Robotic Transrectal Ultrasound Guided Prostate Biopsy

A prostate seed implantation robot system based on human-computer interactions: Augmented reality and voice control

The technology of robot-assisted prostate seed implantation has developed rapidly. However, during the process, there are some problems to be solved, such as non-intuitive visualization effects and complicated robot control. To improve the intelligence and visualization of the operation process, a voice control technology of prostate seed implantation robot in augmented reality environment was proposed. Initially, the MRI image of the prostate was denoised and segmented. The three-dimensional model of prostate and its surrounding tissues was reconstructed by surface rendering technology. Combined with holographic application program, the augmented reality system of prostate seed implantation was built. An improved singular value decomposition three-dimensional registration algorithm based on iterative closest point was proposed, and the results of three-dimensional registration experiments verified that the algorithm could effectively improve the three-dimensional registration accuracy. A fusion algorithm based on spectral subtraction and BP neural network was proposed. The experimental results showed that the average delay of the fusion algorithm was 1.314 s, and the overall response time of the integrated system was 1.5 s. The fusion algorithm could effectively improve the reliability of the voice control system, and the integrated system could meet the responsiveness requirements of prostate seed implantation.

TransVFS: A spatio-temporal local-global transformer for vision-based force sensing during ultrasound-guided prostate biopsy

Robot-assisted prostate biopsy is a new technology to diagnose prostate cancer, but its safety is influenced by the inability of robots to sense the tool-tissue interaction force accurately during biopsy. Recently, vision based force sensing (VFS) provides a potential solution to this issue by utilizing image sequences to infer the interaction force. However, the existing mainstream VFS methods cannot realize the accurate force sensing due to the adoption of convolutional or recurrent neural network to learn deformation from the optical images and some of these methods are not efficient especially when the recurrent convolutional operations are involved. This paper has presented a Transformer based VFS (TransVFS) method by leveraging ultrasound volume sequences acquired during prostate biopsy. The TransVFS method uses a spatio-temporal local-global Transformer to capture the local image details and the global dependency simultaneously to learn prostate deformations for force estimation. Distinctively, our method explores both the spatial and temporal attention mechanisms for image feature learning, thereby addressing the influence of the low ultrasound image resolution and the unclear prostate boundary on the accurate force estimation. Meanwhile, the two efficient local-global attention modules are introduced to reduce 4D spatio-temporal computation burden by utilizing the factorized spatio-temporal processing strategy, thereby facilitating the fast force estimation. Experiments on prostate phantom and beagle dogs show that our method significantly outperforms existing VFS methods and other spatio-temporal Transformer models. The TransVFS method surpasses the most competitive compared method ResNet3dGRU by providing the mean absolute errors of force estimation, i.e., 70.4 ± 60.0 millinewton (mN) vs 123.7 ± 95.6 mN, on the transabdominal ultrasound dataset of dogs.

Likelihood of sampling prostate cancer at systematic biopsy as a function of gland volume and number of cores

BACKGROUND

Pre-biopsy multiparametric magnetic resonance imaging (mpMRI) of the prostate is used to conduct targeted prostate biopsy (TB), guided by ultrasound and registered (fused) to the MRI. Systematic biopsy (SB) continues to be used together with TB or in mpMRI-negative patients. There is insufficient evidence on how to use SB to inform clinical decision-making in the mpMRI era. The purpose of this study was to estimate the effect of prostate volume and number of SB cores on sampling clinically significant prostate cancer (csPCa) using a simulation method based on clinical data.

METHODS

SBs were simulated using data from 42 patients enrolled in a transrectal ultrasound robot-assisted biopsy trial. Linear mixed models were used to examine the relationship between the number of SB cores and prostate volume on 1) clinically significant cancer detection probability (csCDP) and 2) percent of mpMRI depicted regions of interest (ROIs) sampled with the SB.

RESULTS

Median values and interquartile range (IQR) were 47.16 cm3 (35.61-65.57) for prostate volume, 0.57 cm3 (0.39-0.83) for ROI volume, and 4.0 (2-4) for PI-RADS v2.1 scores on MRI. csCDP increased with the increasing number of simulated SB cores and decreased substantially with larger prostate volume. Similarly, the percent of ROIs sampled increased with the increasing number of simulated SB cores and was lower for prostate volumes ≥60 cm3 compared to glands <60 cm3.

