Towards ultrasound probe positioning optimization during prostate needle biopsy using pressure feedback

Purpose

Accurate Transrectal Ultrasound (TRUS)-guided prostate needle biopsy requires registering preoperative 3D TRUS or MR image, in which tumors and other suspicious areas are visible, to intraoperative 2D TRUS images. Such image registration is time-consuming while its real-time implementation is yet to be developed. To bypass this registration step, robotic needle biopsy systems can be used to place the US probe at the same position relative to the prostate during the 3D and 2D image acquisition to ensure similar prostate deformation. To have such similar deformation, only visual feedback is not sufficient as such feedback can be used to only guarantee that the whole prostate is within the field of view irrespective of the probe’s orientation. As such, contact pressure feedback can be utilized to ensure consistent minimum contact between the probe and prostate.

Method

A robotic system is proposed where a TRUS probe with pressure sensor array is used. The contact pressure can be measured during imaging and used to provide feedback in conjunction with an optimization algorithm for consistent probe positioning. The robotic system is driven by the feedback to position the probe such that pressure pattern of the sensors during 2D image acquisition is similar to the pressure pattern during 3D image acquisition. The proposed method takes into account the patient’s body movement expected during image acquisition. In this study, an in silico phantom is used where the simulated contact pressure distribution required in the optimization algorithm is obtained using a prostate finite element model.

Result

Starting from an arbitrary position where the probe contacts the phantom, this position was varied systematically until a position corresponding to maximum pressure pattern similarity between contact pressure patterns corresponding to the 2D and 3D imaging was achieved successfully.

Conclusion

Results obtained from the in silico phantom study indicate that the proposed technique is capable of ensuring having only minimal relative prostate deformation between preoperative image acquisition and intraoperative imaging used for guiding needle biopsy, paving the way for faster and more accurate registration.     

A partial augmented reality system with live ultrasound and registered preoperative MRI for guiding robot-assisted radical prostatectomy

We propose an image guidance system for robot assisted laparoscopic radical prostatectomy (RALRP). A virtual 3D reconstruction of the surgery scene is displayed underneath the endoscope’s feed on the surgeon’s console. This scene consists of an annotated preoperative Magnetic Resonance Image (MRI) registered to intraoperative 3D Trans-rectal Ultrasound (TRUS) as well as real-time sagittal 2D TRUS images of the prostate, 3D models of the prostate, the surgical instrument and the TRUS transducer. We display these components with accurate real-time coordinates with respect to the robot system. Since the scene is rendered from the viewpoint of the endoscope, given correct parameters of the camera, an augmented scene can be overlaid on the video output. The surgeon can rotate the ultrasound transducer and determine the position of the projected axial plane in the MRI using one of the registered da Vinci instruments. This system was tested in the laboratory on custom-made agar prostate phantoms. We achieved an average total registration accuracy of 3.2  ±  1.3 mm. We also report on the successful application of this system in the operating room in 12 patients. The average registration error between the TRUS and the da Vinci system for the last 8 patients was 1.4  ±  0.3 mm and average target registration error of 2.1  ±  0.8 mm, resulting in an in vivo overall robot system to MRI mean registration error of 3.5 mm or less, which is consistent with our laboratory studies.     

Prostate multimodality image registration based on B-splines and quadrature local energy

Purpose  

Needle biopsy of the prostate is guided by Transrectal Ultrasound (TRUS) imaging. The TRUS images do not provide proper spatial localization of malignant tissues due to the poor sensitivity of TRUS to visualize early malignancy. Magnetic Resonance Imaging (MRI) has been shown to be sensitive for the detection of early stage malignancy, and therefore, a novel 2D deformable registration method that overlays pre-biopsy MRI onto TRUS images has been proposed.     

Prostate segmentation in transrectal ultrasound using magnetic resonance imaging priors

Purpose

In the current standard of care, real-time transrectal ultrasound (TRUS) is commonly used for prostate brachytherapy guidance. As TRUS provides limited soft tissue contrast, segmenting the prostate gland in TRUS images is often challenging and subject to inter-observer and intra-observer variability, especially at the base and apex where the gland boundary is hard to define. Magnetic resonance imaging (MRI) has higher soft tissue contrast allowing the prostate to be contoured easily. In this paper, we aim to show that prostate segmentation in TRUS images informed by MRI priors can improve on prostate segmentation that relies only on TRUS images.

