Cited by 120Bone health and osteoporosis researchMedical Imaging and AnalysisScoliosis diagnosis and treatment

The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index; 8 of the 20 sources its claims cite were checked for support.

Automatic opportunistic osteoporosis screening in routine CT: improved prediction of patients with prevalent vertebral fractures compared to DXA

Open access

Abstract

Objectives: To compare spinal bone measures derived from automatic and manual assessment in routine CT with dual energy X-ray absorptiometry (DXA) in their association with prevalent osteoporotic vertebral fractures using our fully automated framework (https://anduin.bonescreen.de) to assess various bone measures in clinical CT. Methods: We included 192 patients (141 women, 51 men; age 70.2 ± 9.7 years) who had lumbar DXA and CT available (within 1 year). Automatic assessment of spinal bone measures in CT included segmentation of vertebrae using a convolutional neural network (CNN), reduction to the vertebral body, and extraction of bone mineral content (BMC), trabecular and integral volumetric bone mineral density (vBMD), and CT-based areal BMD (aBMD) using asynchronous calibration. Moreover, trabecular bone was manually sampled (manual vBMD). Results: A total of 148 patients (77%) had vertebral fractures and significantly lower values in all bone measures compared to patients without fractures (p ≤ 0.001). Except for BMC, all CT-based measures performed significantly better as predictors for vertebral fractures compared to DXA (e.g., AUC = 0.885 for trabecular vBMD and AUC = 0.86 for integral vBMD vs. AUC = 0.668 for DXA aBMD, respectively; both p < 0.001). Age- and sex-adjusted associations with fracture status were strongest for manual vBMD (OR = 7.3, [95%] CI 3.8–14.3) followed by automatically assessed trabecular vBMD (OR = 6.9, CI 3.5–13.4) and integral vBMD (OR = 4.3, CI 2.5–7.6). Diagnostic cutoffs of integral vBMD for osteoporosis (< 160 mg/cm 3) or low bone mass (160 ≤ BMD < 190 mg/cm 3) had sensitivity (84%/41%) and specificity (78%/95%) similar to trabecular vBMD. Conclusions: Fully automatic osteoporosis screening in routine CT of the spine is feasible. CT-based measures can better identify individuals with reduced bone mass who suffered from vertebral fractures than DXA. Key Points: • Opportunistic osteoporosis screening of spinal bone measures derived from clinical routine CT is feasible in a fully automatic fashion using a deep learning-driven framework (https://anduin.bonescreen.de). • Manually sampled volumetric BMD (vBMD) and automatically assessed trabecular and integral vBMD were the best predictors for prevalent vertebral fractures. • Except for bone mineral content, all CT-based bone measures performed significantly better than DXA-based measures. • We introduce diagnostic thresholds of integral vBMD for osteoporosis (< 160 mg/cm3) and low bone mass (160 ≤ BMD < 190 mg/cm3) with almost equal sensitivity and specificity compared to conventional thresholds of quantitative CT as proposed by the American College of Radiology (osteoporosis < 80 mg/cm3).

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This retrospective study compared fully automatic CT-derived spinal bone measures with DXA for identifying prevalent osteoporotic vertebral fractures in 192 patients. CT-based volumetric measures, especially trabecular and integral vBMD, predicted prevalent fractures better than DXA, and the authors propose integral vBMD thresholds for osteoporosis and low bone mass.

Key findings

  • Among 192 patients (141 women, 51 men; mean age 70.2 ± 9.7 years), 148 (77%) had at least one prevalent vertebral fracture; fractured patients were older (72.0 ± 9.3 vs. 64.3 ± 8.6 years, p < 0.001) and had significantly lower values in all bone measures (p ≤ 0.001).
  • Except for BMC, all CT-based measures predicted prevalent vertebral fractures significantly better than DXA aBMD: AUC = 0.885 for trabecular vBMD, 0.86 for integral vBMD, and 0.894 for manual vBMD vs. 0.668 for DXA aBMD (p < 0.001 for vBMD comparisons); CT-based BMC was not significantly different from DXA aBMD or T-score.
  • Age- and sex-adjusted associations with fracture status were strongest for manual vBMD (OR = 7.3, 95% CI 3.8–14.3), followed by automatically assessed trabecular vBMD (OR = 6.9, CI 3.5–13.4) and integral vBMD (OR = 4.3, CI 2.5–7.6); DXA T-score and aBMD each had OR = 1.9 (CI 1.3–2.8).
  • Proposed integral vBMD thresholds were osteoporosis < 160 mg/cm³ and low bone mass 160 ≤ BMD < 190 mg/cm³, with sensitivity/specificity of 84%/78% and 41%/95%, respectively, similar to trabecular vBMD (86%/78% and 41%/98%).

