Bayesian estimation of cerebral perfusion using a physiological model of microvasculature

NeuroImage

Volumn 33, Issue 2, 2006, Pages 570-579

  Mouridsen, Kim ^a   Friston, Karl ^b   Hjort, Niels ^a   Gyldensted, Louise ^a   Østergaard, Leif ^a   Kiebel, Stefan ^b  

^a AARHUS UNIVERSITY HOSPITAL   (Denmark)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

Bayesian analysis; Cerebral blood flow (CBF); Deconvolution; Dynamic susceptibility contrast MRI; Singular value decomposition (SVD); Vascular model

Indexed keywords

ADULT; ARTICLE; BAYES THEOREM; BRAIN BLOOD FLOW; BRAIN BLOOD VOLUME; BRAIN MAPPING; BRAIN MICROCIRCULATION; BRAIN PERFUSION; CAPILLARY FLOW; CASE REPORT; CONTROLLED STUDY; FEMALE; HEMODYNAMICS; HUMAN; MALE; MICROVASCULATURE; NEUROIMAGING; NEUROPHYSIOLOGY; NORMAL HUMAN; PERFUSION WEIGHTED IMAGING; PRIORITY JOURNAL; SIMULATION; STROKE PATIENT;

BAYES THEOREM; BRAIN; CEREBROVASCULAR CIRCULATION; COMPUTER SIMULATION; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MICROCIRCULATION; MODELS, CARDIOVASCULAR; MODELS, NEUROLOGICAL;

EID: 33749267950     PISSN: 10538119     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2006.06.015     Document Type: Article

References (31)

