Kinematic Alignment Technique Outperforms Mechanical Alignment in Simultaneous Bilateral Total Knee Arthroplasty: A Randomized Controlled Trial.

BACKGROUND: The aim of this study was to compare the clinical results of kinematic alignment (KA) with those of mechanical alignment (MA) in single-stage bilateral total knee arthroplasty. METHODS: In this double-blinded randomized controlled trial, 65 patients who had bilateral knee osteoarthritis underwent simultaneous bilateral total knee arthroplasty. One knee was randomly selected to be operated on with the calipered-KA technique and the other with MA. The participants were assessed via the Oxford Knee Score, Western Ontario and McMaster Universities Osteoarthritis Index questionnaire, and visual analog scale before the surgery and the same plus the Forgotten Joint Score at their last follow-up visit, 2 years postoperatively. Maximum knee flexion and the time reaching maximum knee flexion, named the recovery time, were also recorded. Hip-knee-ankle angle, medial proximal tibial angle, and lateral distal femoral angle were measured before and after the surgery using 3-joint-view radiographs. RESULTS: At 2 years, there were significant differences between the KA and MA techniques in terms of duration of surgery, recovery time, and final Western Ontario and McMaster Universities Osteoarthritis Index, Forgotten Joint Score, and maximum flexion range in favor of KA (P < .05), but no significant difference in visual analog scale score or Oxford Knee Score. In patients who have a preferred knee, the KA knee was preferred over the MA knee by most patients. No prosthetic failure or revision was reported in either group. CONCLUSIONS: The KA technique yields acceptable functional outcomes compared to the MA technique. The KA technique was associated with a shorter surgery time, a faster recovery time, and higher patient satisfaction in 2-year follow-ups. Larger multicenter studies with longer follow-ups are warranted to confirm these findings. LEVEL OF EVIDENCE: I.

Enhancing skill learning with dual-user haptic feedback: insights from a task-specific approach.

Introduction: This study was to examine whether inter-user haptic feedback would have a differential impact on skill acquisition based on the nature of the surgical task involved. Specifically, we hypothesized that haptic feedback would facilitate target orientation more than cutting tasks in the context of laparoscopic surgery. Methods: Ten novice participants were recruited and assigned to one of two training groups. Each group underwent six half-hour training sessions dedicated to laparoscopic pattern-cutting tasks. In the haptic group, five participants received expert guidance during the training sessions, whereas the remaining five participants in the control group engaged in self-practice. All trials were recorded on video, enabling a comparative analysis of task performance between the participants' left hand (target manipulation) and right hand (cutting task). Additionally, the number of haptic feedback instances provided to the trainees in the haptic group was recorded. Results: Practice led to a reduction in total task time, grasping time, and cutting errors. However, no significant differences were observed between the two training groups, except for the grasping time, where haptic feedback significantly reduced the grasping time compared to the control group. Moreover, the frequency of haptic feedback instances provided to the trainees was notably higher for the grasping than for the cutting task. Discussion: Our study suggests that haptic feedback has a more substantial impact on orientation tasks than on cutting tasks in laparoscopic surgery training. However, we acknowledge that a larger sample size would provide a more robust evaluation of this effect.

Surgical tooltip motion metrics assessment using virtual marker: an objective approach to skill assessment for minimally invasive surgery.

PURPOSE: Surgical skill assessment has primarily been performed using checklists or rating scales, which are prone to bias and subjectivity. To tackle this shortcoming, assessment of surgical tool motion can be implemented to objectively classify skill levels. Due to the challenges involved in motion tracking of surgical tooltips in minimally invasive surgeries, formerly used assessment approaches may not be feasible for real-world skill assessment. We proposed an assessment approach based on the virtual marker on surgical tooltips to derive the tooltip's 3D position and introduced a novel metric for surgical skill assessment. METHODS: We obtained the 3D tooltip position based on markers placed on the tool handle. Then, we derived tooltip motion metrics to identify the metrics differentiating the skill levels for objective surgical skill assessment. We proposed a new tooltip motion metric, i.e., motion inconsistency, that can assess the skill level, and also can evaluate the stage of skill learning. In this study, peg transfer, dual transfer, and rubber band translocation tasks were included, and nine novices, five surgical residents and five attending general surgeons participated. RESULTS: Our analyses showed that tooltip path length (p [Formula: see text] 0.007) and path length along the instrument axis (p [Formula: see text] 0.014) differed across the three skill levels in all the tasks and decreased by skill level. Tooltip motion inconsistency showed significant differences among the three skill levels in the dual transfer (p [Formula: see text] 0.025) and the rubber band translocation tasks (p [Formula: see text] 0.021). Lastly, bimanual dexterity differed across the three skill levels in all the tasks (p [Formula: see text] 0.012) and increased by skill level. CONCLUSION: Depth perception ability (indicated by shorter tooltip path lengths along the instrument axis), bimanual dexterity, tooltip motion consistency, and economical tooltip movements (shorter tooltip path lengths) are related to surgical skill. Our findings can contribute to objective surgical skill assessment, reducing subjectivity, bias, and associated costs.

