMR Biomed 1995; 8:104–112.PubMedGoogle Scholar
  102. 102.
    Murphy M, Loosemore A, Clifton AG, et al. The contribution of proton magnetic resonance spectroscopy (1HMRS) to clinical brain tumor diagnosis. Br J Neurosurg 2002; 16:329–334.PubMedGoogle Scholar
  103. 103.
    Ishimaru H, Morikawa M, Iwanaga S, Kaminogo M, Ochi M, Hayashi K. Differentiation between high-grade glioma and metastatic brain tumor using single-voxel proton MR spectroscopy. Eur Radiol 2001; 11:1784–1791.PubMedGoogle Scholar
  104. 104.
    Kreis R, Ernst T, Ross BD. Development of the human brain: In vivo quantification of metabolite and water content with proton magnetic resonance spectroscopy. Magn Reson Med 1993; 30:424–437.PubMedGoogle Scholar
  105. 105.
    Castillo M, Smith JK, Kwock L. Correlation of myo-inositol levels and grading of cerebral astrocytomas. AJNR Am J Neuroradiol 2000; 21:1645–1649.PubMedGoogle Scholar
  106. 106.
    Barba I, Moreno A, Martinez-Perez I, et al. Magnetic resonance spectroscopy of brain hemangiopericytomas: high myoinositol concentrations and discrimination from meningiomas. J Neurosurg 2001; 94:55–60.PubMedGoogle Scholar
  107. 107.
    Norfray JF, Tomita T, Byrd SE, Ross BD, Berger PA, Miller RS. Clinical impact of MR spectroscopy when MRI is indeterminate for pediatric brain tumors. AJR Am J Roentgenol 1999; 173:119–125.PubMedGoogle Scholar
  108. 108.
    Opstad KS, Provencher SW, Bell BA, Griffiths JR, Howe FA. Detection of elevated glutathione in meningiomas by quantitative in vivo 1H MRS. Magn Reson Med 2003; 49:632–637.PubMedGoogle Scholar
  109. 109.
    Stubbs M, Veech RL, Griffiths JR. Tumor metabolism: the lessons of magnetic resonance spectroscopy. Adv Enzyme Regul 1995; 35:101–115.PubMedGoogle Scholar
  110. 110.
    Kugel H, Heindel W, Ernestus RI, Bunke J, du Mesnil R, Friedmann G. Human brain tumors: spectral patterns detected with localized H-1 MR spectroscopy. Radiology 1992; 183:701–709.PubMedGoogle Scholar
  111. 111.
    Alger JR, Frank JA, Bizzi A, et al. Metabolism of human gliomas: assessment with H-1 MR spectroscopy and F-18 fluorodeoxyglucose PET. Radiology 1990; 177:633–641.PubMedGoogle Scholar
  112. 112.
    Auer DP, Gossl C, Schirmer T, Czisch M. Improved analysis of 1H-MR spectra in the presence of mobile lipids. Magn Reson Med 2001; 46:615–618.PubMedGoogle Scholar
  113. 113.
    Kuesel AC, Sutherland GR, Halliday W, Smith IC. 1H MRS of high-grade astrocytomas: mobile lipid accumulation in necrotic tissue. NMR Biomed 1994; 7:149–155.PubMedGoogle Scholar
  114. 114.
    Barba I, Cabanas ME, Arus C. The relationship between nuclear magnetic resonance-visible lipids, lipid droplets, and cell proliferation in cultured C6 cells. Cancer Res 1999; 59:1861–1868.PubMedGoogle Scholar
  115. 115.
    Hakumaki JM, Poptani H, Sandmair AM, Yla-Herttuala S, Kauppinen RA. 1H MRS detects polyunsaturated fatty acid accumulation during gene therapy of glioma: implications for the in vivo detection of apoptosis. Nat Med 1999; 5:1323–1327.PubMedGoogle Scholar
  116. 116.