CONCLUSIONS

The effect of the number of SBs performed on detecting csPCa varies largely with gland volume. The common 12-core SB can achieve adequate cancer detection and sampling of ROIs in smaller glands, but not in larger glands. In addition to TB or in mpMRI-negative patients, the number of SB cores can be adjusted to prostate volume. Performing 12-core SB alone in ≥60 cm3 glands results in inadequate sampling and potential PCa underdiagnosis.

Computer-aided detection of prostate cancer in early stages using multi-parameter MRI: A promising approach for early diagnosis

BACKGROUND

Transrectal ultrasound-guided prostate biopsy is the gold standard diagnostic test for prostate cancer, but it is an invasive examination of non-targeted puncture and has a high false-negative rate.

OBJECTIVE

In this study, we aimed to develop a computer-assisted prostate cancer diagnosis method based on multiparametric MRI (mpMRI) images.

METHODS

We retrospectively collected 106 patients who underwent radical prostatectomy after diagnosis with prostate biopsy. mpMRI images, including T2 weighted imaging (T2WI), diffusion weighted imaging (DWI), and dynamic-contrast enhanced (DCE), and were accordingly analyzed. We extracted the region of interest (ROI) about the tumor and benign area on the three sequential MRI axial images at the same level. The ROI data of 433 mpMRI images were obtained, of which 202 were benign and 231 were malignant. Of those, 50 benign and 50 malignant images were used for training, and the 333 images were used for verification. Five main feature groups, including histogram, GLCM, GLGCM, wavelet-based multi-fractional Brownian motion features and Minkowski function features, were extracted from the mpMRI images. The selected characteristic parameters were analyzed by MATLAB software, and three analysis methods with higher accuracy were selected.

RESULTS

Through prostate cancer identification based on mpMRI images, we found that the system uses 58 texture features and 3 classification algorithms, including Support Vector Machine (SVM), K-nearest Neighbor (KNN), and Ensemble Learning (EL), performed well. In the T2WI-based classification results, the SVM achieved the optimal accuracy and AUC values of 64.3% and 0.67. In the DCE-based classification results, the SVM achieved the optimal accuracy and AUC values of 72.2% and 0.77. In the DWI-based classification results, the ensemble learning achieved optimal accuracy as well as AUC values of 75.1% and 0.82. In the classification results based on all data combinations, the SVM achieved the optimal accuracy and AUC values of 66.4% and 0.73.

CONCLUSION

The proposed computer-aided diagnosis system provides a good assessment of the diagnosis of the prostate cancer, which may reduce the burden of radiologists and improve the early diagnosis of prostate cancer.

Navigation and Robotics in Interventional Oncology: Current Status and Future Roadmap

Interventional oncology (IO) is the field of Interventional Radiology that provides minimally invasive procedures under imaging guidance for the diagnosis and treatment of malignant tumors. Sophisticated devices can be utilized to increase standardization, accuracy, outcomes, and "repeatability" in performing percutaneous Interventional Oncology techniques. These technologies can reduce variability, reduce human error, and outperform human hand-to-eye coordination and spatial relations, thus potentially normalizing an otherwise broad diversity of IO techniques, impacting simulation, training, navigation, outcomes, and performance, as well as verification of desired minimum ablation margin or other measures of successful procedures. Stereotactic navigation and robotic systems may yield specific advantages, such as the potential to reduce procedure duration and ionizing radiation exposure during the procedure and, at the same time, increase accuracy. Enhanced accuracy, in turn, is linked to improved outcomes in many clinical scenarios. The present review focuses on the current role of percutaneous navigation systems and robotics in diagnostic and therapeutic Interventional Oncology procedures. The currently available alternatives are presented, including their potential impact on clinical practice as reflected in the peer-reviewed medical literature. A review of such data may inform wiser investment of time and resources toward the most impactful IR/IO applications of robotics and navigation to both standardize and address unmet clinical needs.

