Research Papers

Lactation in the Human Breast From a Fluid Dynamics Point of View

[+] Author and Article Information
S. Negin Mortazavi

Department of Mechanical Engineering,
University of Texas at Dallas,
Richardson, TX 75080
e-mail: negin@utdallas.edu

Donna Geddes

School of Chemistry and Biochemistry,
University of Western Australia,
Crawley, Western Australia 6009, Australia
e-mail: donna.geddes@uwa.edu.au

Fatemeh Hassanipour

Department of Mechanical Engineering,
University of Texas at Dallas,
Richardson, TX 75080
e-mail: fatemeh@utdallas.edu

1Corresponding author.

Manuscript received May 26, 2015; final manuscript received October 6, 2016; published online November 30, 2016. Assoc. Editor: Alison Marsden.

J Biomech Eng 139(1), 011009 (Nov 30, 2016) (9 pages) Paper No: BIO-15-1261; doi: 10.1115/1.4034995 History: Received May 26, 2015; Revised October 06, 2016

This study is a collaborative effort among lactation specialists and fluid dynamic engineers. The paper presents clinical results for suckling pressure pattern in lactating human breast as well as a 3D computational fluid dynamics (CFD) modeling of milk flow using these clinical inputs. The investigation starts with a careful, statistically representative measurement of suckling vacuum pressure, milk flow rate, and milk intake in a group of infants. The results from clinical data show that suckling action does not occur with constant suckling rate but changes in a rhythmic manner for infants. These pressure profiles are then used as the boundary condition for the CFD study using commercial ansys fluent software. For the geometric model of the ductal system of the human breast, this work takes advantage of a recent advance in the development of a validated phantom that has been produced as a ground truth for the imaging applications for the breast. The geometric model is introduced into CFD simulations with the aforementioned boundary conditions. The results for milk intake from the CFD simulation and clinical data were compared and cross validated. Also, the variation of milk intake versus suckling pressure are presented and analyzed. Both the clinical and CFD simulation show that the maximum milk flow rate is not related to the largest vacuum pressure or longest feeding duration indicating other factors influence the milk intake by infants.

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Fig. 3

The breast phantom model being used in this paper for reproducing the geometry model [30]

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Fig. 4

Three-dimensional visualization of breast ductal branching model based on the phantom model

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Fig. 2

Comparison of ductal system images (in terms of resolution and accuracy) to produce a representative geometry for CFD simulation purposes: (a) ultrasound, (b) MRI, (c) human body library, and (d) ductogram, where “N” stands for nipple

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Fig. 1

Anatomy of the lactating breast

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Fig. 5

Pressure measurement of intra-oral cavity during breastfeeding

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Fig. 6

View of generated mesh of six generations of breast ductal system with 2.52×106 elements based on phantom model

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Fig. 12

Results from the CFD simulation: instantaneous milk intake (ml) during the total duration of breastfeeding

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Fig. 13

Results from the CFD simulation: average value of milk flow rate (ml/s) in different stages of suckling (shown in Fig. 10)

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Fig. 7

Suckling pressure range and the average milk flow rate for each infant based on the clinical measurements

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Fig. 8

Representative of a suck cycle versus tongue position

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Fig. 9

Various phases of suckling by one of the infants (infant-A): Ej (ejection), NNS (non-nutritive burst), NS (nutritive burst), NP (nutritive pause), and NNP (non-nutritive pause)

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Fig. 10

Detailed pressure profiles for 21 stages of breastfeeding by infant-A, 0 ≤t≤ 502 s

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Fig. 11

Representative of burst, interburst, suck, and intersuck durations



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