Correlations between Perfusion MR Imaging Cerebral Blood Volume, Microvessel Quantification, and Clinical Outcome Using Stereotactic Analysis in Recurrent High-Grade Glioma

References

1. 1.↵
   1. Sharma S,
   2. Sharma MC,
   3. Sarkar C

   . Morphology of angiogenesis in human cancer: a conceptual overview, histoprognostic perspective and significance of neoangiogenesis. Histopathology 2005;46:481–89

   CrossRefPubMedWeb of Science
2. 2.↵
   1. Schiffer D,
   2. Chio A,
   3. Mauro GA,
   4. et al

   . The vascular response to tumor infiltration in malignant gliomas. Acta Neuropathol 1989;77:369–78

   CrossRefPubMed
3. 3.↵
   1. Abdulrauf SI,
   2. Edvardsen K,
   3. Ho KL,
   4. et al

   . Vascular endothelial growth factor expression and vascular density as prognostic markers of survival in patients with low-grade astrocytoma. J Neurosurg 1998;88:513–20

   PubMedWeb of Science
4. 4.↵
   1. Korkolopoulou P,
   2. Patsouris E,
   3. Kavantzas N,
   4. et al

   . Prognostic implications of microvessel morphometry in diffuse astrocytic neoplasms. Neuropathol Appl Neurobiol 2002;28:57–66

   CrossRefPubMed
5. 5.↵
   1. Leon SP,
   2. Folkerth RD,
   3. Black PM

   . Microvessel density is a prognostic indicator for patients with astroglial brain tumors. Cancer 1996;77:362–72

   CrossRefPubMedWeb of Science
6. 6.↵
   1. Wesseling P,
   2. van der Laak JA,
   3. Link M,
   4. et al

   . Quantitative analysis of microvascular changes in diffuse astrocytic neoplasms with increasing grade of malignancy. Hum Pathol 1998;29:352–28

   CrossRefPubMedWeb of Science
7. 7.↵
   1. Wesseling P,
   2. van der Laak JA,
   3. de Leeuw H,
   4. et al

   . Quantitative immunohistological analysis of the microvasculature in untreated human glioblastoma multiforme: computer-assisted image analysis of whole-tumor sections. J Neurosurg 1994;81:902–09

   CrossRefPubMedWeb of Science
8. 8.↵
   1. Birner P,
   2. Piribauer M,
   3. Fischer I,
   4. et al

   . Vascular patterns in glioblastoma influence clinical outcome and associate with variable expression of angiogenic proteins: evidence for distinct angiogenic subtypes. Brain Pathol 2003;13:133–43

   PubMedWeb of Science
9. 9.↵
   1. Folkerth RD

   . Histologic measures of angiogenesis in human primary brain tumors. Cancer Treat Res 2004;117:79–95

   PubMed
10. 10.↵
    1. Korkolopoulou P,
    2. Patsouris E,
    3. Konstantinidou AE,
    4. et al

    . Hypoxia-inducible factor 1alpha/vascular endothelial growth factor axis in astrocytomas. Associations with microvessel morphometry, proliferation and prognosis. Neuropathol Appl Neurobiol 2004;30:267–78

    CrossRefPubMedWeb of Science
11. 11.↵
    1. Weidner N,
    2. Semple JP,
    3. Welch WR,
    4. et al

    . Tumor angiogenesis and metastasis: correlation in invasive breast carcinoma. N Engl J Med 1991;324:1–8

    CrossRefPubMedWeb of Science
12. 12.↵
    1. Macchiarini P,
    2. Fontaini G,
    3. Hardin MJ,
    4. et al

    . Relation of neovasculature to metastasis of non-small lung cancer. Lancet 1992;340:145–46

    CrossRefPubMedWeb of Science
13. 13.↵
    1. Hollingsworth HC,
    2. Kohn EC,
    3. Steinberg SM,
    4. et al

    . Tumor angiogenesis in advanced stage ovarian carcinoma. Am J Pathol 1995;147:33

    PubMedWeb of Science
14. 14.↵
    1. Bono AV,
    2. Celato N,
    3. Cova V,
    4. et al

    . Microvessel density in prostate carcinoma. Prostate Cancer Prostatic Dis 2002;5:123–27

    CrossRefPubMedWeb of Science
15. 15.↵
    1. Delahunt B,
    2. Bethwaite PB,
    3. Thornton A

    . Prognostic significance of microscopic vascularity for clear cell renal cell carcinoma. Br J Urol 1997;80:401–04

    PubMedWeb of Science
16. 16.↵
    1. Lev MH,
    2. Ozsunar Y,
    3. Henson JW,
    4. 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]. AJNR Am J Neuroradiol 2004;25:214–21

    Abstract/FREE Full Text
17. 17.↵
    1. Knopp EA,
    2. Cha S,
    3. Johnson G,
    4. et al

    . Glial neoplasms: dynamic contrast-enhanced T2*-weighted MR imaging. Radiology 1999;211:791–98

    CrossRefPubMedWeb of Science
18. 18.↵
    1. Boxerman JL,
    2. Schmainda KM,
    3. 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;27:859–67