Boundary delineation in transrectal ultrasound images for region of interest of prostate

Accurate and robust prostate segmentation in transrectal ultrasound (TRUS) images is of great interest for ultrasound-guided brachytherapy for prostate cancer. However, the current practice of manual segmentation is difficult, time-consuming, and prone to errors. To overcome these challenges, we developed an accurate prostate segmentation framework (A-ProSeg) for TRUS images. The proposed segmentation method includes three innovation steps: (1) acquiring the sequence of vertices by using an improved polygonal segment-based method with a small number of radiologist-defined seed points as prior points; (2) establishing an optimal machine learning-based method by using the improved evolutionary neural network; and (3) obtaining smooth contours of the prostate region of interest using the optimized machine learning-based method. The proposed method was evaluated on 266 patients who underwent prostate cancer brachytherapy. The proposed method achieved a high performance against the ground truth with a Dice similarity coefficient of 96.2% ± 2.4%, a Jaccard similarity coefficient of 94.4% ± 3.3%, and an accuracy of 95.7% ± 2.7%; these values are all higher than those obtained using state-of-the-art methods. A sensitivity evaluation on different noise levels demonstrated that our method achieved high robustness against changes in image quality. Meanwhile, an ablation study was performed, and the significance of all the key components of the proposed method was demonstrated.

The impact of robotic-assisted transperineal biopsy of the prostate on erectile function

BACKGROUND

Prostate biopsy represents one of the most frequently performed urologic procedures worldwide and therefore presupposes knowledge on potential effects like on the erectile function, especially in extensive or repeated biopsies. The robotic-assisted biopsy system (Mona Lisa) offers a minimal invasive approach via only two incision points ensuring maximal accuracy combined with protection of the neurovascular bundle of the prostate.

OBJECTIVE

Our purpose was to analyse the impact of robotic-assisted transperineal biopsy of the prostate on the erectile function.

METHODS

Our prospective study analyses the outcomes of 210 patients, who had undergone minimal-invasive, transperineal robotic-assisted biopsy of the prostate at the University Hospital Basel from January 2020 to March 2022 and provided sufficient data. Of these, 157 (74.8%) were included in final analysis.

RESULTS

Mean (range) age, prostate volume, PSA and IIEF-5 score at baseline were 63.8 years (46.1-83.6), 46.4 ml (9-310), 13.2 ng/ml (0.2-561), and 18.8 points (6-25), respectively. EF before and 1 month after intervention was assessed with the IIEF-5 questionnaire for the whole cohort. No significant change of IIEF-5 was observed for the whole cohort with a mean (± SD) decrease of 0.4 (± 3.1) points. Except for patients > 69 years, subgroup analysis revealed no change of IIEF-5 in statistically significant manner for all subgroups. Number of biopsy cores (< 20 and ≥ 20), previous biopsies and active surveillance showed no significant influence.

CONCLUSION

Our results suggest that the minimally invasive and highly precise robotic technique can spare the erectile function without limiting the extent of biopsy and without compromising diagnostic accuracy.

Image-guided prostate biopsy robots: A review

At present, the incidence of prostate cancer (PCa) in men is increasing year by year. So, the early diagnosis of PCa is of great significance. Transrectal ultrasonography (TRUS)-guided biopsy is a common method for diagnosing PCa. The biopsy process is performed manually by urologists but the diagnostic rate is only 20%-30% and its reliability and accuracy can no longer meet clinical needs. The image-guided prostate biopsy robot has the advantages of a high degree of automation, does not rely on the skills and experience of operators, reduces the work intensity and operation time of urologists and so on. Capable of delivering biopsy needles to pre-defined biopsy locations with minimal needle placement errors, it makes up for the shortcomings of traditional free-hand biopsy and improves the reliability and accuracy of biopsy. The integration of medical imaging technology and the robotic system is an important means for accurate tumor location, biopsy puncture path planning and visualization. This paper mainly reviews image-guided prostate biopsy robots. According to the existing literature, guidance modalities are divided into magnetic resonance imaging (MRI), ultrasound (US) and fusion image. First, the robot structure research by different guided methods is the main line and the actuators and material research of these guided modalities is the auxiliary line to introduce and compare. Second, the robot image-guided localization technology is discussed. Finally, the image-guided prostate biopsy robot is summarized and suggestions for future development are provided.

