Evidence map›Paper›PMID 34562119›Full record

ArticleArchives of orthopaedic and trauma surgery2022

Correlation of quantitative computed tomography derived bone density values with Hounsfield units of a contrast medium computed tomography in 98 thoraco-lumbar vertebral bodies.

Fabian Buenger, Yasser Sakr, Niklas Eckardt, Christian Senft, Falko Schwarz

Open access · hybridAbstract read
In one paragraph

Article in Archives of orthopaedic and trauma surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

20 citing papers in PubMed, 29 citations in OpenAlex.

  1. Multi-center validation of automated CT-based L1 vertebral Hounsfield unit.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2026
    Article
  2. Thoracolumbar vertebral bone quality (TLVBQ) score as a possible screening tool for osteoporosis in patients with severe degenerative lumbar scoliosis: a retrospective cohort study.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 · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Diagnostic model for distinguishing fresh or old osteoporotic vertebral compression fractures based on modified computed tomography window: a retrospective cohort study.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
    Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

5 authors at 1 institution in 1 country.

Fabian Buenger *Department of Neurosurgery, Jena University Hospital-Friedrich Schiller University Jena, Jena, Germany.
Yasser Sakr *Department for Anaesthesiology and Intensive Care, Jena University Hospital-Friedrich Schiller University Jena, Jena, Germany.
Niklas EckardtDepartment for Radiology, Jena University Hospital-Friedrich Schiller University Jena, Jena, Germany.
Christian SenftDepartment of Neurosurgery, Jena University Hospital-Friedrich Schiller University Jena, Jena, Germany.
Falko SchwarzDepartment of Neurosurgery, Jena University Hospital-Friedrich Schiller University Jena, Jena, Germany. falko.schwarz@med.uni-jena.de.ORCID http://orcid.org/0000-0003-0821-193X
Jena University Hospital · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionVertebral fractures in patients with bone density reduction are often a major challenge for the surgeon, as reduced bone density can lead to screw loosening. Several options are available to determine bone density preoperatively. In our study, we investigated the correlation of Hounsfield units (HU) of a contrast medium computed tomography (CT) to the bone density values of a quantitative computed tomography (QCT) and computed a formula to estimate bone density values using HU. MATERIALS AND

methodsIn our retrospective data analysis, we examine 98 vertebral bodies from 35 patients who received a contrast medium CT of the spine and a QCT, performed no longer than 1 month apart. The determined HU from the contrast medium CT were compared with the bone density values of the QCT and examined for correlations. Linear logistic regression was used to estimate bone density values base on HU.

resultsA strong correlation was found between the HU measured in the CT and the bone density values (r = 0.894, p < 0.001), irrespective of patients' gender. We also found no correlation differences when the HU were measured at different levels. Bland-Altman plot demonstrated good agreement between the two measurements. The following formula was developed to estimate bone density values using HU: QCT-value = 0.71 × HU + 13.82.

conclusionsBone density values correlate well to HU measured in contrast medium CT. Using simple formula, the bone density of a contrast medium CT of vertebral bodies can be estimated based on HU without additional examinations and unnecessary costs.

Indexed as

Bone DensityVertebral BodyAbsorptiometry, PhotonContrast MediaHumansLumbar VertebraeRetrospective StudiesTomography, X-Ray ComputedContrast MediaBone mineral densityContrast mediumHounsfield unitsLumbar spineQuantitative computed tomography

Identifiers

PMID34562119
PMCPMC9522714
OpenAlexW3199611702

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.