Literature DB >> 20572155

Simulation model for contrast agent dynamics in brain perfusion scans.

Jörg Bredno1, Mark E Olszewski, Max Wintermark.   

Abstract

Standardization efforts are currently under way to reduce the heterogeneity of quantitative brain perfusion methods. A brain perfusion simulation model is proposed to generate test data for an unbiased comparison of these methods. This model provides realistic simulated patient data and is independent of and different from any computational method. The flow of contrast agent solute and blood through cerebral vasculature with disease-specific configurations is simulated. Blood and contrast agent dynamics are modeled as a combination of convection and diffusion in tubular networks. A combination of a cerebral arterial model and a microvascular model provides arterial-input and time-concentration curves for a wide range of flow and perfusion statuses. The model is configured to represent an embolic stroke in one middle cerebral artery territory and provides physiologically plausible vascular dispersion operators for major arteries and tissue contrast agent retention functions. These curves are fit to simpler template curves to allow the use of the simulation results in multiple validation studies. A gamma-variate function with fit parameters is proposed as the vascular dispersion operator, and a combination of a boxcar and exponential decay function is proposed as the retention function. Such physiologically plausible operators should be used to create test data that better assess the strengths and the weaknesses of various analysis methods. (c) 2010 Wiley-Liss, Inc.

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Year:  2010        PMID: 20572155     DOI: 10.1002/mrm.22431

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


  7 in total

1.  Standardization of Stroke Perfusion CT for Reperfusion Therapy.

Authors:  Guangming Zhu; Patrik Michel; Weiwei Zhang; Max Wintermark
Journal:  Transl Stroke Res       Date:  2012-03-28       Impact factor: 6.829

2.  A fast nonlinear regression method for estimating permeability in CT perfusion imaging.

Authors:  Edwin Bennink; Alan J Riordan; Alexander D Horsch; Jan Willem Dankbaar; Birgitta K Velthuis; Hugo W de Jong
Journal:  J Cereb Blood Flow Metab       Date:  2013-07-24       Impact factor: 6.200

3.  Fast nonlinear regression method for CT brain perfusion analysis.

Authors:  Edwin Bennink; Jaap Oosterbroek; Kohsuke Kudo; Max A Viergever; Birgitta K Velthuis; Hugo W A M de Jong
Journal:  J Med Imaging (Bellingham)       Date:  2016-06-16

4.  Reliability of CT perfusion-derived CBF in relation to hemodynamic compromise in patients with cerebrovascular steno-occlusive disease: a comparative study with 15O PET.

Authors:  Masanobu Ibaraki; Tomomi Ohmura; Keisuke Matsubara; Toshibumi Kinoshita
Journal:  J Cereb Blood Flow Metab       Date:  2015-03-11       Impact factor: 6.200

5.  Inferring CT perfusion parameters and uncertainties using a Bayesian approach.

Authors:  Tao Sun; Roger Fulton; Zhanli Hu; Christina Sutiono; Dong Liang; Hairong Zheng
Journal:  Quant Imaging Med Surg       Date:  2022-01

6.  Estimation of microvascular capillary physical parameters using MRI assuming a pseudo liquid drop as model of fluid exchange on the cellular level.

Authors:  Mansour Ashoor; Abdollah Khorshidi; Leila Sarkhosh
Journal:  Rep Pract Oncol Radiother       Date:  2018-10-10

7.  Physics-Informed Neural Networks for Brain Hemodynamic Predictions Using Medical Imaging.

Authors:  Mohammad Sarabian; Hessam Babaee; Kaveh Laksari
Journal:  IEEE Trans Med Imaging       Date:  2022-08-31       Impact factor: 11.037

  7 in total

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