Using Single-Channel Blind Deconvolution to Choose the Most Realistic Pharmacokinetic Model in Dynamic Contrast-Enhanced MR Imaging
Gespeichert in:
Verfasser / Beitragende:
[Torfinn Taxt, Tina Pavlin, Rolf Reed, Fitz-Roy Curry, Erling Andersen, Radovan Jiřík]
Ort, Verlag, Jahr:
2015
Enthalten in:
Applied Magnetic Resonance, 46/6(2015-06-01), 643-659
Format:
Artikel (online)
Online Zugang:
| LEADER | caa a22 4500 | ||
|---|---|---|---|
| 001 | 605545286 | ||
| 003 | CHVBK | ||
| 005 | 20210128100935.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150601xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00723-015-0679-y |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00723-015-0679-y | ||
| 245 | 0 | 0 | |a Using Single-Channel Blind Deconvolution to Choose the Most Realistic Pharmacokinetic Model in Dynamic Contrast-Enhanced MR Imaging |h [Elektronische Daten] |c [Torfinn Taxt, Tina Pavlin, Rolf Reed, Fitz-Roy Curry, Erling Andersen, Radovan Jiřík] |
| 520 | 3 | |a In dynamic contrast-enhanced magnetic resonance imaging, there has been no consensus in the choice of the pharmacokinetic model. In this paper, a new approach for assessment of the most realistic model for a given tissue is presented. Non-blind and single-channel blind deconvolution algorithms were used in quantitative magnetic resonance dynamic contrast-enhanced imaging of the mouse masseter muscle to compare the realism of two different pharmacokinetic models for the tissue residue function. The first was the adiabatic approximation tissue homogeneity model (aaJW) and the second, the two-compartment exchange model (2CXM). Normals and mice treated with the substance C48/80 were studied. C48/80 increases both blood flow and contrast leakage in muscle substantially. The obtained approximation accuracy was evaluated for both pharmacokinetic models. In addition, the arterial input functions (aifs) estimated using blind deconvolution were compared to the corresponding observed aifs. The hypothesis is that the most realistic model of the tissue residue function leads to the best fits. The non-blind deconvolution did not result in any clear answer. For blind deconvolution, the aifs of the aaJW model were very similar to the corresponding observed aifs, and clearly more so than the aifs of the 2CXM model. Also, the approximation of the observed tracer time sequences was more accurate for the aaJW than the 2CXM model. The realism of different pharmacokinetic models in describing the passage of a tracer through a microvascular bed of a single tissue could be assessed using single-channel blind deconvolution. | |
| 540 | |a Springer-Verlag Wien, 2015 | ||
| 700 | 1 | |a Taxt |D Torfinn |u Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5020, Bergen, Norway |4 aut | |
| 700 | 1 | |a Pavlin |D Tina |u Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5020, Bergen, Norway |4 aut | |
| 700 | 1 | |a Reed |D Rolf |u Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5020, Bergen, Norway |4 aut | |
| 700 | 1 | |a Curry |D Fitz-Roy |u Department of Physiology and Membrane Biology, University of California, 4303 Tupper Hall One Shields Avenue, 95616, Davis, CA, USA |4 aut | |
| 700 | 1 | |a Andersen |D Erling |u Department of Clinical Engineering, Haukeland University Hospital, Jonas Lies vei 83, 5020, Bergen, Norway |4 aut | |
| 700 | 1 | |a Jiřík |D Radovan |u Academy of Sciences of the Czech Republic, Institute of Scientific Instruments, Královopolská 147, 61264, Brno, Czech Republic |4 aut | |
| 773 | 0 | |t Applied Magnetic Resonance |d Springer Vienna |g 46/6(2015-06-01), 643-659 |x 0937-9347 |q 46:6<643 |1 2015 |2 46 |o 723 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00723-015-0679-y |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00723-015-0679-y |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Taxt |D Torfinn |u Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5020, Bergen, Norway |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Pavlin |D Tina |u Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5020, Bergen, Norway |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Reed |D Rolf |u Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5020, Bergen, Norway |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Curry |D Fitz-Roy |u Department of Physiology and Membrane Biology, University of California, 4303 Tupper Hall One Shields Avenue, 95616, Davis, CA, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Andersen |D Erling |u Department of Clinical Engineering, Haukeland University Hospital, Jonas Lies vei 83, 5020, Bergen, Norway |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Jiřík |D Radovan |u Academy of Sciences of the Czech Republic, Institute of Scientific Instruments, Královopolská 147, 61264, Brno, Czech Republic |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Applied Magnetic Resonance |d Springer Vienna |g 46/6(2015-06-01), 643-659 |x 0937-9347 |q 46:6<643 |1 2015 |2 46 |o 723 | ||