Prostate Biopsy Assistance System with Gland Deformation Estimation for Enhanced Precision

Computer-assisted prostate biopsies became a very active research area during the last years. Prostate tracking makes it possi- ble to overcome several drawbacks of the current standard transrectal ultrasound (TRUS) biopsy procedure, namely the insufficient targeting accuracy which may lead to a biopsy distribution of poor quality, the very approximate knowledge about the actual location of the sampled tissues which makes it difficult to implement focal therapy strategies based on biopsy results, and finally the difficulty to precisely reach non-ultrasound (US) targets stemming from different modalities, statistical atlases or previous biopsy series. The prostate tracking systems presented so far are limited to rigid transformation tracking. However, the gland can get considerably deformed during the intervention because of US probe pres- sure and patient movements. We propose to use 3D US combined with image-based elastic registration to estimate these deformations. A fast elastic registration algorithm that copes with the frequently occurring US shadows is presented. A patient cohort study was performed, which yielded a statistically significant in-vivo accuracy of 0.83+-0.54mm.Comment: This version of the paper integrates a correction concerning the local similarity measure w.r.t. the proceedings (this typing error could not be corrected before editing the proceedings

Image-based registration methods for quantification and compensation of prostate motion during trans-rectal ultrasound (TRUS)-guided biopsy

Prostate biopsy is the clinical standard for cancer diagnosis and is typically performed under two-dimensional (2D) transrectal ultrasound (TRUS) for needle guidance. Unfortunately, most early stage prostate cancers are not visible on ultrasound and the procedure suffers from high false negative rates due to the lack of visible targets. Fusion of pre-biopsy MRI to 3D TRUS for targeted biopsy could improve cancer detection rates and volume of tumor sampled. In MRI-TRUS fusion biopsy systems, patient or prostate motion during the procedure causes misalignments in the MR targets mapped to the live 2D TRUS images, limiting the targeting accuracy of the biopsy system. In order to sample smallest clinically significant tumours of 0.5 cm3with 95% confidence, the root mean square (RMS) error of the biopsy system needs to be The target misalignments due to intermittent prostate motion during the procedure can be compensated by registering the live 2D TRUS images acquired during the biopsy procedure to the pre-acquired baseline 3D TRUS image. The registration must be performed both accurately and quickly in order to be useful during the clinical procedure. We developed an intensity-based 2D-3D rigid registration algorithm and validated it by calculating the target registration error (TRE) using manually identified fiducials within the prostate. We discuss two different approaches that can be used to improve the robustness of this registration to meet the clinical requirements. Firstly, we evaluated the impact of intra-procedural 3D TRUS imaging on motion compensation accuracy since the limited anatomical context available in live 2D TRUS images could limit the robustness of the 2D-3D registration. The results indicated that TRE improved when intra-procedural 3D TRUS images were used in registration, with larger improvements in the base and apex regions as compared with the mid-gland region. Secondly, we developed and evaluated a registration algorithm whose optimization is based on learned prostate motion characteristics. Compared to our initial approach, the updated optimization improved the robustness during 2D-3D registration by reducing the number of registrations with a TRE \u3e 5 mm from 9.2% to 1.2% with an overall RMS TRE of 2.3 mm. The methods developed in this work were intended to improve the needle targeting accuracy of 3D TRUS-guided biopsy systems. The successful integration of the techniques into current 3D TRUS-guided systems could improve the overall cancer detection rate during the biopsy and help to achieve earlier diagnosis and fewer repeat biopsy procedures in prostate cancer diagnosis

