Correlation Between Contrast Time-Density Time on Digital Subtraction Angiography and Flow: An in Vitro Study

2D parametric contrast time-density analysis for the prediction of complete aneurysm occlusion at six months' post-flow diversion stent

OBJECTIVE

Indications for the treatment of cerebral aneurysms with flow diversion stents are expanding. The current aneurysm occlusion rate at six months ranges between 60 and 80%. Predictability of complete vs. partial aneurysm occlusion is poorly defined. Here, we evaluate the angiographic contrast time-density as a predictor of aneurysm occlusion rate at six months' post-flow diversion stents.

METHODS

Patients with unruptured cerebral aneurysms proximal to the internal carotid artery terminus treated with single flow diversion stents were included. 2D parametric parenchymal blood flow software (Siemens-Healthineers, Forchheim, Germany) was used to calculate contrast time-density within the aneurysm and in the proximal adjacent internal carotid artery. The area under the curve ratio between the two regions of interests was assessed at baseline and after flow diversion stents deployment. The area under the curve ratio between completely vs. partially occluded aneurysms at six months' follow-up was compared.

RESULTS

Thirty patients with 31 aneurysms were included. Mean aneurysm diameter was 8 mm (range 2-28 mm). Complete occlusion was obtained in 19 aneurysms. Younger patients (P = 0.006) and smaller aneurysms (P = 0.046) presented higher chance of complete obliteration. Incomplete occlusion of the aneurysm was more likely if the area under the curve contrast time-density ratio showed absolute (P = 0.001) and relative percentage (P = 0.001) decrease after flow diversion stents deployment. Area under ROC curve was 0.85.

CONCLUSION

Negative change in the area under the curve ratio indicates less contrast stagnation in the aneurysm and lower chance of occlusion. These data provide a real-time analysis after aneurysm treatment. If validated in larger datasets, this can prompt input to the surgeon to place a second flow diversion stents.

Cerebral arteriovenous malformation venous stenosis is associated with hemodynamic changes at the draining vein-venous sinus junction

Cerebral arteriovenous malformations (AVMs) are an uncommon vascular anomaly that carry the risk of rupture and hemorrhage. Several factors have been implicated in the propensity of an AVM to bleed. One such factor is stenosis of AVM draining veins, as impairment of the AVM venous drainage system is associated with increased risk of intracranial hemorrhage. Currently, our understanding of the pathogenesis of AVM venous outflow stenosis is limited, as there is insufficient data on the blood flow patterns and local hemodynamic parameters of these draining veins. The angioarchitecture of AVMs features a nidus lacking a high resistance capillary network. Accordingly, our previous studies on AVM arterial feeders have demonstrated an abnormally high flow volume rate along with low pulsatility and resistance indices on quantitative magnetic resonance angiography. As such, AVM vessels endure high, non-physiologic levels of flow that may partially contribute to ectasia or stenosis depending on whether wall shear stress (WSS) is high or low, respectively. We hypothesize that AVM venous outflow stenosis occurs most commonly near the junction of the draining vein and the dural venous sinus. Increased flow volume rate through the AVM circuit coupled with the variation in compliance and rigidity between the walls of the draining vein and the dural venous sinus likely create turbulence of blood flow. The resulting flow separation, low WSS, and departure from axially aligned, unidirectional flow may create atherogenic conditions that can be implicated in venous intimal hyperplasia and outflow stenosis. We have previously found there to be a significant association between intimal hyperplasia risk factors and venous outflow stenosis. Additionally, we have found a significant association between age and likelihood as well as degree of stenosis, suggesting a progressive disease process. Similar conditions have been demonstrated in the pathophysiology of stenosis of the carotid artery and dialysis arteriovenous fistulas. In both of these conditions, the use of computational fluid dynamics (CFD) has been employed to characterize the local hemodynamic features that contribute to the pathogenesis of intimal hyperplasia and stenosis. We recommend the utilization of CFD to characterize the anatomic and hemodynamic features of AVM venous outflow stenosis. An improved understanding of the possible causative features of venous outflow stenosis may impact how clinicians choose to manage the treatment of patients with AVMs.