Methods

First, we compare the TRUS-based prostate segmentation used in the treatment of 598 patients with a high-quality MRI prostate atlas and observe inconsistencies at the apex and base. Second, motivated by this finding, we propose an alternative TRUS segmentation technique that is fully automatic and uses MRI priors. The algorithm uses a convolutional neural network to segment the prostate in TRUS images at mid-gland, where the gland boundary can be clearly seen. It then reconstructs the gland boundary at the apex and base with the aid of a statistical shape model built from an MRI atlas of 78 patients.

Results

Compared to the clinical TRUS segmentation, our method achieves similar mid-gland segmentation results in the 598-patient database. For the seven patients who had both TRUS and MRI, our method achieved more accurate segmentation of the base and apex with the MRI segmentation used as ground truth.

Conclusion

Our results suggest that utilizing MRI priors in TRUS prostate segmentation could potentially improve the performance at base and apex.

     

Learning Non-rigid Deformations for Robust,Constrained Point-based Registration in Image-Guided MR-TRUS Prostate Intervention

Accurate and robust non-rigid registration of pre-procedure magnetic resonance (MR) imaging to intra-procedure trans-rectal ultrasound (TRUS) is critical for image-guided biopsies of prostate cancer. Prostate cancer is one of the most prevalent forms of cancer and the second leading cause of cancer-related death in men in the United States. TRUS-guided biopsy is the current clinical standard for prostate cancer diagnosis and assessment. State-of-the-art, clinical MR-TRUS image fusion relies upon semi-automated segmentations of the prostate in both the MR and the TRUS images to perform non-rigid surface-based registration of the gland. Segmentation of the prostate in TRUS imaging is itself a challenging task and prone to high variability. These segmentation errors can lead to poor registration and subsequently poor localization of biopsy targets, which may result in false-negative cancer detection. In this paper, we present a non-rigid surface registration approach to MR-TRUS fusion based on a statistical deformation model (SDM) of intra-procedural deformations derived from clinical training data. Synthetic validation experiments quantifying registration volume of interest overlaps of the PI-RADS parcellation standard and tests using clinical landmark data demonstrate that our use of an SDM for registration, with median target registration error of 2.98 mm, is significantly more accurate than the current clinical method. Furthermore, we show that the low-dimensional SDM registration results are robust to segmentation errors that are not uncommon in clinical TRUS data.     

TRUS–MRI image registration: a paradigm shift in the diagnosis of significant prostate cancer

Accuracy of multiparametric MRI has greatly improved the ability of localizing tumor foci of prostate cancer. This property can be used to perform a TRUS–MR image registration, new technological advance, which allows for an overlay of an MRI onto a TRUS image to target a prostate biopsy toward a suspicious area Three types of registration have been developed: cognitive-based, sensor-based, and organ-based registration. Cognitive registration consists of aiming a suspicious area during biopsy with the knowledge of the lesion location identified on multiparametric MRI. Sensor-based registration consists of tracking in real time the TRUS probe with a magnetic device, achieving a global positioning system which overlays in real-time prostate image on both modalities. Its main limitation is that it does not take into account prostate and patient motion during biopsy. Two systems (Artemis and Uronav) have been developed to partially circumvent this drawback. Organ-based registration (Koelis) does not aim to track the TRUS probe, but the prostate itself to compute in a 3D acquisition the TRUS prostate shape, allowing for a registration with the corresponding 3D MRI shape. This system is not limited by prostate/patient motion and allows for a deformation of the organ during registration. Pros and cons of each technique and the rationale for a targeted biopsy only policy are discussed.     

Image Registration Accuracy of a 3‐Dimensional Transrectal Ultrasound–Guided Prostate Biopsy System

Objective. For a follow‐up prostate biopsy procedure, it is useful to know the previous biopsy locations in anatomic relation to the current transrectal ultrasound (TRUS) scan. The goal of this study was to validate the performance of a 3‐dimensional TRUS‐guided prostate biopsy system that can accurately relocate previous biopsy sites. Methods. To correlate biopsy locations from a sequence of visits by a patient, the prostate surface data obtained from a previous visit needs to be registered to the follow‐up visits. Two interpolation methods, thin‐plate spline (TPS) and elastic warping (EW), were tested for registration of the TRUS prostate image to follow‐up scans. We validated our biopsy system using a custom‐built phantom. Beads were embedded inside the phantom and were located in each TRUS scan. We recorded the locations of the beads before and after pressures were applied to the phantom and then compared them with computer‐estimated positions to measure performance. Results. In our experiments, before system processing, the mean target registration error (TRE) ± SD was 6.4 ± 4.5 mm (range, 3–13 mm). After registration and TPS interpolation, the TRE was 5.0 ± 1.03 mm (range, 2–8 mm). After registration and EW interpolation, the TRE was 2.7 ± 0.99 mm (range, 1–4 mm). Elastic warping was significantly better than the TPS in most cases (P < .0011). For clinical applications, EW can be implemented on a graphics processing unit with an execution time of less than 2.5 seconds. Conclusions. Elastic warping interpolation yields more accurate results than the TPS for registration of TRUS prostate images. Experimental results indicate potential for clinical application of this method.     

