Single-channel blind estimation of arterial input function and tissue impulse response in DCE-MRI

IEEE Transactions on Biomedical Engineering

Volumn 59, Issue 4, 2012, Pages 1012-1021

  Taxt, Torfinn ^a,b   Jiřík, Radovan ^c,d   Rygh, Cecilie Brekke ^a   Grüner, Renate ^a   Bartoš, Michal ^d   Andersen, Erling ^b   Curry, Fitz Roy ^e   Reed, Rolf K ^a  

^a UNIVERSITY OF BERGEN   (Norway)

^b HAUKELAND UNIVERSITY HOSPITAL   (Norway)

^c INSTITUTE OF SCIENTIFIC INSTRUMENTS   (Czech Republic)

^d BRNO UNIVERSITY OF TECHNOLOGY   (Czech Republic)

^e UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Arterial input function (AIF); blind deconvolution; dynamic contrast enhanced magnetic resonance imaging (DCE MRI); multichannel; perfusion; single channel

Indexed keywords

ARTERIAL INPUT FUNCTION; BLIND DECONVOLUTION; DYNAMIC CONTRAST-ENHANCED MAGNETIC RESONANCE IMAGING; MULTI-CHANNEL; PERFUSION; SINGLE CHANNELS;

BLIND SOURCE SEPARATION; CONVOLUTION; CURVE FITTING; ERRORS; ESTIMATION; IMPULSE RESPONSE; MAGNETIC RESONANCE IMAGING; SOLID SOLUTIONS;

TISSUE;

CONTRAST MEDIUM; GADOLINIUM; TRACER;

ALGORITHM; ARTERIAL INPUT FUNCTION; ARTERY; ARTICLE; ARTIFACT; CAPILLARY; CONTRAST ENHANCEMENT; CORRELATION ANALYSIS; DYNAMIC CONTRAST ENHANCED MAGNETIC RESONANCE IMAGING; HUMAN; MATHEMATICAL ANALYSIS; MATHEMATICAL PARAMETERS; MOUSE; NONHUMAN; NUCLEAR MAGNETIC RESONANCE IMAGING; SIGNAL NOISE RATIO; TISSUE PERFUSION; VASCULAR DISEASE;

ALGORITHMS; ANIMALS; ARTERIES; BLOOD FLOW VELOCITY; COMPUTER SIMULATION; CONTRAST MEDIA; FEMALE; GADOLINIUM DTPA; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE ANGIOGRAPHY; MICE; MICE, INBRED C57BL; MODELS, BIOLOGICAL; MODELS, STATISTICAL; MUSCLE, SKELETAL; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84858986618     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2011.2182195     Document Type: Article

References (43)

