Vaibhav Bagaria1, Kshitij Chaudhary2. 1. Sir HN Reliance Foundation Hospital, Mumbai, India. Electronic address: bagariavaibhav@gmail.com. 2. Sir HN Reliance Foundation Hospital, Mumbai, India.
Abstract
INTRODUCTION: Preoperative planning is an important aspect of any orthopedic surgery. Traditionally, surgeons mentally rehearse the operation and anticipate problems based on data available from "radiography" like MRI and CT. 3D printed bio-models and tools, or "3Dgraphy" can simplify this mental exercise and provide a realistic and user-friendly portrayal of this radiographic data. METHODS: Five surgeons participated in this multicenter study. 3D printed biomodels were obtained for 50 surgical cases that included periarticular trauma (24), pelvic trauma (11), complex primary (7), and revision arthroplasty (8). CT scan data was used to generate computer models which were then 3D printed in real size. These models were used to understand pathoanatomy and conduct simulated surgery as a part of preoperative planning. The models were sterilized and were used for intraoperative referencing. Following each case, the operating surgeon was asked to fill out a structured questionnaire to report on the perceived benefits of these tools. RESULTS: All surgeons reported that the biomodels provided additional information to conventional imaging that enhanced their knowledge of the complex pathoanatomy. It was useful in preoperative planning, rehearsing the operation, surgical simulation, intraoperative referencing, surgical navigation, preoperative implant selection, and inventory management. This probably reduced surgical time and improved accuracy of the surgery. All surgeons reported that they would not only use it themselves but also recommend it to other surgeons. CONCLUSION: 3Dgraphy was found to be a valuable tool in orthopedic surgeries that involve complex pathoanatomy like pelvic trauma, revision arthroplasty, and periarticular fracture. As the technology evolves and improves, they are likely to become a standard component of many orthopedic procedures.
INTRODUCTION: Preoperative planning is an important aspect of any orthopedic surgery. Traditionally, surgeons mentally rehearse the operation and anticipate problems based on data available from "radiography" like MRI and CT. 3D printed bio-models and tools, or "3Dgraphy" can simplify this mental exercise and provide a realistic and user-friendly portrayal of this radiographic data. METHODS: Five surgeons participated in this multicenter study. 3D printed biomodels were obtained for 50 surgical cases that included periarticular trauma (24), pelvic trauma (11), complex primary (7), and revision arthroplasty (8). CT scan data was used to generate computer models which were then 3D printed in real size. These models were used to understand pathoanatomy and conduct simulated surgery as a part of preoperative planning. The models were sterilized and were used for intraoperative referencing. Following each case, the operating surgeon was asked to fill out a structured questionnaire to report on the perceived benefits of these tools. RESULTS: All surgeons reported that the biomodels provided additional information to conventional imaging that enhanced their knowledge of the complex pathoanatomy. It was useful in preoperative planning, rehearsing the operation, surgical simulation, intraoperative referencing, surgical navigation, preoperative implant selection, and inventory management. This probably reduced surgical time and improved accuracy of the surgery. All surgeons reported that they would not only use it themselves but also recommend it to other surgeons. CONCLUSION: 3Dgraphy was found to be a valuable tool in orthopedic surgeries that involve complex pathoanatomy like pelvic trauma, revision arthroplasty, and periarticular fracture. As the technology evolves and improves, they are likely to become a standard component of many orthopedic procedures.
Authors: David A Salazar; Justin Cramer; Nicholas W Markin; Nathaniel H Hunt; Gabe Linke; Justin Siebler; Jorge Zuniga Journal: Ann Transl Med Date: 2022-04
Authors: Kai Xiao; Bo Xu; Lin Ding; Weiguang Yu; Lei Bao; Xinchao Zhang; Meiji Chen; Xiangzhen Liu; Huanyi Lin; Tengfei Li Journal: J Int Med Res Date: 2021-06 Impact factor: 1.671