The authors thank Professor Yu Feng, Dr. Jenna Briddell, Ian Woodward, and Lucas Attia for their helpful discussions.

1. Preparation of 3D printed experimental components
NOTE: All software used in the protocol are indicated in the Table of Materials. Additionally, the slicing software utilized is specific to the 3D printer listed in the Table of Materials; however, this protocol can be extended to a wide range of stereolithography (SLA) 3D printers.
<ol>
	<li>Convert patient CT scans to 3D objects (.stl files). 
	NOTE: For a more detailed discussion of the geometric&#160;features of the specific lung model used in these studies, refer to Feng et al.5.
	<ol>
		<li>Render CT scans into a 3D object using CT scan software (see Table of Materials). Open the CT scan and create a mask on the airspace using the Threshold tool with a setting in the range of -800 to -1000. Using the 3D Preview tool, view the 3D rendering and export the object (File | Export) as an .stl file.</li>
		<li>Importing the files into mesh editing software (see Table of Materials), remove any jagged features using the Select tool (Sculpt | Brushes: &#34;Shrink/Smooth&#34; | Properties: Strength (50), Size (10), Depth(0)). Smooth the surface (Ctrl+A | Deform | Smooth | Smoothing (0.2), Smoothing Scale (1)).</li>
		<li>In mesh editing software, extend the wall of these objects by 2 mm (Ctrl+A | Edit | Offset), and allow the inner object to remain hollow such that only the wall remains. Slice the object (Select | Edit | Plane Cut) at the trachea to form an inlet and at generations 2 or 3 where the object branches off to each lobe to create outlets (Figure 1A). 
		NOTE: The thickness of 2 mm was chosen based on the acceptable feature sizes specified by the manufacturer of the 3D printer listed in the Table of Materials. This thickness can be adjusted based on the specifications of the 3D printer available if the interior geometry of the model is maintained.</li>
	</ol>
	</li>
	<li>Modify patient lung model outlet geometries to be compatible with previously designed lobe outlet cap components (Figure 1B,C) listed in the Table of Materials.
	<ol>
		<li>Import the 3D object, which replicates the CT scan on the inside, has a wall thickness of 2 mm, and is open at the inlet and outlets, into 3D modeling software (see Table of Materials) as a Solid Body (Open | Mesh Files | Options | Solid Body).</li>
		<li>Create a plane based on a face at each of the outlets (Insert | Reference Geometry | Plane). Using the splicing tool, trace the inner wall and outer wall of the outlet in a sketch on the plane (Sketch | Spline).</li>
		<li>Loft a cylinder (OD 18.5 mm, ID 12.5 mm, H 15.15 mm) to connect to the inner and outer wall of the model, thus extending the outlet to be uniform at each lobe (Features | Lofted Boss/Base). Add a notch around the edge of the outlet to match with the cap (Features | Extruded Cut | Offset). 
		NOTE: The cap (Figure 1D) is a hollow cylinder matching the dimensions of the outlets and having a shelf that interconnects with the notch of the model outlet. One end of the cap is blocked such that the ID is smaller than the rest of the part, this ensures a tight fit around the barbed tubing connection (Figure 1E). The barbed tubing connection is a barbed cone-shape such that the barbing fits through the opening of the cap, but the rest of the part does not, allowing the tubing connection to securely fit in the cap. Thus, the cap fits tightly around both the barbed tubing connection and the lung model (Figure 1F,G).</li>
		<li>Modify the inlet of the lung model depending on the desired experimental conditions. The throat and glottal regions can be included to mimic a patient that can breathe on their own (Figure 1B). Regions above the trachea can be removed using an extruded cut to mimic an intubated patient on ventilator support (Features | Extruded Cut) (Figure 1C).</li>
	</ol>
	</li>
	<li>Orient and support experimental components in slicing software provided by the 3D printer manufacturer.
	<ol>
		<li>Import 3D part files into 3D printer slicing software and choose the appropriate resin. Use a hard resin to print the lung models and barbed tubing connections, and a soft resin to print the caps. 
		NOTE: The resin used for printing the caps must have elastic properties to allow it to stretch over the lobe outlet and create an airtight seal.</li>
		<li>Set the part orientation such that any &#8220;islands&#8221; and unvented volumes are minimized. The best orientation for the lung models is with the lobe outlets facing away from the print platform. Ensure both the barbed tubing connections and the caps have the wider portions facing the print platform. 
		NOTE: Individual slices can be viewed to check for the appearance of &#8220;islands,&#8221; sections of the part that first appear in a slice without being connected to the main body of the part. The review function can be used to check for slices with unvented volumes, areas where uncured resin can get trapped inside the part during printing. Both &#8220;islands&#8221; and unvented volumes decrease print quality and could lead to print failure.</li>
		<li>Viewing each slice individually, add supports to any remaining &#8220;islands&#8221; in the part as well as any areas with significant overhangs. Export and view the slices for the print to verify all areas are properly supported.</li>
	</ol>
	</li>
	<li>Print experimental components and complete post-processing as per manufacturer instructions. 
	NOTE: All post-processing steps described below are specific to the 3D printer listed in the Table of Materials. When utilizing alternate printers or materials, adjust these steps to reflect manufacturer instructions.
	<ol>
		<li>For parts printed in soft resin, wash with &#8805;99% purity isopropyl alcohol (IPA) to remove excess uncured resin and thermal cure in a convection oven for 8 h according to manufacturer specifications. 
		NOTE: Parts printed in soft resin can be very delicate immediately after printing, so special care should be taken during cleaning steps. Exposure to IPA should be kept below the material&#8217;s solvent exposure limit to prevent part degradation.</li>
		<li>For parts printed in hard resin, wash with IPA to remove excess uncured resin and cure in a UV oven (365 nm light at 5-10 mW/cm2) for 1 min per side. 
		NOTE: To evaluate the accuracy of the 3D printed replica, it is recommended to use &#956;CT scanning of the printed part and CT scan software to compare, quantitatively, variations between the original 3D rendering and the 3D printed replica.</li>
	</ol>
	</li>
</ol>
2. Assembly of tubing system for flow rate control
<ol>
	<li>Screw 1/4&#8221; barbed tube fittings into the side of the manifold with 6 ports (Figure 2A-6) and a 3/8&#8221; barbed tube fitting into the remaining port.</li>
	<li>Cut 1/4&#34; tubing to desired lengths and insert into each end of the push-to-connect valves (Figure 2A-5). Attach each valve to one of the 1/4&#34; fittings inserted in the manifold.</li>
	<li>Connect a flow meter (Figure 2A-4) to the other end of each valve.</li>
	<li>Position the tubing system on top of the wooden board such that the manifold&#8217;s single 3/8&#8221; fitting extends past the edge of the board. To secure in place, add two screws to the side of the wooden board and attach the manifold to the screws using wire.</li>
	<li>Add four screws positioned around each of the valves and flow meters and use wire to secure each of them to the wooden board (Figure 2E).</li>
	<li>With approximately 6&#8221; of 3/8&#8221; ID tubing, connect the manifold to an in-line 0.1 &#181;m pore size vacuum grade filter. Connect the other end of the filter to the flow controller using another 6&#8221; of 3/8&#8221; ID tubing 
	NOTE: The tubing system only needs to be assembled once.</li>
</ol>
3. Assembly of lobe outlet caps with patient lung model
NOTE: This portion of the protocol must be completed prior to every experimental run.
<ol>
	<li>Insert barbed tubing connection into the cap with nozzle protruding through the opening in the cap base. First, insert one end of the oval barbed tubing connection base into the cap. Then, carefully stretch the flexible cap over the other end of the oval base, taking special care not to crack the thin base. 
	NOTE: Newly printed caps may be stiffer than desired and can be stretched out by running two fingers along the cap interior.</li>
