Abstract

Osteoporosis causes bones to become weak, porous and fracture more easily. While a vertebral fracture is the archetypal fracture of osteoporosis, it is also the most difficult to diagnose clinically. Patients often suffer further spine or other fractures, deformity, height loss and pain before diagnosis. There were an estimated 520,000 fragility fractures in the United Kingdom (UK) in 2017 (costing £4.5 billion), a figure set to increase 30% by 2030. One way to improve both vertebral fracture identification and the diagnosis of osteoporosis is to assess a patient’s spine or hips during routine computed tomography (CT) scans. Patients attend routine CT for diagnosis and monitoring of various medical conditions, but the skeleton can be overlooked as radiologists concentrate on the primary reason for scanning. More than half a million CT scans done each year in the National Health Service (NHS) could potentially be screened for osteoporosis (increasing 5% annually). If CT-based screening became embedded in practice, then the technique could have a positive clinical impact in the identification of fragility fracture and/or low bone density. Several companies have developed software methods to diagnose osteoporosis/fragile bone strength and/or identify vertebral fractures in CT datasets, using various methods that include image processing, computational modelling, artificial intelligence and biomechanical engineering concepts. Technology to evaluate Hounsfield units is used to calculate bone density, but not necessarily bone strength. In this rapid evidence review, we summarise the current literature underpinning approved technologies for opportunistic screening of routine CT images to identify fractures, bone density or strength information. We highlight how other new software technologies have become embedded in NHS clinical practice (having overcome barriers to implementation) and highlight how the novel osteoporosis technologies could follow suit. We define the key unanswered questions where further research is needed to enable the adoption of these technologies for maximal patient benefit.

Highlights

  • With modern computed tomography (CT) scans, some portion of the patients’ spine is visualised in detail during ordinary chest, abdomen and pelvis scanning, giving ample opportunity for diagnosing osteoporosis and for various methods of vertebral fracture assessment (VFA) technologies

  • This approach is different from the other types of software we review, where products have emerged from coding done intentionally

  • Definition of ‘approved’ software and services This review considers all technologies that have either received United States (US) Food and Drug Administration (FDA) approval, ISO 13485 certification, a European CE mark for diagnosis, or are National Health Service (NHS) Care Quality Commission (CQC) regulated technology services

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Summary

Introduction

With modern computed tomography (CT) scans, some portion of the patients’ spine is visualised in detail during ordinary chest, abdomen and pelvis scanning, giving ample opportunity for diagnosing osteoporosis and for various methods of vertebral fracture assessment (VFA) technologies. ML is a set of software algorithms and statistical models used to perform a specific task, without using explicit instructions. This approach is different from the other types of software we review, where products have emerged from coding done intentionally (based on what developers already know about proven osteoporosis predictors). With AI, large data sets of CT images are coupled with knowledge of eventual fracture outcomes and prevalence to ‘learn’ which imaging features predict the outcome of interest

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