Prostate biopsy tracking with deformation estimation

Transrectal biopsies under 2D ultrasound (US) control are the current clinical standard for prostate cancer diagnosis. The isoechogenic nature of prostate carcinoma makes it necessary to sample the gland systematically, resulting in a low sensitivity. Also, it is difficult for the clinician to follow the sampling protocol accurately under 2D US control and the exact anatomical location of the biopsy cores is unknown after the intervention. Tracking systems for prostate biopsies make it possible to generate biopsy distribution maps for intra- and post-interventional quality control and 3D visualisation of histological results for diagnosis and treatment planning. They can also guide the clinician toward non-ultrasound targets. In this paper, a volume-swept 3D US based tracking system for fast and accurate estimation of prostate tissue motion is proposed. The entirely image-based system solves the patient motion problem with an a priori model of rectal probe kinematics. Prostate deformations are estimated with elastic registration to maximize accuracy. The system is robust with only 17 registration failures out of 786 (2%) biopsy volumes acquired from 47 patients during biopsy sessions. Accuracy was evaluated to 0.76$\pm$0.52mm using manually segmented fiducials on 687 registered volumes stemming from 40 patients. A clinical protocol for assisted biopsy acquisition was designed and implemented as a biopsy assistance system, which allows to overcome the draw-backs of the standard biopsy procedure.Comment: Medical Image Analysis (2011) epub ahead of prin

Development and Phantom Validation of a 3D-Ultrasound-Guided System for Targeting MRI-visible Lesions during Transrectal Prostate Biopsy

OBJECTIVE: Three- and four-dimensional transrectal ultrasound transducers are now available from most major ultrasound equipment manufacturers, but currently are incorporated into only one commercial prostate biopsy guidance system. Such transducers offer the benefits of rapid volumetric imaging, but can cause substantial measurement distortion in electromagnetic tracking sensors, which are commonly used to enable 3D navigation. In this paper, we describe the design, development and validation of a 3D-ultrasound-guided transrectal prostate biopsy system that employs high-accuracy optical tracking to localize the ultrasound probe and prostate targets in 3D physical space. METHODS: The accuracy of the system was validated by evaluating the targeted needle placement error after inserting a biopsy needle to sample planned targets in a phantom using standard 2D ultrasound guidance versus real-time 3D guidance provided by the new system. RESULTS: The overall mean needle-segment-to-target distance error was 3.6±4.0 mm and mean needle-to-target distance was 3.2±2.4 mm. CONCLUSION: a significant increase in needle placement accuracy was observed when using the 3D guidance system compared with visual targeting of invisible (virtual) lesions using a standard B-mode ultrasound guided biopsy technique

Prostate Biopsy Assistance System with Gland Deformation Estimation for Enhanced Precision

This version of the paper integrates a correction concerning the local similarity measure w.r.t. the proceedings (this typing error could not be corrected before editing the proceedings)International audienceComputer-assisted prostate biopsies became a very active research area during the last years. Prostate tracking makes it possi- ble to overcome several drawbacks of the current standard transrectal ultrasound (TRUS) biopsy procedure, namely the insufficient targeting accuracy which may lead to a biopsy distribution of poor quality, the very approximate knowledge about the actual location of the sampled tissues which makes it difficult to implement focal therapy strategies based on biopsy results, and finally the difficulty to precisely reach non-ultrasound (US) targets stemming from different modalities, statistical atlases or previous biopsy series. The prostate tracking systems presented so far are limited to rigid transformation tracking. However, the gland can get considerably deformed during the intervention because of US probe pres- sure and patient movements. We propose to use 3D US combined with image-based elastic registration to estimate these deformations. A fast elastic registration algorithm that copes with the frequently occurring US shadows is presented. A patient cohort study was performed, which yielded a statistically significant in-vivo accuracy of 0.83+-0.54mm