A systematic review of image-guided, surgical robot-assisted percutaneous puncture: Challenges and benefits

Percutaneous puncture is a common medical procedure that involves accessing an internal organ or tissue through the skin. Image guidance and surgical robots have been increasingly used to assist with percutaneous procedures, but the challenges and benefits of these technologies have not been thoroughly explored. The aims of this systematic review are to furnish an overview of the challenges and benefits of image-guided, surgical robot-assisted percutaneous puncture and to provide evidence on this approach. We searched several electronic databases for studies on image-guided, surgical robot-assisted percutaneous punctures published between January 2018 and December 2022. The final analysis refers to 53 studies in total. The results of this review suggest that image guidance and surgical robots can improve the accuracy and precision of percutaneous procedures, decrease radiation exposure to patients and medical personnel and lower the risk of complications. However, there are many challenges related to the use of these technologies, such as the integration of the robot and operating room, immature robotic perception, and deviation of needle insertion. In conclusion, image-guided, surgical robot-assisted percutaneous puncture offers many potential benefits, but further research is needed to fully understand the challenges and optimize the utilization of these technologies in clinical practice.

Robot-Assisted Magnetic Resonance Imaging-Targeted versus Systematic Prostate Biopsy; Systematic Review and Meta-Analysis

INTRODUCTION

Robot-assisted devices have been recently developed for use in prostate biopsy. However, it is possible advantages over standard biopsy remain unclear. We aimed to assess the diagnostic performance and safety of robot-assisted targeted (RA-TB) and systematic prostate biopsies (RA-SB).

METHODS

A systematic literature search was performed in MEDLINE and Scopus databases. The detailed search strategy is available at Prospero (CRD42021269290). The primary outcome was the clinically significant prostate cancer (PCa) detection rate. The secondary outcomes included the overall detection rate of PCa, cancer detection rate per core, and complications.

RESULTS

The clinically significant cancer detection rate, overall cancer detection rate, and "per patient" did not significantly differ between RA-TB and RA-SB [OR = 1.02 (95% CI 0.83; 1.26), p = 0.05, I² = 62% and OR = 0.95 (95% CI 0.78; 1.17), p = 0.17, I² = 40%, respectively]. There were no differences in the clinically insignificant cancer detection rate "per patient" between RA-TB and RA-SB [OR = 0.81 (95% CI 0.54; 1.21), p = 0.31, I² = 0%]. RA-TB had a significantly higher cancer detection rate "per core" [OR = 3.01 (95% CI 2.77; 3.27), p < 0.0001, I² = 96%].

CONCLUSION

RA-TB and RA-SB are both technically feasible and have comparable clinical significance and overall PCa detection rates.

An adaptive beamformer based on dynamic phase coherence factor for pixel-based medical ultrasound imaging

BACKGROUND

Pixel-based beamforming realizes dynamic focusing at the pixel level with a focused beam by assuming that the received signals are composed of spherical pulses. Far-focused pixel-based (FPB) imaging was proposed to avoid artifacts around the focal depth. However, the contrast improvement is limited.

OBJECTIVE

We propose an adaptive weighting method based on dynamic phase coherence factor (DPCF) to improve the image contrast while preserving the speckle pattern.

METHODS

The phase variation is dynamically estimated based on the noise energy proportion of echo signals and it is used to calculate phase coherence weights for suppressing interference and preserving desired signals. A depth-dependent parameter is designed for DPCF to enhance the performance of noise and clutter suppression in the far-field region. We further use the subarray averaging technique to smooth the speckle texture.

RESULTS

The proposed method was evaluated on simulated, phantom experimental, and in vivo data. Results show that, compared with the phase coherence factor (PCF) based method, DPCF respectively leads to average CR improvements by more than 60% and 24% in simulation and experiment, while obtaining an improved speckle signal-to-noise ratio.

CONCLUSIONS

The proposed method is a potentially valuable approach to obtaining high-quality ultrasound images in clinical applications.

Robotics in Interventional Radiology: Review of Current and Future Applications

This review is a brief overview of the current status and the potential role of robotics in interventional radiology. Literature published in the last decades, with an emphasis on the last 5 years, was reviewed and the technical developments in robotics and navigational systems using CT-, MR- and US-image guidance were analyzed. Potential benefits and disadvantages of their current and future use were evaluated. The role of fusion imaging modalities and artificial intelligence was analyzed in both percutaneous and endovascular procedures. A few hundred articles describing results of single or several systems were included in our analysis.

