Evidence map›Paper›PMID 34290831›Full record

ReviewTherapeutic advances in musculoskeletal disease2021

Opportunistic diagnosis of osteoporosis, fragile bone strength and vertebral fractures from routine CT scans; a review of approved technology systems and pathways to implementation.

Veena Aggarwal, Christina Maslen, Richard L Abel, Pinaki Bhattacharya, Paul A Bromiley, Emma M Clark, Juliet E Compston, Nicola Crabtree, Jennifer S Gregory, Eleni P Kariki and 3 more

Open access · goldAbstract readReview
In one paragraph

Review in Therapeutic advances in musculoskeletal disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
7.1field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

  1. CT image-based biomarkers for opportunistic screening of osteoporotic fractures: a systematic review and meta-analysis.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2024
    Pooled it
  2. Review
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  11. Opportunistic Hounsfield units measurements on computed tomography scans can predict the number of prevalent vertebral compression fractures in older adults.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025
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  14. Trabecular bone mineral density as measured by thoracic vertebrae predicts incident hip and vertebral fractures: the multi-ethnic study of atherosclerosis.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2024
    Article
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  18. External validation of a convolutional neural network algorithm for opportunistically detecting vertebral fractures in routine CT scans.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 10 institutions in 1 country.

Veena AggarwalKingston Hospital NHS Foundation Trust, Kingston Upon Thames, UK.ORCID https://orcid.org/0000-0002-3641-6388
Christina MaslenHealth Evidence Matters, Bristol, UK.
Richard L AbelImperial College London, London, UK.
Pinaki BhattacharyaThe University of Sheffield, Sheffield, UK.
Paul A BromileyThe University of Manchester, Manchester, UK.
Emma M ClarkUniversity of Bristol, Bristol, UK.
Juliet E CompstonDepartment of Medicine, UK.
Nicola CrabtreeBirmingham Women's and Children's NHS Foundation Trust, Birmingham, UK.
Jennifer S GregoryUniversity of Aberdeen School of Medicine Medical Sciences and Nutrition, Aberdeen, UK.ORCID https://orcid.org/0000-0002-6328-4560
Eleni P KarikiThe University of Manchester, Manchester, UK.
Nicholas C HarveyUniversity of Southampton Faculty of Medicine, Southampton, UK.
Kate A WardUniversity of Southampton, Southampton, Hampshire, UK.
Kenneth E S PooleUniversity of Cambridge School of Clinical Medicine, Addenbrooke's Hospital, NIHR Cambridge Biomedical Research Centre, Cambridge, CB2 0QQ, UK.ORCID https://orcid.org/0000-0003-4546-7352
University of Manchester · GBUniversity of Southampton · GBBirmingham Women’s and Children’s NHS Foundation Trust · GBImperial College London · GBKingston Hospital · GBUniversities UK · GBUniversity of Aberdeen · GBUniversity of Bristol · GBUniversity of Cambridge · GBUniversity of Sheffield · GB

Funding

Medical Research Council MC_PC_21001Medical Research Council MC_PC_21003Versus Arthritis 20109
6 · The paper itself

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.

Indexed as

artificial intelligencecomputed tomographyepidemiologyfragility fractureinnovationOsteoporosisQCTscreeningtechnologyvertebral fracture

Identifiers

PMID34290831
PMCPMC8274099
OpenAlexW3162570438

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.