Dynamic Reconstruction with Statistical Ray Weighting for C-Arm CT Perfusion Imaging

Tissue perfusion measurement using C-arm angiography systems is a novel technique with potential high benefit for catheter-guided treatment of stroke in the interventional suite. However, perfusion C-arm CT (PCCT) is challenging: the slow C-arm rotation speed only allows measuring samples of contrast time attenuation curves (TACs) every 5 – 6 s if reconstruction algorithms for static data are used. Furthermore, the peaks of the tissue TACs typically lie in a range of 5 – 30 HU, thus perfusion imaging is very sensitive to noise. Recently we presented a dynamic, iterative reconstruction (DIR) approach to reconstruct TACs described by a weighted sum of linear spline functions with a regularization based on joint bilateral filtering (JBF). In this work we incorporate statistical ray weighting into the algorithm and show how this helps to improve the reconstructed cerebral blood flow (CBF) maps in a simulation study with a realistic dynamic brain phantom. The Pearson correlation of the CBF maps to ground truth maps increases from 0.85 (FDK), 0.87 (FDK with JBF), and 0.90 (DIR with JBF) to 0.92 (DIR with JBF and ray weighting). The results suggest that the statistical ray weighting approach improves the diagnostic accuracy of PCCT based on DIR.