Biomechanically constrained non-rigid MR-TRUS prostate registration using deep learning based 3D point cloud matching

A non-rigid MR-TRUS image registration framework is proposed for prostate interventions. The registration framework consists of a convolutional neural networks (CNN) for MR prostate segmentation, a CNN for TRUS prostate segmentation and a point-cloud based network for rapid 3D point cloud matching. Volumetric prostate point clouds were generated from the segmented prostate masks using tetrahedron meshing. The point cloud matching network was trained using deformation field that was generated by finite element analysis. Therefore, the network implicitly models the underlying biomechanical constraint when performing point cloud matching. A total of 50 patients’ datasets were used for the network training and testing. Alignment of prostate shapes after registration was evaluated using three metrics including Dice similarity coefficient (DSC), mean surface distance (MSD) and Hausdorff distance (HD). Internal point-to-point registration accuracy was assessed using target registration error (TRE). Jacobian determinant and strain tensors of the predicted deformation field were calculated to analyze the physical fidelity of the deformation field. On average, the mean and standard deviation were 0.94±0.02, 0.90±0.23 mm, 2.96±1.00 mm and 1.57±0.77 mm for DSC, MSD, HD and TRE, respectively. Robustness of our method to point cloud noise was evaluated by adding different levels of noise to the query point clouds. Our results demonstrated that the proposed method could rapidly perform MR-TRUS image registration with good registration accuracy and robustness.     

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.     

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.     

3D prostate model formation from non-parallel 2D ultrasound biopsy images

Biopsy of the prostate using 2D transrectal ultrasound (TRUS) guidance is the current gold standard for diagnosis of prostate cancer; however, the current procedure is limited by using 2D biopsy tools to target 3D biopsy locations. We propose a technique for patient-specific 3D prostate model reconstruction from a sparse collection of non-parallel 2D TRUS biopsy images. Our method conforms to the restrictions of current TRUS biopsy equipment and could be efficiently incorporated into current clinical biopsy procedures for needle guidance without the need for expensive hardware additions. In this paper, the model reconstruction technique is evaluated using simulated biopsy images from 3D TRUS prostate images of 10 biopsy patients. All reconstructed models are compared to their corresponding 3D manually segmented prostate models for evaluation of prostate volume accuracy and surface errors (both regional and global). The number of 2D TRUS biopsy images used for prostate modeling was varied to determine the optimal number of images necessary for accurate prostate surface estimation.     

Multiparametric Ultrasound for Targeting Prostate Cancer: Combining ARFI,SWEI, QUS and B-Mode

Diagnosing prostate cancer through standard transrectal ultrasound (TRUS)-guided biopsy is challenging because of the sensitivity and specificity limitations of B-mode imaging. We used a linear support vector machine (SVM) to combine standard TRUS imaging data with acoustic radiation force impulse (ARFI) imaging data, shear wave elasticity imaging (SWEI) data and quantitative ultrasound (QUS) midband fit data to enhance lesion contrast into a synthesized multiparametric ultrasound volume. This SVM was trained and validated using a subset of 20 patients and tested on a second subset of 10 patients. Multiparametric US led to a statistically significant improvements in contrast, contrast-to-noise ratio (CNR) and generalized CNR (gCNR) when compared with standard TRUS B-mode and SWEI; in contrast and CNR when compared with MF; and in CNR when compared with ARFI. ARFI, MF and SWEI also outperformed TRUS B-mode in contrast, with MF outperforming B-mode in CNR and gCNR as well. ARFI, although only yielding statistically significant differences in contrast compared with TRUS B-mode, captured critical qualitative features for lesion identification. Multiparametric US enhanced lesion visibility metrics and is a promising technique for targeted TRUS-guided prostate biopsy in the future.     

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.     

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.     