	<li>Cut 10 &#956;m filter paper such that it is slightly larger than the outlet area. Fold the filter paper over the lobe outlet and hold in place with one hand.</li>
	<li>With the other hand, use tweezers to stretch the cap with barbed tubing connection over the outlet. Press the cap down until the cap&#8217;s notch matches up with the corresponding notch on the lobe outlet (Figure 2C). 
	NOTE: Ripping the filter paper in this step can invalidate results, so special care should be taken to avoid excessive force when pressing the cap onto the outlet.</li>
	<li>Repeat for all remaining lobe outlets (Figure 2D).</li>
</ol>
4. Generation of clinically relevant air flow profile
NOTE: This portion of the protocol must be completed prior to every experimental run.
<ol>
	<li>Connect each lung model lobe outlet to the tubing of the corresponding flow meter and valve, taking care not to apply too much lateral pressure to the barbed tubing connection. Attach the electronic flow meter to the lung model mouth inlet to measure total air flow rate to the lung model.</li>
	<li>Turn on the flow controller (Figure 2A-7) and vacuum pump (Figure 2A-8). Select the &#8220;test setup&#8221; setting on the flow controller and slowly increase the flow rate until the electronic flow meter displays the desired total flow rate.</li>
	<li>Using the valves (Figure 2E-5), adjust the flow rate through each of the five lung lobes: Right Upper (RU), Right Middle (RM), Right Lower (RL), Left Upper (LU), and Left Lower (LL). Once the lobe flow rates shown on the flow meters (Figure 2E-4) are steady at the desired value, check the overall flow rate again on the electronic flow meter to verify that there are no leaks in the system.
	<ol>
		<li>If there is a discrepancy in the total flow rate, lower the flow rate with the flow controller, set all valves to the fully open configuration, and repeat steps 4.2 and 4.3. 
		NOTE: Results presented here were obtained using air flow profiles based on data reported by Sul et al.10 These lobar flow fractions were calculated using thin-slice computed tomography images of patient lungs at full inspiration and expiration, comparing the relative changes in the volume of each lung lobe. Results are presented for two distinct flow conditions, both at an overall inlet flow rate of 1 L/min. The healthy lung lobe outlet flow profile is distributed to each outlet by the following percentage of the inlet flow: LL-23.7%, LU-23.7%, RL-18.7%, RM-14.0%, RU-20.3%. The COPD lobe outlet flow profile is distributed between each outlet by the following percentage of the inlet flow: LL-10.0%, LU-29.0%, RL-13.0%, RM-5.0%, RU-43.0%9,10.</li>
	</ol>
	</li>
	<li>Exit the &#8220;test setup&#8221; function of the flow controller but leave the vacuum pump on. 
	NOTE: Turning the vacuum pump off in between setting the flow rates and performing the deposition experiment can lead to inaccuracies in the flow profile generated. It is recommended to leave the vacuum pump on once desired flow rates are set to complete the aerosol deposition testing.</li>
</ol>
5. Delivery of aerosol to the lung model
NOTE: Experiments must be performed in a fume hood with the sash closed to minimize exposure to any aerosols generated by the nebulizer.
<ol>
	<li>Fill nebulizer with solution of desired fluorescent particles (Figure 2A-1) and connect to the lung model inlet (Figure 2B). 
	NOTE: Results presented here were obtained using 30 mL of a 1:100 dilution of 1 &#956;m fluorescent polystyrene particles in methanol.
	<ol>
		<li>To validate the experimental setup, connect the nebulizer directly to the lung model inlet without any targeting device.</li>
		<li>To measure the efficacy of a targeting device, connect the nebulizer to the device and insert the device into the lung model.</li>
	</ol>
	</li>
	<li>Connect the compressed air line to the nebulizer and close the fume hood sash as much as possible.</li>
	<li>Set the flow controller to run for one 10 s trial. Before pressing start, open the compressed air valve slightly to begin generating an aerosol within the nebulizer.</li>
	<li>Press start on the flow controller and immediately open the compressed air valve fully. Once the flow controller reaches about 9 s, begin to close the compressed air valve.</li>
	<li>Once the compressed air valve is fully closed, disconnect the nebulizer from the compressed air line, fully close the fume hood sash, shut off the vacuum pump, and let any aerosols clear from the fume hood for about 10 min. 
	NOTE: It is important to shut the vacuum pump off after completing a run to prevent a vacuum from building up within the tubing system.</li>
	<li>After waiting for a sufficient amount of time, disconnect the lung model from the tubing system, taking special care not to crack the barbed tubing connections.</li>
	<li>Remove the lobe outlet caps by running a pair of tweezers under the edge of the cap and gently lifting it off the lung model.</li>
	<li>Remove the filter paper from the cap and place it into a 24 well plate with the side onto which particles deposited being on the bottom facing the well of the plate. Repeat for the remaining outlets and label the well corresponding to each lobe. 
	NOTE: To prevent any residual particle deposition from impacting subsequent experiments, it is important to rinse both the lung model and cap components with IPA or appropriate solvent in between runs. This can be collected and included in the analysis as desired. Additionally, a log is kept to ensure all replicas used have been minimally exposed to IPA to maintain part integrity,&#160;and visual part inspection is recommended prior to use.</li>
</ol>
6. Outlet filter paper imaging
<ol>
	<li>Place the well plate into the digital fluorescence microscope and set the microscope to 4x magnification and the appropriate fluorescence channel.</li>
	<li>Visually identify which lobe&#8217;s filter paper has the highest amount of particle deposition and use the &#8220;Auto Expose&#8221; function. Take note of the resulting exposure and integration time values.</li>
	<li>Apply this exposure to all the filters for the run and assess whether the setting produces a satisfactory image for all high deposition areas of the filters. 
	NOTE: Focus settings can be changed from filter to filter; however, all the filters for a given run must be analyzed at the same exposure settings. It is only possible to have one frame of focus at a time, so bends or tears in the filter paper may prevent all the deposited particles in the view from being in focus. This can be avoided by ensuring the filter paper is flat against the bottom of the well plate.</li>
	<li>Take at least three images of each lobe&#8217;s filter paper at random locations and save as .tiff files.</li>
</ol>
7. Quantification of particle deposition
<ol>
	<li>Import all the filter paper pictures for a given run into an ImageJ session.</li>
	<li>Change each image&#8217;s type to 8-bit by selecting Image | Type | 8-bit.</li>
	<li>Open the picture with the highest fluorescence and select Image | Adjust | Threshold to open a threshold window. Adjust the threshold values to minimize background signal from the filter paper and clearly define the edges of particles. See Figure 3 for depictions of good-quality and poor-quality thresholding. 
	NOTE: For filters with high levels of deposition, a &#8220;corona&#8221; of fluorescence, caused by the diffraction of light by the filter paper fibers, may be observed around large groupings of particles. When thresholding these images, a range that is too large displays small dots or &#8220;feather-like&#8221; shapes around these groupings, as observed in the &#8220;poor&#8221; threshold images in Figure 3. This can be improved by gradually increasing the lower limit of the threshold until the signal from the filter paper fibers is minimized without obscuring the signal from the particles themselves.</li>
	<li>Propagate the threshold settings for the highest fluorescence image to all other images.</li>
	<li>Quantify the number of particles and the total fluorescent area by selecting Analyze | Analyze Particles. 
	NOTE: Data sets are compared using Sidak&#8217;s Multiple Comparisons Test and a two-way ANOVA. Additionally, deposition in just the lobe of interest is compared using a Student T-test assuming equal variance.</li>
</ol>