Ultrasound Probe and Hand-Eye Calibrations for Robot-Assisted Needle Biopsy

In robot-assisted ultrasound-guided needle biopsy, it is essential to conduct calibration of the ultrasound probe and to perform hand-eye calibration of the robot in order to establish a link between intra-operatively acquired ultrasound images and robot-assisted needle insertion. Based on a high-precision optical tracking system, novel methods for ultrasound probe and robot hand-eye calibration are proposed. Specifically, we first fix optically trackable markers to the ultrasound probe and to the robot, respectively. We then design a five-wire phantom to calibrate the ultrasound probe. Finally, an effective method taking advantage of steady movement of the robot but without an additional calibration frame or the need to solve the AX=XB equation is proposed for hand-eye calibration. After calibrations, our system allows for in situ definition of target lesions and aiming trajectories from intra-operatively acquired ultrasound images in order to align the robot for precise needle biopsy. Comprehensive experiments were conducted to evaluate accuracy of different components of our system as well as the overall system accuracy. Experiment results demonstrated the efficacy of the proposed methods.

Semi-Automatic Prostate Segmentation From Ultrasound Images Using Machine Learning and Principal Curve Based on Interpretable Mathematical Model Expression

Accurate prostate segmentation in transrectal ultrasound (TRUS) is a challenging problem due to the low contrast of TRUS images and the presence of imaging artifacts such as speckle and shadow regions. To address this issue, we propose a semi-automatic model termed Hybrid Segmentation Model (H-SegMod) for prostate Region of Interest (ROI) segmentation in TRUS images. H-SegMod contains two cascaded stages. The first stage is to obtain the vertices sequences based on an improved principal curve-based model, where a few radiologist-selected seed points are used as prior. The second stage is to find a map function for describing the smooth prostate contour based on an improved machine learning model. Experimental results show that our proposed model achieved superior segmentation results compared with several other state-of-the-art models, achieving an average Dice Similarity Coefficient (DSC), Jaccard Similarity Coefficient (Ω), and Accuracy (ACC) of 96.5%, 95.2%, and 96.3%, respectively.

Transrectal Ultrasound in Prostate Cancer: Current Utilization, Integration with mpMRI, HIFU and Other Emerging Applications

Transrectal ultrasound (TRUS) has been an invaluable tool in the assessment of prostate size, anatomy and aiding in prostate cancer (PCa) diagnosis for decades. Emerging techniques warrant an investigation into the efficacy of TRUS, how it compares to new techniques, and options to increase the accuracy of prostate cancer diagnosis. Currently, TRUS is used to guide both transrectal and transperineal biopsy approaches with similar cancer detection rates, but lower rates of infection have been reported with the transperineal approach, while lower rates of urinary retention are often reported with the transrectal approach. Multiparametric MRI has substantial benefits for prostate cancer diagnosis and triage such as lesion location, grading, and can be combined with TRUS to perform fusion biopsies targeting specific lesions. Micro-ultrasound generates higher resolution images that traditional ultrasound and has been shown effective at diagnosing PCa, giving it the potential to become a future standard of care. Finally, high-intensity focused ultrasound focal therapy administered via TRUS has been shown to offer safe and effective short-term oncological control for localized disease with low morbidity, and the precise nature makes it a viable option for salvage and repeat therapy.

The Global Research of Artificial Intelligence on Prostate Cancer: A 22-Year Bibliometric Analysis

Background

With the rapid development of technology, artificial intelligence (AI) has been widely used in the diagnosis and prognosis prediction of a variety of diseases, including prostate cancer. Facts have proved that AI has broad prospects in the accurate diagnosis and treatment of prostate cancer.

Objective

This study mainly summarizes the research on the application of artificial intelligence in the field of prostate cancer through bibliometric analysis and explores possible future research hotspots.

Methods

The articles and reviews regarding application of AI in prostate cancer between 1999 and 2020 were selected from Web of Science Core Collection on August 23, 2021. Microsoft Excel 2019 and GraphPad Prism 8 were applied to analyze the targeted variables. VOSviewer (version 1.6.16), Citespace (version 5.8.R2), and a widely used online bibliometric platform were used to conduct co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references, and keywords in this field.

