Task-driven source–detector trajectories in cone-beam computed tomography: II. Application to neuroradiology

Abstract

We apply the methodology detailed in "Task-driven source-detector trajectories in cone-beam computed tomography: I. Theory and methods" by Stayman <i>et al.</i> for task-driven optimization of source-detector orbits in cone-beam computed tomography (CBCT) to scenarios emulating imaging tasks in interventional neuroradiology. The task-driven imaging framework is used to optimize the CBCT source-detector trajectory by maximizing the detectability index, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msup><mml:mrow><mml:mi>d</mml:mi></mml:mrow> <mml:mrow><mml:mo>'</mml:mo></mml:mrow> </mml:msup> </mml:mrow> </mml:math> . The approach was applied to simulated cases of endovascular embolization of an aneurysm and arteriovenous malformation and was translated to real data first using a CBCT test bench followed by implementation on an interventional robotic C-arm. Task-driven trajectories were found to generally favor higher fidelity (i.e., less noisy) views, with an average increase in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msup><mml:mrow><mml:mi>d</mml:mi></mml:mrow> <mml:mrow><mml:mo>'</mml:mo></mml:mrow> </mml:msup> </mml:mrow> </mml:math> ranging from 7% to 28%. Visually, this resulted in improved conspicuity of particular stimuli by reducing the noise and altering the noise correlation to a form distinct from the spatial frequencies associated with the imaging task. The improvements in detectability and the demonstration of the task-driven workflow using a real interventional imaging system show the potential of the task-driven imaging framework to improve imaging performance on motorized, multiaxis C-arms in neuroradiology.