<ol>
	<li>Goel, A., Baboota, S., Sahni, J. K., Ali, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exploring+targeted+pulmonary+delivery+for+treatment+of+lung+cancer.">Exploring targeted pulmonary delivery for treatment of lung cancer.</a> International Journal of Pharmaceutical Investigation. 3 (1), 8-14 (2013).</li><li>Kleinstreuer, C., Zhang, Z., Li, Z., Roberts, W. L., Rojas, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+new+methodology+for+targeting+drug-aerosols+in+the+human+respiratory+system.">A new methodology for targeting drug-aerosols in the human respiratory system.</a> International Journal of Heat and Mass Transfer. 51 (23), 5578-5589 (2008).</li><li>Feng, Y., Chen, X., Yang, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+In+Silico+Investigation+of+a+Lobe-Specific+Targeted+Pulmonary+Drug+Delivery+Method.">An In Silico Investigation of a Lobe-Specific Targeted Pulmonary Drug Delivery Method.</a> Design of Medical Devices Conference. , (2018).</li><li>Marple, V. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Next+generation+pharmaceutical+impactor+(a+new+impactor+for+pharmaceutical+inhaler+testing).+Part+I:+Design.">Next generation pharmaceutical impactor (a new impactor for pharmaceutical inhaler testing). Part I: Design.</a> Journal of Aerosol Medicine. 16 (3), 283-299 (2003).</li><li>Feng, Y., Zhao, J., Chen, X., Lin, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+In+Silico+Subject-Variability+Study+of+Upper+Airway+Morphological+Influence+on+the+Airflow+Regime+in+a+Tracheobronchial+Tree.">An In Silico Subject-Variability Study of Upper Airway Morphological Influence on the Airflow Regime in a Tracheobronchial Tree.</a> Bioengineering. 4 (4), 90 (2017).</li><li>Huynh, B. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Development+and+Validation+of+an+In+Vitro+Airway+Model+to+Assess+Realistic+Airway+Deposition+and+Drug+Permeation+Behavior+of+Orally+Inhaled+Products+Across+Synthetic+Membranes.">The Development and Validation of an In Vitro Airway Model to Assess Realistic Airway Deposition and Drug Permeation Behavior of Orally Inhaled Products Across Synthetic Membranes.</a> Journal of Aerosol Medicine and Pulmonary Drug Delivery. 31 (2), 103-108 (2018).</li><li>Lizal, F., Elcner, J., Hopke, P. K., Jedelsky, J., Jicha, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+a+realistic+human+airway+model.">Development of a realistic human airway model.</a> Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine. 226 (3), 197-207 (2011).</li><li>Wei, X., Hindle, M., Delvadia, R. R., Byron, P. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+Vitro+Tests+for+Aerosol+Deposition.+V:+Using+Realistic+Testing+to+Estimate+Variations+in+Aerosol+Properties+at+the+Trachea.">In Vitro Tests for Aerosol Deposition. V: Using Realistic Testing to Estimate Variations in Aerosol Properties at the Trachea.</a> Journal of Aerosol Medicine and Pulmonary Drug Delivery. 30 (5), 339-348 (2017).</li><li>Kolewe, E. L., Feng, Y., Fromen, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Realizing+Lobe-Specific+Aerosol+Targeting+in+a+3D-Printed+In+Vitro+Lung+Model.">Realizing Lobe-Specific Aerosol Targeting in a 3D-Printed In Vitro Lung Model.</a> Journal of Aerosol Medicine and Pulmonary Drug Delivery. , (2020).</li><li>Sul, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assessing+Airflow+Sensitivity+to+Healthy+and+Diseased+Lung+Conditions+in+a+Computational+Fluid+Dynamics+Model+Validated+In+Vitro.">Assessing Airflow Sensitivity to Healthy and Diseased Lung Conditions in a Computational Fluid Dynamics Model Validated In Vitro.</a> Journal of Biomechanical Engineering. 140 (5), (2018).</li><li>Martonen, T. B., Katz, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deposition+Patterns+of+Polydisperse+Aerosols+Within+Human+Lungs.">Deposition Patterns of Polydisperse Aerosols Within Human Lungs.</a> Journal of Aerosol Medicine. 6 (4), 251-274 (1993).</li><li>Nahar, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vitro,+in+vivo+and+ex+vivo+models+for+studying+particle+deposition+and+drug+absorption+of+inhaled+pharmaceuticals.">In vitro, in vivo and ex vivo models for studying particle deposition and drug absorption of inhaled pharmaceuticals.</a> European Journal of Pharmaceutical Sciences. 49 (5), 805-818 (2013).</li><li>Nichols, S. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Multi-laboratory+in+Vitro+Study+to+Compare+Data+from+Abbreviated+and+Pharmacopeial+Impactor+Measurements+for+Orally+Inhaled+Products:+a+Report+of+the+European+Aerosol+Group+(EPAG).">A Multi-laboratory in Vitro Study to Compare Data from Abbreviated and Pharmacopeial Impactor Measurements for Orally Inhaled Products: a Report of the European Aerosol Group (EPAG).</a> AAPS PharmSciTech. 17 (6), 1383-1392 (2016).</li><li>Yoshida, H., Kuwana, A., Shibata, H., Izutsu, K. I., Goda, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+Aerodynamic+Particle+Size+Distribution+Between+a+Next+Generation+Impactor+and+a+Cascade+Impactor+at+a+Range+of+Flow+Rates.">Comparison of Aerodynamic Particle Size Distribution Between a Next Generation Impactor and a Cascade Impactor at a Range of Flow Rates.</a> AAPS PharmSciTech. 18 (3), 646-653 (2017).</li><li>Feng, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+in+silico+inter-subject+variability+study+of+extra-thoracic+morphology+effects+on+inhaled+particle+transport+and+deposition.">An in silico inter-subject variability study of extra-thoracic morphology effects on inhaled particle transport and deposition.