Biomechanical Modeling of the Pelvic System: Improving the Accuracy of Prostate Lesions Location in MRI–TRUS Fusion

Background: An accurate knowledge of prostate lesions relocation during biopsy is of great importance to prevent mispositioning of the needle and thus reduce the chance of faulty biopsy results (false negatives). Prostate lesions are visible in magnetic resonance images (MRI) but it is difficult for the practitioner to locate them at the time of performing a transrectal ultrasound (TRUS) guided biopsy. In this study, we present a new methodology that predicts both prostate deformation and lesion migration during the biopsy.Methods: A thee-dimensional (3-D) anatomy model of the pelvic region, based on medical images, is constructed. A finite element (FE) simulation of the organs motion and deformation as a result of the pressure exerted by the TRUS probe was carried out using the code_aster open source software. Initial positions of potential prostate lesions prior to biopsy are taken into consideration and the final location of each lesion is targeted in the FE simulation output.Results: Our 3-D FE simulations show that the effect of the pressure exerted by the TRUS probe is twofold as the prostate experiences both a motion (in the absolute frame of reference) and a deformation of its original shape. We targeted the relocation of five small prostate lesions when the TRUS probe exerts a force of 30 N on the rectum inner wall. The distance traveled by these lesions ranged between 5.6 and 13.9 mm. Moreover, we showed that as a result of the deformation of the prostate the resulting lesion migration might be very difficult to predict if the biopsy practitioner has to rely exclusively on a visual comparison of axial or sagittal prostate slices taken from MRI and TRUS images.Conclusions: The preliminary results presented here show that our new methodology can be of great help for improving the prediction of cancerous lesions location when a TRUS guided biopsy is performed. Moreover, the new methodology is completely developed on open source software, which means that its implementation would be affordable even for healthcare providers with small budgets.