Evidence map›Paper›PMID 42819027›Full record

ArticleBJR artificial intelligence2026

Analysis of leg bone lengths from whole-body dual-energy X-ray absorptiometry in the UK biobank.

Faten Alomar, Junkai Wang, Timothy F Cootes

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

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Faten AlomarDepartment of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 12372, Saudi Arabia.ORCID https://orcid.org/0000-0002-2095-6590
Junkai WangDepartment of Computer Science, The University of Manchester, Manchester M13 9PL, United Kingdom.ORCID https://orcid.org/0000-0002-7188-3635
Timothy F CootesDivision of Informatics, Imaging and Data Science, The University of Manchester, Manchester M13 9PT, United Kingdom.ORCID https://orcid.org/0000-0002-2695-9063

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To calculate the distributions of leg bone lengths (as measured from dual-energy X-ray absorptiometry [DXA] images) and their relationship with height. Estimating human height from long bone measurements is widely used in forensic and biological anthropology. Methods: An automated system was developed to find the outlines of the femur and tibia in DXA images from the UK Biobank. These were used to measure the length of the bones. Images with implants, severe abnormalities, or missing data were excluded. Relationships between lengths and with height were estimated using linear regression. Results: Of the 73 405 available DXA images, we successfully measured both femurs and tibia in 66 730 cases (91%). The lengths of femurs and tibias for males and females each show normal distributions, with left and right being very similar. The mean absolute difference between measurements at 2 time points was below 1.8 mm (femur), 2.3 mm (tibia), showing the system is repeatable. Linear regression gives the relationships between individual bone lengths and between them and height. Conclusions: The developed software system and the resulting analysis provide promising insights into bone geometry using DXA imaging, enabling large-scale, precise bone measurements. These models are relevant for predicting height, a subject of interest in archaeology and forensic science. Advances in knowledge: This is the largest study of the distributions of leg bone lengths and their relationship to height that we are aware of.

Indexed as

DXA imagesfemurtibiaUK Biobank

Identifiers

PMID42819027
PMCPMC13623526

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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.