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Development of a mathematical model to estimate intra-tumor oxygen concentrations through multi-parametric imaging

Overview of attention for article published in BioMedical Engineering OnLine, October 2016
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Title
Development of a mathematical model to estimate intra-tumor oxygen concentrations through multi-parametric imaging
Published in
BioMedical Engineering OnLine, October 2016
DOI 10.1186/s12938-016-0235-5
Pubmed ID
Authors

Chung-Wein Lee, Keith M. Stantz

Abstract

Tumor hypoxia is involved in every stage of solid tumor development: formation, progression, metastasis, and apoptosis. Two types of hypoxia exist in tumors-chronic hypoxia and acute hypoxia. Recent studies indicate that the regional hypoxia kinetics is closely linked to metastasis and therapeutic responses, but regional hypoxia kinetics is hard to measure. We propose a novel approach to determine the local pO2 by fusing the parameters obtained from in vivo functional imaging through the use of a modified multivariate Krogh model. To test our idea and its potential to translate into an in vivo setting through the use of existing imaging techniques, simulation studies were performed comparing the local partial oxygen pressure (pO2) from the proposed multivariate image fusion model to the referenced pO2 derived by Green's function, which considers the contribution from every vessel segment of an entire three-dimensional tumor vasculature to profile tumor oxygen with high spatial resolution. pO2 derived from our fusion approach were close to the referenced pO2 with regression slope near 1.0 and an r(2) higher than 0.8 if the voxel size (or the spatial resolution set by functional imaging modality) was less than 200 μm. The simulation also showed that the metabolic rate, blood perfusion, and hemoglobin concentration were dominant factors in tissue oxygenation. The impact of the measurement error of functional imaging to the pO2 precision and accuracy was simulated. A Gaussian error function with FWHM equal to 20 % of blood perfusion or fractional vascular volume measurement contributed to average 7 % statistical error in pO2. The simulation results indicate that the fusion of multiple parametric maps through the biophysically derived mathematical models can monitor the intra-tumor spatial variations of hypoxia in tumors with existing imaging methods, and the potential to further investigate different forms of hypoxia, such as chronic and acute hypoxia, in response to cancer therapies.

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Mendeley readers

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The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 33%
Student > Master 2 13%
Researcher 2 13%
Student > Doctoral Student 1 7%
Other 1 7%
Other 1 7%
Unknown 3 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 13%
Agricultural and Biological Sciences 2 13%
Engineering 2 13%
Psychology 1 7%
Computer Science 1 7%
Other 2 13%
Unknown 5 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 October 2016.
All research outputs
#18,475,157
of 22,893,031 outputs
Outputs from BioMedical Engineering OnLine
#564
of 822 outputs
Outputs of similar age
#242,031
of 319,855 outputs
Outputs of similar age from BioMedical Engineering OnLine
#7
of 10 outputs
Altmetric has tracked 22,893,031 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 822 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 319,855 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.