Motion Smoothness-Based Assessment of Surgical Expertise: The Importance of Selecting Proper Metrics.

The smooth movement of hand/surgical instruments is considered an indicator of skilled, coordinated surgical performance. Jerky surgical instrument movements or hand tremors can cause unwanted damages to the surgical site. Different methods have been used in previous studies for assessing motion smoothness, causing conflicting results regarding the comparison among surgical skill levels. We recruited four attending surgeons, five surgical residents, and nine novices. The participants conducted three simulated laparoscopic tasks, including peg transfer, bimanual peg transfer, and rubber band translocation. Tooltip motion smoothness was computed using the mean tooltip motion jerk, logarithmic dimensionless tooltip motion jerk, and 95% tooltip motion frequency (originally proposed in this study) to evaluate their capability of surgical skill level differentiation. The results revealed that logarithmic dimensionless motion jerk and 95% motion frequency were capable of distinguishing skill levels, indicated by smoother tooltip movements observed in high compared to low skill levels. Contrarily, mean motion jerk was not able to distinguish the skill levels. Additionally, 95% motion frequency was less affected by the measurement noise since it did not require the calculation of motion jerk, and 95% motion frequency and logarithmic dimensionless motion jerk yielded a better motion smoothness assessment outcome in distinguishing skill levels than mean motion jerk.

Haptic virtual surgery simulation system under field programmable analogue array-based hybrid control.

In this paper, a bilateral haptic virtual surgery simulation system under a hybrid controller was studied. An analogue controller realized by a field programmable analogue array (FPAA) was paralleled in the operator robot side, which reduced the impact of controller discretisation on the system. A system stability conditions under hybrid control with multiple-operators were deduced. The stability analysis indicates that the addition of analogue derivative term widens the range of haptic controls gains that satisfy the multiple-users' stability conditions. Finally, the human's performance of a stiffness discrimination task was studied in an independently developed minimally invasive surgical (MIS) platform. The experiment results show that, human operators under the hybrid controller achieve the highest task success rates.

Robotics and AI for Teleoperation, Tele-Assessment, and Tele-Training for Surgery in the Era of COVID-19: Existing Challenges, and Future Vision.

The unprecedented shock caused by the COVID-19 pandemic has severely influenced the delivery of regular healthcare services. Most non-urgent medical activities, including elective surgeries, have been paused to mitigate the risk of infection and to dedicate medical resources to managing the pandemic. In this regard, not only surgeries are substantially influenced, but also pre- and post-operative assessment of patients and training for surgical procedures have been significantly impacted due to the pandemic. Many countries are planning a phased reopening, which includes the resumption of some surgical procedures. However, it is not clear how the reopening safe-practice guidelines will impact the quality of healthcare delivery. This perspective article evaluates the use of robotics and AI in 1) robotics-assisted surgery, 2) tele-examination of patients for pre- and post-surgery, and 3) tele-training for surgical procedures. Surgeons interact with a large number of staff and patients on a daily basis. Thus, the risk of infection transmission between them raises concerns. In addition, pre- and post-operative assessment also raises concerns about increasing the risk of disease transmission, in particular, since many patients may have other underlying conditions, which can increase their chances of mortality due to the virus. The pandemic has also limited the time and access that trainee surgeons have for training in the OR and/or in the presence of an expert. In this article, we describe existing challenges and possible solutions and suggest future research directions that may be relevant for robotics and AI in addressing the three tasks mentioned above.

