Contrast-Density Gradient Cone-Beam CT: A Novel Dual-Injection Technique for Visualization of dAVF Angioarchitecture and Treatment Targets.

OBJECTIVE

Precise identification of the functional shunt compartment and its relationship to arterial feeders and venous drainage pathways is essential for treatment of intracranial dural arteriovenous fistulas (dAVFs). However, conventional digital subtraction angiography (DSA) is limited by vessel overlap, whereas conventional three-dimensional angiographic techniques provide limited flow-related information. We describe a novel contrast-density gradient cone-beam CT (CBCT) technique that enables simultaneous visualization of arterial feeders, shunt points, vascular networks, and venous drainage pathways for treatment planning.

METHODS

Forty-five consecutive patients with intracranial dAVFs underwent contrast-density gradient CBCT in 55 imaging sessions. Contrast-density gradient CBCT was performed by sequential administration of diluted contrast medium followed by undiluted contrast medium through a dual-barrel injector. Injection timing and contrast dilution were determined from arterial opacification time (AOT) and venous opacification time (VOT) measured on DSA.

RESULTS

The technique generated a contrast-density gradient that differentiated arterial inflow from venous outflow while preserving spatial relationships. No acquisition ultimately failed. Two acquisitions required repeat imaging because of inappropriate acquisition timing, with satisfactory images obtained after timing adjustment. No adverse events related to the imaging technique were observed. Representative cases demonstrated vascular networks separated from the functional venous sinus lumen, precise localization of shunt points, and identification of lesion-specific treatment targets.

CONCLUSIONS

Contrast-density gradient CBCT enables simultaneous visualization of arterial feeders, shunt points, vascular networks, and venous drainage pathways within a single three-dimensional dataset. By integrating flow-related information with high-resolution three-dimensional anatomy, the technique facilitates comprehensive evaluation of dAVF angioarchitecture and lesion-specific neuroendovascular treatment planning.