Title: STOpFrac: Software Tool for Opportunistic diagnosis of vertebral Fractures
Funder: Department of Health and Social Care

Abstract: Background The partners have a long history of developing systems for helping clinicians to identify vertebral fractures [Roberts2010, Roberts2012a,Roberts2012b]. Since 2013 we have worked together on a project to develop a prototype system for identifying and grading vertebral fractures on DXA VFA images, radiographs and CT images. We have built components of an automatic system to demonstrate the feasibility of finding and analysing vertebrae in clinical images without human interaction. The proposed project will build on this work to develop a clinically validated prototype of an automated-system and to gather the clinical evidence required for CE marking. Workplan We will develop a sequence of three increasingly sophisticated versions of the system, which will be installed and tested in local hospitals. The project consists of five work packages: WP1 Data gathering and annotation [CMFT, UoM, Optasia] The system relies on statistical shape models which are constructed from large numbers of annotated images. We will expand our current data sets by collecting large sets of representative clinical images containing the spine (CT, MR images and digital radiographs) from Picture Archiving and Communication Systems (PACS) in local hospitals. We will annotate each image with points describing the shape of the vertebrae (See Fig.2). Each vertebra will be clinically evaluated (as normal, deformed or fractured) by an expert radiologist. WP2 Algorithm and model development [UoM, Optasia] We will use the data collected in WP1 to identify shortcomings in the systems and to develop algorithms and shape models which are more robust and accurate when applied to representative clinical images. We will build new models for each modality and perform experiments to assess the accuracy of the system both to detect the outlines of the vertebrae and to identify fractured or abnormal vertebrae. The main focus will be on CT and lateral radiographs (spine, chest), but we will also investigate whether the system can be extended to MR (localiser, midline sagittal) images. WP3 System Development [Optasia, UoM] Optasia Medical will develop the prototype system software, integrating model matching software provided by The University of Manchester. Optasia will handle all issues to do with software engineering, quality control etc. to a standard suitable for medical devices, and will prepare for regulatory approval of the system WP4 Clinical Evaluation and Patient Forum [CMFT, Optasia] We will study how effective the system is and how it can best be integrated into the clinical workflow. We will evaluate the prevalence of fractures visible in different image types. We will explore current practice for identifying VFs opportunistically and estimate how many people with unrecognised vertebral fractures are likely to be identified by the system. We will discuss the project with a patient forum to assess acceptability. WP5 Preparing for Adoption [Optasia, CMFT, UoM] We will run clinical implementation pilots at three sites. We will discuss use of the system with local Fracture Liaison Services or their equivalents. We will use headroom analysis to set a pricing strategy and identify the potential cost-effectiveness of the system compared with current practice. We will create case studies and a business plan for UK and EU deployment of the final medical device software solution, and perform relevant market analyses. We will submit the system for CE-marking, required for wider adoption. Milestones M1 [end Q2] System v1 installed and running in CMFT M2 [end Q4] System v2 installed and running in CMFT M3 [end Q8] System v3 installed and running at two additional sites M4 [end Q12] EU regulatory submission of final software system Note: See Research Plan and Gannt chart for a list of deliverables.

Lay abstract: Unmet Need: Osteoporosis is a condition in which there is too little bone in the skeleton. Those affected have &ldquo;brittle&rdquo; bones, and are much more likely to suffer from fractures, most commonly in the spine, wrist and hip. These lead to pain, deformity, loss of independence and early death. Half of all women and 1 in 5 men aged over 50 will suffer a fracture due to osteoporosis. The treatment of fractures could cost the UK over &pound;5.5 billion by 2020. Vertebral (spine) fractures are the most common fractures in osteoporosis and anyone who has one is much more likely to have other fractures in future, so may need treatment. However, more than half of vertebral fractures do not cause any pain so may not be noticed. Though they are visible on medical images taken to investigate other conditions, they are often not reported and the chance to treat the fracture and underlying osteoporosis is missed. Technology: We will develop a fully automated computer system for identifying vertebral fractures in medical images in which the spine is visible. It will be able to work with existing NHS systems to make it as easy as possible to be set up in a hospital. The software will build upon our existing state-of-the-art prototype. We will study how well the system works and how many patients it will help, and will gather patients views on how it should be used and whether it is good value for money for the NHS. Impact: The system will identify people with vertebral fractures who would otherwise have been missed. Treating these people should ultimately reduce the number of future fractures, including potentially fatal hip fractures. This could reduce the suffering of many people, and reduce the cost of management to the NHS.

Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: MUSCULOSKELETAL