Results

A total of 2,749 articles were selected in this study. AI-related research on prostate cancer increased exponentially in recent years, of which the USA was the most productive country with 1,342 publications, and had close cooperation with many countries. The most productive institution and researcher were the Henry Ford Health System and Tewari. However, the cooperation among most institutions or researchers was not close even if the high research outputs. The result of keyword analysis could divide all studies into three clusters: “Diagnosis and Prediction AI-related study”, “Non-surgery AI-related study”, and “Surgery AI-related study”. Meanwhile, the current research hotspots were “deep learning” and “multiparametric MRI”.

Conclusions

Artificial intelligence has broad application prospects in prostate cancer, and a growing number of scholars are devoted to AI-related research on prostate cancer. Meanwhile, the cooperation among various countries and institutions needs to be strengthened in the future. It can be projected that noninvasive diagnosis and accurate minimally invasive treatment through deep learning technology will still be the research focus in the next few years.

Concurrently bendable and rotatable continuum tubular robot for omnidirectional multi-core transurethral prostate biopsy

A transurethral prostate biopsy device is proposed in this paper, which can shoot a biopsy needle at different angles to take samples from multiple locations within the prostate. Firstly, the traditional prostate biopsy methods, including transrectal prostate biopsy and transperineal prostate biopsy, are introduced and compared. Then, the working principles of the new prostate biopsy procedure are illustrated. The designs of the needle bending system and the flexible needle are presented, and a proofs-of-concept study of the robotic biopsy device is demonstrated. Design parameters, material selection, and control unit are introduced. Experiments are carried out to test and demonstrate the functions of the prototype. Theoretical and measured bending angles are compared and analyzed. The bending system can effectively bend the biopsy needle to any angle between 15 and 45°. The penetration force of the biopsy needle decreases with the increase of the bending angle. The range of rotation of the bending system on one hemisphere is ±25°. Together with the translational motion, the biopsy needle can reach any point within the workspace. Finally, a phantom test and a cadaver experiment were carried out to simulate biopsy.

Diagnostic accuracy and clinical implications of robotic assisted MRI-US fusion guided target saturation biopsy of the prostate

MRI-targeted prostate biopsy improves detection of clinically significant prostate cancer (PCa). However, up to 70% of PCa lesions display intralesional tumor heterogeneity. Current target sampling strategies do not yet adequately account for this finding. This prospective study included 118 patients who underwent transperineal robotic assisted biopsy of the prostate. We identified a total of 58 PCa-positive PI-RADS lesions. We compared diagnostic accuracy of a target-saturation biopsy strategy to accuracy of single, two, or three randomly selected targeted biopsy cores and analysed potential clinical implications. Intralesional detection of clinically significant cancer (ISUP ≥ 2) was 78.3% for target-saturation biopsy and 39.1%, 52.2%, and 67.4% for one, two, and three targeted cores, respectively. Target-saturation biopsies led to a more accurate characterization of PCa in terms of Gleason score and reduced rates of significant cancer missed. Compared to one, two, and three targeted biopsy cores, target-saturation biopsies led to intensified staging procedures in 21.7%, 10.9, and 8.7% of patients, and ultimately to a potential change in therapy in 39.1%, 26.1%, and 10.9% of patients. This work presents the concept of robotic-assisted target saturation biopsy. This technique has the potential to improve diagnostic accuracy and thus individual staging procedures and treatment decisions.

Toward autonomous robotic prostate biopsy: a pilot study

Purpose

We present the validation of PROST, a robotic device for prostate biopsy. PROST is designed to minimize human error by introducing some autonomy in the execution of the key steps of the procedure, i.e., target selection, image fusion and needle positioning. The robot allows executing a targeted biopsy through ultrasound (US) guidance and fusion with magnetic resonance (MR) images, where the target was defined.

Methods

PROST is a parallel robot with 4 degrees of freedom (DOF) to orient the needle and 1 DOF to rotate the US probe. We reached a calibration error of less than 2 mm, computed as the difference between the needle positioning in robot coordinates and in the US image. The autonomy of the robot is given by the image analysis software, which employs deep learning techniques, the integrated image fusion algorithms and automatic computation of the needle trajectory. For safety reasons, the insertion of the needle is assigned to the doctor.