    Law M, Yang S, Wang H, et al. Glioma grading: sensitivity, specificity, and predictive values of perfusion MRI and proton MR spectroscopic imaging compared with conventional MRI. AJNR Am J Neuroradiol 2003; 24:1989–1998.PubMedGoogle Scholar
  117. 117.
    Herminghaus S, Dierks T, Pilatus U, et al. Determination of histopathological tumor grade in neuroepithelial brain tumors by using spectral pattern analysis of in vivo spectroscopic data. J Neurosurg 2003; 98:74–81.PubMedGoogle Scholar
  118. 118.
    Hsu YY, Chang CN, Wie KJ, Lim KE, Hsu WC, Jung SM. Proton magnetic resonance spectroscopic imaging of cerebral gliomas: correlation of metabolite ratios with histopathologic grading. Chang Gung Med J 2004; 27:399–407.PubMedGoogle Scholar
  119. 119.
    Kaminogo M, Ishimaru H, Morikawa M, et al. Diagnostic potential of short echo time MR spectroscopy of gliomas with single-voxel and point-resolved spatially localised proton spectroscopy of brain. Neuroradiology 2001; 43:353–363.PubMedGoogle Scholar
  120. 120.
    Ott D, Hennig J, Ernst T. Human brain tumors: assessment with in vivo proton MR spectroscopy. Radiology 1993; 186:745–752.PubMedGoogle Scholar
  121. 121.
    Paulus W, Peiffer J. Intratumoral histologic heterogeneity of gliomas. A quantitative study. Cancer 1989; 64:442–447.PubMedGoogle Scholar
  122. 122.
    Cheng LL, Chang IW, Louis DN, Gonzalez RG. Correlation of high-resolution magic angle spinning proton magnetic resonance spectroscopy with histopathology of intact human brain tumor specimens. Cancer Res 1998; 58:1825–1832.PubMedGoogle Scholar
  123. 123.
    Sabatier J, Ibarrola D, Malet-Martino M, Berry I. [Brain tumors: interest of magnetic resonance spectroscopy for the diagnosis and the prognosis]. Rev Neurol (Paris) 2001; 157:858–862.Google Scholar
  124. 124.
    McKnight TR, von dem Bussche MH, Vigneron DB, et al. Histopathological validation of a three-dimensional magnetic resonance spectroscopy index as a predictor of tumor presence. J Neurosurg 2002; 97:794–802.PubMedGoogle Scholar
  125. 125.
    Zhang M, Olsson Y. Hematogenous metastases of the human brain–characteristics of peritumoral brain changes: a review. J Neurooncol 1997; 35:81–89.PubMedGoogle Scholar
  126. 126.
    Fayed N, Modrego PJ. The contribution of magnetic resonance spectroscopy and echoplanar perfusion-weighted MRI in the initial assessment of brain tumors. J Neurooncol 2005; 72:261–265.PubMedGoogle Scholar
  127. 127.
    Beaulieu C, Allen PS. Determinants of anisotropic water diffusion in nerves. Magn Reson Med 1994; 31:394–400.PubMedGoogle Scholar
  128. 128.
    Ogawa S, Menon RS, Tank DW, et al. Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model. Biophys J 1993; 64:803–812.PubMedGoogle Scholar
  129. 129.
    Heeger DJ, Ress D. What does fMRI tell us about neuronal activity? Nat Rev Neurosci 2002; 3:142–151.PubMedGoogle Scholar
  130. 130.
    Toronov V, Walker S, Gupta R, et al. The roles of changes in deoxyhemoglobin concentration and regional cerebral blood volume in the fMRI BOLD signal. Neuroimage 2003; 19:1521–1531.PubMedGoogle Scholar
  131. 131.
    Wilkinson ID, Romanowski CA, Jellinek DA, Morris J, Griffiths PD. Motor functional MRI for pre-operative and intraoperative neurosurgical guidance. Br J Radiol 2003; 76:98–103.PubMedGoogle Scholar
  132. 132.
    Pujol J, Conesa G, Deus J, et al. Presurgical identification of the primary sensorimotor cortex by functional magnetic resonance imaging. J Neurosurg 1996; 84:7–13.PubMedGoogle Scholar
  133. 133.
