Technical-commercial viability analysis of an augmented reality and additive manufacturing application for surgery training in patient-specific anatomy

• Grant number: 18/25348-3
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Start date: September 01, 2019
• End date: July 31, 2020
• Field of knowledge: Health Sciences - Medicine - Surgery
• Principal Investigator: Carlo Rondinoni
• Grantee: Carlo Rondinoni
• CNAE: Impressão de materiais para outros usos
• Associated researchers: Antonio Adilton Oliveira Carneiro ; Helio Rubens Machado ; Helton Luiz Aparecido Defino ; Oswaldo Baffa Filho ; Renan Hiroshi Matsuda ; Theo Zeferino Pavan
• Associated research grant(s): 20/05306-4 - Development of a platform for specific patient surgery training using augmented reality and additive manufacturing, AP.PIPE
• Associated scholarship(s): 19/20091-7 - Technical and commercial feasibility analysis of augmented reality application and additive manufacturing for patient-specific surgery training, BP.PIPE

Abstract

According to estimates from the Second Yearbook of Hospital Care Security in Brazil in 2017, the mortality associated with the occurrence of any adverse event related to hospital care occurs in approximately 644 patients per day. An alarming estimate to be highlighted is the mortality of approximately 98 patients per day related fatality fraction attributable to a preventable severe event. This scenario makes it urgent to create new forms of specialized and interactive medical training. This proposal aims to combine the use of digital visualization and additive manufacturing (AM) techniques to create a platform for complex surgeries by matching objects representing the human anatomy with interactive digital visualization. In this case, augmented reality (AR) provides the surgeon cues to visualize the internal anatomy while acting externally. On the other hand, the use of additive manufacturing allows the mimicking of individual cases in training, including aspects of a unique anatomy of a given patient to be treated. In this way, complex and emblematic cases can be elected to serve the training of a large number of students. This proposal aims to validate and measure the commercial feasibility of the application of augmented reality and additive manufacture in training in endoscopic surgery of the human spine. To do so, we plan to devise a physical training platform, which will include the automatic recognition of its format for use of augmented reality on mobile devices. The method consists in allying the anatomy of the bones of the vertebral column to the visualization of overlaying three-dimensional model. An opaque casing allows the marking of external topological references while avoiding direct visualization of the internal anatomy. The three-dimensional models of bone anatomy will be generated using 3D Slicer through the threshold segmentation of brightness and generation of STL files. These files will be sent to a 3D printer to produce the objects. The augmented reality system using 3D Unity and Vuforia allows one to view overlapping virtual objects. This system is based on scanning the external surface of the object of interest with the webcam, generating coordinates for its recognition. With the application ready, the webcam recognizes objects that have previously recorded features. The software offers the possibility of making animations and include soundtracks to guide the procedures to be trained. In addition, the AR system has flat markers, which can be fixed in surgical tools, promoting interactivity over virtual and real objects simultaneously. The commercial feasibility will be tested with lean methodology, with consecutive build - measure cycles - learn with minimal effort and the least development time possible. From the first prototype, the product will be tested in the market with its actual use in training, in a complete endoscopic transforaminal discectomy procedure. Annotations from interviews and questionnaires will report the expert impressions about the product. These results will serve to improve the product subsequent versions and to prepare submission to PIPE Phase 2. (AU)