Dynamic contrast-enhanced perfusion processing for neuroradiologists: Model-dependent analysis may not be necessary for determining recurrent high-grade glioma versus treatment effect

American Journal of Neuroradiology

Volumn 36, Issue 4, 2015, Pages 686-693

  Hamilton, J D ^a,b   Lin, J ^a,c   Ison, C ^a   Leeds, N E ^a   Jackson, E F ^a   Fuller, G N ^a   Ketonen, L ^a   Kumar, A J ^a,d  

^a UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

^b Radiology   (United States)

^c RICE UNIVERSITY   (United States)

^d BAYLOR COLLEGE OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GADOLINIUM PENTETATE MEGLUMINE; TEMOZOLOMIDE; CONTRAST MEDIUM;

ADULT; BRAIN NECROSIS; BRAIN PERFUSION; CANCER RADIOTHERAPY; CANCER RECURRENCE; CLINICAL ARTICLE; COMPARTMENT MODEL; CONFERENCE PAPER; CONTRAST ENHANCEMENT; FEMALE; GLIOMA; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; MALE; MIDDLE AGED; NEURORADIOLOGY; NUCLEAR MAGNETIC RESONANCE SCANNER; SUPERIOR SAGITTAL SINUS; AGED; ALGORITHM; BRAIN; BRAIN NEOPLASMS; CANCER GRADING; COMPUTER ASSISTED DIAGNOSIS; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PERFUSION; PROCEDURES; RETROSPECTIVE STUDY; TUMOR RECURRENCE; VERY ELDERLY;

ADULT; AGED; AGED, 80 AND OVER; ALGORITHMS; BRAIN; BRAIN NEOPLASMS; CONTRAST MEDIA; FEMALE; GLIOMA; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; NEOPLASM GRADING; NEOPLASM RECURRENCE, LOCAL; PERFUSION; RETROSPECTIVE STUDIES;

EID: 84927519509     PISSN: 01956108     EISSN: 1936959X     Source Type: Journal    
DOI: 10.3174/ajnr.A4190     Document Type: Conference Paper

References (21)

1. Ostrom QT, Gittleman H, Liao P., et al. CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2007-2011. Neuro Oncol 2014; 16(SUPPL. 4):iv1-iv63
2. Ballman KV, Buckner JC, Brown P.D., et al. The relationship between six-month progression-free survival and 12-month overall survival end points for phase II trials in patients with glioblastoma multiforme. Neuro Oncol 2007; 9:29-38
3. Yang I, Aghi MK. New advances that enable identification of glio-blastoma recurrence. Nat Rev Clin Oncol 2009; 6:648-57
4. Kumar AJ, Leeds NE, Fuller G.N., et al. Malignant gliomas: MR imaging spectrum of radiation therapy- and chemotherapy-induced necrosis of the brain after treatment. Radiology 2000; 217:377-84
5. Kohshi K, Imada H, Nomoto S., et al. Successful treatment of radiation-induced brain necrosisbyhyperbaric oxygen therapy. J Neurol Sci 2003; 209:115-17
6. Levin VA, Bidaut L, Hou P., et al. Randomized double-blind placebo-controlled trial of bevacizumab therapy for radiation necrosis of the central nervous system. Int J Radiat Oncol Biol Phys 2011; 79:1487-95
7. Gonzalez J, Kumar AJ, Conrad C.A., et al. Effect of bevacizumab on radiation necrosis of the brain. Int J Radiat Oncol Biol Phys 2007; 67:323-36
8. Weller M, Cloughesy T, Perry J.R., et al. Standards of care for treatment of recurrent glioblastoma: are we there yet? Neuro Oncol 2013; 15:4-27
9. Bisdas S, Naegele T, Ritz R., et al. Distinguishing recurrent highgrade gliomas from radiation injury: a pilot study using dynamic contrast-enhanced MR imaging. Acad Radiol 2011; 18:575-83
10. Narang J, Jain R, Arbab A.S., et al. Differentiating treatment-induced necrosis from recurrent/progressive brain tumor using nonmodel-based semiquantitative indices derived from dynamic contrast-enhanced T1-weighted MR perfusion. Neuro Oncol 2011; 13:1037-46
11. Barajas RF Jr, Chang JS, Segal M.R., et al. Differentiation of recurrent glioblastoma multiforme from radiation necrosis after external beam radiation therapy with dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology 2009; 253:486-96
12. Hu LS, Baxter LC, Smith K.A., et al. Relative cerebral blood volume values to differentiate high-grade glioma recurrence from post-treatment 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
13. Zeng QS, Li CF, Liu H, et al. Distinction between recurrent glioma and radiation injury using magnetic resonance spectroscopy in combination with diffusion-weighted imaging. Int J Radiat Oncol Biol Phys 2007; 68:151-58
14. Leach MO, Brindle KM, Evelhoch J.L., et al. The assessment of anti-angiogenic and antivascular therapies in early-stage clinical trials using magnetic resonance imaging: issues and recommendations. Br J Cancer 2005; 92:1599-610
15. 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; 17:357-67
16. Murase K, Yamazaki Y, Miyazaki S. Deconvolution analysis of dynamic contrast-enhanced data based on singular value decomposition optimized by generalized cross validation. Magn Reson Med Sci 2004; 3:165-75
17. Mouridsen K, Christensen S, Gyldensted L., et al. Automatic selection of arterial input function using cluster analysis. Magn Reson Med 2006; 55:524-31
18. Sourbron S, Ingrisch M, Siefert A., et al. Quantification of cerebral blood flow, cerebral blood volume, and blood-brain-barrier leakage with DCE-MRI. Magn Reson Med 2009; 62:205-17
19. Pope WB, Young JR, Ellingson BM. Advances in MRI assessment of gliomas and response to anti-VEGF therapy. Curr Neurol Neurosci Rep 2011; 11:336-44
20. ∗-dominant extravasation correction in DSC-MRI: part I-theoretical considerations and implications for assessment of tumor hemodynamic properties. J Cereb Blood Flow Metab 2011; 31:2041-53
21. Jackson A, O'Connor JP, Parker GJ, et al. Imaging tumor vascular heterogeneity and angiogenesis using dynamic contrast-enhanced magnetic resonance imaging. Clin Cancer Res 2007; 13:3449-59