    Pujol J, Conesa G, Deus J, Lopez-Obarrio L, Isamat F, Capdevila A. Clinical application of functional magnetic resonance imaging in presurgical identification of the central sulcus. J Neurosurg 1998; 88:863–869.PubMedGoogle Scholar
  134. 134.
    Lehericy S, Duffau H, Cornu P, et al. Correspondence between functional magnetic resonance imaging somatotopy and individual brain anatomy of the central region: comparison with intraoperative stimulation in patients with brain tumors. J Neurosurg 2000; 92:589–598.PubMedGoogle Scholar
  135. 135.
    Lee CC, Ward HA, Sharbrough FW, et al. Assessment of functional MRI in neurosurgical planning. AJNR Am J Neuroradiol 1999; 20:1511–1519.PubMedGoogle Scholar
  136. 136.
    Fandino J, Kollias SS, Wieser HG, Valavanis A, Yonekawa Y. Intraoperative validation of functional magnetic resonance imaging and cortical reorganization patterns in patients with brain tumors involving the primary motor cortex. J Neurosurg 1999; 91:238–250.PubMedGoogle Scholar
  137. 137.
    Holodny AI, Schulder M, Liu WC, Wolko J, Maldjian JA, Kalnin AJ. The effect of brain tumors on BOLD functional MRI activation in the adjacent motor cortex: implications for image-guided neurosurgery. AJNR Am J Neuroradiol 2000; 21:1415–1422.PubMedGoogle Scholar
  138. 138.
    Ulmer JL, Hacein-Bey L, Mathews VP, et al. Lesion-induced pseudo-dominance at functional magnetic resonance imaging: implications for preoperative assessments. Neurosurgery 2004; 55:569–579; discussion 580–561PubMedGoogle Scholar
  139. 139.
    Schreiber A, Hubbe U, Ziyeh S, Hennig J. The influence of gliomas and nonglial space-occupying lesions on blood-oxygen-level-dependent contrast enhancement. AJNR Am J Neuroradiol 2000; 21:1055–1063.PubMedGoogle Scholar
  140. 140.
    Hossmann KA, Linn F, Okada Y. Bioluminescence and fluoroscopic imaging of tissue pH and metabolites in experimental brain tumors of cat. NMR Biomed 1992; 5:259–264.PubMedGoogle Scholar
  141. 141.
    Laurienti PJ, Field AS, Burdette JH, Maldjian JA, Yen YF, Moody DM. Dietary caffeine consumption modulates fMRI measures. Neuroimage 2002; 17:751–757.PubMedGoogle Scholar
  142. 142.
    Buhmann C, Glauche V, Sturenburg HJ, Oechsner M, Weiller C, Buchel C. Pharmacologically modulated fMRI–cortical responsiveness to levodopa in drug-naive hemiparkinsonian patients. Brain 2003; 126:451–461.PubMedGoogle Scholar
  143. 143.
    Kamada K, Todo T, Masutani Y, et al. Combined use of tractography-integrated functional neuronavigation and direct fiber stimulation. J Neurosurg 2005; 102:664–672.PubMedGoogle Scholar
  144. 144.
    Li ZX, Dai JP, Jiang T, et al. [Function magnetic resonance imaging and diffusion tensor tractography in patients with brain gliomas involving motor areas: clinical application and outcome]. Zhonghua Wai Ke Za Zhi 2006; 44:1275–1279.PubMedGoogle Scholar
  145. 145.
    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; 30:1100–1111.PubMedGoogle Scholar
  146. 146.
    Bonavita S, Di Salle F, Tedeschi G. Proton MRS in neurological disorders. Eur J Radiol 1999; 30:125–131.PubMedGoogle Scholar
  147. 147.
    Burger PC, Fuller GN. Pathology–trends and pitfalls in histologic diagnosis, immunopathology, and applications of oncogene research. Neurol Clin 1991; 9:249–271.PubMedGoogle Scholar
  148. 148.
