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An Anthropometric-Based Subject-Specific Finite Element Model of the Human Breast for Predicting Large Deformations

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, December 2015
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Title
An Anthropometric-Based Subject-Specific Finite Element Model of the Human Breast for Predicting Large Deformations
Published in
Frontiers in Bioengineering and Biotechnology, December 2015
DOI 10.3389/fbioe.2015.00201
Pubmed ID
Authors

Silvia Pianigiani, Leonardo Ruggiero, Bernardo Innocenti

Abstract

The large deformation of the human breast threatens proper nodules tracking when the subject mammograms are used as pre-planning data for biopsy. However, techniques capable of accurately supporting the surgeons during biopsy are missing. Finite element (FE) models are at the basis of currently investigated methodologies to track nodules displacement. Nonetheless, the impact of breast material modeling on the mechanical response of its tissues (e.g., tumors) is not clear. This study proposes a subject-specific FE model of the breast, obtained by anthropometric measurements, to predict breast large deformation. A healthy breast subject-specific FE parametric model was developed and validated by Cranio-caudal (CC) and Medio-Lateral Oblique (MLO) mammograms. The model was successively modified, including nodules, and utilized to investigate the effect of nodules size, typology, and material modeling on nodules shift under the effect of CC, MLO, and gravity loads. Results show that a Mooney-Rivlin material model can estimate healthy breast large deformation. For a pathological breast, under CC compression, the nodules displacement is very close to zero when a linear elastic material model is used. Finally, when nodules are modeled, including tumor material properties, under CC, or MLO or gravity loads, nodules shift shows ~15% average relative difference.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 23%
Student > Bachelor 5 16%
Student > Ph. D. Student 4 13%
Professor 3 10%
Researcher 3 10%
Other 4 13%
Unknown 5 16%
Readers by discipline Count As %
Engineering 18 58%
Medicine and Dentistry 3 10%
Nursing and Health Professions 1 3%
Physics and Astronomy 1 3%
Agricultural and Biological Sciences 1 3%
Other 2 6%
Unknown 5 16%
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 24 December 2015.
All research outputs
#18,433,196
of 22,836,570 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#3,399
of 6,565 outputs
Outputs of similar age
#281,953
of 390,633 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#29
of 48 outputs
Altmetric has tracked 22,836,570 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 6,565 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 30th percentile – i.e., 30% 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 390,633 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.