Intraoperative optimization of seed implantation plan in breast brachytherapy.

PURPOSE: Low-dose-rate permanent-seed (LDR-PS) brachytherapy has shown a great potential for treating breast cancer. An implantation scheme indicating the template pose and needle trajectories is determined before the operation. However, when performing the pre-planned scheme intraoperatively, a change of the patient's posture will cause seed placements away from the desired locations. Hence, the implantation scheme should update based on the current patient's posture. METHODS: A numerical method of optimizing the implantation scheme for the LDR-PS breast brachytherapy is presented here. The proposed algorithm determines the fewest needle trajectories and template poses for delivering the seeds to the intraoperative desired locations. The clinical demand, such as the minimum distance between the chest wall and the needle, is considered in the optimization process. RESULTS: The method was simulated for a given LDR-PS brachytherapy procedure to evaluate the optimal scheme as the number of the template poses changing. The optimization parameters of the needles' number and the implantation errors are used to adjust the algorithm outcome. The results show that the implantation schemes obtained by our method have a satisfactory accuracy in the cases of 2 or 3 template poses. The computation time is about 76s to 150s according to the number of the template poses from 1 to 3. CONCLUSION: The proposed method can find the optimal implantation scheme corresponding to the current desired seed locations immediately once there is a change of patient's posture. This work can be applied to the robot-assisted LDR-PS breast brachytherapy for improving the operation accuracy and efficiency.

Periodic Kinesthetic Guidance Cannot Expedite Learning Surgical Skills.

Introduction. Connecting multiple haptic devices in a master-slave fashion enables us to deliver kinesthetic (haptic) feedback from 1 person to another. This study examined whether inter-user feedback delivered from an expert to a novice would facilitate skill acquisition of the novice in learning laparoscopic surgery and expedite it compared to traditional methods. Methods. We recruited fourteen novices and divided them into 1 of 2 training groups with 6 half-hour training sessions. The task was precision cutting adopted from one of the tasks listed in Fundamentals of Laparoscopic Surgery using laparoscopic instruments. In the haptic feedback group (haptic), 8 subjects had the chance to passively feel an expert's performance before they started to practice in each training session. In the self-learning group (control), 6 subjects watched a video before practicing. Each session was video recorded, and task performance was measured by task completion time, number of grasper adjustments, and instrument crossings. Cutting accuracy, defined as the percentage of deviation of the cutting line from the predefined line, was analyzed via computer analysis. Results. Results show no significant difference among performance measures between the 2 groups. Participants performed similarly when practicing alone or with periodic haptic feedback. Discussion. Further research will be needed for improving our way of integrating between-person haptic feedback with skills training protocol.

Augmented Reality Guided Needle Biopsy of Soft Tissue: A Pilot Study.

Percutaneous biopsies are popular for extracting suspicious tissue formations (primarily for cancer diagnosis purposes) due to the: relatively low cost, minimal invasiveness, quick procedure times, and low risk for the patient. Despite the advantages provided by percutaneous biopsies, poor needle and tumor visualization is a problem that can result in the clinicians classifying the tumor as benign when it was malignant (false negative). The system developed by the authors aims to address the concern of poor needle and tumor visualization through two virtualization setups. This system is designed to track and visualize the needle and tumor in three-dimensional space using an electromagnetic tracking system. User trials were conducted in which the 10 participants, who were not medically trained, performed a total of 6 tests, each guiding the biopsy needle to the desired location. The users guided the biopsy needle to the desired point on an artificial spherical tumor (diameters of 30, 20, and 10 mm) using the 3D augmented reality (AR) overlay for three trials and a projection on a second monitor (TV) for the other three trials. From the randomized trials, it was found that the participants were able to guide the needle tip 6.5 ± 3.3 mm away from the desired position with an angle deviation of 1.96 ± 1.10° in the AR trials, compared to values of 4.5 ± 2.3 mm and 2.70 ± 1.67° in the TV trials. The results indicate that for simple stationary surgical procedures, an AR display is non-inferior a TV display.

Robotic-Assisted Needle Steering Around Anatomical Obstacles Using Notched Steerable Needles.

