4.7 Article

Anatomically realistic computational model of flow and mixing in the human duodenum

Journal

PHYSICS OF FLUIDS
Volume 35, Issue 1, Pages -

Publisher

AIP Publishing
DOI: 10.1063/5.0135070

Keywords

-

Ask authors/readers for more resources

The small intestine is important for digestion and nutrient absorption. This study developed a realistic model of flow and mixing in the small intestine and provided new tools for understanding nutrient absorption under normal and diseased conditions.
The small intestine is the primary site of enzymatic digestion and nutrient absorption in humans. Intestinal contractions facilitate digesta transport, mixing, and contact with the absorptive surfaces. Previous computational models have been limited to idealized contraction patterns and/or simplified geometries to study digesta transport. This study develops a physiologically realistic model of flow and mixing in the first segment of the small intestine (duodenum) based upon a geometry obtained from the Visible Human Project dataset and contraction patterns derived from electrophysiological simulations of slow wave propagation. Features seen in previous simpler models, such as reversed flow underneath the contracting region, were also present in this model for water, Newtonian liquid digesta, and non-Newtonian (power law) whole digesta. An increase in the contraction amplitude from 10% to 50% resulted in faster transport with mean speeds over a cycle increasing from 1.7 to 8.7 mm/s. Glucose transport was advection dominated with Peclet numbers greater than 10(4). A metric of glucose mixing was computed, with 0 representing no mixing and 1 representing perfect mixing. For antegrade contractions at a 50% amplitude, the metric after 60 s was 0.99 for water, 0.6 for liquid digesta, and 0.19 for whole digesta. Retrograde contractions had a negligible impact on the flow and mixing. Colliding wavefronts resulted in swirling flows and increased the mixing metric by up to 2.6 times relative to antegrade slow wave patterns. The computational framework developed in this study provides new tools for understanding the mixing and nutrient absorption patterns under normal and diseased conditions.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available