ArticleJBMR plus2022
Definition of Normal Vertebral Morphometry Using NHANES-II Radiographs.
Article in JBMR plus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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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.
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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.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Benchmarking AI: comparing a fully automated spinal motion solution to a validated analyst-driven technology.North American Spine Society journal · 2026Article
- Investigating the Effects of Image Scaling Techniques in Radiographic Measurements of Spinal Alignment and Motion: A Comparative Analysis.Journal of imaging informatics in medicine · 2026Article
- Lumbar region perception segmentation: a novel algorithm for automated vertebral motion parameter measurement.Quantitative imaging in medicine and surgery · 2025Article
- Automated radiographic metrics for diagnosing lumbar spine instability: a cross-sectional observational study.Quantitative imaging in medicine and surgery · 2025Article
- 3D U-Net Neural Network Architecture-Assisted LDCT to Acquire Vertebral Morphology Parameters: A Vertebral Morphology Comprehensive Analysis in a Chinese Population.Calcified tissue international · 2024Article
- Reference Data for Diagnosis of Spondylolisthesis and Disc Space Narrowing Based on NHANES-II X-rays.Bioengineering (Basel, Switzerland) · 2024Article
- Differences in Vertebral Morphology and bone Mineral Density between Grade 1 Vertebral Fracture and Non-Fractured Participants in the Chinese Population.Calcified tissue international · 2024Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A robust definition of normal vertebral morphometry is required to confidently identify abnormalities such as fractures. The Second National Health and Nutrition Examination Survey (NHANES-II) collected a nationwide probability sample to document the health status of the United States. Over 10,000 lateral cervical spine and 7,000 lateral lumbar spine X-rays were collected. Demographic, anthropometric, health, and medical history data were also collected. The coordinates of the vertebral body corners were obtained for each lumbar and cervical vertebra using previously validated, automated technology consisting of a pipeline of neural networks and coded logic. These landmarks were used to calculate six vertebral body morphometry metrics. Descriptive statistics were generated and used to identify and trim outliers from the data. Descriptive statistics were tabulated using the trimmed data for use in quantifying deviation from average for each metric. The dependency of these metrics on sex, age, race, nation of origin, height, weight, and body mass index (BMI) was also assessed. There was low variation in vertebral morphometry after accounting for vertebrae (eg, L1, L2), and the
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Registered trials
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.