Feasibility study for 3D quantitative angiography in internal carotid aneurysms using in silico biplane imaging and...

Quantitative angiography (QA) in two dimensions has been instrumental in assessing neurovascular contrast flow, aiding disease severity evaluation and treatment outcome prediction. However, QA requires high temporal and spatial resolution, restricting its use to digital subtraction angiography (DSA). The 2D, projective nature of DSA introduces errors in representing the inherently three-dimensional flow dynamics. This study examines whether 3D QA information can be recovered by reconstructing four-dimensional (4D) angiography using data from standard clinical imaging protocols. Patient-specific 3D vascular geometries were used to generate high-fidelity computational fluid dynamics (CFD) simulations of contrast flow in internal carotid aneurysms. The resulting 4D angiograms, representing ground truth, were used to simulate biplane DSA under clinical imaging protocols, including projection spacing and injection timing. 4D angiography was reconstructed from two views using back-projection constrained by a 3D vascular geometry obtained a priori via CT angiography. Angiographic parametric imaging (API) metrics obtained from the CFD-based 4D angiography and reconstructed 4D angiography, respectively, were compared using mean square error (MSE) and mean absolute percentage error (MAPE). The reconstructed 4D datasets effectively captured 3D flow dynamics, achieving an average MSE of 0.007 across models and flow conditions. Intensity-based API metrics closely matched the CFD ground truth, with temporal metrics showing some variability in regions with overlapping projections. These results highlight the feasibility of recovering 3D QA information using 4D DSA reconstructed from standard biplane angiography. The method provides a robust framework for evaluating and improving QA in neurovascular applications, offering new insights into the dynamics of aneurysmal contrast flow.