</a> Journal of Aerosol Science. 123, 185-207 (2018).</li><li>Kleinstreuer, C., Seelecke, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inhaler+system+for+targeted+maximum+drug-aerosol+delivery.">Inhaler system for targeted maximum drug-aerosol delivery.</a> United States patent. , (2005).</li><li>. How Medical 3D Printing is Gaining Ground in Top Hospitals Available from: <a target="_blank" href="https://www.materialise.com/en/blog/3d-printing-hospitals">https://www.materialise.com/en/blog/3d-printing-hospitals</a> (2019)</li><li>Weber, P. W., Price, O. T., McClellan, G. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Demographic+Variability+of+Inhalation+Mechanics:+A+Review.">Demographic Variability of Inhalation Mechanics: A Review.</a> Defense Threat Reduction Agency. , (2016).</li><li>Jiang, Y. Y., Xu, X., Su, H. L., Liu, D. X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gender-related+difference+in+the+upper+airway+dimensions+and+hyoid+bone+position+in+Chinese+Han+children+and+adolescents+aged+6-18+years+using+cone+beam+computed+tomography.">Gender-related difference in the upper airway dimensions and hyoid bone position in Chinese Han children and adolescents aged 6-18 years using cone beam computed tomography.</a> Acta Odontologica Scandinavica. 73 (5), 391-400 (2015).</li><li>Martin, S. E., Mathur, R., Marshall, I., Douglas, N. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effect+of+age,+sex,+obesity+and+posture+on+upper+airway+size.">The effect of age, sex, obesity and posture on upper airway size.</a> European Respiratory Journal. 10 (9), 2087 (1997).</li><li>Xi, J., Longest, P. W., Martonen, T. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+the+laryngeal+jet+on+nano-+and+microparticle+transport+and+deposition+in+an+approximate+model+of+the+upper+tracheobronchial+airways.">Effects of the laryngeal jet on nano- and microparticle transport and deposition in an approximate model of the upper tracheobronchial airways.</a> Journal of Applied Physiology. 104 (6), 1761-1777 (2008).</li><li>Zhao, J., Feng, Y., Fromen, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Glottis+motion+effects+on+the+particle+transport+and+deposition+in+a+subject-specific+mouth-to-trachea+model:+A+CFPD+study.">Glottis motion effects on the particle transport and deposition in a subject-specific mouth-to-trachea model: A CFPD study.</a> Computers in Biology and Medicine. 116, 103532 (2020).</li><li>Kim, S. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chronic+obstructive+pulmonary+disease:+lobe-based+visual+assessment+of+volumetric+CT+by+Using+standard+images--comparison+with+quantitative+CT+and+pulmonary+function+test+in+the+COPDGene+study.">Chronic obstructive pulmonary disease: lobe-based visual assessment of volumetric CT by Using standard images--comparison with quantitative CT and pulmonary function test in the COPDGene study.</a> Radiology. 266 (2), 626-635 (2013).</li><li>. The Cancer Imaging Archive Available from: <a target="_blank" href="https://www.cancerimagingarchive.net/">https://www.cancerimagingarchive.net/</a> (2020)</li><li>Li, A., Ahmadi, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computer+Simulation+of+Deposition+of+Aerosols+in+a+Turbulent+Channel+Flow+with+Rough+Walls.">Computer Simulation of Deposition of Aerosols in a Turbulent Channel Flow with Rough Walls.</a> Aerosol Science and Technology. 18 (1), 11-24 (1993).</li><li>Khalili, S. F., Ghanbarzadeh, S., Nokhodchi, A., Hamishehkar, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effect+of+different+coating+materials+on+the+prevention+of+powder+bounce+in+the+next+generation+impactor.">The effect of different coating materials on the prevention of powder bounce in the next generation impactor.</a> Research in Pharmaceutical Sciences. 13 (3), 283-287 (2018).</li><li>Galliger, Z., Vogt, C. D., Panoskaltsis-Mortari, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3D+bioprinting+for+lungs+and+hollow+organs.">3D bioprinting for lungs and hollow organs.</a> Translational Research. 211, 19-34 (2019).</li><li>Schwarz, K., Biller, H., Windt, H., Koch, W., Hohlfeld, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+exhaled+particles+from+the+healthy+human+lung--a+systematic+analysis+in+relation+to+pulmonary+function+variables.">Characterization of exhaled particles from the healthy human lung--a systematic analysis in relation to pulmonary function variables.</a> Journal of Aerosol Medicine and Pulmonary Drug Delivery. 23 (6), 371-379 (2010).</li><li>Patton, J. S., Byron, P. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inhaling+medicines:+delivering+drugs+to+the+body+through+the+lungs.">Inhaling medicines: delivering drugs to the body through the lungs.</a> Nature Reviews Drug Discovery. 6 (1), 67-74 (2007).</li><li>Zhang, Z., Kleinstreuer, C., Kim, C. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cyclic+micron-size+particle+inhalation+and+deposition+in+a+triple+bifurcation+lung+airway+model.">Cyclic micron-size particle inhalation and deposition in a triple bifurcation lung airway model.</a> Journal of Aerosol Science. 33 (2), 257-281 (2002).</li><li>Ju, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Engineering+of+Nebulized+Metal-Phenolic+Capsules+for+Controlled+Pulmonary+Deposition.">Engineering of Nebulized Metal-Phenolic Capsules for Controlled Pulmonary Deposition.</a> Advanced Science. 7 (6), 1902650 (2020).</li></ol>

