ArticlePloS one2018
Temporal blood flow changes measured by diffuse correlation tomography predict murine femoral graft healing.
Article in PloS one, 2018. 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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Who cites it
7 citing papers in PubMed, 15 citations in OpenAlex.
- Leveraging the predictive power of a 3D in vitro vascularization screening assay for hydrogel-based tissue-engineered periosteum allograft healing.Biomaterials advances · 2025Article
- Semiparametric mixed-effects model for analysis of non-invasive longitudinal hemodynamic responses during bone graft healing.PloS one · 2022Article
- Wirelessly operated bioelectronic sutures for the monitoring of deep surgical wounds.Nature biomedical engineering · 2021Article
- Collimating micro-lens fiber array for noncontact near-infrared diffuse correlation tomography.Biomedical optics express · 2021Article
- Spatial frequency domain imaging for the longitudinal monitoring of vascularization during mouse femoral graft healing.Biomedical optics express · 2020Article
- Longitudinal 3D Blood Flow Distribution Provided by Diffuse Correlation Tomography during Bone Healing in a Murine Fracture Model.Photochemistry and photobiology · 2020Article
- High-density speckle contrast optical tomography of cerebral blood flow response to functional stimuli in the rodent brain.Neurophotonics · 2019Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Blood flow changes during bone graft healing have the potential to provide important information about graft success, as the nutrients, oxygen, circulating cells and growth factors essential for integration are delivered by blood. However, longitudinal monitoring of blood flow changes during graft healing has been a challenge due to limitations in current techniques. To this end, non-invasive diffuse correlation tomography (DCT) was investigated to enable longitudinal monitoring of three-dimensional blood flow changes in deep tissue. Specific to this study, longitudinal blood flow changes were utilized to predict healing outcomes of common interventions for massive bone defects using a common mouse femoral defect model. Weekly blood flow changes were non-invasively measured using a diffuse correlation tomography system for 9 weeks in three types of grafts: autografts (N = 7), allografts (N = 6) and tissue-engineered allografts (N = 6). Healing outcomes were quantified using an established torsion testing method 9 weeks after transplantation. Analysis of the spatial and temporal blood flow reveals that major differences among the three groups were captured in weeks 1-5 after graft transplantation. A multivariate model to predict maximum torque by relative blood flow changes over 5 weeks after graft transplantation was built using partial least squares regression. The results reveal lower bone strength correlates with greater cumulative blood flow over an extended period of time (i.e., 1-5 weeks). The current research demonstrates that DCT-measured blood flow changes after graft transplantation can be utilized to predict long-term healing outcomes in a mouse femoral graft model.
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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.