Rapid Production Nasal Osteotomy Simulators With Multi-Modality Manufacturing: 3D Printing, Casting, and Molding

被引:0
|
作者
Tumlin, Parker [1 ]
Sunyecz, Ian [1 ]
Cui, Ruifeng [1 ]
Armeni, Mark [1 ]
Freiser, Monika E. [1 ]
机构
[1] West Virginia Univ, Dept Otolaryngol, One Med Ctr Dr, Morgantown, WV 26508 USA
关键词
3D printing; medical education; osteotomy; rhinoplasty; surgical simulation; FIXATION;
D O I
10.1002/ohn.877
中图分类号
R76 [耳鼻咽喉科学];
学科分类号
100213 ;
摘要
Objective. To expand and improve upon previously described nasal osteotomy models with the goals of decreasing cost and production time while ensuring model fidelity. To assess change in participant confidence in their understanding of and ability to perform nasal osteotomies following completion of the simulation course. Study Design. Prospective study. Setting. Simulation training course for otolaryngology residents at West Virginia University. Methods. A combined methodology of 3D printing, silicone molding, and resin casting was used to design a nasal osteotomy model to address material issues such as print delamination. Multiple models were then used in a simulation lab on performing nasal osteotomies. Model utility and impact on participant confidence was assessed at baseline, postlecture, and postsimulation lab. Results. Using a combined manufacturing methodology, we achieved a production time reduction of 97.71% and a cost reduction of 82.02% for this polyurethane resin nasal osteotomy model relative to a previously described osteotomy model. Participants in the simulation course were noted to have a significant improvement in confidence in their understanding of and ability to perform nasal osteotomies from baseline and postlecture and also from postlecture and postsimulation lab (P < .05 for all). Conclusion. By incorporating multiple manufacturing modalities (molding and casting) in addition to 3D printing, this study achieved a large reduction in both production time and cost in fabrication of a nasal osteotomy simulator and addressed material limitations imposed by fused deposition modeling printers. This design methodology serves as an example on how these barriers may be addressed in unrelated simulation projects. Model fidelity was improved with addition of a silicone soft tissue midface. Improvement in participant confidence was noted following completion of the simulation lab.
引用
收藏
页码:1000 / 1007
页数:8
相关论文
共 50 条
  • [41] Integration of multi-modality imaging for accurate 3D reconstruction of human coronary arteries in vivo
    Giannoglou, George D.
    Chatzizisis, Yiannis S.
    Sianos, George
    Tsikaderis, Dimitrios
    Matakos, Antonis
    Koutkias, Vassilios
    Diamantopoulos, Panagiotis
    Maglaveras, Nicos
    Parcharidis, George E.
    Louridas, George E.
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 2006, 569 (02): : 310 - 313
  • [42] Diagnosis of Alzheimer's Disease via Multi-Modality 3D Convolutional Neural Network
    Huang, Yechong
    Xu, Jiahang
    Zhou, Yuncheng
    Tong, Tong
    Zhuang, Xiahai
    FRONTIERS IN NEUROSCIENCE, 2019, 13
  • [43] Art care: A multi-modality coronary 3D reconstruction and hemodynamic status assessment software
    Siogkas, Panagiotis K.
    Stefanou, Kostas A.
    Athanasiou, Lambros S.
    Papafaklis, Michail I.
    Michalis, Lampros K.
    Fotiadis, Dimitrios I.
    TECHNOLOGY AND HEALTH CARE, 2018, 26 (01) : 187 - 193
  • [44] Multi-modality self-attention aware deep network for 3D biomedical segmentation
    Jia, Xibin
    Liu, Yunfeng
    Yang, Zhenghan
    Yang, Dawei
    BMC MEDICAL INFORMATICS AND DECISION MAKING, 2020, 20 (Suppl 3)
  • [45] 3D voxel fusion of multi-modality medical images in a clinical treatment planning system
    Xie, HC
    Li, G
    Ning, H
    Ménard, C
    Coleman, CN
    Miller, RW
    17TH IEEE SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, PROCEEDINGS, 2004, : 48 - 53
  • [46] The visualization of hepatic and biliary anatomy in a single 3D image using multi-phase and multi-modality 3D rendering (multi-volume rendering)
    Frauenfelder, T.
    Fornaro, J.
    BRITISH JOURNAL OF SURGERY, 2010, 97 : 9 - 9
  • [47] Sustainable Manufacturing through Digital Multi-Material 3D Printing
    Naveed, Nida
    Anwar, Muhammad Naveed
    2024 29TH INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING, ICAC 2024, 2024, : 429 - 433
  • [48] Manufacturing of Microfluidic Sensors Utilizing 3D Printing Technologies: A Production System
    Khorsandi, Danial
    Nodehi, Mehrab
    Waqar, Tayyab
    Shabani, Majid
    Kamare, Behnam
    Zare, Ehsan Nazarzadeh
    Ersoy, Sezgin
    Annabestani, Mohsen
    Çelebi, Mehmet Fatih
    Kafadenk, Abdullah
    Journal of Nanomaterials, 2021, 2021
  • [49] Manufacturing of Microfluidic Sensors Utilizing 3D Printing Technologies: A Production System
    Khorsandi, Danial
    Nodehi, Mehrab
    Waqar, Tayyab
    Shabani, Majid
    Kamare, Behnam
    Zare, Ehsan Nazarzadeh
    Ersoy, Sezgin
    Annabestani, Mohsen
    Celebi, Mehmet Fatih
    Kafadenk, Abdullah
    JOURNAL OF NANOMATERIALS, 2021, 2021
  • [50] Customized production based on distributed 3D printing services in cloud manufacturing
    Jingeng Mai
    Lin Zhang
    Fei Tao
    Lei Ren
    The International Journal of Advanced Manufacturing Technology, 2016, 84 : 71 - 83