Percent change of perfusion skewness and kurtosis: A potential imaging biomarker for early treatment response in patients with newly diagnosed glioblastomas

Radiology

Volumn 264, Issue 3, 2012, Pages 834-843

  Baek, Hye Jin ^a   Kim, Ho Sung ^a   Kim, Namkug ^a   Choi, Young Jun ^a   Kim, Young Joong ^a  

^a University of Ulsan College of Medicine   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

GADOLINIUM PENTETATE; TEMOZOLOMIDE;

ADULT; AGED; ARTICLE; BRAIN BLOOD VOLUME; CHEMORADIOTHERAPY; CONTRAST ENHANCEMENT; FEMALE; FOLLOW UP; GLIOBLASTOMA; HISTOGRAM; HUMAN; MAJOR CLINICAL STUDY; MALE; NUCLEAR MAGNETIC RESONANCE IMAGING; PREDICTIVE VALUE; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; RETROSPECTIVE STUDY; SENSITIVITY AND SPECIFICITY; TREATMENT RESPONSE; TUMOR GROWTH;

ADULT; AGED; AGED, 80 AND OVER; BIOLOGICAL MARKERS; BLOOD VOLUME; BRAIN NEOPLASMS; CEREBROVASCULAR CIRCULATION; CHEMORADIOTHERAPY; CHI-SQUARE DISTRIBUTION; CONTRAST MEDIA; DISEASE PROGRESSION; FEMALE; GLIOBLASTOMA; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LOGISTIC MODELS; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; PREDICTIVE VALUE OF TESTS; RETROSPECTIVE STUDIES; ROC CURVE; SENSITIVITY AND SPECIFICITY;

EID: 84865413255     PISSN: 00338419     EISSN: 15271315     Source Type: Journal    
DOI: 10.1148/radiol.12112120     Document Type: Article

References (30)