1. Alsop D.D., Wedmid A., and Schlaug G. Defining a local input function for perfusion quantification with bolus constrast MRI. Proc. ISMRM (2002)
2. Andersen I.K., Szymkowiak A., Rasmussen C.E., Hanson L.G., Marstrand J.R., Larsson H.B.W., and Hansen L.K. Perfusion quantification using Gaussian process deconvolution. Magn. Reson. Med. 48 (2002) 351-361
3. Baird A.E., and Warach S. Magnetic resonance imaging of acute stroke. J. Cereb. Blood Flow Metab. 18 (1998) 583-609
4. Calamante F., Thomas D.L., Pell G.S., Wiersma J., and Turner R. Measuring cerebral blood flow using magnetic resonance imaging techniques. J. Cereb. Blood Flow Metab. 19 (1999) 701-735
5. Calamante F., Gadian D.G., and Connelly A. Delay and dispersion effects in dynamic susceptibility contrast MRI: simulations using singular value decomposition. Magn. Reson. Med. 44 (2000) 466-473
6. Calamante F., Gadian D.G., and Connelly A. Quantification of perfusion using bolus tracking magnetic resonance imaging in stroke: assumptions, limitations, and potential implications for clinical use. Stroke 33 (2002) 1146-1151
7. Calamante F., Gadian D.G., and Connelly A. Quantification of bolus-tracking MRI: improved characterization of the tissue residue function using Tikhonov regularization. Magn. Reson. Med. 50 (2003) 1237-1247
8. Calamante F., Morup M., and Hansen L.K. Defining a local arterial input function for perfusion MRI using independent component analysis. Magn. Reson. Med. 52 (2004) 789-797
9. Friston K.J., Harrison L., and Penny W. Dynamic causal modelling. NeuroImage 19 (2003) 1273-1302
10. Gelman A., Carlin J., Stern H., and Rubin D. Bayesian Data Analysis. 2nd ed. (2003), Chapman and Hall/CRC
11. Gudbjartsson H., and Patz S. The Rician distribution of noisy MRI data. Magn. Reson. Med. 34 (1995) 910-914
12. Kennan R., and Jäger H.R. T2- and T2*-w DCE-MRI: blood perfusion and volume estimation using bolus tracking. In: Tofts P. (Ed). Quantitative MRI of the Brain (2003), John Wiley and Sons, Ltd.
13. Kiebel S.J., David O., and Friston K.J. Dynamic Causal Modelling of Evoked Responses in EEG/MEG with lead-field parameterization. NeuroImage 30 4 (2006) 1273-1284
14. Kroll K., Wilke N., Jerosch-Herold M., Wang Y., Zhang Y., Bache R.J., and Bassingthwaighte J.B. Modeling regional myocardial flows from residue functions of an intravascular indicator. Am. J. Physiol.: Heart Circ. Physiol. 40 (1996) H1643-H1655
15. Leenders K.L., Perani D., Lammertsma A.A., Heather J.D., Buckingham P., Healy M.J.R., Gibbs J.M., Wise R.J.S., Hatazawa J., Herold S., Beaney R.P., Brooks D.J., Spinks T., Rhodes C., Frackowiak R.S.J., and Jones T. Cerebral blood-flow, blood-volume and oxygen utilization-normal values and effect of age. Brain 113 (1990) 27-47
16. Mardia K.V., Kent J.T., and Bibby J.M. Multivariate Analysis (1979), Academic Press, London
17. Mouridsen K., Christensen S., Gyldensted L., and Østergaard L. Automatic selection of arterial input function using cluster analysis. Magn. Reson. Med. 55 3 (2006) 524-531
18. Ostergaard L., Weisskoff R.M., Chesler D.A., Gyldensted C., and Rosen B.R. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages: 1. Mathematical approach and statistical analysis. Magn. Reson. Med. 36 (1996) 715-725
19. Ostergaard L., Chesler D.A., Weisskoff R.M., Sorensen A.G., and Rosen B.R. Modeling cerebral blood flow and flow heterogeneity from magnetic resonance residue data. J. Cereb. Blood Flow Metab. 19 (1999) 690-699
20. Ostergaard L., Sorensen A.G., Chesler D.A., Weisskoff R.M., Koroshetz W.J., Wu O., Gyldensted C., and Rosen B.R. Combined diffusion-weighted and perfusion-weighted flow heterogeneity magnetic resonance imaging in acute stroke. Stroke 31 (2000) 1097-1103
21. Penny W.D., Stephan K.E., Mechelli A., and Friston K.J. Comparing dynamic causal models. NeuroImage 22 (2004) 1157-1172
22. Perkio J., Soinne L., Ostergaard L., Helenius J., Kangasmaki A., Martinkauppi S., Salonen O., Savolainen S., Kaste M., Tatlisumak T., and Aronen H.J. Abnormal intravoxel cerebral blood flow heterogeneity in human ischemic stroke determined by dynamic susceptibility contrast magnetic resonance imaging. Stroke 36 (2005) 44-49
23. Rausch M., Scheffler K., Rudin M., and Radu E.W. Analysis of input functions from different arterial branches with gamma variate functions and cluster analysis for quantitative blood volume measurements. Magn. Reson. Imaging 18 (2000) 1235-1243
24. Sijbers J., den Dekker A.J., Van Audekerke J., Verhoye M., and Van Dyck D. Estimation of the noise in magnitude MR images. Magn. Reson. Imaging 16 (1998) 87-90
25. Simonsen C.Z., Rohl L., Vestergaard-Poulsen P., Gyldensted C., Andersen G., and Ostergaard L. Final infarct size after acute stroke: prediction with flow heterogeneity. Radiology 225 (2002) 269-275
26. Sorensen A.G., Copen W.A., Ostergaard L., Buonanno F.S., Gonzalez R.G., Rordorf G., Rosen B.R., Schwamm L.H., Weisskoff R.M., and Koroshetz W.J. Hyperacute stroke: simultaneous measurement of relative cerebral blood volume, relative cerebral blood flow, and mean tissue transit time. Radiology 210 (1999) 519-527
27. Stewart G.N. Researches on the circulation time in organs and on the influences which affect it: Parts I-III. J. Physiol. (1894) 15
28. Villringer A., Rosen B.R., Belliveau J.W., Ackerman J.L., Lauffer R.B., Buxton R.B., Chao Y.S., Wedeen V.J., and Brady T.J. Dynamic imaging with lanthanide chelates in normal brain-contrast due to magnetic-susceptibility effects. Magn. Reson. Med. 6 (1988) 164-174
29. Weisskoff R.M., Zuo C.S., Boxerman J.L., and Rosen B.R. Microscopic susceptibility variation and transverse relaxation-Theory and experiment. Magn. Reson. Med. 31 (1994) 601-610
30. Wu O., Koroshetz W.J., Ostergaard L., Buonanno F.S., Copen W.A., Gonzalez R.G., Rordorf G., Rosen B.R., Schwamm L.H., Weisskoff R.M., and Sorensen A.G. Predicting tissue outcome in acute human cerebral ischemia using combined diffusion- and perfusion-weighted MR imaging. Stroke 32 (2001) 933-942
31. Wu O., Ostergaard L., Weisskoff R.M., Benner T., Rosen B.R., and Sorensen A.G. Tracer arrival timing-insensitive technique for estimating flow in MR perfusion-weighted imaging using singular value decomposition with a block-circulant deconvolution matrix. Magn. Reson. Med. 50 (2003) 164-174