Evidence map›Paper›PMID 41696694›Full record

ArticleJBMR plus2026

Novel image registration approach for combining 2D Osterix and collagen bundles images with 3D micro-CT.

Mireille Ngokingha Tchouto, Julia Mehl, Saeed Khomeijani Farahani, Daniel Baum, Georg N Duda

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Article in JBMR plus, 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

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

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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

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5 · Who and what money

Authors and funding

5 authors.

Mireille Ngokingha TchoutoJulius Wolff Institute, Berlin Institute of Health at Charité, Universitätsmedizin Berlin, 13353 Berlin, Germany.ORCID https://orcid.org/0009-0007-1427-9179
Julia MehlJulius Wolff Institute, Berlin Institute of Health at Charité, Universitätsmedizin Berlin, 13353 Berlin, Germany.ORCID https://orcid.org/0000-0002-8279-7142
Saeed Khomeijani FarahaniJulius Wolff Institute, Berlin Institute of Health at Charité, Universitätsmedizin Berlin, 13353 Berlin, Germany.
Daniel BaumZuse Institute Berlin, Visual and Data-Centric Computing, 14195 Berlin, Germany.ORCID https://orcid.org/0000-0003-1550-7245
Georg N DudaJulius Wolff Institute, Berlin Institute of Health at Charité, Universitätsmedizin Berlin, 13353 Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To study bone healing, different imaging techniques are typically employed. Histological and immunohistological methods allow the visualization of Osterix (OSX) expression and collagen structures, whereas μCT imaging enables the assessment of mineralized tissue. However, a clear spatial alignment between the information obtained from these 2 modalities is still lacking. In this study, we present a technological approach for registering 2D histological sections of collagen bundles and OSX signals with 3D volumetric μCT data. We applied this method to datasets from animals with rigid and semi-rigid fracture fixation to resemble fast and effective healing and delayed healing. Using our 2D-3D registration workflow, we were able to identify corresponding 2D μCT and histological slices, and we showed that the algorithm performed consistently across both fixation conditions, resembling the healing consequences. Thus, we could illustrate how such image registration techniques could be used to study the co-localization of OSX, collagen, and hydroxyapatite (HA). This framework enables the visualization and direct comparison of OSX, collagen, and HA within a single, spatially matched image, providing a tool for future studies to quantitatively explore tissue co-localization and spatial relationships during bone healing.

Indexed as

2D-3D registrationbone healingimmuno-histochemistrymechano-sensationSHGμCT

Identifiers

PMID41696694
PMCPMC12906291

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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.