Andreas Voskrebenzev ^1,2* Marcel Gutberlet ^1,2 Filip Klimeš ^1,2 Till Kaireit ^1,2 Hoen-oh Shin ^1,2 Hans-Ulrich Kauczor ^3,4 Tobias Welte ^1,5 Frank Wacker ^1,2 Jens Vogel-Claussen ^1,2

• ¹ Institute for Diagnostic and Interventional Radiology, Hannover Medical School, Hanover, Germany
• ² Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany
• ³ Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Baden-Württemberg, Germany
• ⁴ Translational Lung Research Center, Heidelberg University Hospital, Heidelberg, Baden-Württemberg, Germany
• ⁵ Clinic for Pediatric Pneumology, Allergology and Neonatology, Center for Pediatrics and Adolescent Medicine, Hannover Medical School, Hannover, Germany

Introduction: Validation of functional free breathing MRI involves a comparison to more established or more direct measurements. This procedure is cost intensive, as it requires access to patient cohorts, lengthy protocols, expenses for consumables and binds working time. Therefore, the purpose of this study is to introduce a synthetic lung model (ASYLUM), which mimics dynamic MRI acquisition and includes predefined lung abnormalities for an alternative validation approach. The model is evaluated with different registration and quantification methods and compared with real data.Methods: A combination of trigonometric functions, deformation fields and signal combination were used to create 20 synthetic image time-series. Lung voxels were assigned either to normal or one of six abnormality classes. The images were registered with three registration algorithms. The registered images were further analyzed with three quantification methods: Deformation-Based or Signal-Based regional ventilation (JVent/RVent) analysis and perfusion-amplitude (QA). The registration results were compared with predefined deformations. Quantification methods were evaluated regarding predefined amplitudes and with respect to sensitivity, specificity and spatial overlap of defects. In addition, 36 patients with chronic obstructive pulmonary disease were included for verification of model interpretations using CT as gold standard.Results: One registration method showed considerably lower quality results (76% correlation vs. 92/97%, P≤0.0001). Most ventilation defects were correctly detected with RVent and QA (e.g., one registration variant with sensitivity ≥78%, specificity ≥88). Contrary, JVent showed very low sensitivity for lower lung quadrants (0-16%)) and also very low specificity (1-29%) for upper lung quadrants. Similar patterns of defect detection differences between RVent and JVent were also observable in patient data: Firstly, RVent was more aligned with CT than JVent for all quadrants (P≤0.01) except for one registration variant in the lower left region. Secondly, stronger differences in overlap were observed for upper quadrants suggesting a defect bias in the JVent measurements in the upper lung regions.The feasibility of a validation framework for free-breathing functional lung imaging using synthetic time-series was demonstrated. Evaluating different ventilation measurements, important differences were detected in synthetic and real data with signal-based regional ventilation assessment being a more reliable method in the investigated setting.