Robotic-assisted needle steering can enhance the accuracy of needle-based interventions. Application of current needle steering techniques are restricted by the limited deflection curvature of needles. Here, a novel steerable needle with improved curvature is developed and used with an online motion planner to steer the needle along curved paths inside tissue. The needle is developed by carving series of small notches on the shaft of a standard needle. The notches decrease the needle flexural stiffness, allowing the needle to follow tightly curved paths with small radius of curvature. In this paper, first, a finite element model of the notched needle deflection in tissue is presented. Next, the model is used to estimate the optimal location for the notches on needle's shaft for achieving a desired curvature. Finally, an ultrasound-guided motion planner for needle steering inside tissue is developed and used to demonstrate the capability of the notched needle in achieving high curvature and maneuvering around obstacles in tissue. We simulated a clinical scenario in brachytherapy, where the target is obstructed by the pubic bone and cannot be reached using regular needles. Experimental results show that the target can be reached using the notched needle with a mean accuracy of 1.2 mm. Thus, the proposed needle enables future research on needle steering toward deeper or more difficult-to-reach targets.

Towards robot-assisted anchor deployment in beating-heart mitral valve surgery.

BACKGROUND: Beating-heart intracardiac surgery promises significant benefits for patients compared with cardiopulmonary bypass based procedures. However, the fast motions of the heart introduce serious challenges for surgeons. METHODS: In this work, a new impedance-controlled master-slave telerobotic system is developed to help perform anchor deployment for mitral valve annuloplasty under the guidance of live ultrasound images of the heart. The proposed bilateral teleoperation system can both reflect the non-oscillatory portion of slave-heart tissue interaction force on the surgeon's hand as haptic feedback and implement rapid compensation for the beating heart's motion. The surgical task involves performing anchor deployment on a simulated moving heart tissue to evaluate the effectiveness of the proposed strategy for safely interacting with a moving organ. RESULTS AND CONCLUSIONS: The results obtained show that the telerobotic system increases the success rate of anchor deployment by 100% and reduces the excess force application rate by 70% compared with manual attempts.

Quantifying 125I placement accuracy in prostate brachytherapy using postimplant transrectal ultrasound images.

PURPOSE: The quality of a prostate brachytherapy implant depends on the accurate placement of sources. This study quantifies the misplacement of 125I sources from the intended location using intraoperative ultrasound images. METHODS AND MATERIALS: 125I sources were manually identified in the postimplant ultrasound images and compared to the preoperative plan. Due to the subjective nature of the identifying sources, only sources identified with high confidence were included in the analysis. Misplacements from the original intended coordinate were measured along the X, Y, and Z axes and were stratified between overall misplacements and regions of the prostate gland. RESULTS: A total of 1619 125I sources using 357 strands were implanted in 15 patients' prostate glands, with 1197 (74%) confidently identified for misplacement analysis. The overall mean displacement was 0.49 cm and in the X, Y, and Z direction was 0.13, 0.15, and 0.38 cm, respectively. Greater source misplacement occurred in the anterior part of the prostate gland than the posterior part of the prostate gland by a factor 1.33 (p < 0.0001). Comparing sources in the lateral vs. medial regions of the prostate, no statistically significant differences on source misplacement were observed. Comparing misplacement in the base vs. midgland vs. apex identified the greatest difference between the base and midgland by a factor of 1.29 (p < 0.0001). CONCLUSIONS: This study has identified significant misplacement of 125I sources from their intended locations with the greatest error misplacement occurring in the Z direction. Source misplacement tends to occur more commonly in the anterior gland and in the base of the prostate.

A Hand-Held Assistant for Semiautomated Percutaneous Needle Steering.

OBJECTIVE: Permanent prostate brachytherapy is an effective and popular treatment modality for prostate cancer in which long needles are inserted into the prostate. Challenges associated with manual needle insertion such as needle deflection limit this procedure to primarily treat the entire prostate gland even for patients with localized cancer. In this paper, we present a new semiautomated hand-held needle steering assistant designed to help surgeons improve needle placement accuracy. METHODS: Regular clinical brachytherapy needles are connected to a compact device that the surgeon holds. As the surgeon inserts the needle, the device rotates the needle base on a measured and calculated basis in order to produce a desired trajectory of the needle tip. A novel needle-tissue interaction model and a steering algorithm calculate such control actions based on ultrasound images of the needle in tissue. The assistant can also apply controlled longitudinal microvibrations to the needle that reduce needle-tissue friction. RESULTS: Experimental validation of the proposed system in phantom and ex-vivo biological tissue report an average needle targeting accuracy of 0.33 mm over 72 needle insertions in 12 different experimental scenarios. CONCLUSION: We introduce a new framework for needle steering in prostate brachytherapy in which the surgeon remains in charge of the needle insertion. The device weighs 160 g, making it easy to incorporate with current insertion techniques. SIGNIFICANCE: Expected benefits of the proposed system include more precise needle targeting accuracy, which can result in improved focal treatment of prostate cancer.