1. J. Barkhausen, P. Hunold, M. Jochims, and J. F. Debatin, "Imaging of myocardial perfusion with magnetic resonance," J. Magn. Reson. Imag., vol. 19, no. 6, pp. 750-757, 2004. (Pubitemid 38788657)
2. P. L. Choyke, A. J. Dwyer, and M. V. Knopp, "Functional tumor imaging with dynamic contrast-enhanced magnetic resonance imaging," J. Magn. Reson. Imag., vol. 17, no. 5, pp. 509-520, 2003.
3. I. S. Gribbestad, K. I. Gjesdal, G. Nilsen, S. Lundgren, M. H. B. Hjelstuen, and A. Jackson, An Introduction to Dynamic Contrast-Enhanced MRI in Oncology. New York: Springer-Verlag, Jun. 2005, ch. 1, pp. 3-22.
4. L. Hermoye, L. Annet, P. Lemmerling, F. Peeters, F. Jamar, P. Gianello, S. Van Huffel, and B. Van Beers, "Calculation of the renal perfusion and glomerular filtration rate from the renal impulse response obtained with MRI," Magn. Reson. Med., vol. 51, no. 5, pp. 1017-1025, 2004. (Pubitemid 38580615)
5. R. Materne, A. Smith, F. Peeters, J. Dehoux, A. Keyeux, Y. Horsmans, and B. Van Beers, "Assessment of hepatic perfusion parameters with dynamic MRI," Magn. Reson. Med., vol. 47, no. 1, pp. 135-142, 2002. (Pubitemid 34019702)
6. P. Germain, G. Roul, J. Baruthio, C. Jahn, P. M. Coulbois, B. Dumitresco, J. L. Dietemann, P. Bareiss, and A. Constantinesco, "Myocardial flow reserve parametric map, assessed by first-pass MRI compartmental analysis at the chronic stage of infarction," J. Magn. Reson. Imag., vol. 13, no. 3, pp. 352-360, 2001. (Pubitemid 32173400)
7. A.M. Lutz, D.Weishaupt,B.R.Amann-Vesti, T. Pfammatter,K.Goepfert, B. Marincek, and D. Nanz, "Assessment of skeletal muscle perfusion by contrast medium first-pass magnetic resonance imaging: Technical feasibility and preliminary experience in healthy volunteers," J. Magn. Reson. Imag., vol. 20, no. 1, pp. 111-121, 2004. (Pubitemid 38857524)
8. G. Brix, F. Kiessling, R. Lucht, S. Darai, K. Wasser, S. Delorme, and J. Griebel, "Microcirculation and microvasculature in breast tumors: Pharmacokinetic analysis of dynamic MR image series," Magn. Reson. Med., vol. 52, no. 2, pp. 420-429, 2004. (Pubitemid 39025290)
9. A. E. Hansen, H. Pedersen, E. Rostrup, and H. B. Larsson, "Partial volume effect (PVE) on the arterial input function (AIF) in T1-weighted perfusion imaging and limitations of the multiplicative rescaling approach," Magn. Reson. Med., vol. 62, no. 4, pp. 1055-1059, 2009.
10. S. Sourbron, M. Ingrisch, A. Siefert, M. Reiser, and K. Herrmann, "Quantification of cerebral blood flow, cerebral blood volume, and blood-brainbarrier leakage with DCE-MRI," Magn. Reson. Med., vol. 62, no. 1, pp. 205-217, 2009.
11. A. R. Padhani, "Dynamic contrast-enhanced MRI in clinical oncology: Current status and future directions," J. Magn. Reson. Imag., vol. 16, no. 4, pp. 407-422, 2002.
12. P. S. Tofts, G. Brix, D. L. Buckley, J. L. Evelhoch, E. Henderson, M. V. Knopp, H. B. Larsson, T.-Y. Lee, N. A. Mayr, G. J. Parker, R. E. Port, J. Taylor, and R. M. Weisskoff, "Estimating kinetic parameters from dynamic contrast-enhanced T1-weighted MRI of a diffusable tracer: Standardized quantities and symbols," J. Magn. Reson. Imag., vol. 10, no. 3, pp. 223-232, 1999. (Pubitemid 29463104)
13. K. S. St. Lawrence, T.-Y. Lee, "An adiabatic approximation to the tissue homogeneity model for water exchange in the brain: I. theoretical derivation,"J. Cereb. Blood Flow Metab, vol. 18, no. 12, pp. 1365-1377, Dec. 1998. (Pubitemid 28559684)