    Fulham MJ, Bizzi A, Dietz MJ, et al. Mapping of brain tumor metabolites with proton MR spectroscopic imaging: clinical relevance. Radiology 1992; 185:675–686.PubMedGoogle Scholar
  149. 149.
    Sijens PE, Vecht CJ, Levendag PC, van Dijk P, Oudkerk M. Hydrogen magnetic resonance spectroscopy follow-up after radiation therapy of human brain cancer. Unexpected inverse correlation between the changes in tumor choline level and post-gadolinium magnetic resonance imaging contrast. Invest Radiol 1995; 30:738–744.PubMedGoogle Scholar
  150. 150.
    Usenius T, Usenius JP, Tenhunen M, et al. Radiation-induced changes in human brain metabolites as studied by 1H nuclear magnetic resonance spectroscopy in vivo. Int J Radiat Oncol Biol Phys 1995; 33:719–724.PubMedGoogle Scholar
  151. 151.
    Taylor JS, Langston JW, Reddick WE, et al. Clinical value of proton magnetic resonance spectroscopy for differentiating recurrent or residual brain tumor from delayed cerebral necrosis. Int J Radiat Oncol Biol Phys 1996; 36:1251–1261.PubMedGoogle Scholar
  152. 152.
    Sugahara T, Korogi Y, Tomiguchi S, et al. Posttherapeutic intraaxial brain tumor: the value of perfusion-sensitive contrast-enhanced MRI for differentiating tumor recurrence from nonneoplastic contrast-enhancing tissue. AJNR Am J Neuroradiol 2000; 21:901–909.PubMedGoogle Scholar
  153. 153.
    Hein PA, Eskey CJ, Dunn JF, Hug EB. Diffusion-weighted imaging in the follow-up of treated high-grade gliomas: tumor recurrence versus radiation injury. AJNR Am J Neuroradiol 2004; 25:201–209.PubMedGoogle Scholar
  154. 154.
    Asao C, Korogi Y, Kitajima M, et al. Diffusion-weighted imaging of radiation-induced brain injury for differentiation from tumor recurrence. AJNR Am J Neuroradiol 2005; 26:1455–1460.PubMedGoogle Scholar
  155. 155.
    Willems JG, Alva-Willems JM. Accuracy of cytologic diagnosis of central nervous system neoplasms in sterotactic biopsies. Acta Cytol 1984; 28:243–249.PubMedGoogle Scholar
  156. 156.
    Fratkin JD, Ward MM, Roberts DW, Sullivan MM. CT-guided stereotactic biopsy of intracranial lesions: correlation between core biopsy and aspiration smear. Diagn Cytopathol 1986; 2:126–132.PubMedGoogle Scholar
  157. 157.
    Krieger MD, Chandrasoma PT, Zee CS, Apuzzo ML. Role of stereotactic biopsy in the diagnosis and management of brain tumors. Semin Surg Oncol 1998; 14:13–25.PubMedGoogle Scholar
  158. 158.
    Kelly PJ, Daumas-Duport C, Kispert DB, Kall BA, Scheithauer BW, Illig JJ. Imaging-based stereotaxic serial biopsies in untreated intracranial glial neoplasms. J Neurosurg 1987; 66:865–874.PubMedGoogle Scholar
  159. 159.
    Cha S, Knopp EA, Johnson G, Wetzel SG, Litt AW, Zagzag D. Intracranial mass lesions: dynamic contrast-enhanced susceptibility-weighted echo-planar perfusion MRI. Radiology 2002; 223:11–29.PubMedGoogle Scholar
  160. 160.
    Baik HM, Choe BY, Son BC, et al. Feasibility of proton chemical shift imaging with a stereotactic headframe. Magn Reson Imaging 2003; 21:55–59.PubMedGoogle Scholar
  161. 161.
    Kondziolka D, Somaza S, Comey C, et al. Radiosurgery and fractionated radiation therapy: comparison of different techniques in an in vivo rat glioma model. J Neurosurg 1996; 84:1033–1038.PubMedGoogle Scholar
  162. 162.
