Observational studyRadiology2025
A Deep Learning Model for Three-Dimensional Determination of Whole Thoracic Vertebral Bone Mineral Density from Noncontrast Chest CT: The Multi-Ethnic Study of Atherosclerosis.
Abstract readMulticenter StudyObservational Study
In one paragraph
Observational study in Radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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.
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.
Who cites it
5 citing papers in PubMed.
- Deep learning-based CT-derived vertebral bone mineral density and metformin therapy: a longitudinal study in the Multi-Ethnic Study of Atherosclerosis.Skeletal radiology · 2026Article
- Automated 3D chest CT muscle segmentation-derived model development and explanation in discrimination of normal, preserved ratio impaired spirometry, and COPD: a multicenter study.Insights into imaging · 2026Article
- Artificial Intelligence in Rheumatology: From Algorithms to Clinical Impact in Osteoporosis and Chronic Inflammatory Rheumatic Diseases.Journal of clinical medicine · 2026Article
- Diabetes and longitudinal changes in deep learning-derived measures of vertebral bone mineral density using conventional CT: the Multi-Ethnic Study of Atherosclerosis.Skeletal radiology · 2026Article
- Artificial Intelligence for Osteoporosis Diagnosis, Risk Prediction and Therapy: Current Advances, Clinical Challenges, and Future Perspectives.Clinical interventions in aging · 2026Review
Corrections and comments
- Commented on by
Authors and funding
15 authors.
Quincy A Hathaway *Department of Radiology and Radiologic Sciences, Johns Hopkins University, Baltimore, Md.ORCID 0000-0001-8226-2319
Arta Kasaeian *Department of Radiology and Radiologic Sciences, Johns Hopkins University, Baltimore, Md.ORCID 0000-0002-6094-4471
Tommy PanDepartment of Radiology and Radiologic Sciences, Johns Hopkins University, Baltimore, Md.ORCID 0000-0002-6112-8206
David A BluemkeDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis.ORCID 0000-0002-8323-8086
Elena GhotbiDepartment of Radiology and Radiologic Sciences, Johns Hopkins University, Baltimore, Md.ORCID 0009-0001-8371-9795
Joshua G KleinDepartment of Radiology and Radiologic Sciences, Johns Hopkins University, Baltimore, Md.ORCID 0000-0002-7810-6767
Hamza Ahmed IbadDepartment of Radiology and Radiologic Sciences, Johns Hopkins University, Baltimore, Md.ORCID 0000-0003-1557-9484
Chris DailingLundquist Institute at Harbor-University of California Los Angeles School of Medicine, Torrance, Calif.ORCID 0000-0001-9122-8518
Geoffrey H TisonDivision of Cardiology, Department of Medicine, University of California, San Francisco, San Francisco, Calif.ORCID 0000-0002-0310-3326
R Graham BarrDepartments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY.
Wendy PostDivision of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Md.ORCID 0000-0002-8655-5204
Matthew AllisonDepartment of Family Medicine, University of California San Diego, La Jolla, Calif.ORCID 0000-0003-0777-8272
João A C LimaDivision of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Md.ORCID 0000-0001-8756-6995
Matthew Budoff *Lundquist Institute at Harbor-University of California Los Angeles School of Medicine, Torrance, Calif.ORCID 0000-0002-9616-1946
Shadpour Demehri *Department of Radiology and Radiologic Sciences, Johns Hopkins University, Baltimore, Md.ORCID 0000-0001-5991-5924
Funding
Institute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1MWake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3MClinical and Translational Science AwardUL1TR000040 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2012 to 2015
$26.2MPulmonary microvascular perfusion in the Multi-Ethnic Study of AtherosclerosisR01HL077612 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI R Graham BARR · 2004 to 2026
$18.8MPulmonary Vascular Changes in Early Chronic Obstructive Pulmonary Disease (COPD)R01HL093081 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI R Graham BARR · 2008 to 2026
$17.2MTask Area A Core Study Operations.Task Area A shall encompass annual follow-up of cohort members, clinical endpoints ascertainment, study coordination activities, maintenance of the database and biosp75N92020D00001 · NHLBI · UNIVERSITY OF WASHINGTON · PI MCCLELLAND, ROBYN LEAGH · 2020 to 2025
$17.2MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00005 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WATSON, KAROL E · 2020 to 2025
$5.1MTO EXERCISE OPTION PERIOD ONE (1) FOR TASK AREA A - MESA CORE OPERATIONS, FIELD CENTER.75N92020D00004 · NHLBI · NORTHWESTERN UNIVERSITY · PI SIEGEL, JONATHAN H · 2020 to 2025
$4.5MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00006 · NHLBI · UNIVERSITY OF MINNESOTA · PI PANKOW, JAMES S · 2020 to 2025
$4.4MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00003 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI POST, WENDY S · 2020 to 2025
$3.8MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00007 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI BERTONI, ALAIN GERALD · 2020 to 2025
$3.5MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00002 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHEA, STEVEN J · 2020 to 2025
$3.4MNCATS NIH HHS UL1 TR000040NCATS NIH HHS UL1 TR001079NCATS NIH HHS UL1 TR001420NHLBI NIH HHS 75N92020D00001NHLBI NIH HHS 75N92020D00002NHLBI NIH HHS 75N92020D00003NHLBI NIH HHS 75N92020D00004NHLBI NIH HHS 75N92020D00005NHLBI NIH HHS 75N92020D00006NHLBI NIH HHS 75N92020D00007NHLBI NIH HHS HHSN268201500003CNHLBI NIH HHS HHSN268201500003INHLBI NIH HHS N01 HC095159NHLBI NIH HHS N01 HC095160NHLBI NIH HHS N01 HC095161NHLBI NIH HHS N01 HC095162NHLBI NIH HHS N01 HC095163NHLBI NIH HHS N01 HC095164NHLBI NIH HHS N01 HC095165NHLBI NIH HHS N01 HC095166NHLBI NIH HHS N01 HC095167NHLBI NIH HHS N01 HC095168NHLBI NIH HHS N01 HC095169NHLBI NIH HHS R01 HL077612NHLBI NIH HHS R01 HL093081NHLBI NIH HHS R01 HL146666NIAMS NIH HHS R42 AR070713
Abstract
Background Recent studies have investigated how deep learning (DL) algorithms applied to CT using two-dimensional (2D) segmentation (sagittal or axial planes) can calculate bone mineral density (BMD) and predict osteoporosis-related outcomes. Purpose To determine whether TotalSegmentator, an nnU-net algorithm, can measure three-dimensional (3D) vertebral body BMD across consistently imaged thoracic levels (T1-T10) at any conventional, noncontrast chest CT examination. Materials and Methods This study is a secondary analysis of a multicenter (
Indexed as
AtherosclerosisBone DensityDeep LearningImaging, Three-DimensionalThoracic VertebraeTomography, X-Ray ComputedAgedAged, 80 and overFemaleHumansMaleMiddle AgedOsteoporosisProspective StudiesRadiographic Image Interpretation, Computer-Assisted
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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.