Although liquid ventilation has been researched and studied for the last six decades, it did not achieve its expected optimal performance. Within this work, a deeper understanding of the fluid dynamics during liquid ventilation shall be gathered to extend the already available clinical knowledge about this ventilation strategy. In order to reach this goal, advanced optical flow measurement techniques are applied in different models of the human conductive airways to obtain global velocity fields, identifying prominent flow structures and to determine important dissolved oxygen transport paths. As the velocity measurements revealed, the evolving flow field is strongly dominated by secondary flow effects and is highly dependent on the local airway geometry. During the visualization experiments of the dissolved oxygen concentration fields, different transportation paths occur at inspirational and expirational flow. The initial concentration distribution can be linked to the underlying flow fields but decouples after the peak velocity phases. With higher flow rates/ tidal volumes, a more homogeneously distributed oxygen concentration can be reached.:List of Figures ....................................................................................... VII List of Tables ........................................................................................XIII Nomenclature ........................................................................................ XV 1 Introduction......................................................................................... 1 1.1 Motivation ........................................................................................1 1.2 Research objectives........................................................................... 3 1.3 Outline............................................................................................ 4 2 State of the art .................................................................................... 5 2.1 Liquid Ventilation............................................................................. 5 2.2 In vitro modeling.............................................................................. 8 2.3 Flow measurements ......................................................................... 11 2.4 Gas transport..................................................................................13 3 Flow field measurements ................................................................... 16 3.1 Hydrodynamic Model.......................................................................16 3.1.1 Lung replica ..........................................................................16 3.1.2 Flow parameter .....................................................................18 3.1.3 Limitations ...........................................................................22 3.2 Particle Tracking Velocimetry (PTV) ................................................24 3.2.1 Measurement principle ...........................................................24 3.2.2 Double-frame 2D-PTV ...........................................................25 3.2.3 Time-resolved 3D-PTV ..........................................................28 3.2.4 Phase-locked ensemble PTV ................................................... 31 3.3 Experimental set-up and measurement procedure ...............................33 3.3.1 Lung flow facility...................................................................33 3.3.2 2D-PTV configuration............................................................36 3.3.3 3D-PTV configuration............................................................36 3.4 Results & Discussion........................................................................38 3.4.1 Artificial lung........................................................................38 3.4.2 Realistic lung ........................................................................52 3.5 Conclusion ......................................................................................59 4 Oxygen transport ...............................................................................61 4.1 Hydrodynamic Model....................................................................... 61 4.1.1 Lung replica .......................................................................... 61 4.1.2 Flow parameter .....................................................................62 4.1.3 Limitations ...........................................................................65 4.2 Oxygen Sensitive Dye ......................................................................66 4.3 Experimental set-up......................................................................... 71 4.4 Results & Discussion........................................................................75 4.4.1 Constant flow rate .................................................................75 4.4.2 Oscillatory flow .....................................................................83 4.5 Conclusion ......................................................................................90 5 Summary............................................................................................ 92 6 Outlook .............................................................................................. 95 Bibliography ............................................................................................ 97 / Trotz intensiver Forschung in den letzten sechs Jahrzehnten, befindet sich die Flüssigkeitsbeatmung immernoch weit entfernt vom klinischen Alltag. Mit dieser Arbeit soll ein Beitrag geleistet werden, um das Wissen um die strömungsmechanischen Effekte während der Flüssigkeitsbeatmung zu vertiefen. Dazu werden verschiedene Modellexperimente durchgeführt, bei welchen moderne laseroptische Strömungsmessmethoden zum Einsatz kommen. Untersucht werden dabei unterschiedlich komplexe Geometrien der leitenden menschlichen Atemwege mit dem Ziel wesentliche Strömungsstrukturen, globale Geschwindigkeitsfelder und wichtige Transportwege des gelösten Sauerstoffs zu identifiziern. Die Geschwindigkeitsmessungen zeigen ein stark durch sekundäre Strömungseffekte dominiertes Geschwindigkeitsfeld, welches wesentlich von der lokalen Geometrie abhängig ist. Durch die qualitative und quantitative Erfassung der gelösten Sauerstoffkonzentrationsfelder können wichtige Transportwege aufgedeckt werden. Diese unterscheiden sich deutlich zwischen inspiratorischer und expiratorischer Strömungsrichtung. Die initialen Konzentrationsfelder stimmen mit den unterliegenden Geschwindigkeitsfeldern überein, unterscheiden sich ab der verzögernden Strömungsphase jedoch. Höhere Volumenströme/Tidalvolumen tragen dabei zu einer gleichmäßigeren Konzentrationsverteilung bei.:List of Figures ....................................................................................... VII List of Tables ........................................................................................XIII Nomenclature ........................................................................................ XV 1 Introduction......................................................................................... 1 1.1 Motivation ........................................................................................1 1.2 Research objectives........................................................................... 3 1.3 Outline............................................................................................ 4 2 State of the art .................................................................................... 5 2.1 Liquid Ventilation............................................................................. 5 2.2 In vitro modeling.............................................................................. 8 2.3 Flow measurements ......................................................................... 11 2.4 Gas transport..................................................................................13 3 Flow field measurements ................................................................... 16 3.1 Hydrodynamic Model.......................................................................16 3.1.1 Lung replica ..........................................................................16 3.1.2 Flow parameter .....................................................................18 3.1.3 Limitations ...........................................................................22 3.2 Particle Tracking Velocimetry (PTV) ................................................24 3.2.1 Measurement principle ...........................................................24 3.2.2 Double-frame 2D-PTV ...........................................................25 3.2.3 Time-resolved 3D-PTV ..........................................................28 3.2.4 Phase-locked ensemble PTV ................................................... 31 3.3 Experimental set-up and measurement procedure ...............................33 3.3.1 Lung flow facility...................................................................33 3.3.2 2D-PTV configuration............................................................36 3.3.3 3D-PTV configuration............................................................36 3.4 Results & Discussion........................................................................38 3.4.1 Artificial lung........................................................................38 3.4.2 Realistic lung ........................................................................52 3.5 Conclusion ......................................................................................59 4 Oxygen transport ...............................................................................61 4.1 Hydrodynamic Model....................................................................... 61 4.1.1 Lung replica .......................................................................... 61 4.1.2 Flow parameter .....................................................................62 4.1.3 Limitations ...........................................................................65 4.2 Oxygen Sensitive Dye ......................................................................66 4.3 Experimental set-up......................................................................... 71 4.4 Results & Discussion........................................................................75 4.4.1 Constant flow rate .................................................................75 4.4.2 Oscillatory flow .....................................................................83 4.5 Conclusion ......................................................................................90 5 Summary............................................................................................ 92 6 Outlook .............................................................................................. 95 Bibliography ............................................................................................ 97

Stains and stained incipient lesions can be challenging to differentiate with established clinical tools. New diagnostic techniques are required for improved distinction to enable early noninvasive treatment. This in vitro study evaluates the performance of artificial intelligence (AI)-based classification of hyperspectral imaging data for early occlusal lesion detection and differentiation from stains. Sixty-five extracted permanent human maxillary and mandibular bicuspids and molars (International Caries Detection and Assessment System [ICDAS] II 0–4) were imaged with a hyperspectral camera (Diaspective Vision TIVITA® Tissue, Diaspective Vision, Pepelow, Germany) at a distance of 350 mm, acquiring spatial and spectral information in the wavelength range 505–1000 nm; 650 fissural spectra were used to train classification algorithms (models) for automated distinction between stained but sound enamel and stained lesions. Stratified 10-fold cross-validation was used. The model with the highest classification performance, a fine k-nearest neighbor classification algorithm, was used to classify five additional tooth fissural areas. Polarization microscopy of ground sections served as reference. Compared to stained lesions, stained intact enamel showed higher reflectance in the wavelength range 525–710 nm but lower reflectance in the wavelength range 710–1000 nm. A fine k-nearest neighbor classification algorithm achieved the highest performance with a Matthews correlation coefficient (MCC) of 0.75, a sensitivity of 0.95 and a specificity of 0.80 when distinguishing between intact stained and stained lesion spectra. The superposition of color-coded classification results on further tooth occlusal projections enabled qualitative assessment of the entire fissure’s enamel health. AI-based evaluation of hyperspectral images is highly promising as a complementary method to visual and radiographic examination for early occlusal lesion detection.

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