Quantitative Evaluation of Flow Diversion in Intracranial Aneurysms Using DSA-Derived Intensity Metrics
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Endovascular treatment has become essential for managing intracranial aneurysms, with flow diverters as a central component. Optimizing implant performance relies on early-stage evaluation, critical for guiding design and development. This study introduces a method to assess flow diversion efficacy using patient-specific aneurysm phantoms. Patient-specific aneurysm phantoms were created using 3D printing based on clinical datasets from rotational angiography. Each phantom is oriented for optimal imaging and includes connectors for inlet and outlet. Flow-diverting stents were deployed and phantoms attached to a pulsatile pump to mimic physiological blood flow. A water–glycerine mixture circulated the system, and a 5-second contrast bolus was injected. 2D digital subtraction angiography was performed at 30 fps with a Siemens ARTIS icono biplane angiography system. MATLAB was used for post-processing DICOM series to generate time intensity curves. DSA imaging showed detailed contrast distribution variations. Temporal changes at various sites were analysed: the parent vessel proximal and distal to the aneurysm ostium and multiple probes inside the aneurysm sac. Delayed and dampened filling curves indicated altered flow into the aneurysm sac after flow diverter deployment. In addition, increased contrast residence time and reduced intra-aneurysmal washout were observed. This presented workflow allows quantitative assessment of flow diverters in realistic vascular structures without risking patient safety. Unlike computational models, it avoids uncertain boundary condition estimations, serving as a dependable alternative or complement to image-based blood flow simulation. By measuring clinically pertinent parameters like flow reduction and residence time, this approach offers insights into device performance, presenting a promising tool for device development and preclinical analysis.
