Mona Salehi Ravesh1, Michael Puderbach2, Sebastian Ley3, Julia Ley-Zaporzhan3, Frank Risse1, Wilfried Schranz4, Wolfhard Semmler1, Frederik Bernd Laun1
1Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany; 2Department of Radiology, German Cancer Research Center, Heidelberg, Germany; 3Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany; 4Nonlinear Physics Group, Faculty of Physics, University of Vienna, Vienna, Austria
Lung perfusion is a crucial prerequisite for effective gas exchange. An accurate quantification of pulmonary perfusion is therefore important for diagnostic considerations and treatment planning in various diseases of the lungs.The assessment of pulmonary perfusion by Dynamic Contrast-Enhanced Magnetic Resonance Imaging requires deconvolution of the arterial input function. In the presence of noise this is an ill-posed problem which leads to strongly oscillating, unphysical solutions when it is solved without regularization. In this study a novel method to quantify the pulmonary perfusion is used and compared to the singular value decomposition and L-curve criterion based on simulated and patient data.