The authors have nothing to disclose.

The current state-of-the-art device for pulmonary pharmaceutical testing of a complete inhalation dose is the Next Generator Impactor (NGI), which measures the aerodynamic diameter of an aerosol4. This sizing data is then used to predict the lung generation at which the aerosol will deposit based on a correlation developed for a healthy adult male11. Unfortunately, this method is limited in its ability to assess differences in regional lung deposition, determine the effects...

Many pulmonary diseases such as lung cancer and chronic obstructive pulmonary disease (COPD) exhibit regional differences in disease characteristics; however, there are a lack of therapeutic techniques available to target drug delivery to only diseased regions of the lung1. Multiple computational fluid dynamic (CFD) models have demonstrated that it is possible to modulate drug deposition profiles by identifying specific streamlines in the lung2,3. Development of both inhalers and endotracheal (ET) tube adaptors with regional targeting capabilities are on-going in our lab to control aerosol distribution to diseased lung regions. Extension of these principles to clinical use is limited by current preclinical testing capacity. The precise location a drug deposits within the lung is known to be the best predictor of efficacy; however, current pharmaceutical assessments of inhalable therapeutics are most often predicted using in vitro-in vivo correlations of particle size to merely approximate deposition4. This technique does not allow for any spatial analysis to determine the effects of different airway geometries on regional distribution through the various lobes of the lung. Additionally, this testing lacks anatomically accurate lung geometries, which researchers have shown can have a significant impact on deposition profiles5. Some efforts have been made to incorporate patient-specific lung geometries into testing protocols through the addition of the upper airways; however, most of these approaches sample aerosol delivery to various generations of the lung rather than each lung lobe6,7,8. The following protocol presents a high-throughput method of generating patient-specific lung models with the capacity to quantify relative particle deposition in each of the five lobes of the lung9.
Anatomically accurate model lungs are generated by 3D printing patient computed tomography (CT) scans. When used in conjunction with an easily assembled flow system, the relative flow rates through each of the model lung&#8217;s lobes can be independently controlled and tailored to mimic those of different patient demographics and/or disease states. With this method, researchers can test the efficacy of potential therapeutic methods in a relevant lung geometry and correlate each method&#8217;s performance with the progression of diseased morphology. Here, two device designs developed in our lab are tested for their ability to increase deposition in a desired lung lobe by controlling the location of aerosol release in the mouth or trachea. This protocol also has the potential to significantly impact the development of personalized procedures for patients by facilitating the rapid prediction of treatment efficacy in a model lung specific to that patient&#8217;s CT scan data.

<table><tbody><tr><td>1/4&quot; Plastic Barbed Tube Fitting</td><td>McMaster Carr</td><td>5372K111</td><td></td></tr><tr><td>10 um Filter Paper</td><td>Fisher</td><td>1093-110</td><td></td></tr><tr><td>1um Fluorescent Polystyrene Particles</td><td>Polysciences</td><td>15702-10</td><td></td></tr><tr><td>1um Non-Fluorescent Polystyrene Particles</td><td>Polysciences</td><td>8226</td><td></td></tr><tr><td>2-Propanol</td><td>Fisher</td><td>A516-4</td><td>Referred to in protocol as &quot;IPA&quot;</td></tr><tr><td>3/8&quot; Plastic Barbed Tube Fitting</td><td>McMaster Carr</td><td>5372K117</td><td></td></tr><tr><td>Air Flow Meter (1 - 280 mL/min)</td><td>McMaster Carr</td><td>41695K32</td><td>Referred to in protocol as &quot;flow meter&quot;</td></tr><tr><td>Carbon M1 3D Printer</td><td>Carbon 3D</td><td></td><td>https://www.carbon3d.com/, Associated software referred to in protocol as &quot;slicing software&quot;</td></tr><tr><td>Collison Jet Nebulizer</td><td>CH Technologies</td><td>ARGCNB0008 (CN-25)</td><td>6 Jet MRE style horizontal collision with glass jar, Referred to in protocol as &quot;nebulizer&quot;, http://chtechusa.com/Manuals/MRE_Collison_Manual.pdf</td></tr><tr><td>Convection Oven</td><td>Yamato</td><td>DKN602</td><td></td></tr><tr><td>Copley Critical Flow Controller TPK2000 Reve 120V</td><td>MSP Corp</td><td>0001-01-9810</td><td>Referred to in protocol as &quot;flow controller&quot;</td></tr><tr><td>Copley High Capacity Pump Model HCP5</td><td>MSP Corp</td><td>0001-01-9982</td><td>Referred to in protocol as &quot;vacuum pump&quot;</td></tr><tr><td>Cytation</td><td>BioTek</td><td>CYT5MPV</td><td>Multifunctional Spectrophotometer/Fluorescent imager equiped with 4x/20x/40x objectives and DAPI/GFP/TexasRed laser/filter cubes</td></tr><tr><td>EPU40 Resin</td><td>Carbon 3D</td><td></td><td>https://www.carbon3d.com/materials/epu-elastomeric-polyurethane/, Referred to in protocol as &quot;soft resin&quot;</td></tr><tr><td>Filter for vacuum pump</td><td>Whatman</td><td>6722-5000</td><td></td></tr><tr><td>Flow Meter Model DFM 2000</td><td>MSP Corp</td><td>0001-01-8764</td><td>Referred to in protocol as &quot;electronic flow meter&quot;</td></tr><tr><td>ImageJ Software</td><td>ImageJ</td><td></td><td>https://imagej.nih.gov/ij/download.html</td></tr><tr><td>Inline Air Flow Control Valve (Push-to-Connect)</td><td>McMaster Carr</td><td>62005K333</td><td>Referred to in protocol as &quot;valve&quot;</td></tr><tr><td>Inline Filter Devices</td><td>Whatman</td><td>WHA67225000</td><td></td></tr><tr><td>Marine-Grade Plywood Sheet</td><td>McMaster Carr</td><td>62005K333</td><td>Referred to in protocol as &quot;wooden board&quot;</td></tr><tr><td>Materialise Mimics Software</td><td>Materialise</td><td></td><td>https://www.materialise.com/en/medical/mimics-innovation-suite, Referred to in protocol as &quot;CT scan software&quot;</td></tr><tr><td>Meshmixer Software</td><td>Autodesk</td><td></td><td>http://www.meshmixer.com/, Referred to in protocol as &quot;mesh editing software&quot;</td></tr><tr><td>Methanol</td><td>Fisher</td><td>A454-4</td><td></td></tr><tr><td>Opticure LED Cube</td><td>APM Technica</td><td>102843</td><td>Referred to in protocol as &quot;UV oven&quot;</td></tr><tr><td>PR25 Resin</td><td>Carbon 3D</td><td></td><td>https://www.carbon3d.com/materials/uma-urethanemethacrylate, /Referred to in protocol as &quot;hard resin&quot;</td></tr><tr><td>PVC Tube for Chemicals</td><td>McMaster Carr</td><td>5231K161</td><td>1/4&quot; ID</td></tr><tr><td>Screws</td><td></td><td></td><td></td></tr><tr><td>SolidWorks Software</td><td>Dassault Syst&amp;egrave;mes&amp;nbsp;SolidWorks Corporation</td><td></td><td>https://www.solidworks.com/, Referred to in protocol as &quot;3D modeling software&quot;</td></tr><tr><td>Straight Flow Rectangular Manifold</td><td>McMaster Carr</td><td>1125T31</td><td></td></tr><tr><td>Tubing to Flow Controller</td><td>McMaster Carr</td><td>5233K65</td><td>3/8&quot; ID</td></tr><tr><td>Wire</td><td></td><td></td><td></td></tr></tbody></table>

evaluating regional pulmonary deposition using patient-specific 3d printed lung models

Development of targeted therapies for pulmonary diseases is limited by the availability of preclinical testing methods with the ability to predict regional aerosol delivery. Leveraging 3D printing to generate patient-specific lung models, we outline the design of a high-throughput, in vitro experimental setup for quantifying lobular pulmonary deposition. This system is made with a combination of commercially available and 3D printed components and allows the flow rate through each lobe of the lung to be independently controlled. Delivery of fluorescent aerosols to each lobe is measured using fluorescence microscopy. This protocol has the potential to promote the growth of personalized medicine for respiratory diseases through its ability to model a wide range of patient demographics and disease states. Both the geometry of the 3D printed lung model and the air flow profile setting can be easily modulated to reflect clinical data for patients with varying age, race, and gender. Clinically relevant drug delivery devices, such as the endotracheal tube shown here, can be incorporated into the testing setup to more accurately predict a device&#8217;s capacity to target therapeutic delivery to a diseased region of the lung. The versatility of this experimental setup allows it to be customized to reflect a multitude of inhalation conditions, enhancing the rigor of preclinical therapeutic testing.