MR to ultrasound registration for image-guided prostate interventions

A deformable registration method is described that enables automatic alignment of magnetic resonance (MR) and 3D transrectal ultrasound (TRUS) images of the prostate gland. The method employs a novel "model-to-image" registration approach in which a deformable model of the gland surface, derived from an MR image, is registered automatically to a TRUS volume by maximising the likelihood of a particular model shape given a voxel-intensity-based feature that represents an estimate of surface normal vectors at the boundary of the gland. The deformation of the surface model is constrained by a patient-specific statistical model of gland deformation, which is trained using data provided by biomechanical simulations. Each simulation predicts the motion of a volumetric finite element mesh due to the random placement of a TRUS probe in the rectum. The use of biomechanical modelling in this way also allows a dense displacement field to be calculated within the prostate, which is then used to non-rigidly warp the MR image to match the TRUS image. Using data acquired from eight patients, and anatomical landmarks to quantify the registration accuracy, the median final RMS target registration error after performing 100 MR-TRUS registrations for each patient was 2.40 mm.     

A 2D/3D correspondence building method for reconstruction of a patient-specific 3D bone surface model using point distribution models and calibrated X-ray images

Constructing a 3D bone surface model from a limited number of calibrated 2D X-ray images (e.g. 2) and a 3D point distribution model is a challenging task, especially, when we would like to construct a patient-specific surface model of a bone with pathology. One of the key steps for such a 2D/3D reconstruction is to establish correspondences between the 2D images and the 3D model. This paper presents a 2D/3D correspondence building method based on a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformations to find a fraction of best matched 2D point pairs between features extracted from the X-ray images and those extracted from the 3D model. The estimated point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one, whose solutions are well studied. Incorporating this 2D/3D correspondence building method, a 2D/3D reconstruction scheme combining a statistical instantiation with a regularized shape deformation has been developed. Comprehensive experiments on clinical datasets and on images of cadaveric femurs with both non-pathologic and pathologic cases are designed and conducted to evaluate the performance of the 2D/3D correspondence building method as well as that of the 2D/3D reconstruction scheme. Quantitative and qualitative evaluation results are given, which demonstrate the validity of the present method and scheme.     

Complications and limitations related to periprostatic local anesthesia before TRUS-guided prostate biopsy

PURPOSE: To assess the frequency of complications specifically related to local anesthetic infiltration prior to transrectal ultrasound (TRUS)-guided prostate biopsy. METHODS: A total of 200 patients receiving 10 cm(3) (5 cm(3) on each side) of 2% lidocaine injected around the periprostatic nerve plexus under TRUS guidance before prostate biopsy were included. Various complications presumed to be associated with local anesthesia were noted during and after the biopsy procedure. Two weeks later, periprostatic tissue integrity and vascularization were re-examined with TRUS Doppler examination to assess for fibrosis or infection. RESULTS: The most common finding was pain due to puncture with the needle used for local anesthesia (27%). Also recorded were the need for repeated injections during the biopsy procedure (4.5%), symptoms associated with systemic lidocaine toxicity (2%), urinary incontinence (1.5%), and degradation of the image resolution due to anesthetic injection (1%). Increased vascularization within the periprostatic region was uncommon (2%) on the 2-week follow-up examination. No TRUS finding consistent with rectal wall hematoma or other periprostatic change and no erectile dysfunction associated with the procedure occurred. There was a significant difference in overall pain scores between the subgroups of patients (p < 0.001). CONCLUSION: TRUS-guided periprostatic nerve blockade is an effective method for relieving discomfort from prostate biopsy with very few complications.     

MR-guided interventions for prostate cancer

MR imaging is currently the most effective diagnostic imaging tool for visualizing the anatomy and pathology of the prostate gland. Currently, the practicality and cost effectiveness of transrectal ultrasound dominates image guidance for needle-based prostate interventions. Challenges to the integration of diagnostic and interventional MR imaging have included the lack of real-time feed-back, the complexity of the imaging technique, and limited access to the perineum within the geometric constraints of the MR imaging scanner. Two basic strategies have been explored and clinically demonstrated in the literature: (1) coregistration of previously acquired diagnostic MR imaging to interventional TRUS or open scanner MR images, and (2) stereotactic needle interventions within conventional diagnostic scanners using careful patient positioning or the aid of simple manipulators. Currently, researchers are developing techniques that render MR imaging the method of choice for the direct guidance of many procedures. This article focuses on needle-based interventions for prostate cancer, including biopsy, brachytherapy, and thermal therapy With rapid progress in biologic imaging of the prostate gland, the authors believe that MR imaging guidance will play an increasing role in the diagnosis and treatment of prostate cancer.     

