Temporal blood flow changes measured by diffuse correlation tomography predict murine femoral graft healing

Songfeng Han, Ashley R Proctor, Jingxuan Ren, Danielle S W Benoit and Regine Choe

PLOS ONE, 2018, vol. 13, issue 5, 1-15

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.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0197031

DOI: 10.1371/journal.pone.0197031

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