This readme.txt file was generated on <20200520> by ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset Supporting data for "3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors" 2. Author Information Principal Investigator Contact Information Name: Michael C. McAlpine Institution: University of Minnesota Address: Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA Email: mcalpine@umn.edu ORCID: 0000-0001-7869-7598 Associate or Co-investigator Contact Information Name: Kaiyan Qiu Institution: University of Minnesota Address: Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA Email: kqiu@umn.edu ORCID: 0000-0002-3138-0275 Associate or Co-investigator Contact Information Name: Robert M. Sweet Institution: University of Washington Address: WWAMI Institute for Simulation in Healthcare, University of Washington, Seattle, WA 98195, USA Email: rsweet@uw.edu 3. Date of data collection Approximate date: 20151005-20171005 4. Geographic location of data collection (where was data collected?): The University of Minnesota 5. Information about funding sources that supported the collection of the data: National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under Award Number 1DP2EB020537 National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number R01HL137204 Army Research Office under Award Number W911NF-15-1-0469 Department of Urology, University of Minnesota Rebecca Q. Morgan Foundation -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: Attribution-NonCommercial 3.0 United States 2. Links to publications that cite or use the data: Qiu et al., Adv. Mater. Technol. 2018, 3, 1700235. DOI: 10.1002/admt.201700235 3. Links to other publicly accessible locations of the data: NA 4. Links/relationships to ancillary data sets: NA 5. Was data derived from another source? No 6. Recommended citation for the data: Qiu et al., (2020). Supporting data for "3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors". Retrieved from the Data Repository for the University of Minnesota, https://doi.org/10.13020/rbvt-5s33. --------------------- DATA & FILE OVERVIEW --------------------- All the .opj files were generated using OriginPro 9.0.0 (64-bit). The .stl file was generated using Vitrea software to process the MRI image pack of a patient organ (prostate). 1. File List A. Filename: Figure 2 data.zip Short description: Raw data files for Figures 2c-i (7 ops files for the corresponding 7 figures) B. Filename: Figure 3 data.zip Short description: Raw data files for Figures 3f,3h,3i (3 opj files for the corresponding 3 figures). C. Filename: Figure 4 data.zip Short description: Raw data files for Figures 4e-j (6 opj files for the corresponding subfigures). D. Filename: Figure S2 data.opj Short description: Raw data files for Figure S2. E. Filename: Figure S4 data.opj Short description: Raw data file for Figure S4b. F. Filename: Figure S10 data.zip Short description: Raw data file for Figures S10a,S10b (2 opj files for the corresponding 2 figures). G. Filename: Prostate geometry from patient MRI.stl Short description: Raw data file for prostate organ geometry for 3D printing of the organ models and other related experiments. 2. Are there multiple versions of the dataset? yes/no No. 3. Descriptions of Figures Figure 2: Design and development of customized polymeric inks based on patient-specific prostate tissue data, and resulting ink fidelity with physical properties of the tissue. c) A plot of prime component weight ratios versus Young's moduli for the polymeric inks. d) Log–log plots of apparent viscosity versus shear rate for a customized polymeric ink (including its constituent components) used for printing the prostate model. e) Static compression fidelity via stress–strain curves between different patient prostate tissue samples (Tissues 1–3) and printed samples of customized polymeric inks (Inks 1–3). f) Dynamic compression fidelity of storage modulus between a patient prostate tissue sample (Tissue 2) and a sample of customized polymeric ink (Ink 2) at frequencies of 0.1–20 Hz and strains of 0.05, 0.10, and 0.20. g) Dynamic compression fidelity of loss modulus between a patient prostate tissue (Tissue 2) and a sample of customized polymeric ink (Ink 2) at frequencies of 0.1–20 Hz and strains of 0.05, 0.10, and 0.20. h) Hardness fidelity via load–depth curves between a patient prostate tissue sample (Tissue 2) and a sample of customized polymeric ink (Ink 2). i) Optical fidelity via reflection curves between patient prostate gross tissue and a customized polymeric ink (Ink 2) Figure 3: 3D printing of prostate model, anatomical fidelity analysis, and organ physical behavior prediction using the 3D printed prostate model. f) Histogram of the calibrated distances of the surface points for comparison of anatomical fidelity between the patient prostate model and 3D printed prostate model. h) Displacement comparison for feature dots between results from compression of the 3D printed prostate model (with standard deviation error bars) and the FEM simulated model. Inset: Displacement of the feature dots on the 3D printed prostate model after compression with the displacement trajectories. i) Reaction force comparison between results from compression of the 3D printed prostate model and the FEM simulated model. Figure 4: Quantitative surgical rehearsal using the 3D printed prostate model. e) Characterization of the response repeatability for the soft tactile sensor via capacitance changes with an applied cyclic pressure of 50 kPa. f) Calibration of the 3D printed sensor based on the correlation between capacitance change and the applied pressure. g) Quantitative surgical rehearsal involving the 3D printed prostate model upon applying a finger, on the sensor integrated on the outer surface of the model and the corresponding pressure responses (indicated at each of the peaks) from the capacitance changes of the sensor. h) Quantitative surgical rehearsal involving the 3D printed prostate model upon applying a surgical grasper, on the sensor integrated on the outer surface of the model and the corresponding pressure responses (indicated at each of the peaks) from the capacitance changes of the sensor. i) Quantitative surgical rehearsal involving the 3D printed prostate model when applying an endoscope, on the sensor integrated on the urethra surface inside of the model, and the corresponding pressure responses (indicated at each of the peaks) from the capacitance changes of the sensor. j) Quantitative surgical rehearsal involving the 3D printed prostate model when applying an surgical scissors, on the sensor integrated on the urethra surface inside of the model, and the corresponding pressure responses (indicated at each of the peaks) from the capacitance changes of the sensor. Figure S2: Comparison of mechanical properties via plots of stress vs strain between commercial polymers, tissue, and the customized polymeric inks Figure S4: Organ physical behavior via compression of 3D printed organ model and FEM simulation of the same. b) Stress-strain curves for patient prostate tissue, custom polymeric ink, and Ogden third order model used for FEM simulation. Figure S10: Two quantitative surgical rehearsal applications using the 3D printed prostate model. a) Quantitative surgical aid application of the 3D printed prostate model for applying surgical scissors on the sensor integrated on the outer surface of the model and the corresponding pressure responses (indicated at each of the peaks) from the capacitance changes of the sensor. b) Quantitative surgical aid application of the 3D printed prostate model for applying a surgical grasper on the sensor integrated on the urethra surface inside of the model, and the corresponding pressure responses (indicated at each of the peaks) from the capacitance changes of the sensor.