Vascular neural network in subarachnoid hemorrhage

Abstract

This perspective article uses a new concept named vascular neural network as an umbrella to redefine vascular pathophysiology for subarachnoid hemorrhage (SAH) induced vasospasm and early/delayed brain injury. Five vascular components are discussed including large artery moderate vasospasm which may not contribute to reduced cerebral blood flow (CBF) and poor outcomes after SAH. Even severe vasospasm alone with lumen diameter narrowing less than 75% of the normal diameter may not cause delayed brain injury, unless it is combined with peripheral and distal smaller artery dysfunctions. Vasospasm in smaller artery or arterioles contributes to the reduction of CBF and poor outcomes after SAH, because of limited or no collateral circulation reserves. Capillary or pre-capillary pear-string-type of contraction may block red blood cell flow and astrocyte edema compression may contribute to the loss of capillary density after SAH. Venules may be compressed by brain edema because venules have a thin wall of only one layer of endothelial cells with adventitia tissues. Deep cerebral vein vasospasm reduces venous flow and may cause venous infarction. When venous flow is obstructed, it is presumed that arterial dilatation may enhance brain edema and be harmful. Overall, all of these five vascular components in the vascular neural network are interrelated and more than one component or even all five components may be affected after SAH. All of these vascular components should be taken into consideration for patient care. Studying potential roles of venules and deep veins in the outcome of SAH patients and mechanisms of venule compression and vein spasm may be new aspects for future investigations.