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Limitations of DSC-MRI for quantitative brain perfusion

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Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Synthesis of quantitative parametric images in DSC-MRI is presented. Critical review of major limitations of the DSC-MRI method is discussed. It includes investigation of measurement procedures/conditions as well as parametric image synthesis methodology. Simulations, as well as phantom studies were used to verify theoretical limitations of the DSC-MRI. Especially, estimation of the contrast (Gd-DTPA) concentration by EPI measurements, the role of a phantom and its pipes orientation, influence of a bolus dispersion, bolus arrival time, and other signal parameters on an image quality. As a conclusion testing software package is proposed.
Rocznik
Tom
Strony
MM49--58
Opis fizyczny
Bibliogr. 18 poz., rys.
Twórcy
autor
  • Department of Biomedical Engineering, Gdansk University of Technology
  • Department of Neuroradiology, Medical University of Gdansk
Bibliografia
  • [1] ANDERSEN I.K., SZYMKOWIAK A., RASMUSSEN C.E., HANSON L.G., MARSTRAND J.R., LARSSON H.B.W., HANSEN1 L.K., PERFUSION Quantification Using Gaussian Process Deconvolution, Magnetic Resonance in Medicine, 48:351-361, 2002.
  • [2] BOXERMAN JL, HAMBERG LM, ROSEN BR, WEISSKOFF RM. MR contrast due to intravascular magnetic susceptibility perturbations. Magn. Reson. Med. 34:555-66, 1995.
  • [3] CAI W., FENG D. D., FULTON R., Content based retrieval of dynamic PET functional images, IEEE Transactions on Information Technology in Biomedicine 4 (2)152-158, 2000.
  • [4] CALAMANTE F., GADIAN D.G., CONNELLY A., Quantification of Perfusion Using Bolus Tracking Magnetic Resonance Imaging in Stroke. Assumptions, Limitations, and Potential Implications for Clinical Use, Stroke, 33:1146-1151, 2002.
  • [5] 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. 19 701-35, 1999.
  • [6] CALAMANTE F, GADIAN D G and CONNELLY A 2000 Delay and dispersion effects in dynamic susceptibility contrast MRI: simulations using singular value decomposition Magn. Reson. Med. 44 466-73
  • [7] CHEONG L H, KOH T S, HOU Z, An automatic approach for estimating bolus arrival time in dynamic contrast MRI using piecewise continuous regression models Phys. Med. Biol. 48:N83-N88, 2003.
  • [8] MORRIS E.D., TASCIYAN T.A., VANMETER J.W., MAISONG J.M., ZEFFIRO T.A., Automated determination of the arterial input function for MR perfusion analysis. Available: www.indyrad.iupui.edu/public/emorris/Sensor/poster.pdf
  • [9] ØSTERGAARD 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: I. Mathematical approach and statistical analysis, II. Experimental comparison and preliminary results Magn. Reson. Med. 36 715-36, 1996.
  • [10] ØSTERGAARD L, SMITH DF, VESTERGAARD-POULSEN P, HANSEN SB, GEE A, GJEDDE A, GYLDENSTED C. Absolute Cerebral Blood Flow and Blood Volume Measured by MRI Bolus Tracking: Comparison with PET Values. J. Cereb. Blood Flow Metab. 18:425-32, 1998.
  • [11] QUARLES, C.C., PATHAK, A.P., WARD, B.D., REBRO, K.J., SCHMAINDA, K.M. Reliability of Measuring Tumor Perfusion using Dynamic Susceptibility Contrast MRI: The Influence of Vascular Structure and Imaging Technique. 10th Scientific Meeting & Exhibition of the International Society for Magnetic Resonance in Medicine, Honululu, Hawai'i, USA, May 18-24, 2002.
  • [12] RUMIŃSKI J., KACZMAREK M., NOWAKOWSKI A., Medical Active Thermography - A New Image Reconstruction Method, Lecture Notes in Computer Science LNCS2124, Springer, 274-181, 2001.
  • [13] SCHREIBER WG, GÜCKEL 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 18:1143-1156, 1998.
  • [14] SIMONSEN C.Z., OSTERGAARD L., SMITH D.F., VASTERGAARD-PULSEN P., GYLDENSTED C., Comparision of gradient- and spin-echo imaging: CBF, CBV and MTT measurements by bolus tracking, Journal of Magnetic Resonance Imaging, 12:411-46, 2000.
  • [15] SORENSEN A.G., REIMER P., Cerebral MR Perfusion Imaging, Principles and Current Applications, Georg Thieme Verlag, Stuttgart, 2000.
  • [16] VAN OSCH T., Evaluation of cerebral hemodynamics by quantitative perfusion MRI, PhD thesis, Image Science Institute, Utrecht, 2002.
  • [17] VONKEN EP, BEEKMAN FJ, BAKKER CJ, VIERGEVER MA. Maximum likelihood estimation of cerebral blood flow in dynamic susceptibility contrast MRI. Magn.Reson.Med. 41:343-50, 1999.
  • [18] WANG J., ALSOP D. C., Li L., LISTERUD J., GONZALEZ-At J. B., SCHNALL M. D., DETRE J. A., Comparison of Quantitative Perfusion Imaging Using Arterial Spin Labeling at 1.5 and 4.0 Tesla, Magnetic Resonance in Medicine 48:242-254, 2002.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA4-0014-0011
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