Methods

  • Monocentric retrospective study: 360 patients were identified, exclusions left 192 with lumbar DXA and CT available within 1 year; prevalent vertebral fractures were classified using the Genant semiquantitative technique (grade ≥ 1).
  • CT bone measures used a fully automatic framework: CNN-based vertebral segmentation, reduction to vertebral bodies, asynchronous HU-to-BMD calibration with contrast correction, and extraction of integral vBMD, trabecular vBMD (eroded by 5 mm), BMC, and CT-based aBMD; manual trabecular vBMD was also sampled.
  • Statistical analysis used t tests and chi-squared tests for group comparisons, logistic regression for odds ratios per 1 SD change (unadjusted and age/sex-adjusted), and ROC AUC analysis with DeLong’s test for correlated ROC curves; significance was p < 0.05.

Limitations

  • Stated: retrospective selection bias toward elderly, mainly neurosurgical and oncological patients who already had both CT and DXA within 1 year, meaning osteoporosis was already suspected; the study assessed prevalent, not incident, vertebral fractures, so the new integral vBMD thresholds require validation in follow-up fracture-risk studies.
  • Evident: the single-center design and high fracture prevalence (77%) may limit generalizability, and the automatic framework and proposed thresholds were not externally validated in this paper.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1007/s00330-020-07655-2

Cites

42 of 42 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

8 of 20 cited sources checked · 3 supported · 1 flagged · accuracy not yet measured

  • Probably not a substantial claim. 12
  • It may state two separate claims as one. 15
  • The quote only partly states this claim. 1
21 of 21
  • The authors state this as an assumption.

    CT-based aBMD has superior accuracy to DXA because of the 3-dimensional character of CT scans, despite being a monoenergetic technique.

    “We chose this approach to take advantage of the 3-dimensional character of CT scans compared to DXA, thus postulating its superior accuracy notwithstanding the fact that it is a monoenergetic technique.”
1 of 1

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • AUCs are assigned to the wrong CT measures

    Minor

    The results assign AUCs of 0.735, 0.860, and 0.885 to integral, trabecular, and manual vBMD, respectively. Table 3 instead reports 0.86, 0.885, and 0.894 for those measures; 0.735 belongs to BMC.

  • A T-score of −2.5 is classified as both low bone mass and osteoporosis

    Minor

    The methods define osteoporosis as T ≤ −2.5 SD, but the Fig. 2 caption calls a T-score of −2.5 SD low bone mass.

2 of 2

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Metadata

Authors
Löffler, M. T., Jacob, A., Scharr, A., Sollmann, N., Burian, E., El Husseini, M., Sekuboyina, A., Tetteh, G., Zimmer, C., Gempt, J., Baum, T., & Kirschke, J. S.
Affiliations
  • University of Freiburg (DE)
  • TUM Klinikum (DE)
  • Technical University of Munich (DE)
Corresponding author
Löffler, Maximilian T.
Venue
European Radiology
Published
2021-01-28
Volume
31
Issue
8
Pages
6069-6077
ISSN
  • 0938-7994 (ISSN-L)
  • 1432-1084
OpenAlex
W3121936649
Cited by
120
References
42
Citations by year
2026: 15 · 2025: 27 · 2024: 20 · 2023: 32 · 2022: 20 · 2021: 5
FWCI
16.99
Type
journal article
Language
en
Open access
Locations
  • European Radiology (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion, cc-by)
  • Informationszentrum Lebenswissenschaften (ZB MED) (submittedVersion, cc-by)
  • mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion, other-oa)
  • mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
  • OPen Access Repositorium der Universität Ulm (OPARU) (Ulm University) (submittedVersion, cc-by)
  • Universität Ulm, Kommunikations- und Informationszentrum (kiz) (cc-by)
Funders
  • European Research Council (637164)
  • Deutsche Forschungsgemeinschaft (432290010)
Topics
  • Health Sciences › Medicine › Orthopedics and Sports Medicine › Bone health and osteoporosis research
  • Physical Sciences › Engineering › Biomedical Engineering › Medical Imaging and Analysis
  • Health Sciences › Medicine › Surgery › Scoliosis diagnosis and treatment
Keywords
osteoporosis screening, vertebral fractures, dual-energy X-ray absorptiometry, volumetric bone mineral density, trabecular bone, bone mineral content, vertebral segmentation, convolutional neural networks, osteopenia, fracture prediction, low-dose CT, diagnostic accuracy
MeSH terms
Aged, Female, Humans, Lumbar Vertebrae, Male, Middle Aged, Osteoporosis, Tomography, X-Ray Computed, Absorptiometry, Photon, Bone Density, Spinal Fractures

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