Targeted prostate biopsy and MR-guided therapy for prostate cancer

Prostate cancer is the most commonly diagnosed noncutaneous cancer and second-leading cause of death in men. Many patients with clinically organ-confined prostate cancer undergo definitive treatment of the whole gland including radical prostatectomy, radiation therapy, and cryosurgery. Active surveillance is a growing alternative option for patients with documented low-volume, low-grade prostate cancer. With recent advances in software and hardware of MRI, multiparametric MRI of the prostate has been shown to improve the accuracy in detecting and characterizing clinically significant prostate cancer. Targeted biopsy is increasingly utilized to improve the yield of MR-detected, clinically significant prostate cancer and to decrease in detection of indolent prostate cancer. MR-guided targeted biopsy techniques include cognitive MR fusion TRUS biopsy, in-bore transrectal targeted biopsy using robotic transrectal device, and in-bore direct MR-guided transperineal biopsy with a software-based transperineal grid template. In addition, advances in MR compatible thermal ablation technology allow accurate focal or regional delivery of optimal thermal energy to the biopsy-proved, MRI-detected tumor, utilizing cryoablation, laser ablation, high-intensity focused ultrasound ablation under MR guidance and real-time or near simultaneous monitoring of the ablation zone. Herein we present a contemporary review of MR-guided targeted biopsy techniques of MR-detected lesions as well as MR-guided focal or regional thermal ablative therapies for localized naïve and recurrent cancerous foci of the prostate.     

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.     

Spectrum-analysis and neural networks for imaging to detect and treat prostate cancer

Conventional B-mode ultrasound currently is the standard means of imaging the prostate for guiding prostate biopsies and planning brachytherapy to treat prostate cancer. Yet B-mode images do not adequately display cancerous lesions of the prostate. Ultrasonic tissue-type imaging based on spectrum analysis of radiofrequency (rf) echo signals has shown promise for overcoming the limitations of B-mode imaging for visualizing prostate tumors. This method of tissue-type imaging utilizes nonlinear classifiers, such as neural networks, to classify tissue based on values of spectral parameter and clinical variables. Two- and three-dimensional images based on these methods demonstrate potential for guiding prostate biopsies and targeting radiotherapy of prostate cancer. Two-dimensional images are being generated in real time in ultrasound scanners used for real-time biopsy guidance and have been incorporated into commercial dosimetry software used for brachytherapy planning. Three-dimensional renderings show promise for depicting locations and volumes of cancer foci for disease evaluation to assist staging and treatment planning, and potentially for registration or fusion with CT images for targeting external-beam radiotherapy.     

多参数MRI前列腺影像报告和数据系统评分与经直肠超声引导下穿刺病理的相关性分析

目的旨在探讨多参数MRI(multi-parametric MRI,Mp-MRI)前列腺影像报告和数据系统(prostate imaging reporting and data system version 2,PI-RADS V2)评分与经直肠超声引导下穿刺病理的相关性。材料与方法回顾性分析经病理证实的128例前列腺病变患者的MRI资料,其中前列腺癌75例,良性前列腺增生48例、前列腺炎5例,所有患者均行3.0 T MRI扫描,获取完整的T2WI、DWI及DCE图像;由2名前列腺诊断医师在不知患者临床资料及病理的情况下采用PIRADS V2评分标准进行评分,评分结果分别记录;所有患者均行经直肠超声引导下病理穿刺,并由泌尿专业病理诊断医师进行诊断,对前列腺癌则进行Gleason评分。采用Spearman相关分析PI-RADS V2评分与穿刺病理的相关系数,并采用ROC曲线分析PI-RADS V2评分诊断前列腺癌的敏感性、特异性和准确性。结果 PI-RADS V2评分与穿刺病理呈正相关,r=0.887。PI-RADS V2评分诊断前列腺癌的ROC曲线下面积0.975,其敏感性为93.33%,特异性为96.23%,准确性为94.51%,阳性预测值97.22%,阴性预测值91.07%。Gleason评分≥8分的前列腺癌的PI-RADS V2评分为5分。结论 PI-RADS V2评分与经直肠超声引导下穿刺病理的相关性高,PI-RADS V2评分对前列腺疾病的诊断准确性高。     

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.     

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.     

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±0.52 mm 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.     

