Quantification of pulmonary microcirculation by dynamic contrast-enhanced magnetic resonance imaging: comparison of four regularization methods
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 deconvolut...
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| Hauptverfasser: | , , , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2013
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| In: |
Magnetic resonance in medicine
Year: 2013, Jahrgang: 69, Heft: 1, Pages: 188-199 |
| ISSN: | 1522-2594 |
| DOI: | 10.1002/mrm.24220 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1002/mrm.24220 Verlag, lizenzpflichtig, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.24220 
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| Verfasserangaben: | 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 |
| Zusammenfassung: | 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. |
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| Beschreibung: | Published online 1 March 2012 Gesehen am 16.12.2021 |
| Beschreibung: | Online Resource |
| ISSN: | 1522-2594 |
| DOI: | 10.1002/mrm.24220 |