Resolving the Pressure Paradox of Deep Cervical Lymphatic–Venous Anastomosis: A Dynamic Pressure-Gradient Hypothesis
Year: 2026
Type: preprint
Abstract: Deep cervical lymphatic–venous anastomosis has recently attracted attention as an experimental surgical approach for Alzheimer's disease. The procedure is intended to facilitate drainage from the cervical lymphatic system into the venous circulation, potentially enhancing downstream clearance of fluid and solutes originating from the central nervous system. However, a fundamental hemodynamic problem remains unresolved: reported pressures in cervical veins may equal or exceed those in deep cervical lymphatic vessels. Under a purely static pressure model, such a relationship would not favor sustained lymph-to-vein flow and could even predict venous-to-lymphatic reflux. Here, we propose that this apparent pressure paradox arises from treating two intrinsically pulsatile systems as static compartments. Lymphatic and venous pressures fluctuate with respiration, cardiac activity, body position, lymphatic contraction, and surrounding tissue motion. Consequently, mean pressure does not necessarily determine instantaneous flow direction. Even when mean lymphatic pressure is lower than mean venous pressure, transient intervals may occur during which lymphatic pressure exceeds venous pressure. If these favorable pressure gradients are coupled to valvular or geometric mechanisms that limit reverse flow, repeated oscillations could be rectified into net lymph-to-vein transport. We therefore propose that the relevant driving variable in deep cervical lymphatic–venous anastomosis is not the difference between mean lymphatic and venous pressures, but the time-dependent pressure gradient across the anastomosis. This hypothesis generates direct experimental predictions and may provide a mechanistic framework for evaluating whether and when deep cervical lymphatic–venous anastomosis can enhance central nervous system fluid clearance.
Author: Sato, Seiji
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7203684243
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