1. Chamberlain MC, Glantz MJ, Chalmers L, Van Horn A, Sloan AE. Early necrosis following concurrent Temodar and radiotherapy in patients with glioblastoma. J Neurooncol 2007;82(1):81-83.
2. Gasparetto EL, Pawlak MA, Patel SH, et al. Posttreatment recurrence of malignant brain neoplasm: accuracy of relative cerebral blood volume fraction in discriminating low from high malignant histologic volume fraction. Radiology 2009;250(3):887-896.
3. Lev MH, Ozsunar Y, Henson JW, 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(2):214-221.
4. Lupo JM, Cha S, Chang SM, Nelson SJ. Dynamic susceptibility-weighted perfusion imaging of high-grade gliomas: characterization of spatial heterogeneity. AJNR Am J Neuroradiol 2005;26(6):1446-1454.
5. van den Bent MJ, Vogelbaum MA, Wen PY, Macdonald DR, Chang SM. End point assessment in gliomas: novel treatments limit usefulness of classical Macdonald's Criteria. J Clin Oncol 2009;27(18):2905-2908.
6. Sugahara T, Korogi Y, Tomiguchi S, et al. Posttherapeutic intraaxial brain tumor: the value of perfusion-sensitive contrast-enhanced MR imaging for differentiating tumor recurrence from nonneoplastic contrast- enhancing tissue. AJNR Am J Neuroradiol 2000;21(5):901-909.
7. Chenevert TL, Stegman LD, Taylor JMG, et al. Diffusion magnetic resonance imaging: an early surrogate marker of therapeutic efficacy in brain tumors. J Natl Cancer Inst 2000;92(24):2029-2036.
8. Smith JS, Cha S, Mayo MC, et al. Serial diffusion-weighted magnetic resonance imaging in cases of glioma: distinguishing tumor recurrence from postresection injury. J Neurosurg 2005;103(3):428-438.
9. Chen W. Clinical applications of PET in brain tumors. J Nucl Med 2007;48(9):1468-1481.
10. Terakawa Y, Tsuyuguchi N, Iwai Y, et al. Diagnostic accuracy of 11C-methionine PET for differentiation of recurrent brain tumors from radiation necrosis after radiotherapy. J Nucl Med 2008;49(5):694-699.
11. Zhou J, Tryggestad E, Wen Z, et al. Differentiation between glioma and radiation necrosis using molecular magnetic resonance imaging of endogenous proteins and peptides. Nat Med 2011;17(1):130-134.
12. Chamberlain MC. Pseudoprogression in glioblastoma. J Clin Oncol 2008;26(26):4359-4360; author reply 4359-4360.
13. Emblem KE, Nedregaard B, Nome T, et al. Glioma grading by using histogram analysis of blood volume heterogeneity from MR-derived cerebral blood volume maps. Radiology 2008;247(3):808-817.
14. Law M, Young R, Babb J, Pollack E, Johnson G. Histogram analysis versus region of interest analysis of dynamic susceptibility contrast perfusion MR imaging data in the grading of cerebral gliomas. AJNR Am J Neuroradiol 2007;28(4):761-766.
15. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988;44(3):837-845.
16. Brandsma D, Stalpers L, Taal W, Sminia P, van den Bent MJ. Clinical features, mechanisms, and management of pseudoprogression in malignant gliomas. Lancet Oncol 2008;9(5):453-461.
17. Tsien C, Galbán CJ, Chenevert TL, et al. Parametric response map as an imaging biomarker to distinguish progression from pseudoprogression in high-grade glioma. J Clin Oncol 2010;28(13):2293-2299.
18. Hygino da Cruz LC Jr, Rodriguez I, Domingues RC, Gasparetto EL, Sorensen AG. Pseudoprogression and pseudoresponse: imaging challenges in the assessment of posttreatment glioma. AJNR Am J Neuroradiol 2011;32(11):1978-1985.
19. Sanghera P, Perry J, Sahgal A, et al. Pseudoprogression following chemoradiotherapy for glioblastoma multiforme. Can J Neurol Sci 2010;37(1):36-42.
20. Hustinx R, Pourdehnad M, Kaschten B, Alavi A. PET imaging for differentiating recurrent brain tumor from radiation necrosis. Radiol Clin North Am 2005;43(1):35-47.
21. Ricci PE, Karis JP, Heiserman JE, Fram EK, Bice AN, Drayer BP. Differentiating recurrent tumor from radiation necrosis: time for re-evaluation of positron emission tomography? AJNR Am J Neuroradiol 1998;19(3):407-413.
22. Henry RG, Vigneron DB, Fischbein NJ, et al. Comparison of relative cerebral blood volume and proton spectroscopy in patients with treated gliomas. AJNR Am J Neuroradiol 2000;21(2):357-366.
23. Sundgren PC. MR spectroscopy in radiation injury. AJNR Am J Neuroradiol 2009;30(8):1469-1476.
24. Biousse V, Newman NJ, Hunter SB, Hudgins PA. Diffusion weighted imaging in radiation necrosis. J Neurol Neurosurg Psychiatry 2003;74(3):382-384.
25. Sundgren PC, Fan X, Weybright P, et al. Differentiation of recurrent brain tumor versus radiation injury using diffusion tensor imaging in patients with new contrast-enhancing lesions. Magn Reson Imaging 2006;24(9):1131-1142.
26. Covarrubias DJ, Rosen BR, Lev MH. Dynamic magnetic resonance perfusion imaging of brain tumors. Oncologist 2004;9(5):528-537.
27. Hazle JD, Jackson EF, Schomer DF, Leeds NE. Dynamic imaging of intracranial lesions using fast spin-echo imaging: differentiation of brain tumors and treatment effects. J Magn Reson Imaging 1997;7(6):1084-1093.
28. Kim HS, Kim JH, Kim SH, Cho KG, Kim SY. Posttreatment high-grade glioma: usefulness of peak height position with semiquantitative MR perfusion histogram analysis in an entire contrast-enhanced lesion for predicting volume fraction of recurrence. Radiology 2010;256(3):906-915.
29. Barajas RF Jr, Hodgson JG, Chang JS, et al. Glioblastoma multiforme regional genetic and cellular expression patterns: influence on anatomic and physiologic MR imaging. Radiology 2010;254(2):564-576.
30. Hu LS, Baxter LC, Smith KA, 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(3):552-558.