Use of transrectal ultrasound-guided biopsy in the diagnosis of pelvic malignancies

PURPOSE: To describe our experience with transrectal ultrasound (TRUS)-guided needle biopsy of pelvic malignancies. METHODS: Eleven patients with clinical suspecion of advanced malignant pelvic tumor were referred to our institution with a history of unsuccessful CT-guided biopsy, although a target lesion was demonstrated on pelvic CT or MRI. Cholin-PET and FDG-18-PET were also obtained individually in each patient. TRUS was performed using a commercially available three-dimensional scanner. Biopsies were performed with an 18G biopsy gun. In 9 of 11 patients, biopsy was successfully performed under analgesia, whereas general anesthesia was required in the other 2 patients. RESULTS: The lesions were identified with TRUS in all patients, and biopsies were taken successfully under TRUS guidance. In all patients, the harvested material was of excellent quality and was adequate for definitive pathological diagnosis. Pathological results included 6 nodal metastases from transitional cell carcinoma, 1 case of lymph node metastasis from prostate cancer, 1 paravesical recurrence of cervical cancer, 1 metastasis from cecal cancer, and 2 cases of paravesical metastasis of a gastric cancer. CONCLUSION: TRUS-guided biopsy is a useful technique for the diagnosis of pelvic malignancies. It is faster and less expensive than CT-guided biopsy, and in most cases sufficient material can be harvested for a definitive pathological diagnosis.     

Role of transrectal ultrasonography in the prediction of prostate cancer: artificial neural network analysis.

OBJECTIVE: The purpose of this study was to evaluate the diagnostic performance of an artificial neural network (ANN) model with and without transrectal ultrasonographic (TRUS) data. METHODS: Six hundred eighty-four consecutive patients who had undergone TRUS-guided prostate biopsy from May 2003 to January 2005 were enrolled. We constructed 2 ANN models. One (ANN_1) incorporated patient age, digital rectal examination findings, prostate-specific antigen (PSA) level, PSA density, transitional zone volume, and PSA density in the transitional zone as input data, whereas the other (ANN_2) was constructed with the above and TRUS findings as input data. The performances of these 2 ANN models according to PSA levels (group A, 0-4 ng/mL; group B, 4-10 ng/mL; and group C, >10 ng/mL) were evaluated using receiver operating characteristic analysis. RESULTS: Of the 684 patients who underwent prostate biopsy, 214 (31.3%) were confirmed to have prostate cancer; of 137 patients with positive digital rectal examination results, 60 (43.8%) were confirmed to have prostate cancer; and of 131 patients with positive TRUS findings, 93 (71%) were confirmed to have prostate cancer. In groups A, B, and C, the AUCs for ANN_1 were 0.738, 0.753, and 0.774, respectively; the AUCs for ANN_2 were 0.859, 0.797, and 0.894. In all groups, ANN_2 showed better accuracy than ANN_1 (P < .05). CONCLUSIONS: According to receiver operating characteristic analysis, ANN with TRUS findings was found to be more accurate than ANN without. We conclude that TRUS findings should be included as an input data component in ANN models used to diagnose prostate cancer.     

2D-3D shape reconstruction of the distal femur from stereo X-ray imaging using statistical shape models

Three-dimensional patient specific bone models are required in a range of medical applications, such as pre-operative surgery planning and improved guidance during surgery, modeling and simulation, and in vivo bone motion tracking. Shape reconstruction from a small number of X-ray images is desired as it lowers both the acquisition costs and the radiation dose compared to CT. We propose a method for pose estimation and shape reconstruction of 3D bone surfaces from two (or more) calibrated X-ray images using a statistical shape model (SSM). User interaction is limited to manual initialization of the mean shape. The proposed method combines a 3D distance based objective function with automatic edge selection on a Canny edge map. Landmark-edge correspondences are weighted based on the orientation difference of the projected silhouette and the corresponding image edge. The method was evaluated by rigid pose estimation of ground truth shapes as well as 3D shape estimation using a SSM of the whole femur, from stereo cadaver X-rays, in vivo biplane fluoroscopy image-pairs, and an in vivo biplane fluoroscopic sequence. Ground truth shapes for all experiments were available in the form of CT segmentations. Rigid registration of the ground truth shape to the biplane fluoroscopy achieved sub-millimeter accuracy (0.68 mm) measured as root mean squared (RMS) point-to-surface (P2S) distance. The non-rigid reconstruction from the biplane fluoroscopy using the SSM also showed promising results (1.68 mm RMS P2S). A feasibility study on one fluoroscopic time series illustrates the potential of the method for motion and shape estimation from fluoroscopic sequences with minimal user interaction.     

