| Online-Ressource |
Verfasst von: | Salehi Ravesh, Mona [VerfasserIn]  |
| Brix, G. [VerfasserIn]  |
| Laun, Frederik B. [VerfasserIn]  |
| Kuder, Tristan Anselm [VerfasserIn]  |
| Puderbach, Michael [VerfasserIn]  |
| Ley-Zaporozhan, Julia [VerfasserIn]  |
| Ley, S. [VerfasserIn]  |
| Fieselmann, A. [VerfasserIn]  |
| Herrmann, M. F. [VerfasserIn]  |
| Schranz, W. [VerfasserIn]  |
| Semmler, W. [VerfasserIn]  |
| Risse, Frank [VerfasserIn]  |
Titel: | Quantification of pulmonary microcirculation by dynamic contrast-enhanced magnetic resonance imaging |
Titelzusatz: | comparison of four regularization methods |
Verf.angabe: | M. Salehi Ravesh, G. Brix, F.B. Laun, T.A. Kuder, M. Puderbach, J. Ley-Zaporozhan, S. Ley, A. Fieselmann, M.F. Herrmann, W. Schranz, W. Semmler, and F. Risse |
Jahr: | 2013 |
Umfang: | 12 S. |
Fussnoten: | Published online 1 March 2012 ; Gesehen am 16.12.2021 |
Titel Quelle: | Enthalten in: Magnetic resonance in medicine |
Ort Quelle: | New York, NY [u.a.] : Wiley-Liss, 1984 |
Jahr Quelle: | 2013 |
Band/Heft Quelle: | 69(2013), 1 vom: Jan., Seite 188-199 |
ISSN Quelle: | 1522-2594 |
Abstract: | Tissue microcirculation can be quantified by a deconvolution analysis of concentration-time curves measured by dynamic contrast-enhanced magnetic resonance imaging. However, deconvolution is an ill-posed problem, which requires regularization of the solutions. In this work, four algebraic deconvolution/regularization methods were evaluated: truncated singular value decomposition and generalized Tikhonov regularization (GTR) in combination with the L-curve criterion, a modified LCC (GTR-MLCC), and a response function model that takes a-priori knowledge into account. To this end, dynamic contrast-enhanced magnetic resonance imaging data sets were simulated by an established physiologically reference model for different signal-to-noise ratios and measured on a 1.5-T system in the lung of 10 healthy volunteers and 20 patients. Analysis of both the simulated and measured dynamic contrast-enhanced magnetic resonance imaging datasets revealed that GTR in combination with the L-curve criterion does not yield reliable and clinically useful results. The three other deconvolution/regularization algorithms resulted in almost identical microcirculatory parameter estimates for signal-to-noise ratios > 10. At low signal-to-noise ratios levels (<10) typically occurring in pathological lung regions, GTR in combination with a modified L-curve criterion approximates the true response function much more accurately than truncated singular value decomposition and GTR in combination with response function model with a difference in accuracy of up to 76%. In conclusion, GTR in combination with a modified L-curve criterion is recommended for the deconvolution of dynamic contrast-enhanced magnetic resonance imaging curves measured in the lung parenchyma of patients with highly heterogeneous signal-to-noise ratios. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc. |
DOI: | doi:10.1002/mrm.24220 |
URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Volltext ; Verlag: https://doi.org/10.1002/mrm.24220 |
| Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.24220 |
| DOI: https://doi.org/10.1002/mrm.24220 |
Datenträger: | Online-Ressource |
Sprache: | eng |
Sach-SW: | lung perfusion |
| model-free algebraic deconvolution |
| quantitative analysis |
| Tikhonov regularization |
K10plus-PPN: | 178235929X |
Verknüpfungen: | → Zeitschrift |
Quantification of pulmonary microcirculation by dynamic contrast-enhanced magnetic resonance imaging / Salehi Ravesh, Mona [VerfasserIn]; 2013 (Online-Ressource)