Comparison of 2 open-sourced 3-dimensional modeling techniques for orthopaedic application

Yuan Chai; Robert Simic; Paul N Smith; Krisztina Valter; Ajay Limaye; Rachel W Li

doi:10.1097/OI9.0000000000000213

Comparison of 2 open-sourced 3-dimensional modeling techniques for orthopaedic application

OTA Int. 2022 Sep 21;5(4):e213. doi: 10.1097/OI9.0000000000000213. eCollection 2022 Dec.

Authors

Yuan Chai¹, Robert Simic¹, Paul N Smith², Krisztina Valter³, Ajay Limaye⁴, Rachel W Li⁵

Affiliations

¹ Trauma and Orthopaedic Research Laboratory, Department of Surgery, The Medical School, The Australian National University, Canberra, ACT, Australia.
² Trauma and Orthopaedic Research Unit, Clinical Orthopaedic Surgery, The Canberra Hospital, Garran, ACT, Australia.
³ The Medical School, and John Curtin School of Medical Research, The Australian National University, Canberra, ACT, Australia.
⁴ National Computational Infrastructure, The Australian National University, Canberra, ACT, Australia; and.
⁵ The Medical School, and John Curtin School of Medical Research, The Australian National University, Acton, ACT, Australia.

Abstract

Objectives: Although 3-dimensional (3D) printing is becoming more widely adopted for clinical applications, it is yet to be accepted as part of standard practice. One of the key applications of this technology is orthopaedic surgical planning for urgent trauma cases. Anatomically accurate replicas of patients' fracture models can be produced to guide intervention. These high-quality models facilitate the design and printing of patient-specific implants and surgical devices. Therefore, a fast and accurate workflow will help orthopaedic surgeons to generate high-quality 3D printable models of complex fractures. Currently, there is a lack of access to an uncomplicated and inexpensive workflow. Methods: Using patient DICOM data sets (n = 13), we devised a novel, simple, open-source, and rapid modeling process using Drishti software and compared its efficacy and data storage with the 3D Slicer image computing platform. We imported the computed tomography image directory acquired from patients into the software to isolate the model of bone surface from surrounding soft tissue using the minimum functions. One pelvic fracture case was further integrated into the customized implant design practice to demonstrate the compatibility of the 3D models generated from Drishti. Results: The data sizes of the generated 3D models and the processing files that represent the original DICOM of Drishti are on average 27% and 12% smaller than that of 3D Slicer, respectively (both P < 0.05). The time frame needed to reach the stage of viewing the 3D bone model and the exporting of the data of Drishti is 39% and 38% faster than that of 3D Slicer, respectively (both P < 0.05). We also constructed a virtual model using third-party software to trial the implant design. Conclusions: Drishti is more suitable for urgent trauma cases that require fast and efficient 3D bone reconstruction with less hardware requirement. 3D Slicer performs better at quantitative preoperative planning and multilayer segmentation. Both software platforms are compatible with third-party programs used to produce customized implants that could be useful for surgical training. Level of Evidence: Level V.

Keywords: 3D reconstruction; CT modeling; open-sourced; preoperative planning.