2D-3D registration accuracy estimation for optimised planning of image-guided pancreatobiliary interventions

Abstract

We describe a fast analytical method to estimate landmark-based 2D-3D registration accuracy to aid the planning of pancreatobiliary interventions in which ERCP images are combined with information from diagnostic 3D MR or CT images. The method analytically estimates a target registration error (TRE),accounting for errors in the manual selection of both 2D- and 3D landmarks,that agrees with Monte Carlo simulation to within 4.5 ± 3.6 % (mean ± SD). We also show how to analytically estimate a planning uncertainty incorporating uncertainty in patient positioning,and utilise it to support ERCP-guided procedure planning by selecting the optimal patient position and X-ray C-arm orientation that minimises the expected TRE. Simulated- and derived planning uncertainties agreed to within 17.9 ± 9.7 % when the root-mean-square error was less than 50°. We demonstrate the feasibility of this approach on clinical data from two patients.