Quantification of pulmonary microcirculation by dynamic contrast-enhanced magnetic resonance imaging: comparison of four regularization methods - Salehi Ravesh, Mona; Brix, G.; Laun, Frederik B.; Kuder, Tristan Anselm; Puderbach, Michael; Ley-Zaporozhan, Julia; Ley, S.; Fieselmann, A.; Herrmann, M. F.; Schranz, W.; Semmler, W.; Risse, Frank (Magnetic resonance in medicine, 2013)
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.
Published online 1 March 2012
Gesehen am 16.12.2021