A data-driven soft sensor for needle deflection in heterogeneous tissue using just-in-time modelling.

Global modelling has traditionally been the approach taken to estimate needle deflection in soft tissue. In this paper, we propose a new method based on local data-driven modelling of needle deflection. External measurement of needle-tissue interactions is collected from several insertions in ex vivo tissue to form a cloud of data. Inputs to the system are the needle insertion depth, axial rotations, and the forces and torques measured at the needle base by a force sensor. When a new insertion is performed, the just-in-time learning method estimates the model outputs given the current inputs to the needle-tissue system and the historical database. The query is compared to every observation in the database and is given weights according to some similarity criteria. Only a subset of historical data that is most relevant to the query is selected and a local linear model is fit to the selected points to estimate the query output. The model outputs the 3D deflection of the needle tip and the needle insertion force. The proposed approach is validated in ex vivo multilayered biological tissue in different needle insertion scenarios. Experimental results in five different case studies indicate an accuracy in predicting needle deflection of 0.81 and 1.24 mm in the horizontal and vertical lanes, respectively, and an accuracy of 0.5 N in predicting the needle insertion force over 216 needle insertions.

Semi-Automated Needle Steering in Biological Tissue Using an Ultrasound-Based Deflection Predictor.

The performance of needle-based interventions depends on the accuracy of needle tip positioning. Here, a novel needle steering strategy is proposed that enhances accuracy of needle steering. In our approach the surgeon is in charge of needle insertion to ensure the safety of operation, while the needle tip bevel location is robotically controlled to minimize the targeting error. The system has two main components: (1) a real-time predictor for estimating future needle deflection as it is steered inside soft tissue, and (2) an online motion planner that calculates control decisions and steers the needle toward the target by iterative optimization of the needle deflection predictions. The predictor uses the ultrasound-based curvature information to estimate the needle deflection. Given the specification of anatomical obstacles and a target from preoperative images, the motion planner uses the deflection predictions to estimate control actions, i.e., the depth(s) at which the needle should be rotated to reach the target. Ex-vivo needle insertions are performed with and without obstacle to validate our approach. The results demonstrate the needle steering strategy guides the needle to the targets with a maximum error of 1.22 mm.

Three-Dimensional Needle Shape Estimation in TRUS-Guided Prostate Brachytherapy Using 2-D Ultrasound Images.

In this paper, we propose an automated method to reconstruct the three-dimensional (3-D) needle shape during needle insertion procedures using only 2-D transverse ultrasound (US) images. Using a set of transverse US images, image processing and random sample consensus are used to locate the needle within each image and estimate the needle shape. The method is validated with an in vitro needle insertion setup and a transparent tissue phantom, where two orthogonal cameras are used to capture the true 3-D needle shape for verification. Results showed that the use of at least three images obtained at 75% of the maximum insertion depth or greater allows for maximum needle shape estimation errors of less than 2 mm. In addition, the needle shape can be calculated consistently as long as the needle can be identified in 30% of the transverse US images obtained. Application to permanent prostate brachytherapy is also presented, where the estimated needle shape is compared to manual segmentation and sagittal US images. Our method is intended to help to assess needle placement during manual or robot-assisted needle insertion procedures after the needle has been inserted.

Estimating needle tip deflection in biological tissue from a single transverse ultrasound image: application to brachytherapy.

