Abstract #0304

Comparison of signal- and volume-based ventilation-weighted assessment using 3D FLORET UTE MRI in patients with various pulmonary disease

Filip Klimeš^1,2, Joseph W Plummer^3,4,5, Andreas Voskrebenzev^1,2, Marcel Gutberlet^1,2, Marius M Wernz^1,2, Matthew M Willmering^3,6,7, Alexander M Matheson³, Abdullah S Bdaiwi³, Frank Wacker^1,2, Jason Woods^3,6,7,8, Zackary I Cleveland^3,4,6,7, Laura L Walkup^3,4,6,7, and Jens Vogel-Claussen^1,2

¹nstitute of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany, ²Member of the German Centre for Lung Research (DZL), Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany, ³Center for Pulmonary Imaging Research, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States, ⁴Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH, United States, ⁵National Heath, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States, ⁶Imaging Research Center, Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States, ⁷Department of Pediatrics, University of Cincinnati Medical Center, Cincinnati, OH, United States, ⁸Department of Physics, University of Cincinnati, Cincinnati, OH, United States

Synopsis

Keywords: Lung, Lung, ventilation; image registration

Motivation: 3D free breathing, contrast-free methods are increasingly used for pulmonary ventilation-weighted assessment.

Goal(s): Evaluate the signal-based (RVent-based on lung parenchyma signal changes during respiration) and volume-based (JVent-utilizing the Jacobian determinant of deformation fields) quantification of pulmonary ventilation using 3D UTE MRI in patients with various pulmonary diseases.

Approach: Conduct comparisons of RVent/JVent parameters, quantify the spatial overlap, and assess the correlation of their ventilation defect values (VDPs) to ¹²⁹Xe MRI.

Results: Statistically significant differences were found between RVent and JVent parameters, but not in VDPs. The average regional overlap of their defect maps was 84%. VDP_RVentshowed stronger correlation to VDP_129Xe than JVent.

Impact: Although both proton lung MRI methods successfully identified ventilation defects, the stronger correlation between signal-based (RVent) and ¹²⁹Xe MRI indicates that RVent may provide a more reliable assessment of lung ventilation in clinical applications in comparison to volume-based (JVent) parameter.

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