    Abstract/FREE Full Text
19. 19.↵
    1. Law M,
    2. Yang S,
    3. Wang H,
    4. et al

    . Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging. AJNR Am J Neuroradiol 2003;24:1989–98

    Abstract/FREE Full Text
20. 20.↵
    1. Law M,
    2. Young RJ,
    3. Babb JS,
    4. et al

    . Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology 2008;247:490–98. Epub 2008 Mar 18

    CrossRefPubMedWeb of Science
21. 21.↵
    1. Cha S,
    2. Johnson G,
    3. Wadghiri YZ,
    4. et al

    . Dynamic, contrast-enhanced perfusion MRI in mouse gliomas: correlation with histopathology. Magn Reson Med 2003;49:848–55

    CrossRefPubMedWeb of Science
22. 22.↵
    1. Pathak AP,
    2. Schmainda KM,
    3. Ward BD,
    4. et al

    . MR-derived cerebral blood volume maps: issues regarding histological validation and assessment of tumor angiogenesis. Magn Reson Med 2001;46:735–47

    CrossRefPubMedWeb of Science
23. 23.↵
    1. Ali MM,
    2. Janic B,
    3. Babajani-Feremi A,
    4. et al

    . Changes in vascular permeability and expression of different angiogenic factors following anti-angiogenic treatment in rat glioma. PLoS One 2010;5:e8727

    CrossRefPubMed
24. 24.↵
    1. Muruganandham M,
    2. Lupu M,
    3. Dyke JP,
    4. et al

    . Preclinical evaluation of tumor microvascular response to a novel antiangiogenic/antitumor agent RO0281501 by dynamic contrast-enhanced MRI at 1.5 T. Mol Cancer Ther 2006;5:1950–57

    Abstract/FREE Full Text
25. 25.↵
    1. Wilmes LJ,
    2. Pallavicini MG,
    3. Fleming LM,
    4. et al

    . AG-013736, a novel inhibitor of VEGF receptor tyrosine kinases, inhibits breast cancer growth and decreases vascular permeability as detected by dynamic contrast-enhanced magnetic resonance imaging. Magn Reson Imaging 2007;25:319–27

    CrossRefPubMed
26. 26.↵
    1. Hyodo F,
    2. Chandramouli GV,
    3. Matsumoto S,
    4. et al

    . Estimation of tumor microvessel density by MRI using a blood pool contrast agent. Int J Oncol 2009;35:797–804

    PubMed
27. 27.↵
    1. Drevs J,
    2. Müller-Driver R,
    3. Wittig C,
    4. 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;62:4015–22

    Abstract/FREE Full Text
28. 28.↵
    1. Badruddoja MA,
    2. Krouwer HG,
    3. Rand SD,
    4. et al

    . Antiangiogenic effects of dexamethasone in 9L gliosarcoma assessed by MRI cerebral blood volume maps. Neuro Oncol 2003;5:235–43

    Abstract/FREE Full Text
29. 29.↵
    1. Doblas S,
    2. He T,
    3. Saunders D,
    4. et al

    . Glioma morphology and tumor-induced vascular alterations revealed in seven rodent glioma models by in vivo magnetic resonance imaging and angiography. J Magn Reson Imaging 2010;32:267–75

    CrossRefPubMed
30. 30.↵
    1. Sorensen AG

    . Perfusion MR imaging: moving forward. Radiology 2008;249:416–17

    CrossRefPubMed
31. 31.↵
    1. Hu LS,
    2. Baxter LC,
    3. Pinnaduwage DS,
    4. et al

    . Optimized preload leakage-correction methods to improve the diagnostic accuracy of dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging in posttreatment gliomas. AJNR Am J Neuroradiol 2010;31:40–48

    Abstract/FREE Full Text
32. 32.↵
    1. Paulson ES,
    2. Schmainda KM

    . Comparison of dynamic susceptibility-weighted contrast-enhanced MR methods: recommendations for measuring relative cerebral blood volume in brain tumors. Radiology 2008;249:601–13

    CrossRefPubMedWeb of Science
33. 33.↵
    1. Manka C,
    2. Traber F,
    3. Gleseke J,
    4. et al

    . Three-dimensional dynamic susceptibility weighted perfusion MR imaging at 3.0 T: feasibility and contrast agent dose. Radiology 2005;234:869–77

    CrossRefPubMedWeb of Science
34. 34.↵
    1. Hu LS,
    2. Baxter LC,
    3. Smith KA,
    4. et al

    . Relative cerebral blood volume values to differentiate high-grade glioma recurrence from posttreatment radiation effect: direct correlation between image-guided tissue histopathology and localized dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging measurements. AJNR Am J Neuroradiol 2009;30:552–58

    Abstract/FREE Full Text
35. 35.↵
    1. Stadlbauer A,
    2. Ganslandt O,
    3. Buslei R,
    4. et al

    . Gliomas: histopathologic evaluation of changes in directionality and magnitude of water diffusion at diffusion-tensor MR imaging. Radiology 2006;240:803–10