PURPOSE: This paper proposes a method to predict the deflection of a flexible needle inserted into soft tissue based on the observation of deflection at a single point along the needle shaft. METHODS: We model the needle-tissue as a discretized structure composed of several virtual, weightless, rigid links connected by virtual helical springs whose stiffness coefficient is found using a pattern search algorithm that only requires the force applied at the needle tip during insertion and the needle deflection measured at an arbitrary insertion depth. Needle tip deflections can then be predicted for different insertion depths. RESULTS: Verification of the proposed method in synthetic and biological tissue shows a deflection estimation error of [Formula: see text]2 mm for images acquired at 35 % or more of the maximum insertion depth, and decreases to 1 mm for images acquired closer to the final insertion depth. We also demonstrate the utility of the model for prostate brachytherapy, where in vivo needle deflection measurements obtained during early stages of insertion are used to predict the needle deflection further along the insertion process. CONCLUSION: The method can predict needle deflection based on the observation of deflection at a single point. The ultrasound probe can be maintained at the same position during insertion of the needle, which avoids complications of tissue deformation caused by the motion of the ultrasound probe.

A comparison of US- versus MR-based 3-D Prostate Shapes Using Radial Basis Function Interpolation and Statistical Shape Models.

This paper presents a comparison of three-dimensional (3-D) segmentations of the prostate, based on two-dimensional (2-D) manually segmented contours, obtained using ultrasound (US) and magnetic resonance (MR) imaging data collected from 40 patients diagnosed with localized prostate cancer and scheduled to receive brachytherapy treatment. The approach we propose here for 3-D prostate segmentation first uses radial basis function interpolation to construct a 3-D point distribution model for each prostate. Next, a modified principal axis transformation is utilized for rigid registration of the US and MR images of the same prostate in preparation for the following shape comparison. Then, statistical shape models are used to capture the segmented 3-D prostate geometries for the subsequent cross-modality comparison. Our study includes not only cross-modality geometric comparisons in terms of prostate volumes and dimensions, but also an investigation of interchangeability of the two imaging modalities in terms of automatic contour segmentation at the pre-implant planning stage of prostate brachytherapy treatment. By developing a new scheme to compare the two imaging modalities in terms of the segmented 3-D shapes, we have taken a first step necessary for building coupled US-MR segmentation strategies for prostate brachytherapy pre-implant planning, which at present is predominantly informed by US images only.

Smith predictor-based robot control for ultrasound-guided teleoperated beating-heart surgery.

Performing surgery on fast-moving heart structures while the heart is freely beating is next to impossible. Nevertheless, the ability to do this would greatly benefit patients. By controlling a teleoperated robot to continuously follow the heart's motion, the heart can be made to appear stationary. The surgeon will then be able to operate on a seemingly stationary heart when in reality it is freely beating. The heart's motion is measured from ultrasound images and thus involves a non-negligible delay due to image acquisition and processing, estimated to be 150 ms that, if not compensated for, can cause the teleoperated robot's end-effector (i.e., the surgical tool) to collide with and puncture the heart. This research proposes the use of a Smith predictor to compensate for this time delay in calculating the reference position for the teleoperated robot. The results suggest that heart motion tracking is improved as the introduction of the Smith predictor significantly decreases the mean absolute error, which is the error in making the distance between the robot's end-effector and the heart follow the surgeon's motion, and the mean integrated square error.

Introduction to haptics for neurosurgeons.

Robots are becoming increasingly relevant to neurosurgeons, extending a neurosurgeon's physical capabilities, improving navigation within the surgical landscape when combined with advanced imaging, and propelling the movement toward minimally invasive surgery. Most surgical robots, however, isolate surgeons from the full range of human senses during a procedure. This forces surgeons to rely on vision alone for guidance through the surgical corridor, which limits the capabilities of the system, requires significant operator training, and increases the surgeon's workload. Incorporating haptics into these systems, ie, enabling the surgeon to "feel" forces experienced by the tool tip of the robot, could render these limitations obsolete by making the robot feel more like an extension of the surgeon's own body. Although the use of haptics in neurosurgical robots is still mostly the domain of research, neurosurgeons who keep abreast of this emerging field will be more prepared to take advantage of it as it becomes more prevalent in operating theaters. Thus, this article serves as an introduction to the field of haptics for neurosurgeons. We not only outline the current and future benefits of haptics but also introduce concepts in the fields of robotic technology and computer control. This knowledge will allow readers to be better aware of limitations in the technology that can affect performance and surgical outcomes, and "knowing the right questions to ask" will be invaluable for surgeons who have purchasing power within their departments.