    Hormigo A, Friedlander DR, Brittis PA, Zagzag D, Grumet M. Reduced tumorigenicity of rat glioma cells in the brain when mediated by hygromycin phosphotransferase. J Neurosurg 2001; 94:596–604.PubMedGoogle Scholar
  163. 163.
    Hakumaki JM, Poptani H, Puumalainen AM, et al. Quantitative 1H nuclear magnetic resonance diffusion spectroscopy of BT4C rat glioma during thymidine kinase-mediated gene therapy in vivo: identification of apoptotic response. Cancer Res 1998; 58:3791–3799.PubMedGoogle Scholar
  164. 164.
    Jacobs AH, Dittmar C, Winkeler A, Garlip G, Heiss WD. Molecular imaging of gliomas. Mol Imaging 2002; 1:309–335.PubMedGoogle Scholar
  165. 165.
    Zhang Z, Jiang Q, Jiang F, et al. in vivo magnetic resonance imaging tracks adult neural progenitor cell targeting of brain tumor. Neuroimage 2004; 23:281–287.PubMedGoogle Scholar
  166. 166.
    Magnitsky S, Watson DJ, Walton RM, et al. in vivo and Ex Vivo MRI detection of localized and disseminated neural stem cell grafts in the mouse brain. Neuroimage 2005; 26:744–754.PubMedGoogle Scholar
  167. 167.
    Su H, Forbes A, Gambhir SS, Braun J. Quantitation of cell number by a positron emission tomography reporter gene strategy. Mol Imaging Biol 2004; 6:139–148.PubMedGoogle Scholar
  168. 168.
    Doubrovin M, Ponomarev V, Beresten T, et al. Imaging transcriptional regulation of p53-dependent genes with positron emission tomography in vivo. Proc Natl Acad Sci U S A 2001; 98:9300–9305.PubMedGoogle Scholar
  169. 169.
    Serganova I, Doubrovin M, Vider J, et al. Molecular imaging of temporal dynamics and spatial heterogeneity of hypoxia-inducible factor-1 signal transduction activity in tumors in living mice. Cancer Res 2004; 64:6101–6108.PubMedGoogle Scholar
  170. 170.
    Uhrbom L, Nerio E, Holland EC. Dissecting tumor maintenance requirements using bioluminescence imaging of cell proliferation in a mouse glioma model. Nat Med 2004; 10:1257–1260.PubMedGoogle Scholar
  171. 171.
    Wen B, Burgman P, Zanzonico P, et al. A preclinical model for noninvasive imaging of hypoxia-induced gene expression; comparison with an exogenous marker of tumor hypoxia. Eur J Nucl Med Mol Imaging 2004; 31:1530–1538.PubMedGoogle Scholar
  172. 172.
    Gillies RJ, Raghunand N, Karczmar GS, Bhujwalla ZM. MRI of the tumor microenvironment. J Magn Reson Imaging 2002; 16:430–450.PubMedGoogle Scholar
  173. 173.
    Garcia-Martin ML, Martinez GV, Raghunand N, Sherry AD, Zhang S, Gillies RJ. High resolution pH(e) imaging of rat glioma using pH-dependent relaxivity. Magn Reson Med 2006; 55:309–315.PubMedGoogle Scholar
  174. 174.
    Poptani H, Duvvuri U, Miller CG, et al. T1rho imaging of murine brain tumors at 4 T. Acad Radiol 2001; 8:42–47.PubMedGoogle Scholar
  175. 175.
    Phelps ME, Mazziotta JC. Positron emission tomography: human brain function and biochemistry. Science 1985; 228:799–809.PubMedGoogle Scholar
  176. 176.
    Phelps ME. PET: the merging of biology and imaging into molecular imaging. J Nucl Med 2000; 41:661–681.PubMedGoogle Scholar
  177. 177.