超声与MRI融合导航穿刺在前列腺癌Gleason分级中的应用研究

目的采用MRI与经直肠超声（TRUS）影像融合靶向穿刺方法进行前列腺癌筛查,探讨融合导航穿刺在前列腺癌Gleason分级中的应用价值。 方法选取2016年12月至2019年3月于浙江大学医学院附属杭州市第一人民医院因可疑前列腺癌行穿刺活检的患者150例,所有患者均先行MRI/TRUS融合导航穿刺,再行常规10针系统穿刺。所有穿刺阳性患者均行腹腔镜下前列腺癌根治术,并取得手术病理结果。比较融合导航穿刺与系统穿刺2种方法对前列腺癌的检出率,将2种方法分别与根治手术标本的Gleason评分情况进行对比分析。 结果150例患者中,共检出前列腺癌72例,其中导航穿刺方法前列腺癌检出率为45.3%（68/150）,系统穿刺方法检出率为40.7%（61/150）,2者比较差异无统计学意义（χ²=0.666,P=0.414）。导航穿刺方法对于Gleason评分≥8分的高危前列腺癌患者的检出率高于系统穿刺（33.8% vs 18.0%）,2者比较差异有统计学意义（χ²=4.131,P=0.042）。导航穿刺与根治术标本Gleason评分符合率为72.1%（49/68）,系统穿刺为54.1%（33/61）,导航穿刺Gleason评分符合率高于系统穿刺法（χ²=4.479,P=0.034）。 结论MRI/TRUS融合导航穿刺获得的前列腺组织标本Gleason分级准确性高,可以增加高危前列腺癌的检出率,为临床治疗决策的制定提供客观依据,其对于前列腺癌的准确诊断和合理治疗具有重要的临床应用价值。     

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.     

Magnetic resonance-guided prostate interventions

We review our experience using an open 0.5-T magnetic resonance (MR) interventional unit to guide procedures in the prostate. This system allows access to the patient and real-time MR imaging simultaneously and has made it possible to perform prostate biopsy and brachytherapy under MR guidance. We review MR imaging of the prostate and its use in targeted therapy, and describe our use of image processing methods such as image registration to further facilitate precise targeting. We describe current developments with a robot assist system being developed to aid radioactive seed placement.     

经直肠超声检查对前列腺癌穿刺点选择的价值

目的：探讨经直肠超声(transrectal ultrasonography，TRUS)对前列腺穿刺活检选点的价值。方法：135例前列腺穿刺活检患者术前行TRUS检查，对324个穿刺部位的声像图与病理结果对照分析。结果：324个穿刺部位病理证实为前列腺癌的120个，前列腺增生症175个，前列腺炎29个。在120个前列腺癌部位TRUS发现异常回声结节、局部血流增多等异常目标的有86个，无异常目标的为34个。TRUS检查对前列腺癌穿刺选点的敏感性71．7％(86／120)，特异性76．5％(156／204)。结论：TRUS有助于前列腺癌穿刺活检的选点。     

Targeted Biopsy With Reduced Number of Cores: Optimal Sampling Scheme in Patients Undergoing Magnetic Resonance Imaging/Transrectal Ultrasound Fusion Prostate Biopsy

The 3 Tesla (3T) magnetic resonance imaging (MRI) combined ultrasound (TRUS) targeted biopsy plus 12-core systematic biopsy (TBx + 12-SBx) was considered a reliable method for prostate cancer (PCa) diagnosis. To find another optimal sampling scheme with fewer cores and the same efficiency as TBx + 12-SBx for prostate biopsy, 113 patients who underwent five different hypothetical sampling schemes were analyzed and compared with TBx + 12-SBx. The detection rates of targeted biopsy plus 6-core lateral systematic biopsy (TBx + lateral 6-SBx) for PCa and clinically significant prostate cancer (csPCa) (99.1% and 96.4%, respectively) were higher than other schemes, and the area under the receiver operating characteristic curve of TBx + lateral 6-SBx for PCa and csPCa (0.991 and 0.990, respectively) were also significantly higher than other sampling schemes except TBx plus 6-core ipsilateral systematic biopsy (TBx + ipsilateral 6-SBx). Additionally, TBx + lateral 6-SBx had the lowest missed diagnosis rate. Thus, the TBx + lateral 6-SBx may be the optimal scheme for patients undergoing MRI/TRUS fusion prostate biopsy.