Results

System performance was evaluated in terms of positioning accuracy. Tests were performed on a 3D printed object with nine 2-mm spherical targets and on an anatomical commercial phantom that simulates human prostate with three lesions and the surrounding structures. The average accuracy reached in the laboratory experiments was \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ 1.30 \pm 0.44\, \text {mm}$$\end{document}1.30±0.44mm in the first test and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ 1.54 \pm 0.34\, \text {mm}$$\end{document}1.54±0.34mm in the second test.

Conclusions

We introduced a first prototype of a prostate biopsy robot that has the potential to increase the detection of clinically significant prostate cancer and, by including some level of autonomy, to simplify the procedure, to reduce human errors and shorten training time. The use of a robot for the biopsy of the prostate will create the possibility to include also a treatment, such as focal ablation, to be delivered through the same system.

Image-guided robots for low dose rate prostate brachytherapy: Perspectives on safety in design and use

BACKGROUND

Image-guided brachytherapy (BT) robots can be used to assist urologists during seed implantation, thereby improving therapeutic effects. However, safety issues must be considered in the design of such robots, including their structure, mechanical movements, function, materials and actuators. Previous reviews focused on image-guided prostate BT robot technology (e.g., imaging and robot navigation technology and robot system introduction); however, this review is the first time that safety issues have been investigated as part of a study on low-dose-rate (LDR) prostate BT robots.

METHODS

Multiple electronic databases were searched for LDR prostate BT robot articles published during the last 24 years (1996-2020), with a particular focus on two aspects of robots: safety in design and use.

RESULTS

We retrieved a total of 26 LDR prostate BT robots. BT robots were divided into ultrasound, computed tomography, magnetic resonance imaging and fusion-guided systems. The conditions associated with each system were then analysed to develop a set of requirements for the safety of prostate BT robots. Recommendations are also provided for future BT robot development.

CONCLUSIONS

The transrectal approach for prostate seed implantation is safer than the traditional transperineal approach. Research into the control of a steerable needle by the urologists and robot, the needle deflection model, and robotic automated needle changing and seed injection equipment should be pursued in a future study.

Medical Robotics for Ultrasound Imaging: Current Systems and Future Trends

Purpose of Review

This review provides an overview of the most recent robotic ultrasound systems that have contemporary emerged over the past five years, highlighting their status and future directions. The systems are categorized based on their level of robot autonomy (LORA).

Recent Findings

Teleoperating systems show the highest level of technical maturity. Collaborative assisting and autonomous systems are still in the research phase, with a focus on ultrasound image processing and force adaptation strategies. However, missing key factors are clinical studies and appropriate safety strategies. Future research will likely focus on artificial intelligence and virtual/augmented reality to improve image understanding and ergonomics.

Summary

A review on robotic ultrasound systems is presented in which first technical specifications are outlined. Hereafter, the literature of the past five years is subdivided into teleoperation, collaborative assistance, or autonomous systems based on LORA. Finally, future trends for robotic ultrasound systems are reviewed with a focus on artificial intelligence and virtual/augmented reality.

Ultrasound-guided needle insertion robotic system for percutaneous puncture

PURPOSE

Ultrasound (US)-guided percutaneous puncture technology can realize real-time, minimally invasive interventional therapy without radiation. The location accuracy of the puncture needle directly determines the precision and safety of the operation. It is a challenge for novices and young surgeons to perform a free-hand puncture guided by the ultrasound images to achieve the desired accuracy. This work aims to develop a robotic system to assist surgeons to perform percutaneous punctures with high precision.

METHODS

An US-guided puncture robot was designed to allow the mounting and control of the needle to achieve localization and insertion. The US probe fitted within the puncture robot was held by a passive arm. Moreover, the puncture robot was calibrated with a novel calibration method to achieve coordinate transformation between the robot and the US image. The system allowed the operators to plan the puncture target and puncture path on US images, and the robot performed needle insertion automatically. Five groups of puncture experiments were performed to verify the validity and accuracy of the proposed robotic system.