14. D. Y. Riabkov and E. V. R. Di Bella, "Estimation of kinetic parameters without input functions: Analysis of three methods for multichannel blind identification," IEEE Trans. Biomed. Eng., vol. 49, no. 11, pp. 1318-1327, Nov. 2002.
15. C. Yang, G. S. Karczmar,M.Medved, andW.M. Stadler, "Multiple reference tissue method for contrast agent arterial input function estimation,"Magn. Reson. Med., vol. 58, no. 6, pp. 1266-1275, 2007. (Pubitemid 350234214)
16. M. C. Schabel, J. U. Fluckiger, and E.V. R.DiBella, "A model-constrained MonteCarlo method for blind arterial input function estimation in dynamic contrast-enhanced MRI: I. simulations," Phys.Med. Biol., vol. 55, no. 16, pp. 4783-4806, 2010.
17. M. C. Schabel, E. V. R. DiBella, R. L. Jensen, and K. L. Salzman, "A model-constrained Monte Carlo method for blind arterial input function estimation in dynamic contrast-enhanced MRI: II. in vivo results," Phys. Med. Biol., vol. 55, no. 16, pp. 4807-4823, Aug. 2010.
18. J. U. Fluckiger, M. C. Schabel, and E. V. R. DiBella, "Constrained estimation of the arterial input function for myocardial perfusion cardiovascular magnetic resonance," Magn. Reson. Med., vol. 66, no. 2, pp. 419-427, 2011.
19. R. Grüner and T. Taxt, "Iterative blind deconvolution in magnetic resonance brain perfusion imaging," Magn. Reson. Med., vol. 55, no. 4, pp. 805-815, Apr. 2006.
20. P. Brunecker, A. Villringer, J. Schultze, C. Nolte, G. Jungehulsing, M. Endres, and J. Steinbrink, "Correcting saturation effects of the arterial input function in dynamic susceptibility contrast-enhanced MRI-A Monte Carlo simulation," Magn. Reson. Imag., vol. 25, no. 9, pp. 1300-1311, Nov. 2007. (Pubitemid 47625920)
21. D. A. Fish, A. M. Brinicombe, E. R. Pike, and J. G. Walker, "Blind deconvolution by means of the Richardson-Lucy algorithm," J. Opt. Soc. Amer. A, vol. 12, no. 1, pp. 58-65, Jan. 1995.
22. C. A. Berenstein and E. V. Patrick, "Exact deconvolution for multiple convolution operators - An overview, plus performance characterizations for imaging sensors," Proc. IEEE, vol. 78, no. 4, pp. 723-734, Apr. 1990.
23. D. L. Buckley, "Uncertainty in the analysis of tracer kinetics using dynamic contrast-enhanced T1-weighted MRI," Magn. Reson. Med., vol. 47, no. 3, pp. 601-606, 2002.
24. E. M. Renkin, "Transport of potassium-42 from blood to tissue in isolated mammalian skeletal muscles," Amer. J. Physiol. - Legacy Content, vol. 197, no. 6, pp. 1205-1210, 1959.
25. C. Crone, "The permeability of capillaries in various organs as determined by use of the 'indicator diffusion' method.," Acta Physiologica Scandinavica, vol. 58, pp. 292-305, Aug. 1963.
26. F. Tsumuraya, "Deconvolution based on theWiener-Lucy chain algorithm: An approach to recover local information losses in the deconvolution procedure," J. Opt. Soc. Amer. A, vol. 13, no. 7, pp. 1532-1536, Jul. 1996. (Pubitemid 126551520)
27. N. Dey, L. Blanc-Feraud, C. Zimmer, P. Roux, Z. Kam, J.-C. Olivo-Marin, and J. Zerubia, "Richardson-Lucy algorithm with total variation regularization for 3D confocal microscope deconvolution," Microsc. Res. Tech., vol. 69, no. 4, pp. 260-266, 2006.
28. F. Tsumuraya, N. Miura, and N. Baba, "Iterative blind deconvolution method using Lucy's algorithm," Astron. Astrophys., vol. 282, pp. 699-708, Feb. 1994.
