Targeting error simulator for image-guided prostate needle placement

Motivation: Needle-based biopsy and local therapy of prostate cancer depend multimodal imaging for both target planning and needle guidance. The clinical process involves selection of target locations in a pre-operative image volume and registering these to an intra-operative volume. Registration inaccuracies inevitably lead to targeting error, a major clinical concern. The analysis of targeting error requires a large number of images with known ground truth, which has been infeasible even for the largest research centers. Methods: We propose to generate realistic prostate imaging data in a controllable way, with known ground truth, by simulation of prostate size, shape, motion and deformation typically encountered in prostatic needle placement. This data is then used to evaluate a given registration algorithm, by testing its ability to reproduce ground truth contours, motions and deformations. The method builds on statistical shape atlas to generate large number of realistic prostate shapes and finite element modeling to generate high-fidelity deformations, while segmentation error is simulated by warping the ground truth data in specific prostate regions. Expected target registration error (TRE) is computed as a vector field. Results: The simulator was configured to evaluate the TRE when using a surface-based rigid registration algorithm in a typical prostate biopsy targeting scenario. Simulator parameters, such as segmentation error and deformation, were determined by measurements in clinical images. Turnaround time for the full simulation of one test case was below 3 minutes. The simulator is customizable for testing, comparing, optimizing segmentation and registration methods and is independent of the imaging modalities used.