Evidence map›Paper›PMID 39202277›Full record

ArticleDiagnostics (Basel, Switzerland)2024

Automated Opportunistic Osteoporosis Screening Using Low-Dose Chest CT among Individuals Undergoing Lung Cancer Screening in a Korean Population.

Woo Young Kang, Zepa Yang, Heejun Park, Jemyoung Lee, Suk-Joo Hong, Euddeum Shim, Ok Hee Woo

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Comparison of the value of VBQ scores for assessing abnormal bone mass based on DXA and QCT.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
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

7 authors.

Woo Young KangDepartment of Radiology, Korea University Guro Hospital, Seoul 08308, Republic of Korea.ORCID 0000-0002-8507-1363
Zepa YangDepartment of Radiology, Korea University Guro Hospital, Seoul 08308, Republic of Korea.
Heejun ParkDepartment of Radiology, Korea University Guro Hospital, Seoul 08308, Republic of Korea.
Jemyoung LeeDepartment of Applied Bioengineering, Seoul National University, Seoul 08826, Republic of Korea.
Suk-Joo HongDepartment of Radiology, Korea University Guro Hospital, Seoul 08308, Republic of Korea.
Euddeum ShimDepartment of Radiology, Korea University Ansan Hospital, Ansan 15355, Republic of Korea.
Ok Hee WooDepartment of Radiology, Korea University Guro Hospital, Seoul 08308, Republic of Korea.ORCID 0000-0003-3953-933X

Funding

Technology Innovation Program 20011856
6 · The paper itself

Abstract

Opportunistic osteoporosis screening using deep learning (DL) analysis of low-dose chest CT (LDCT) scans is a potentially promising approach for the early diagnosis of this condition. We explored bone mineral density (BMD) profiles across all adult ages and prevalence of osteoporosis using LDCT with DL in a Korean population. This retrospective study included 1915 participants from two hospitals who underwent LDCT during general health checkups between 2018 and 2021. Trabecular volumetric BMD of L1-2 was automatically calculated using DL and categorized according to the American College of Radiology quantitative computed tomography diagnostic criteria. BMD decreased with age in both men and women. Women had a higher peak BMD in their twenties, but lower BMD than men after 50. Among adults aged 50 and older, the prevalence of osteoporosis and osteopenia was 26.3% and 42.0%, respectively. Osteoporosis prevalence was 18.0% in men and 34.9% in women, increasing with age. Compared to previous data obtained using dual-energy X-ray absorptiometry, the prevalence of osteoporosis, particularly in men, was more than double. The automated opportunistic BMD measurements using LDCT can effectively predict osteoporosis for opportunistic screening and identify high-risk patients. Patients undergoing lung cancer screening may especially profit from this procedure requiring no additional imaging or radiation exposure.

Indexed as

bone mineral densitycomputed tomographydeep learningopportunistic screeningosteoporosisprevalence

Identifiers

PMID39202277
PMCPMC11354205

What Socratic 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 Socratic graph.