Particles in this size range (1-5 &#956;m) and flow conditions (1-10 L/min) follow the fluid stream lines based on both their theoretical Stokes number and in vivo data; therefore, in the absence of a targeted delivery device, particles released into the lung model are expected to deposit according to the percentage of total airflow diverted to each lobe. The relative amounts of particle delivery to each lobe can then be compared to clinical lobe flow rate data obtained through analyzing patient-specific high-resolution ...

Watch this Scientific Journal Video about Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models at JoVE.com

Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models

We present a high-throughput, in vitro method for quantifying regional pulmonary deposition at the lobe level using CT scan-derived, 3D printed lung models with tunable air flow profiles.

Development of targeted therapies for pulmonary diseases is limited by the availability of preclinical testing methods with the ability to predict ...

evaluating-regional-pulmonary-deposition-using-patient-specific-3d

Research

JoVE Journal

Bioengineering

4.2K Views.  University of Delaware. We present a high-throughput, in vitro method for quantifying regional pulmonary deposition at the lobe level using CT scan-derived, 3D printed lung models with tunable air flow profiles.

Video: Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds

In the present study, we combined an in vitro 3D lung tumor model with an in silico model to optimize predictions of drug response based on a specific mutational background. The model is generated on a decellularized porcine scaffold that reproduces tissue-specific characteristics regarding extracellular matrix composition and architecture including the basement membrane. We standardized a protocol that allows artificial tumor tissue generation within 14 days including three days of drug treatment. Our article provides several detailed descriptions of 3D read-out screening techniques like the determination of the proliferation index Ki67 staining&#39;s, apoptosis from supernatants by M30-ELISA and assessment of epithelial to mesenchymal transition (EMT), which are helpful tools for evaluating the effectiveness of therapeutic compounds. We could show compared to 2D culture a reduction of proliferation in our 3D tumor model that is related to the clinical situation. Despite of this lower proliferation, the model predicted EGFR-targeted drug responses correctly according to the biomarker status as shown by comparison of the lung carcinoma cell lines HCC827 (EGFR -mutated, KRAS wild-type) and A549 (EGFR wild-type, KRAS-mutated) treated with the tyrosine-kinase inhibitor (TKI) gefitinib. To investigate drug responses of more advanced tumor cells, we induced EMT by long-term treatment with TGF-beta-1 as assessed by vimentin/pan-cytokeratin immunofluorescence staining. A flow-bioreactor was employed to adjust culture to physiological conditions, which improved tissue generation. Furthermore, we show the integration of drug responses upon gefitinib treatment or TGF-beta-1 stimulation - apoptosis, proliferation index and EMT - into a Boolean in silico model. Additionally, we explain how drug responses of tumor cells with a specific mutational background and counterstrategies against resistance can be predicted. We are confident that our 3D in vitro approach especially with its in silico expansion provides an additional value for preclinical drug testing in more realistic conditions than in 2D cell culture.

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds

We present a three-dimensional (3D) lung cancer model based on a biological collagen scaffold to study sensitivity towards non-small-cell-lung-cancer-(NSCLC)-targeted therapies. We demonstrate different read-out techniques to determine the proliferation index, apoptosis and epithelial-mesenchymal transition (EMT) status. Collected data are integrated into an in silico model for prediction of drug sensitivity.

In the present study, we combined an in vitro 3D lung tumor model with an in silico model to optimize predictions of drug response based on a specific ...

A 3D Human Lung Tissue Model for Functional Studies on Mycobacterium tuberculosis Infection

Tuberculosis (TB) still holds a major threat to the health of people worldwide, and there is a need for cost-efficient but reliable models to help us understand the disease mechanisms and advance the discoveries of new treatment options. In vitro cell cultures of monolayers or co-cultures lack the three-dimensional (3D) environment and tissue responses. Herein, we describe an innovative in vitro model of a human lung tissue, which holds promise to be an effective tool for studying the complex events that occur during infection with Mycobacterium tuberculosis (M. tuberculosis). The 3D tissue model consists of tissue-specific epithelial cells and fibroblasts, which are cultured in a matrix of collagen on top of a porous membrane. Upon air exposure, the epithelial cells stratify and secrete mucus at the apical side. By introducing human primary macrophages infected with M. tuberculosis to the tissue model, we have shown that immune cells migrate into the infected-tissue and form early stages of TB granuloma. These structures recapitulate the distinct feature of human TB, the granuloma, which is fundamentally different or not commonly observed in widely used experimental animal models. This organotypic culture method enables the 3D visualization and robust quantitative analysis that provides pivotal information on spatial and temporal features of host cell-pathogen interactions. Taken together, the lung tissue model provides a physiologically relevant tissue micro-environment for studies on TB. Thus, the lung tissue model has potential implications for both basic mechanistic and applied studies. Importantly, the model allows addition or manipulation of individual cell types, which thereby widens its use for modelling a variety of infectious diseases that affect the lungs.

A 3D Human Lung Tissue Model for Functional Studies on Mycobacterium tuberculosis Infection

Human tuberculosis infection is a complex process, which is difficult to model in vitro. Here we describe a novel 3D human lung tissue model that recapitulates the dynamics that occur during infection, including the migration of immune cells and early granuloma formation in a physiological environment.

Tuberculosis (TB) still holds a major threat to the health of people worldwide, and there is a need for cost-efficient but reliable models to help us ...

Immunology and Infection

Generation of 3D Whole Lung Organoids from Induced Pluripotent Stem Cells for Modeling Lung Developmental Biology and Disease

Human lung development and disease has been difficult to study due to the lack of biologically relevant in vitro model systems. Human induced pluripotent stem cells (hiPSCs) can be differentiated stepwise into 3D multicellular lung organoids, made of both epithelial and mesenchymal cell populations. We recapitulate embryonic developmental cues by temporally introducing a variety of growth factors and small molecules to efficiently generate definitive endoderm, anterior foregut endoderm, and subsequently lung progenitor cells. These cells are then embedded in growth factor reduced (GFR)-basement membrane matrix medium, allowing them to spontaneously develop into 3D lung organoids in response to external growth factors. These whole lung organoids (WLO) undergo early lung developmental stages including branching morphogenesis and maturation after exposure to dexamethasone, cyclic AMP and isobutylxanthine. WLOs possess airway epithelial cells expressing the markers KRT5 (basal), SCGB3A2 (club) and MUC5AC (goblet) as well as alveolar epithelial cells expressing HOPX (alveolar type I) and SP-C (alveolar type II). Mesenchymal cells are also present, including smooth muscle actin (SMA), and platelet-derived growth factor receptor A (PDGFR&#945;). iPSC derived WLOs can be maintained in 3D culture conditions for many months and can be sorted for surface markers to purify a specific cell population. iPSC derived WLOs can also be utilized to study human lung development, including signaling between the lung epithelium and mesenchyme, to model genetic mutations on human lung cell function and development, and to determine the cytotoxicity of infective agents.

