Modeling Lymph Flow and Fluid Exchange with Blood Vessels in Lymph Nodes

Abstract

Background: Lymph nodes (LNs) are positioned strategically throughout the body as critical mediators of lymph filtration and immune response. Lymph carries cytokines, antigens, and cells to the downstream LNs, and their effective delivery to the correct location within the LN directly impacts the quality and quantity of immune response. Despite the importance of this system, the flow patterns in LN have never been quantified, in part because experimental characterization is so difficult. Methods and Results: To achieve a more quantitative knowledge of LN flow, a computational flow model has been developed based on the mouse popliteal LN, allowing for a parameter sensitivity analysis to identify the important system characteristics. This model suggests that about 90% of the lymph takes a peripheral path via the subcapsular and medullary sinuses, while fluid perfusing deeper into the paracortex is sequestered by parenchymal blood vessels. Fluid absorption by these blood vessels under baseline conditions was driven mainly by oncotic pressure differences between lymph and blood, although the magnitude of fluid transfer is highly dependent on blood vessel surface area. We also predict that the hydraulic conductivity of the medulla, a parameter that has never been experimentally measured, should be at least three orders of magnitude larger than that of the paracortex to ensure physiologic pressures across the node. Conclusions: These results suggest that structural changes in the LN microenvironment, as well as changes in inflow/outflow conditions, dramatically alter the distribution of lymph, cytokines, antigens, and cells within the LN, with great potential for modulating immune response.

Critical Issues in Modelling Lymph Node Physiology

“…The vascular network provides the delivery of oxygen, nutrients and signal molecules. Lymphatic fluid can leave the LN through the blood vessels due to a pressure difference, hydrostatic and osmotic, between the interstitial pressure in the node and the pressure in the blood vessels [2,3]. The vessels of the blood microvascular network have lots of close intersections with the FRC network, pervading the whole space inside LN, so the vascular network influencesshma many processes in the lymph node.…”

“…The first variant of pressure distribution is called «Gradient» with a linear decline from P max = 500 Pa to P min = 0 Pa depending on x-coordinate. The pressure estimates are based on values reported in [3,6,33]. The second variant is referred by term «Constant».…”

“…There exists very few computational studies in which the fluid flow through the internal domains of LN was investigated [3,6]. The model is based on an idealized 3D geometry of the LN macro-structures and an approximation of the B-cell follicles, T cell paracortex and medulla as porous 2 of 22 regions.…”

“…This implies that the development of computational models of the LN structure and function requires (i) an idealization of the structure, (ii) the implementation of a modular approach, and (iii) the analysis of the performance of specific functional LN units in health and disease. The elements of the above framework can be found in [3][4][5][6][7].…”

“…LNs are known to present high resistance to lymph flow [3], which results from the internal structure of the LN body comprised of blood microvascular networks, the conduit networks and of domains densely packed with immune cells, i.e., the B cell follicles and T cell zone. In the existing 3D geometry LN models developed for studying the fluid flow, the conduit and blood vascular systems are not structurally described.…”