Partial-volume model for determining white matter and gray matter cerebral blood volume for analysis of gliomas

Journal of Magnetic Resonance Imaging

Volumn 23, Issue 3, 2006, Pages 257-266

  Lee, Michael C ^a,b   Cha, Soonmee ^a   Chang, Susan M ^a   Nelson, Sarah J ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Glioma; Image registration; Image segmentation; Partial volume effect; Perfusion imaging

Indexed keywords

ADULT; AGED; ARTICLE; BRAIN BLOOD VOLUME; BRAIN PERFUSION; BRAIN TUMOR; CLINICAL ARTICLE; CONTRAST ENHANCEMENT; FEMALE; GLIOMA; GRAY MATTER; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE RECONSTRUCTION; IMAGING SYSTEM; MALE; MODEL; PRIORITY JOURNAL; SPECTROSCOPY; TUMOR BLOOD FLOW; WHITE MATTER;

ADULT; AGED; ALGORITHMS; BLOOD VOLUME DETERMINATION; BRAIN; BRAIN NEOPLASMS; CEREBROVASCULAR CIRCULATION; CONTRAST MEDIA; FEMALE; GADOLINIUM DTPA; GLIOMA; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; NERVE FIBERS, MYELINATED; NERVE FIBERS, UNMYELINATED; REGIONAL BLOOD FLOW;

EID: 33644846648     PISSN: 10531807     EISSN: 15222586     Source Type: Journal    
DOI: 10.1002/jmri.20506     Document Type: Article

References (33)

1. 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.
2. 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;21:357-366.
3. Shin JH, Lee HK, Kwun BD, et al. Using relative cerebral blood flow and volume to evaluate the histopathologic grade of cerebral gliomas: preliminary results. AJR Am J Roentgenol 2002;179:783-789.
4. Maeda M, Itoh S, Kimura H, et al. Tumor vascularity in the brain: evaluation with dynamic susceptibility-contrast MR imaging. Radiology 1993;189:233-238.
5. Knopp EA, Cha S, Johnson G, et al. Glial neoplasms: dynamic contrast-enhanced T2*-weighted MR imaging. Radiology 1999;211:791-798.
6. Davenport R. The derivation of the gamma-variate relationship for tracer dilution curves. J Nucl Med 1983;24:945-948.
7. Gobbel GT, Fike JR. A deconvolution method for evaluating indicator-dilution curves. Phys Med Biol 1994;39:1833-1854.
8. Ostergaard L, Weisskoff RM, Chesler DA, Gyldensted C, Rosen BR. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis. Magn Reson Med 1996;36:715-725.
9. Wenz F, Rempp K, Brix G, et al. Age dependency of the regional cerebral blood volume (rCBV) measured with dynamic susceptibility contrast MR imaging (DSC). Magn Reson Imaging 1996;14:157-162.
10. Schreiber WG, Guckel F, Stritzke P, Schmiedek P, Schwartz A, Brix G. Cerebral blood flow and cerebrovascular reserve capacity: estimation by dynamic magnetic resonance imaging. J Cereb Blood Flow Metab 1998;18:1143-1156.
11. Vonken EJ, van Osch MJ, Bakker CJ, Viergever MA. Measurement of cerebral perfusion with dual-echo multi-slice quantitative dynamic susceptibility contrast MRI. J Magn Reson Imaging 1999;10:109-117.
12. Fuss M, Wenz F, Scholdei R, et al. Radiation-induced regional cerebral blood volume (rCBV) changes in normal brain and low-grade astrocytomas: quantification and time and dose-dependent occurrence. Int J Radiat Oncol Biol Phys 2000;48:53-58.
13. Ren H, Shen Q, Bardutzky J, Fisher M, Duong TQ. Partial-volume effect on ischemic tissue-fate delineation using quantitative perfusion and diffusion imaging on a rat stroke model. Magn Reson Med 2004;52:1328-1335.
14. Kao YH, Guo WY, Wu YT, et al. Hemodynamic segmentation of MR brain perfusion images using independent component analysis, thresholding, and Bayesian estimation. Magn Reson Med 2003;49:885-894.
15. Luh W-M. Estimation of pure gray matter perfusion in human brain. In: Proceedings of the 12th Annual Meeting of ISMRM. Kyoto, Japan, 2004. p 1369.
16. Doyle TJ, Bedell BJ, Narayana PA. Relative concentrations of proton MR visible neurochemicals in gray and white matter in human brain. Magn Reson Med 1995;33:755-759.
17. Lim KO, Spielman DM. Estimating NAA in cortical gray matter with applications for measuring changes due to aging. Magn Reson Med 1997;37:372-377.
18. Hetherington HP, Pan JW, Mason GF, et al. Quantitative 1H spectroscopic imaging of human brain at 4.1 T using image segmentation. Magn Reson Med 1996;36:21-29.
19. Noworolski SM, Nelson SJ, Henry RG, et al. High spatial resolution 1H-MRSI and segmented MRI of cortical gray matter and subcortical white matter in three regions of the human brain. Magn Reson Med 1999;41:21-29.
20. Star-Lack J, Vigneron DB, Pauly J, Kurhanewicz J, Nelson SJ. Improved solvent suppression and increased spatial excitation bandwidths for three-dimensional PRESS CSI using phase-compensating spectral/spatial spin-echo pulses. J Magn Reson Imaging 1997;7:745-757.
21. Tran TK, Vigneron DB, Sailasuta N, et al. Very selective suppression pulses for clinical MRSI studies of brain and prostate cancer. Magn Reson Med 2000;43:23-33.
22. Smith SM. Fast robust automated brain extraction. Hum Brain Mapp 2002;17:143-155.
23. Studholme C, Hill DLG, Hawkes DJ. An overlap invariant entropy measure of 3D medical image alignment. Pattern Recognit 1999;32:71-86.
24. Zhang Y, Brady M, Smith S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging 2001;20:45-57.
25. Rueckert D, Sonoda LI, Hayes C, Hill DL, Leach MO, Hawkes DJ. Nonrigid registration using free-form deformations: application to breast MR images. IEEE Trans Med Imaging 1999;18:712-721.
26. Nelson SJ. Analysis of volume MRI and MR spectroscopic imaging data for the evaluation of patients with brain tumors. Magn Reson Med 2001;46:228-239.
27. McKnight TR, Noworolski SM, Vigneron DB, Nelson SJ. An automated technique for the quantitative assessment of 3D-MRSI data from patients with glioma. J Magn Reson Imaging 2001;13:167-177.
28. 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.
29. Thompson Jr HK, Starmer CF, Whalen RE, McIntosh HD. Indicator transit time considered as a gamma variate. Circ Res 1964;14:502-515.
30. Benner T, Heiland S, Erb G, Forsting M, Sartor K. Accuracy of gamma-variate fits to concentration-time curves from dynamic susceptibility-contrast enhanced MRI: influence of time resolution, maximal signal drop and signal-to-noise. Magn Reson Imaging 1997;15:307-317.
31. 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.
32. Boxerman JL, Rosen BR, Weisskoff RM. Signal-to-noise analysis of cerebral blood volume maps from dynamic NMR imaging studies. J Magn Reson Imaging 1997;7:528-537.
33. Pirzkall A, McKnight TR, Graves EE, et al. MR-spectroscopy guided target delineation for high-grade gliomas. Int J Radiat Oncol Biol Phys 2001;50:915-928.