Spinal disorders such as back pain incur a substantial societal and economic burden. Unfortunately, there is lack of understanding and treatment of these disorders are further impeded by the inability to assess spinal forces in vivo. The aim of this project is to address this challenge by developing and testing a novel image-driven approach that will assess the forces in an individual's spine in vivo by incorporating information acquired from multimodal imaging (magnetic resonance imaging (MRI) and biplane X-rays) in a subject-specific model. Magnetic resonance and biplane X-ray imaging are used to capture information about the anatomy, tissues, and motion of an individual's spine as they perform a range of everyday activities. This information is then utilised in a subject-specific computational model based on the finite element method to predict the forces in their spine. The project is also utilising novel machine learning algorithms and in vitro, six-axis mechanical testing on human, porcine and bovine samples to develop and test the modelling methods rigorously.Abstract
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Methods
The COVID-19 pandemic necessitated a pivot to online learning for many traditional, hands-on subjects such as anatomy. This, coupled with the increase in online education programmes, and the reduction of time students spend in anatomy dissection rooms, has highlighted a real need for innovative and accessible learning tools. This study describes the development of a novel 3-dimensional (3D), interactive anatomy teaching tool using structured light scanning (SLS) technology. This technique allows the 3D shape and texture of an object to be captured and displayed online, where it can be viewed and manipulated in real-time. Human bones of the upper limb, vertebrae and whole skulls were digitised using SLS using Einscan Pro2X/H scanners. The resulting meshes were then post-processed to add the captured textures and to remove any extraneous information. The final models were uploaded into Sketchfab where they were orientated, lit and annotated. To gather opinion on these models as effective teaching tools, surveys were completed by anatomy students (n=35) and anatomy educators (n=8). Data was collected using a Likert scale response, as well as free text answers to gather qualitative information. 3D scans of the scapula, humerus, radius, ulna, vertebrae and skull were successfully produced by SLS. Interactive models were produced via scan data in Sketchfab and successfully annotated to provide labelled 3D models for examination. 94% of survey respondents agreed that the interactive models were easy to use (n=35, 31% agree and 63% strongly agree) and 97% agreed that the 3D interactive models were more useful than 2D images for learning bony anatomy (n=35; 26% agree and 71% strongly agree). This initial study has demonstrated a suitable proof-of-concept for SLS technology as a useful technique for producing 3D interactive online tools for learning and teaching bony anatomy. Current studies are focussed on determining the SLS accuracy and the ability of SLS to capture soft tissue/joints. We believe that this tool will be a useful technique for generating online 3D interactive models to study orthopaedic anatomy.
