Literature DB >> 12939770

Model of the human vasculature for studying the influence of contrast injection speed on cerebral perfusion MRI.

Matthias J P van Osch1, Evert-Jan P A Vonken, Ona Wu, Max A Viergever, Jeroen van der Grond, Chris J G Bakker.   

Abstract

Simulations of dynamic susceptibility contrast (DSC) MRI are frequently performed by assuming a certain shape for the input function and the microvascular response function. However, to investigate the influence of parameters that will affect the shape of the input function, a more complex model of the human vasculature is required. In this study, a model of the human vasculature is proposed that consists of a network of vascular operators based on physiological data typical of a 35-year-old male subject. The simulated contrast passage curves were found to be within the range of observed contrast passage curves in a population of patients without vascular disease. The model was used to predict the effect of different injection speeds of the contrast agent on the accuracy of the perfusion experiment. It was found that injection speeds of <3 ml/s lead to an underestimation of the observed cerebral blood flow (CBF). Additionally, it was determined that decreasing the temporal resolution of the acquisition results in an underestimation of the CBF values, and an increase of the standard deviation (SD) of CBF measurements. Copyright 2003 Wiley-Liss, Inc.

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Year:  2003        PMID: 12939770     DOI: 10.1002/mrm.10567

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  13 in total

1.  Extraction of the first bolus passage in dynamic susceptibility contrast perfusion measurements.

Authors:  Peter Gall; Irina Mader; Valerij G Kiselev
Journal:  MAGMA       Date:  2009-04-21       Impact factor: 2.310

Review 2.  Gadolinium contrast agents for CNS imaging: current concepts and clinical evidence.

Authors:  E Kanal; K Maravilla; H A Rowley
Journal:  AJNR Am J Neuroradiol       Date:  2014-05-22       Impact factor: 3.825

3.  ASFNR recommendations for clinical performance of MR dynamic susceptibility contrast perfusion imaging of the brain.

Authors:  K Welker; J Boxerman; A Kalnin; T Kaufmann; M Shiroishi; M Wintermark
Journal:  AJNR Am J Neuroradiol       Date:  2015-04-23       Impact factor: 3.825

Review 4.  Absolute quantification of perfusion using dynamic susceptibility contrast MRI: pitfalls and possibilities.

Authors:  Linda Knutsson; Freddy Ståhlberg; Ronnie Wirestam
Journal:  MAGMA       Date:  2009-12-04       Impact factor: 2.310

5.  Arterial input function in a dedicated slice for cerebral perfusion measurements in humans.

Authors:  Elias Kellner; Irina Mader; Marco Reisert; Horst Urbach; Valerij Gennadevic Kiselev
Journal:  MAGMA       Date:  2017-12-09       Impact factor: 2.310

Review 6.  MR perfusion imaging in acute ischemic stroke.

Authors:  William A Copen; Pamela W Schaefer; Ona Wu
Journal:  Neuroimaging Clin N Am       Date:  2011-05       Impact factor: 2.264

7.  Early time points perfusion imaging.

Authors:  Kenneth K Kwong; Timothy G Reese; Koen Nelissen; Ona Wu; Suk-Tak Chan; Thomas Benner; Joseph B Mandeville; Mary Foley; Wim Vanduffel; David A Chesler
Journal:  Neuroimage       Date:  2010-09-17       Impact factor: 6.556

8.  Blind source separation of hemodynamics from magnetic resonance perfusion brain images using independent factor analysis.

Authors:  Yen-Chun Chou; Chia-Feng Lu; Wan-Yuo Guo; Yu-Te Wu
Journal:  Int J Biomed Imaging       Date:  2010-04-21

9.  Comparison of three physiologically-based pharmacokinetic models for the prediction of contrast agent distribution measured by dynamic MR imaging.

Authors:  Daniel P Barboriak; James R MacFall; Benjamin L Viglianti; Mark W Dewhirst Dvm
Journal:  J Magn Reson Imaging       Date:  2008-06       Impact factor: 4.813

10.  Towards robust glucose chemical exchange saturation transfer imaging in humans at 3 T: Arterial input function measurements and the effects of infusion time.

Authors:  Anina Seidemo; Patrick M Lehmann; Anna Rydhög; Ronnie Wirestam; Gunther Helms; Yi Zhang; Nirbhay N Yadav; Pia C Sundgren; Peter C M van Zijl; Linda Knutsson
Journal:  NMR Biomed       Date:  2021-09-29       Impact factor: 4.478

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