Spatially regularized region-based perfusion estimation in peripherals using angiographic C-arm systems

TLDR: A method for interventional perfusion estimation in peripherals using C-arms which is based on DSA and two additional 3D images reconstructed from rotational scans is proposed and the use of spatial and temporal regularization proved to be an effective way to limit inaccuracies due to instability in the solution of the inverse problem.

Abstract: The outcome assessment of endovascular revascularization procedures in the lower limbs is currently carried out by x-ray digital subtraction angiography (DSA). Due to the two-dimensional nature of this technique, only visual assessment of arterial blood flow is possible and no tissue blood flow information (i.e. perfusion) is available to assess the effective restoration of blood supply to the tissue. In this work, we propose a method for interventional perfusion estimation in peripherals using C-arms which is based on DSA and two additional 3D images reconstructed from rotational scans. The method assumes spatial homogeneity of contrast within multiple regions identified by segmentation of the reconstructed 3D images. A dedicated segmentation method which relies on local contrast homogeneity and connectivity of anatomical structures is introduced. Region-based perfusion is obtained by mapping the 2D blood flow information from DSA to the 3D segments by solving an inverse problem. Instability of the solution due to the spatial overlap of the regions is addressed by applying spatial and temporal regularizations. The method was evaluated on data simulated from CT perfusion scans of the lower limb. Blood flow values estimated with the optimal number of segmented regions exhibited errors of 1 ± 4  and 2 ± 11 ml/100 ml min−1 for the two analyzed cases, respectively, which showed to be sufficient to differentiate hypoperfused and normally perfused areas. The use of spatial and temporal regularization proved to be an effective way to limit inaccuracies due to instability in the solution of the inverse problem. Results in general proved the feasibility of C-arm interventional perfusion imaging by a combination of temporal information derived from DSA and spatial information derived from 3D reconstructions.