The article describes step wise directed differentiation of induced pluripotent stem cells to three-dimensional whole lung organoids containing both proximal and distal epithelial lung cells along with mesenchyme.

Human lung development and disease has been difficult to study due to the lack of biologically relevant in vitro model systems. Human induced pluripotent ...

Developmental Biology

3D Printing of Preclinical X-ray Computed Tomographic Data Sets

Three-dimensional printing allows for the production of highly detailed objects through a process known as additive manufacturing. Traditional, mold-injection methods to create models or parts have several limitations, the most important of which is a difficulty in making highly complex products in a timely, cost-effective manner.1 However, gradual improvements in three-dimensional printing technology have resulted in both high-end and economy instruments that are now available for the facile production of customized models.2 These printers have the ability to extrude high-resolution objects with enough detail to accurately represent in vivo images generated from a preclinical X-ray CT scanner. With proper data collection, surface rendering, and stereolithographic editing, it is now possible and inexpensive to rapidly produce detailed skeletal and soft tissue structures from X-ray CT data. Even in the early stages of development, the anatomical models produced by three-dimensional printing appeal to both educators and researchers who can utilize the technology to improve visualization proficiency. 3, 4 The real benefits of this method result from the tangible experience a researcher can have with data that cannot be adequately conveyed through a computer screen. The translation of pre-clinical 3D data to a physical object that is an exact copy of the test subject is a powerful tool for visualization and communication, especially for relating imaging research to students, or those in other fields. Here, we provide a detailed method for printing plastic models of bone and organ structures derived from X-ray CT scans utilizing an Albira X-ray CT system in conjunction with PMOD, ImageJ, Meshlab, Netfabb, and ReplicatorG software packages.

Using modern plastic extrusion and printing technologies, it is now possible to quickly and inexpensively produce physical models of X-ray CT data taken in a laboratory. The three -dimensional printing of tomographic data is a powerful visualization, research, and educational tool that may now be accessed by the preclinical imaging community.

Three-dimensional printing allows for the production of highly detailed objects through a process known as additive manufacturing.  Traditional, ...

Biology

Generation of Human 3D Lung Tissue Cultures (3D-LTCs) for Disease Modeling

Translation of novel discoveries to human disease is limited by the availability of human tissue-based models of disease. Precision-cut lung slices (PCLS) used as 3D lung tissue cultures (3D-LTCs) represent an elegant and biologically highly relevant 3D cell culture model, which highly resemble in situ tissue due to their complexity, biomechanics and molecular composition. Tissue slicing is widely applied in various animal models. 3D-LTCs derived from human PCLS can be used to analyze responses to novel drugs, which might further help to better understand the mechanisms and functional effects of drugs in human tissue. The preparation of PCLS from surgically resected lung tissue samples of patients, who experienced lung lobectomy, increases the accessibility of diseased and peritumoral tissue. Here, we describe a detailed protocol for the generation of human PCLS from surgically resected soft-elastic patient lung tissue. Agarose was introduced into the bronchoalveolar space of the resectates, thus preserving lung structure and increasing the tissue&#39;s stiffness, which is crucial for subsequent slicing. 500 &#181;m thick slices were prepared from the tissue block with a vibratome. Biopsy punches taken from PCLS ensure comparable tissue sample sizes and further increase the amount of tissue samples. The generated lung tissue cultures can be applied in a variety of studies in human lung biology, including the pathophysiology and mechanisms of different diseases, such as fibrotic processes at its best at (sub-)cellular levels. The highest benefit of the 3D-LTC ex vivo model is its close representation of the in situ human lung in respect of 3D tissue architecture, cell type diversity and lung anatomy as well as the potential for assessment of tissue from individual patients, which is relevant to further develop novel strategies for precision medicine.

Generation of Human 3D Lung Tissue Cultures 3D-LTCs for Disease Modeling

Here, we present a protocol for the preparation of agarose-filled human precision-cut lung slices from resected patient tissue that are suitable for generating 3D lung tissue cultures to model human lung diseases in biological and biomedical studies.

Translation of novel discoveries to human disease is limited by the availability of human tissue-based models of disease. Precision-cut lung slices (PCLS) ...

Medicine

Development and Evaluation of 3D-Printed Cardiovascular Phantoms for Interventional Planning and Training

Catheter-based interventions are standard treatment options for cardiovascular pathologies. Therefore, patient-specific models could help training physicians&#39; wire-skills as well as improving planning of interventional procedures. The aim of this study was to develop a manufacturing process of patient-specific 3D-printed models for cardiovascular interventions.
To create a 3D-printed elastic phantom, different 3D-printing materials were compared to porcine biological tissues (i.e., aortic tissue) in terms of mechanical characteristics. A fitting material was selected based on comparative tensile tests and specific material thicknesses were defined. Anonymized contrast-enhanced CT-datasets were collected retrospectively. Patient-specific volumetric models were extracted from these datasets and subsequently 3D-printed. A pulsatile flow loop was constructed to simulate the intraluminal blood flow during interventions. Models&#39; suitability for clinical imaging was assessed by x-ray imaging, CT, 4D-MRI and (Doppler) ultrasonography. Contrast medium was used to enhance visibility in x-ray-based imaging. Different catheterization techniques were applied to evaluate the 3D-printed phantoms in physicians&#39; training as well as for pre-interventional therapy planning.
Printed models showed a high printing resolution (~30 &#181;m) and mechanical properties of the chosen material were comparable to physiological biomechanics. Physical and digital models showed high anatomical accuracy when compared to the underlying radiological dataset. Printed models were suitable for ultrasonic imaging as well as standard x-rays. Doppler ultrasonography and 4D-MRI displayed flow patterns and landmark characteristics (i.e., turbulence, wall shear stress) matching native data. In a catheter-based laboratory setting, patient-specific phantoms were easy to catheterize. Therapy planning and training of interventional procedures on challenging anatomies (e.g., congenital heart disease (CHD)) was possible.
Flexible patient-specific cardiovascular phantoms were 3D-printed, and the application of common clinical imaging techniques was possible. This new process is ideal as a training tool for catheter-based (electrophysiological) interventions and can be used in patient-specific therapy planning.

Here we present development of a mock circulation setup for multimodal therapy evaluation, pre-interventional planning, and physician-training on cardiovascular anatomies. With the application of patient-specific tomographic scans, this setup is ideal for therapeutic approaches, training, and education in individualized medicine.

Catheter-based interventions are standard treatment options for cardiovascular pathologies. Therefore, patient-specific models could help training ...

