Fracture risk assessment by dual-energy absorptiometry in osteogenesis imperfecta: A systematic review of measurement sites and its predictive value.

Authors

Karlijn Scheepens, Suzanne den Haan, Kelly Warmink, Ralph Sakkers, Anne Spaans, Wouter Nijhuis, Harrie Weinans

Published in

Bone reports. Volume 30. Pages 101929. Epub Jun 10, 2026.

Abstract

People with osteogenesis imperfecta (OI) suffer frequent fracturing of bones. Dual-energy absorptiometry (DXA) is considered a surrogate measure of bone strength, and DXA scans are usually acquired yearly to guide treatment. However, DXA provides only limited insight into bone strength as it does not account for bone geometry or microarchitecture. This systematic review outlines current clinical practice regarding the DXA in children with OI, and evaluates evidence for conventional and alternative DXA-derived measures in OI. The search was conducted in Pubmed, Embase, and Web of Science databases at 12-Dec-2025 and records were screened by two reviewers. Studies presenting DXA measurement locations in children with OI or results on the relation between DXA-derived measures and OI type or fractures were eligible and presented in a descriptive manner. Risk of bias was assessed using the Newcastle-Ottawa Scale. In total, 91 studies were included. Data was extracted from 38 observational studies including 3696 patients. The results showed that DXA measurement locations are not standardized. Although studies were variable in methods and results, the association between DXA-derived areal bone mineral density (aBMD) and fractures was generally weak - particularly when fracture incidence was evaluated over short time intervals. However, location-specific measurements may offer some improvement. DXA-based measures reflecting trabecular structure or estimated bone volume did not outperform aBMD. Given the presented results of conventional DXA in OI, alternative methods of bone strength assessment in patients with OI are needed. Assessment targeting fracture-prone skeletal regions and incorporating geometric properties may enhance DXA's predictive value.

PMID:
42326737
Bibliographic data and abstract were imported from PubMed on 12 Sep 2026.

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