    Price P. PET as a potential tool for imaging molecular mechanisms of oncology in man. Trends Mol Med 2001; 7:442–446.PubMedGoogle Scholar
  178. 178.
    Heiss WD, Heindel W, Herholz K, et al. Positron emission tomography of fluorine-18-deoxyglucose and image-guided phosphorus-31 magnetic resonance spectroscopy in brain tumors. J Nucl Med 1990; 31:302–310.PubMedGoogle Scholar
  179. 179.
    Herholz K, Heindel W, Luyten PR, et al. in vivo imaging of glucose consumption and lactate concentration in human gliomas. Ann Neurol 1992; 31:319–327.PubMedGoogle Scholar
  180. 180.
    Mineura K, Yasuda T, Kowada M, Shishido F, Ogawa T, Uemura K. Positron emission tomographic evaluation of histological malignancy in gliomas using oxygen-15 and fluorine-18-fluorodeoxyglucose. Neurol Res 1986; 8:164–168.PubMedGoogle Scholar
  181. 181.
    Nishioka T, Oda Y, Seino Y, et al. Distribution of the glucose transporters in human brain tumors. Cancer Res 1992; 52:3972–3979.PubMedGoogle Scholar
  182. 182.
    Brooks DJ, Beaney RP, Lammertsma AA, et al. Glucose transport across the blood-brain barrier in normal human subjects and patients with cerebral tumors studied using [11C]3-O-methyl-D-glucose and positron emission tomography. J Cereb Blood Flow Metab 1986; 6:230–239.PubMedGoogle Scholar
  183. 183.
    Glantz MJ, Hoffman JM, Coleman RE, et al. Identification of early recurrence of primary central nervous system tumors by [18F]fluorodeoxyglucose positron emission tomography. Ann Neurol 1991; 29:347–355.PubMedGoogle Scholar
  184. 184.
    Kim EE, Chung SK, Haynie TP, et al. Differentiation of residual or recurrent tumors from post-treatment changes with F-18 FDG PET. Radiographics 1992; 12:269–279.PubMedGoogle Scholar
  185. 185.
    Tyler JL, Diksic M, Villemure JG, et al. Metabolic and hemodynamic evaluation of gliomas using positron emission tomography. J Nucl Med 1987; 28:1123–1133.PubMedGoogle Scholar
  186. 186.
    Isselbacher KJ. Sugar and amino acid transport by cells in culture–differences between normal and malignant cells. N Engl J Med 1972; 286:929–933.PubMedGoogle Scholar
  187. 187.
    Jager PL, Vaalburg W, Pruim J, de Vries EG, Langen KJ, Piers DA. Radiolabeled amino acids: basic aspects and clinical applications in oncology. J Nucl Med 2001; 42:432–445.PubMedGoogle Scholar
  188. 188.
    Sato N, Suzuki M, Kuwata N, et al. Evaluation of the malignancy of glioma using 11C-methionine positron emission tomography and proliferating cell nuclear antigen staining. Neurosurg Rev 1999; 22:210–214.PubMedGoogle Scholar
  189. 189.
    Herholz K, Holzer T, Bauer B, et al. 11C-methionine PET for differential diagnosis of low-grade gliomas. Neurology 1998; 50:1316–1322.PubMedGoogle Scholar
  190. 190.
    Goldman S, Levivier M, Pirotte B, et al. Regional methionine and glucose uptake in high-grade gliomas: a comparative study on PET-guided stereotactic biopsy. J Nucl Med 1997; 38:1459–1462.PubMedGoogle Scholar
  191. 191.
    Jacobs A, Tjuvajev JG, Dubrovin M, et al. Positron emission tomography-based imaging of transgene expression mediated by replication-conditional, oncolytic herpes simplex virus type 1 mutant vectors in vivo. Cancer Res 2001; 61:2983–2995.PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Sanjeev Chawla
    • 1
  • Harish Poptani
    • 1
  • Elias R. Melhem
    • 1
  1. 1.Department of RadiologyUniversity of PennsylvaniaPhiladelphiaUSA

Personalised recommendations