Adaptive total linear least square method for quantification of mean transit time in brain perfusion MRI

Magnetic Resonance Imaging

Volumn 21, Issue 5, 2003, Pages 503-510

  Li, XingFeng ^a   Tian, Jie ^a   Li, EnZhong ^a,b   Wang, XiaoXiang ^a   Dai, JianPing ^b   Ai, Lin ^b  

^a INSTITUTE OF AUTOMATION   (China)

^b CAPITAL MEDICAL UNIVERSITY   (China)

Author keywords

Adaptive total linear least square; Arterial input function; Blood flow; Concentration time curves; Mean transit time

Indexed keywords

ARTICLE; BRAIN BLOOD FLOW; BRAIN BLOOD VOLUME; BRAIN PERFUSION; COMPUTER SIMULATION; CURVE FITTING; DIAGNOSTIC IMAGING; HUMAN; LINEAR REGRESSION ANALYSIS; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL;

EID: 0042307670     PISSN: 0730725X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0730-725X(03)00075-4     Document Type: Article

References (21)

1. Perkio J, Aronen HJ, Kangasmaki A, Liu Y, Karomen J, Savolainen S, Østergaard L. Evaluation of four postprocessing methods for determination of cerebral blood volume and mean transit time by dynamic susceptibility contrast imaging. Magn Reson Med 2002;47:973-81.
2. Østergaard L, Weisskoff RM, Chesler DA, Gyldensted C, Rosen BR. High resolution measurement of cerebral blood flood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis. Magn Reson Med 1996;36:715-25.
3. Østergaard L, Sorensen AG, Kwong KK, Weisskoff RM, Gyldensted C, Rosen BR. High resolution measurement of cerebral blood flood flow using intravascular tracer bolus passages. Part II: Experimental comparison and preliminary results. Magn Reson Med 1996;36:726-36.
4. Calamante F, Gadian DG, Connelly A. Delay and dispersion effects in dynamic susceptibility contrast MRI: simulations using singular value decomposition. Magn Reson Med 2000;44:466-73.
5. Rempp KA, Brix G, Wenz F, Becker CR, Friedemann, Lorenz WJ. Quantification of regional cerebral blood flow and volume with dynamic susceptibility contrast-enhanced MR imaging. Radiology 1994;193:637-41.
6. Smith AM, Grandin CB, Duprez T, Mataigne F, Cosnard G. Whole brain quantitative CBF, CBV, and MTT measurements using MRI bolus tracking: implementation and application to data acquired from hyperacute stroke patients. J Magn Reson Imag 2000;12:400-10.
7. Makiranta MJ, Lehtinen S, Jauhiainen JPT, Oikarinen JT, Pyhtinen J, Teronenl O. MR perfusion, diffusion and BOLD imaging of methotrexate-exposed swine brain. J Magn Reson Imag 2002;15:511-9.
8. Benner T, Heiland S, Erb G, Forsting M, Sartor K. Accuracy of γ-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 Imag 1997;15:307-17.
9. Rosen BR, Belliveau JW, Vevea JM, Brady TJ. Perfusion imaging with contrast agents. Magn Reson Med 1990;14:249-65.
10. Meier P, Zierler KL. On the theory of the indictor-dilution method for measurement of blood flow and volume. J Appl Physiol 1954;6:731-44.
11. Zierier BKL. Theoretical basis of indicator-dilution methods for measuring flow and volume. Cirs Res 1962;10:393-407.
12. Thompon HK, Starmer CF, Whoalen RE, McIntosh HD. Indicator transit time considered as a gamma variate. Circ Res 1964;14:502-15.
13. Starmer CF, Clark DO. Computer computations of cardiac output using the gamma function. J Appl Physiol 1970;28:219-20.
14. Rawlings JO, Pantula SG, Dickey DA. Applied regression analysis: a research tool. New York: Springer, 1998. p. 485-514.
15. Van Huffel S. Recent advances in total least squares techniques and errors-in-variables modeling. SIAM Philadelphia, Proceedings of the second international workshop on total least squares and errors-invariables modeling, 1997. p. 307-18.
16. Van Huffel S, Vandewalle J, De Roe MCh, Willems JL. Reliable and efficient deconvolution technique based on total linear least squares for calculating the renal retention function. Med Biol Eng Comput 1987;25:26-33.
17. Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical recipes in C: the art of scientific computing. 2nd ed. Oxford: Cambridge University Press, 1993.
18. Wilcox R. Fundamentals of modern statistical methods: substantially improving power and accuracy. New York: Springer Press, 2001. p. 139-58.
19. Boxerman JL, Rsen BR, Weisskoff RM. Signal-to-noise analysis of cerebral blood volume maps from dynamic NMR imaging studies. J Magn Reson Imag 1997;7:528-37.
20. Pijpkema M, Kaanders JHAM, Joosten FBM, van der Kogel AJ, Heerschap A. Method for quantitative mapping of dynamic MRI contrast agent uptake in human tumors. J Magn Reson Imag 2001;14:457-63.
21. Murase K, Kikuchi K, Miki H, Shimizu T, Ikezoe J. Determination of arterial input function using fuzzy clustering for quantification of cerebral blood flow with dynamic susceptibility contrast-enhanced MR imaging. J Magn Reson Imag 2001;13:797-806.