Evidence map›Paper›PMID 42348573›Full record

ArticlePloS one2026

Clinical validation of automatic phantom-less quantitative computed tomography for osteoporosis screening: fat region of interest comparison and multidevice validation.

Yizhang Tong, Rong Gao, Chunxi Liu, Zhiling Ren, Wenjie Fu, Hongyan Yao, Ping Wang, Sheng Zhou

Abstract readValidation StudyComparative Study
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Yizhang TongFirst School of Clinical Medicine, Gansu University of Chinese Medicine, Lanzhou, China.ORCID https://orcid.org/0009-0002-5623-5717
Rong GaoFirst School of Clinical Medicine, Gansu University of Chinese Medicine, Lanzhou, China.
Chunxi LiuFirst School of Clinical Medicine, Gansu University of Chinese Medicine, Lanzhou, China.
Zhiling RenFirst School of Clinical Medicine, Gansu University of Chinese Medicine, Lanzhou, China.
Wenjie FuDepartment of Radiology, Gansu Provincial Hospital, Lanzhou, China.
Hongyan YaoDepartment of Radiology, Gansu Provincial Hospital, Lanzhou, China.
Ping WangFirst School of Clinical Medicine, Gansu University of Chinese Medicine, Lanzhou, China.ORCID https://orcid.org/0009-0000-0030-2103
Sheng ZhouFirst School of Clinical Medicine, Gansu University of Chinese Medicine, Lanzhou, China.ORCID https://orcid.org/0009-0005-0427-7597

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOsteoporosis significantly increases fracture risk and healthcare burden. Traditional bone mineral density screening requires dedicated equipment, limiting opportunistic screening. Phantom-less quantitative computed tomography (PL-QCT) enables bone density assessment during routine chest CT examinations but requires comprehensive validation. This study uses fat region of interest (ROI) comparison and multidevice validation to verify the feasibility and accuracy of automatic PL-QCT for osteoporosis screening.

methodsThis prospective study included 252 participants who underwent routine chest CT examinations. An automatic PL-QCT system was used to measure the volumetric bone mineral density at the T11-L1 vertebrae. Clinical validation compared measurements with phantom-based quantitative computed tomography (PB-QCT) using the system's standard pipeline with automatically selected subcutaneous fat ROIs and, for methodological comparison, manually selected visceral fat ROIs. Diagnostic performance was evaluated via receiver operating characteristic curve analysis with the DeLong test, whereas accuracy was assessed via linear regression, ICC, and Bland‒Altman analysis. Multidevice validation was conducted across five CT scanners.

resultsThe automated PL-QCT system under validation (using automatically selected subcutaneous fat ROI) demonstrated excellent diagnostic performance, with an area under the curve (AUC) of 0.962 for osteoporosis and 0.794 for osteopenia, and showed strong correlation with PB-QCT (r = 0.867, ICC = 0.926). In the methodological comparison, the PL-QCT values derived from the manually selected visceral fat ROI showed significantly superior performance to those from the automated system (subcutaneous fat ROI) for the diagnosis of osteopenia (P = 0.029). Multidevice validation demonstrated consistency across the five CT scanners. Gender analysis revealed greater accuracy in females with distinct age-related bone density patterns.

conclusionsThis study validates that the automated PL-QCT system (utilizing its standard pipeline with automatically selected subcutaneous fat ROI) provides a reliable approach for opportunistic osteoporosis screening during routine chest CT examinations. A key methodological finding is that the manually selected visceral fat ROI demonstrated superior performance to the system's automatically selected subcutaneous fat ROI specifically in osteopenia detection, offering important evidence for optimizing future calibration strategies. The technology's cross-platform consistency, confirmed by multidevice validation, supports its broad clinical applicability.

Indexed as

OsteoporosisTomography, X-Ray ComputedAgedBone DensityFemaleHumansMaleMass ScreeningMiddle AgedPhantoms, ImagingProspective StudiesReproducibility of ResultsROC Curve

Identifiers

PMID42348573
PMCPMC13298776

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.