基于人工智能经直肠超声诊断前列腺癌研究进展

人工智能（AI）技术现已用于辅助经直肠超声（TRUS）诊断前列腺癌（PCa）,主要包括建立计算机辅助诊断系统和预测模型及引导前列腺穿刺活检,以提高诊断效率和诊断准确率,并降低检查成本。本文对基于AI的TRUS诊断PCa研究进展进行综述。     

Automatic Shape-Based Level Set Segmentation for Needle Tracking in 3-D TRUS-Guided Prostate Brachytherapy

Prostate brachytherapy is an effective treatment for early prostate cancer. The success depends critically on the correct needle implant positions. We have devised an automatic shape-based level set segmentation tool for needle tracking in 3-D transrectal ultrasound (TRUS) images, which uses the shape information and level set technique to localize the needle position and estimate the endpoint of needle in real-time. The 3-D TRUS images used in the evaluation of our tools were obtained using a 2-D TRUS transducer from Ultrasonix (Richmond, BC, Canada) and a computer-controlled stepper motor system from Thorlabs (Newton, NJ, USA). The accuracy and feedback mechanism had been validated using prostate phantoms and compared with 3-D positions of these needles derived from experts' readings. The experts' segmentation of needles from 3-D computed tomography images was the ground truth in this study. The difference between automatic and expert segmentations are within 0.1 mm for 17 of 19 implanted needles. The mean errors of automatic segmentations by comparing with the ground truth are within 0.25 mm. Our automated method allows real-time TRUS-based needle placement difference within one pixel compared with manual expert segementation.     

Transrectal ultrasonography for the detection and staging of carcinoma of the prostate

Transrectal ultrasonography (TRUS) has become the most frequently used imaging modality for the prostate. The internal architecture of the prostate is readily detailed by TRUS, and the procedure allows an accurate measurement of prostate size. Carcinoma of the prostate has a characteristic hypoechoic pattern which is sometimes distinct from the normal echo pattern of the peripheral portion of the prostate. TRUS does not have sufficient sensitivity and specificity to support its use for routine screening for prostate cancer. In men with an abnormality of either digital rectal palpation of the prostate or serum prostate specific antigen, TRUS is useful for directing prostate biopsy. Transrectal core biopsies are obtained under ultrasound direction, and precise placement of the biopsy needles can be accomplished using TRUS. © 1996 John Wiley & Sons, Inc.     

Three-dimensional registration of prostate images from histology and ultrasound

A whole mount histology protocol for 3-D tissue reconstruction to compare the size and spatial location of tumors (and other components) identified in histology data with that from 3-D ultrasound (US) images is presented. Prostate specimens are imaged in 3-D using B-mode (US) and sonoelastography. The prostate surface is outlined in each B-mode image and a 3-D surface reconstruction is made. The specimen is then prepared for whole mount histology and the histology slides are digitally reconstructed to make a 3-D surface. These two surfaces are then aligned using a 3-D correlation algorithm, and the tumor boundary determined by the pathologist is compared with that using sonoelastography. 3-D images showing the overlapping histology and sonoelastography of prostate surface reconstructions for one prostate are presented to illustrate the technique; results for four prostates yielded an accuracy of 92% +/- 3%.     

Contrast‐Enhanced Transrectal Ultrasound for Follow‐up After Focal HIFU Ablation for Prostate Cancer

The optimal strategy for imaging after focal therapy for prostate cancer is evolving. This series is an initial report on the use of contrast‐enhanced transrectal ultrasound (TRUS) in follow‐up of patients after high‐intensity focused ultrasound (HIFU) hemiablation for prostate cancer. In 7 patients who underwent HIFU hemiablation, contrast‐enhanced TRUS findings were as follows: (1) contrast‐enhanced TRUS clearly showed the HIFU ablation defect as a sharply marginated nonenhancing zone in all patients; (2) contrast‐enhanced TRUS identified suspicious foci of recurrent enhancement within the ablation zone in 2 patients, facilitating image‐guided prostate biopsy, which showed prostate cancer; and (3) contrast‐enhanced TRUS findings correlated with multiparametric magnetic resonance imaging and biopsy histologic findings.