RESULTS

Assisted by the robotic system, the positioning and orientation accuracies of the needle insertion were 0.9 ± 0.29 mm and 0.76 ± 0.34°, respectively. These are improved compared with the results obtained with the free-hand puncture (1.82 ± 0.51 mm and 2.79 ± 1.32°, respectively). Moreover, the proposed robotic system can reduce the operation time and number of needle insertions (14.28 ± 3.21 s and one needle insertion, respectively), compared with the free-hand puncture (25.14 ± 6.09 s and 1.96 ± 0.68 needle insertions, respectively).

CONCLUSION

A robotic system for percutaneous puncture guided by US images was developed and demonstrated. The experimental results indicate that the proposed system is accurate and feasible. It can assist novices and young surgeons to perform the puncture operation with increased accuracy.

Integration of Real-Time Image Fusion in the Robotic-Assisted Treatment of Hepatocellular Carcinoma

Simple Summary

Hepatocellular carcinoma is one of the leading causes of cancer-related deaths worldwide. An image fusion system is developed for the robotic-assisted treatment of hepatocellular carcinoma, which is not only capable of imaging data interpretation and reconstruction, but also automatic tumor detection. The optimization and integration of the image fusion system within a novel robotic system has the potential to demonstrate the feasibility of the robotic-assisted targeted treatment of hepatocellular carcinoma by showing benefits such as precision, patients safety and procedure ergonomics.

Abstract

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide, with its mortality rate correlated with the tumor staging; i.e., early detection and treatment are important factors for the survival rate of patients. This paper presents the development of a novel visualization and detection system for HCC, which is a composing module of a robotic system for the targeted treatment of HCC. The system has two modules, one for the tumor visualization that uses image fusion (IF) between computerized tomography (CT) obtained preoperatively and real-time ultrasound (US), and the second module for HCC automatic detection from CT images. Convolutional neural networks (CNN) are used for the tumor segmentation which were trained using 152 contrast-enhanced CT images. Probabilistic maps are shown as well as 3D representation of HCC within the liver tissue. The development of the visualization and detection system represents a milestone in testing the feasibility of a novel robotic system in the targeted treatment of HCC. Further optimizations are planned for the tumor visualization and detection system with the aim of introducing more relevant functions and increase its accuracy.

Intelligent magnetic manipulation for gastrointestinal ultrasound

Diagnostic endoscopy in the gastrointestinal tract has remained largely unchanged for decades and is limited to the visualization of the tissue surface, the collection of biopsy samples for diagnoses, and minor interventions such as clipping or tissue removal. In this work, we present the autonomous servoing of a magnetic capsule robot for in-situ, subsurface diagnostics of microanatomy. We investigated and showed the feasibility of closed-loop magnetic control using digitized microultrasound (μUS) feedback; this is crucial for obtaining robust imaging in an unknown and unconstrained environment. We demonstrated the functionality of an autonomous servoing algorithm that uses μUS feedback, both on benchtop trials as well as in-vivo in a porcine model. We have validated this magnetic-μUS servoing in instances of autonomous linear probe motion and were able to locate markers in an agar phantom with 1.0 ± 0.9 mm position accuracy using a fusion of robot localization and μUS image information. This work demonstrates the feasibility of closed-loop robotic μUS imaging in the bowel without the need for either a rigid physical link between the transducer and extracorporeal tools or complex manual manipulation.

Polypoidal Choroidal Vasculopathy

Purpose of review

The aim of this review is to summarize developments in the treatment of active polypoidal choroidal vasculopathy (PCV). PCV is associated with a poor visual prognosis as a consequence the condition's hallmark polypoidal dilatation and a branching network resulting in recurrent hemorrhages and serous leakage.

Recent findings

Recent research has provided new insights into the pathogenesis of PCV. While still considered a subtype of age-related macular degeneration, suggestions that PCV belongs to a spectrum of conditions that present with a pachychoroid are increasingly well accepted. Treatment remains challenging. Combination therapy (photodynamic therapy (PDT) and intravitreal anti-vascular endothelial growth factor (VEGF)) is associated with higher polyp closure rate, but polyp closure rate has not been correlated with superior visual outcomes. Current data points to non-inferiority of anti-VEGF alone versus combined with PDT when final vision acuity is the study outcome.

Summary

PCV remains a clinical challenge. Classification and treatment of the condition continues to evolve. Combination therapy may not be superior to anti-VEGF treatment alone in terms of visual acuity outcome, however data on long-term recurrence should be compared in formulating preferred treatment plans.