29. W. H. Press, B. P. Flannery, S. A. Teukolsky, and W. T. Vetterling, Numerical Recipes in C: The Art of Scientific Computing, 2nd ed. Cambridge, U.K.: Cambridge Univ. Press, Oct. 1992.
30. K.-L. Li, X. P. Zhu, J. Waterton, and A. Jackson, "Improved 3D quantitative mapping of blood volume and endothelial permeability in brain tumors,"J. Magn. Reson. Imag., vol. 12, no. 2, pp. 347-357, 2000. (Pubitemid 30612881)
31. J. U. Fluckiger, M. C. Schabel, and E. V. DiBella, "Model-based blind estimation of kinetic parameters in dynamic contrast enhanced (DCE)-MRI," Magn. Reson. Med., vol. 62, no. 6, pp. 1477-1486, 2009.
32. M. Anderberg, Cluster Analysis for Application (Probability and Mathematical Statistics Series). New York: Academic, 1973.
33. M. Hollander and D. A. Wolfe, Nonparametric Statistical Methods. New York: Wiley, 1973.
34. D. K. Ragan, S. Y. Lai, and J. A. Bankson, "Fast, reproducible measurement of the vascular input function in mice using constrained reconstruction and cardiac sampling," NMR Biomed., vol. 24, no. 4, pp. 373-384, 2011.
35. Z. Rumboldt, R. Al-Okaili, and J. P. Deveikis, "Perfusion CT for head and neck tumors: Pilot study," AJNR Amer. J. Neuroradiol., vol. 26, no. 5, pp. 1178-1185, May 2005. (Pubitemid 43821970)
36. P. N. Colleran, M. K. Wilkerson, S. A. Bloomfield, L. J. Suva, R. T. Turner, and M. D. Delp, "Alterations in skeletal perfusion with simulated microgravity: A possible mechanism for bone remodeling," J. Appl. Physiol., vol. 89, no. 3, pp. 1046-1054, Sep. 2000.
37. D. B. Matic, T. Y. Lee, R. G. Wells, and B. S. Gan, "The effects of botulinum toxin type A on muscle blood perfusion and metabolism,"Plast. Reconstruct. Surg., vol. 120, no. 7, pp. 1823-1833, Dec. 2007.
38. J. L. Starck, E. Pantin, and F. Murtagh, "Deconvolution in astronomy: A review," Publicat. Astron. Soc. Pacific, vol. 114, no. 800, pp. 1051-1069, Oct. 2002.
39. O. Keunen, M. Johansson, A. Oudin, M. Sanzey, S. A. A. Rahim, F. Fack, F. Thorsen, T. Taxt, M. Bartos, R. Jirik, H. Miletic, J. Wang, D. Stieber, L. Stuhr, I. Moen, C. B. B. Rygh, R. Bjerkvig, and S. P. Niclou, "Anti-VEGF treatment reduces blood supply and increases tumor cell invasion in glioblastoma," Proc. Nat. Acad. Sci. USA, vol. 108, no. 9, pp. 3749-3754, Mar. 2011.
40. T. Kogler, J. Raith, S. Keeling, F. Payer, and R. Stollberger, "Impact of the model impulse residue function on quantitative separation of perfusion and permeability," in Proc. Int. Soc. Mag. Reson. Med., Berkeley, CA, 2004, p. 1972.
41. T. S. Koh, V. Zeman, J. Darko, T.-Y. Lee, M. F. Milosevic, M. Haider, P. Warde, and I. W. T. Yeung, "The inclusion of capillary distribution in the adiabatic tissue homogeneity model of blood flow," Phys. Med. Biol., vol. 46, no. 5, pp. 1519-1538, 2001. (Pubitemid 32440202)
42. R. Jirik, M. Standara, A. Mala, S. Sedlakova, M. Bartos, T. Taxt, and Z. Starcuk, Jr., "Flow phantom for validation of absolute quantification in dynamic contrast-enhanced MRI," in Book of Abstracts, ESMRMB Congr., MAGMA - Magnetic Resonance Materials Phys., Biol. Med., vol. 24, no. Suppl. 1, pp. 247-248, 2011.
43. M. Heilmann, J. Vautier, P. Robert, and A. Volk, "In vitro setup to study permeability characteristics of contrast agents by MRI," Contrast Media Mol Imag., vol. 4, no. 2, pp. 66-72, 2009.