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.Impact date | 2018 → 2020 |
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Category of impact | Technological impacts, Health and wellbeing |
Impact level | Engagement |
Research Beacons, Institutes and Platforms
- Christabel Pankhurst Institute
- Institute for Data Science and AI
- Lydia Becker Institute
Documents & Links
Related content
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Research output
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Under-reporting of osteoporotic vertebral fractures on computed tomography
Research output: Contribution to journal › Article › peer-review
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Abstracts of Osteoporosis Conference 2016: Opportunistic identification of vertebral fractures on computed radiography: need for improvement
Research output: Contribution to conference › Abstract › peer-review
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Fully Automatic Localisation of Vertebrae in CT images using Random Forest Regression Voting
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Robust and Accurate Shape Model Matching Using Random Forest Regression-Voting
Research output: Contribution to journal › Article › peer-review
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Royal Osteoporosis Society, Osteoporosis Online Conference December 1 st 2020: Abstracts: Royal Osteoporosis Society, Osteoporosis Online Conference December 1st 2020: Abstracts
Research output: Contribution to journal › Article › peer-review
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Localisation of Vertebrae on DXA Images using Constrained Local Models with Random Forest Regression Voting
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Impacts
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Improving healthcare and animal welfare using statistical shape models
Impact: Health and wellbeing, Economic, Technological