Literature DB >> 17975296

Deconvolution of bolus-tracking data: a comparison of discretization methods.

S Sourbron1, R Luypaert, D Morhard, K Seelos, M Reiser, M Peller.   

Abstract

Model-free measurement of perfusion from bolus-tracking data requires a discretization of the tracer kinetic model. In this study a classification is provided of existing approaches to discretization, and the accuracy of these methods is compared. Two methods are included which are delay invariant (circulant and time shift) and three methods which are not (volterra, singular and hybrid). Simulations of magnetic resonance imaging (MRI) in the brain are performed for two tissue types (plug flow and compartment) with variable delay and dispersion times, temporal resolution and signal to noise. Simulations were compared to measurements in a patient data set. Both delay-invariant methods are equally accurate, but the circulant method is sensitive to data truncation. Overall volterra produces highest estimates of perfusion, followed by hybrid, singular and delay-invariant methods. Volterra is most accurate except in plug-flow without delay or dispersion, which represents an unrealistic tissue type. Differences between methods vanish when delay or dispersion times increase above the temporal resolution. It is concluded that when negative delays cannot be avoided or when an accurate estimate of left-right perfusion ratios is required, the time shift is the method of choice. When delays are certain to be positive and absolute accuracy is the objective, the volterra method is to be preferred.

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Year:  2007        PMID: 17975296     DOI: 10.1088/0031-9155/52/22/014

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  11 in total

1.  Correction for arterial-tissue delay and dispersion in absolute quantitative cerebral perfusion DSC MR imaging.

Authors:  Jessy J Mouannes-Srour; Wanyong Shin; Sameer A Ansari; Michael C Hurley; Parmede Vakil; Bernard R Bendok; John L Lee; Colin P Derdeyn; Timothy J Carroll
Journal:  Magn Reson Med       Date:  2011-12-12       Impact factor: 4.668

Review 2.  [Magnetic resonance imaging of pulmonary perfusion. Technical requirements and diagnostic impact].

Authors:  U I Attenberger; M Ingrisch; K Büsing; M Reiser; S O Schoenberg; C Fink
Journal:  Radiologe       Date:  2009-08       Impact factor: 0.635

Review 3.  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

4.  UMMPerfusion: an open source software tool towards quantitative MRI perfusion analysis in clinical routine.

Authors:  Frank G Zöllner; Gerald Weisser; Marcel Reich; Sven Kaiser; Stefan O Schoenberg; Steven P Sourbron; Lothar R Schad
Journal:  J Digit Imaging       Date:  2013-04       Impact factor: 4.056

5.  Correlation analysis of dual-energy CT iodine maps with quantitative pulmonary perfusion MRI.

Authors:  Jan Hansmann; Paul Apfaltrer; Frank G Zoellner; Thomas Henzler; Mathias Meyer; Gerald Weisser; Stefan O Schoenberg; Ulrike I Attenberger
Journal:  World J Radiol       Date:  2013-05-28

6.  Quantitative blood flow measurements in the small animal cardiopulmonary system using digital subtraction angiography.

Authors:  MingDe Lin; Craig T Marshall; Yi Qi; Samuel M Johnston; Cristian T Badea; Claude A Piantadosi; G Allan Johnson
Journal:  Med Phys       Date:  2009-11       Impact factor: 4.071

7.  Validation study of perfusion parameter in hypervascular hepatocellular carcinoma and focal nodular hyperplasia using dynamic susceptibility magnetic resonance imaging with super-paramagnetic iron oxide: comparison with single level dynamic CT arteriography.

Authors:  Kazuhiro Saito; Joseph Ledsam; Steven Sourbron; Yoichi Araki
Journal:  Quant Imaging Med Surg       Date:  2020-06

8.  Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details.

Authors:  Andreas Fieselmann; Markus Kowarschik; Arundhuti Ganguly; Joachim Hornegger; Rebecca Fahrig
Journal:  Int J Biomed Imaging       Date:  2011-08-28

9.  Comparison of dual-energy computer tomography and dynamic contrast-enhanced MRI for evaluating lung perfusion defects in chronic thromboembolic pulmonary hypertension.

Authors:  Tawfik Moher Alsady; Till F Kaireit; Lea Behrendt; Hinrich B Winther; Karen M Olsson; Frank Wacker; Marius M Hoeper; Serghei Cebotari; Jens Vogel-Claussen
Journal:  PLoS One       Date:  2021-06-17       Impact factor: 3.240

10.  Water-Exchange-Modified Kinetic Parameters from Dynamic Contrast-Enhanced MRI as Prognostic Biomarkers of Survival in Advanced Hepatocellular Carcinoma Treated with Antiangiogenic Monotherapy.

Authors:  Sang Ho Lee; Koichi Hayano; Andrew X Zhu; Dushyant V Sahani; Hiroyuki Yoshida
Journal:  PLoS One       Date:  2015-09-14       Impact factor: 3.240

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