A Personalized 3D-Printed Model for Preoperative Evaluation in Thyroid Surgery

The anatomic structure of the surgical area of thyroid cancer is complex. It is very important to comprehensively and carefully evaluate the tumor location and its relation with the capsule, trachea, esophagus, nerves, and blood vessels before operation. This paper introduces an innovative 3D-printed model establishment method based on computerized tomography (CT) DICOM images. We established a personalized 3D-printed model of the cervical thyroid surgery field for each patient who needed thyroid surgery to help clinicians evaluate the key points and difficulties of the surgery and select the operation methods of key parts as a basis. The results showed that this model is conducive to preoperative discussion and the formulation of operation strategies. In particular, as a result of the clear display of the recurrent laryngeal nerve and parathyroid gland locations in the thyroid operation field, injury to them can be avoided during surgery, the difficulty of thyroid surgery reduced, and the incidence of postoperative hypoparathyroidism and complications related to recurrent laryngeal nerve injury reduced too. Moreover, this 3D-printed model is intuitive and aids communication for the signing of informed consent by patients before surgery.

Here, a new method of establishing a personalized 3D-printed model for preoperative evaluation of thyroid surgery is proposed. It is conducive to preoperative discussion, reducing the difficulty of thyroid surgery.

The anatomic structure of the surgical area of thyroid cancer is complex. It is very important to comprehensively and carefully evaluate the tumor ...

3D Reconstruction for the Diagnosis and Treatment of Pulmonary Nodules

A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

The three-dimensional (3D) reconstruction of pulmonary nodules using medical images has introduced new technical approaches for diagnosing and treating pulmonary nodules, and these approaches are progressively being acknowledged and adopted by physicians and patients. Nonetheless, constructing a relatively universal 3D digital model of pulmonary nodules for diagnosis and treatment is challenging due to device differences, shooting times, and nodule types. The objective of this study is to propose a new 3D digital model of pulmonary nodules that serves as a bridge between physicians and patients and is also a cutting-edge tool for pre-diagnosis and prognostic evaluation. Many AI-driven pulmonary nodule detection and recognition methods employ deep learning techniques to capture the radiological features of pulmonary nodules, and these methods can achieve a good area under-the-curve (AUC) performance. However, false positives and false negatives remain a challenge for radiologists and clinicians. The interpretation and expression of features from the perspective of pulmonary nodule classification and examination are still unsatisfactory. In this study, a method of continuous 3D reconstruction of the whole lung in horizontal and coronal positions is proposed by combining existing medical image processing technologies. Compared with other applicable methods, this method allows users to rapidly locate pulmonary nodules and identify their fundamental properties while also observing pulmonary nodules from multiple perspectives, thereby providing a more effective clinical tool for diagnosing and treating pulmonary nodules.

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules  

The objective of this study is to develop a novel 3D digital model of pulmonary nodules that serves as a communication bridge between physicians and patients and is also a cutting-edge tool for pre-diagnosis and prognostic evaluation.

The three-dimensional (3D) reconstruction of pulmonary nodules using medical images has introduced new technical approaches for diagnosing and treating ...

Enhancing Pulmonary Nodule Diagnosis Using Whole-Lung 3D Reconstruction

Three-Dimensional Reconstruction for the Whole Lung with Early Multiple Pulmonary Nodules

For patients with early multiple pulmonary nodules, it is essential, from a diagnostic perspective, to determine the spatial distribution, size, location, and relationship with surrounding lung tissue of these nodules throughout the entire lung. This is crucial for identifying the primary lesion and developing more scientifically grounded treatment plans for doctors. However, pattern recognition methods based on machine vision are susceptible to false positives and false negatives and, therefore, cannot fully meet clinical demands in this regard. Visualization methods based on maximum intensity projection (MIP) can better illustrate local and individual pulmonary nodules but lack a macroscopic and holistic description of the distribution and spatial features of multiple pulmonary nodules.
Therefore, this study proposes a whole-lung 3D reconstruction method. It extracts the 3D contour of the lung using medical image processing technology against the background of the entire lung and performs 3D reconstruction of the lung, pulmonary artery, and multiple pulmonary nodules in 3D space. This method can comprehensively depict the spatial distribution and radiological features of multiple nodules throughout the entire lung, providing a simple and convenient means of evaluating the diagnosis and prognosis of multiple pulmonary nodules.

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer 

This study introduces a three-dimensional (3D) reconstruction method for the entire lung in patients with early multiple pulmonary nodules. It offers a comprehensive visualization of nodule distribution and their interplay with lung tissue, simplifying the assessment of diagnosis and prognosis for these patients.

For patients with early multiple pulmonary nodules, it is essential, from a diagnostic perspective, to determine the spatial distribution, size, location, ...

Dynamic Lung Ventilation Assessment with 3D Phase Resolved Functional Lung MRI

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Pulmonary magnetic resonance imaging (MRI) offers a variety of radiation-free techniques tailored to assess regional lung ventilation or its surrogates. These techniques encompass direct measurements, exemplified by hyperpolarized gas MRI and fluorinated gas MRI, as well as indirect measurements facilitated by oxygen-enhanced MRI and proton-based Fourier decomposition (FD) MRI. In recent times, there has been substantial progress in the field of FD MRI, which involved improving spatial/temporal resolution, refining sequence design and postprocessing, and developing a comprehensive whole-lung approach.
The two-dimensional (2D) phase-resolved functional lung (PREFUL) MRI stands out as an FD-based approach developed for the comprehensive assessment of regional ventilation and perfusion dynamics, all within a single MR acquisition. Recently, a new advancement has been made with the development of 3D PREFUL to assess dynamic ventilation of the entire lung using 8 min exam with a self-gated sequence.
The 3D PREFUL acquisition involves employing a stack-of-stars spoiled-gradient-echo sequence with a golden angle increment. Following the compressed sensing image reconstruction of approximately 40 breathing phases, all the reconstructed respiratory-resolved images undergo registration onto a fixed breathing phase. Subsequently, the ventilation parameters are extracted from the registered images.
In a study cohort comprising healthy volunteers and patients with chronic obstructive pulmonary disease, the 3D PREFUL ventilation parameters demonstrated strong correlations with measurements obtained from pulmonary function tests. Additionally, the interscan repeatability of the 3D PREFUL technique was deemed to be acceptable, indicating its reliability for repeated assessments of the same individuals.
In summary, 3D PREFUL ventilation MRI provides a whole lung coverage and captures ventilation dynamics with enhanced spatial resolution compared to 2D PREFUL. 3D PREFUL technique offers a cost-effective alternative to hyperpolarized 129Xe MRI, making it an attractive option for patient-friendly evaluation of pulmonary ventilation.

Three-dimensional (3D) phase-resolved functional lung (PREFUL) is a functional magnetic resonance imaging (MRI) technique that allows for quantification of regional ventilation of the whole human lung volume, using tidal breathing and contrast-agent free acquisition for 8 min. Here, we present an MR protocol to collect and analyze 3D PREFUL imaging data.

Pulmonary magnetic resonance imaging (MRI) offers a variety of radiation-free techniques tailored to assess regional lung ventilation or its surrogates. ...

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