    CrossRefPubMedWeb of Science
36. 36.↵
    1. Sadeghi N,
    2. Salmon I,
    3. Decaestecker C,
    4. et al

    . Stereotactic comparison among cerebral blood volume, methionine uptake, and histopathology in brain glioma. AJNR Am J Neuroradiol 2007;28:455–61

    Abstract/FREE Full Text
37. 37.↵
    1. Louis DN,
    2. Ohgaki H,
    3. Wiestler OD,
    4. et al

    ., eds. WHO classification of tumours of the central nervous system. Lyon, France: IARC; 2002
38. 38.↵
    1. Haris M,
    2. Husain N,
    3. Singh A,
    4. et al

    . Dynamic contrast-enhanced derived cerebral blood volume correlates better with leak correction than with no correction for vascular endothelial growth factor, microvascular density, and grading of astrocytoma. J Comput Assist Tomogr 2008;32:955–65

    CrossRefPubMed
39. 39.↵
    1. Winkler F,
    2. Kozin SV,
    3. Tong RT,
    4. et al

    . Kinetics of vascular normalization by VEGFR2 blockade governs brain tumor response to radiation: role of oxygenation, angiopoietin-1, and matrix metalloproteinases. Cancer Cell 2004;6:553–63

    CrossRefPubMedWeb of Science
40. 40.↵
    1. Weibel ER

    . Estimation of Basic Stereologic Parameters: Theoretical Foundations of Stereology. Vol. 2. London, UK: Academic Press; 1980
41. 41.↵
    1. Liao W,
    2. Liu Y,
    3. Wang X,
    4. et al

    . Differentiation of primary central nervous system lymphoma and high-grade glioma with dynamic susceptibility contrast-enhanced perfusion magnetic resonance imaging. Acta Radiol 2009;50:217–25

    Abstract/FREE Full Text
42. 42.↵
    1. Bisdas S,
    2. Kirkpatrick M,
    3. Giglio P,
    4. et al

    . Cerebral blood volume measurements by perfusion-weighted MR imaging in gliomas: ready for prime time in predicting short-term outcome and recurrent disease? AJNR Am J Neuroradiol 2009;30:681–88

    Abstract/FREE Full Text
43. 43.↵
    1. Hirai T,
    2. Murakami R,
    3. Nakamura H,
    4. et al

    . Prognostic value of perfusion MR imaging of high-grade astrocytomas: long-term follow-up study. AJNR Am J Neuroradiol 2008;29:1505–10

    Abstract/FREE Full Text
44. 44.↵
    1. Jackson RJ,
    2. Fuller GN,
    3. Abi-Said D,
    4. et al

    . Limitations of stereotactic biopsy in the initial management of gliomas. Neuro Oncol 2001;3:193–200

    Abstract/FREE Full Text
45. 45.↵
    1. Young GS,
    2. Setayesh K

    . Spin-echo echo-planar perfusion MR imaging in the differential diagnosis of solitary enhancing brain lesions: distinguishing solitary metastases from primary glioma. AJNR Am J Neuroradiol 2009;30:575–77

    Abstract/FREE Full Text
46. 46.↵
    1. Schmainda KM,
    2. Rand SD,
    3. Joseph AM,
    4. et al

    . Characterization of a first-pass gradient-echo spin-echo method to predict brain tumor grade and angiogenesis. AJNR Am J Neuroradiol 2004;25:1524–32

    Abstract/FREE Full Text
47. 47.↵
    1. Kassner A,
    2. Annesley DJ,
    3. Zhu XP,
    4. et al

    . Abnormalities of the contrast re-circulation phase in cerebral tumors demonstrated using dynamic susceptibility contrast-enhanced imaging: a possible marker of vascular tortuosity. J Magn Reson Imaging 2000;11:103–13

    CrossRefPubMed
48. 48.↵
    1. Emblem KE,
    2. Nedregaard B,
    3. Nome T,
    4. et al

    . Glioma grading by using histogram analysis of blood volume heterogeneity from MR-derived cerebral blood volume maps. Radiology 2008;247:808–17

    CrossRefPubMedWeb of Science
49. 49.↵
    1. Gijtenbeek JM,
    2. Wesseling P,
    3. Maass C,
    4. et al

    . Three-dimensional reconstruction of tumor microvasculature: simultaneous visualization of multiple components in paraffin-embedded tissue. Angiogenesis 2005;8:297–305

    CrossRefPubMed
50. 50.↵
    1. Rowley HA,
    2. Scialfa G,
    3. Gao PY,
    4. et al

    . Contrast-enhanced MR imaging of brain lesions: a large-scale intraindividual crossover comparison of gadobenate dimeglumine versus gadodiamide. AJNR Am J Neuroradiol 2008;29:1684–91

    Abstract/FREE Full Text
51. 51.↵
    1. Poetker DM,
    2. Jursinic PA,
    3. Runge-Samuelson CL,
    4. et al

    . Distortion of magnetic resonance images used in gamma knife radiosurgery treatment planning: implications for acoustic neuroma outcomes. Otol Neurotol 2005;26:1220–28

    CrossRefPubMed