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3D Printing Design for Infants’ Medical Consumables
           Authority Clinical  Medicine  Development  of Special   the Rules: A Novel Approach to Placement and Retrospective
           Funding Support (No. XMLX202145 to Xin Zhao),           Experience with the 5 French Arndt Endobronchial Blocker in
           Capital’s  Funds  for Health Improvement and Research   Children <2 Years. Paediatr Anaesth, 26:512–20.
           (No.2022-2Z-2098 to Xin Zhao), and Beijing Natural      https://doi.org/10.1111/pan.12978
           Science Foundation (No.7222018 to Wenping Ma).
                                                               8.   Abdel-Bary M, Abdel-Naser M, Okasha A, et al., 2020, Clinical
           Conflict of interest                                    and  Surgical  Aspects  of  Congenital  Lobar  Over-inflation:

           There are no conflicts of interest to declare.          A Single Center Retrospective Study. J Cardiothorac, 15:102.
                                                                   https://doi.org/10.1186/s13019-020-01145-8
           Author contributions                                9.   Luscan R, Leboulanger  N, Fayoux P,  et al., 2020,

           X.D. and W.W. are radiologists responsible for gathering   Developmental  Changes of Upper  Airway Dimensions in
           DICOM data  from pediatric  CT scans and  taking        Children. Paediatr Anaesth, 30:435–45.
           measurements under computer software. W.M. and F.X.      https://doi.org/10.1111/pan.13832
           proficiently  explore  3D  bioprinting  technology.  Z.M.   10.  Heydarian M, Noseworthy MD, Kamath MV,  et al., 2014,
           and X.Z. are overall responsible for pediatric anesthesia   A Morphological Algorithm for Measuring Angle of Airway
           management, designed project, and validation.           Branches in Lung CT Images. Crit Rev Biomed Eng, 42:369–81.

           References                                              https://doi.org/10.1615/critrevbiomedeng.2014012135
                                                               11.  Tanabe N, Oguma  T, Sato S,  et al., 2018, Quantitative
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               Stimulation Implants. J Vis Exp, 7:151.             https://doi.org/10.3390/ma14185189
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           4.   Rengier F, Mehndiratta A, von Tengg-Kobligk H, et al., 2010,   Method for Fabricating In Vitro Patient-Specific Vascular Models
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               Applications. Int J Comput Assist Radiol Surg, 5:335–41.     https://doi.org/10.1007/s13239-020-00504-9
               https://doi.org/10.1007/s11548-010-0476-x       15.  Zhang J, Wang T, Li R, et al., 2021, Prediction of Risk Factors
           5.   Yoshida H, Hasegawa  Y, Matsushima M,  et al., 2021,   of Bronchial  Mucus Plugs in Children with  Mycoplasma
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               Dead Space and its Application to Lung Elasticity Evaluation.   16.  Hegde SV, Lensing SY, Greenberg SB, 2015, Determining
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               https://doi.org/10.3390/s21155123                   https://doi.org/10.1148/radiol.14140500
           6.   Yan J, Rufang Z, Rong  W,  et al., 2020, Extraluminal   17.  Moran JL, Solomon PJ, 2007, Statistics  in Review Part  I:
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               J Cardiothorac Vasc Anesth, 34:2435–9.          18.  Tam MD, Laycock SD, Jayne D, et al., 2013, 3-D Printouts
               https://doi.org/10.1053/j.jvca.2020.02.006          of the  Tracheobronchial  Tree Generated from CT Images
           7.   Templeton TW, Downard MG, Simpson CR, et al., 2016, Bending   as an  Aid to Management  in a Case of  Tracheobronchial

           38                          International Journal of Bioprinting (2022)–Volume 8, Issue 3
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