ASPIRE™: Using Machine Learning to detect undiagnosed fractures in patients with osteoporosis

Impact: Technological impacts, Health and wellbeing

Narrative

Osteoporosis weakens bones, increases risk of fractures and affects half of all people aged over 50. Vertebral fragility fractures (VFFs) are a common early manifestation, but those seen opportunistically on computed tomography (CT) images are often not reported by radiologists. At the University of Manchester (UoM) we have developed software to identify VFFs in CT images, combining it with oversight from radiologists to create ASPIRE™, a service that improves VFF identification. Implementation at NHS sites (2018-2019) analysed 9,797 patients and identified VFFs in 2,018 of them. Only 74 patients had been referred by hospital radiologists; ASPIRE™ referred 1,945, ensuring better management.

Category of impact

  • Technological impacts
  • Health and wellbeing
Date
2018 - 2020

Related information