Développement et application préclinique du robot de curiethérapie PROSPER

Introduction : Rapporter le développement et les expérimentations d'un nouveau système robotisé destiné à la curiethérapie prostatique possédant un système de suivi de la prostate et une possibilité de fusion écho-IRM. Matériel et méthodes : Un robot d'implantation d'aiguilles transpérinéales guidé par échographie transrectale avec suivi peropératoire des mouvements et de la déformation de la prostate a été crée. Les expériences ont été conduites sur 90 cibles réalisées dans 9 fantômes conçus pour être mobiles et déformables. Les expériences ont été ensuite conduites chez 2 cadavres. Le robot a cherché à déposer des billes de verre simulant des grains de curiethérapie aussi près que possible des cibles dans des fantômes évaluables par différentes modalités d'imagerie dont le scanner et dans des prostates de cadavre. Les résultats étaient mesurés en segmentant les cibles et les billes de verre sur des volumes tomodensitométriques des fantômes et des cadavres. Résultats : Le robot était capable d'atteindre les cibles choisies dans les fantômes avec une précision médiane de 2.73 mm, avec un déplacement médian de la prostate de 5.46 mm. La précision était meilleure à la base qu'à l'apex (2.28 mm vs 3.83 mm, p<0.01) et n'était pas significativement différente pour les implantations horizontales et obliques (2.7 vs 2.82 mm, p=0.18). Les tests sur cadavre ont montré la faisabilité et l'ergonomie du robot en salle d'opération mais des expérimentations plus poussées sont nécessaires. Conclusion : Ce robot destiné à la curiethérapie prostatique est le premier système utilisant le suivi de la prostate intra-opératoire pour guider des aiguilles dans la prostate. Les expériences préliminaires montrent sa capacité à atteindre des cibles malgré les mouvements de la prostate. Les applications pourraient être élargies à la thérapie focale et aux biopsies guidées compte-tenu de sa possibilité à fusionner l'imagerie IRM et l'échographie.Purpose: To report on the development and the initial experience with a new 3D ultrasound robotic system for prostate brachytherapy assistance and focal therapy. MRI-TRUS fusion as well as its ability to track prostate motion intra-operatively allows it to manage motions and guide needles to MRI enhanced tumor foci. Materials and methods: A robotic system for TRUS-guided needle implantation combined with intraoperative prostate tracking was created. Experiments were conducted on 90 targets embedded in 9 mobile and deformable synthetic prostate phantoms. A preliminary feasibility study on 2 cadavers was also carried out. The experiments involved trying to insert glass beads as close as possible to targets in multimodal imaging phantoms and in cadaver prostates. The results were measured by segmenting the inserted beads in CT scan volumes of the phantoms and of the cadaver's radical prostatectomy specimens. Results: The robot was able to reach the chosen targets in phantoms with a median accuracy of 2.73 mm, with a median prostate motion of 5.46 mm. Accuracy was better in apex than in base (2.28 vs 3.83 mm, p<0.001) and was similar for horizontal and angled needle inclinations (2.7 vs 2.82 mm, p=0.18). Cadaver tests showed the feasibility of the robot's ergonomics in the operating room but further in vivo assessments are needed. Conclusion: This robot for prostate focal therapy and brachytherapy is the first system using intraoperative prostate motion tracking to guide needles into the prostate. The preliminary experiments described show its ability to reach targets in spite of the motion of the prostate.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Registration of magnetic resonance and ultrasound images for guiding prostate cancer interventions

Prostate cancer is a major international health problem with a large and rising incidence in many parts of the world. Transrectal ultrasound (TRUS) imaging is used routinely to guide surgical procedures, such as needle biopsy and a number of minimally-invasive therapies, but its limited ability to visualise prostate cancer is widely recognised. Magnetic resonance (MR) imaging techniques, on the other hand, have recently been developed that can provide clinically useful diagnostic information. Registration (or alignment) of MR and TRUS images during TRUS-guided surgical interventions potentially provides a cost-effective approach to augment TRUS images with clinically useful, MR-derived information (for example, tumour location, shape and size). This thesis describes a deformable image registration framework that enables automatic and/or semi-automatic alignment of MR and 3D TRUS images of the prostate gland. The method combines two technical developments in the field: First, a method for constructing patient-specific statistical shape models of prostate motion/deformation, based on learning from finite element simulations of gland motion using geometric data from a preoperative MR image, is proposed. Second, a novel “model-to-image” registration framework is developed to register this statistical shape model automatically to an intraoperative TRUS image. This registration approach is implemented using a novel model-to-image vector alignment (MIVA) algorithm, which maximises the likelihood of a particular instance of a statistical shape model given a voxel-intensity-based feature vector that represents an estimate of the surface normal vectors at the boundary of the organ in question. Using real patient data, the MR-TRUS registration accuracy of the new algorithm is validated using intra-prostatic anatomical landmarks. A rigorous and extensive validation analysis is also provided for assessing the image registration experiments. The final target registration error after performing 100 MR–TRUS registrations for each patient have a median of 2.40 mm, meaning that over 93% registrations may successfully hit the target representing a clinically significant lesion. The implemented registration algorithms took less than 30 seconds and 2 minutes for manually defined point- and normal vector features, respectively. The thesis concludes with a summary of potential applications and future research directions