9,171 research outputs found

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

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    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

    Deep Learning Guided Autonomous Surgery: Guiding Small Needles into Sub-Millimeter Scale Blood Vessels

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    We propose a general strategy for autonomous guidance and insertion of a needle into a retinal blood vessel. The main challenges underpinning this task are the accurate placement of the needle-tip on the target vein and a careful needle insertion maneuver to avoid double-puncturing the vein, while dealing with challenging kinematic constraints and depth-estimation uncertainty. Following how surgeons perform this task purely based on visual feedback, we develop a system which relies solely on \emph{monocular} visual cues by combining data-driven kinematic and contact estimation, visual-servoing, and model-based optimal control. By relying on both known kinematic models, as well as deep-learning based perception modules, the system can localize the surgical needle tip and detect needle-tissue interactions and venipuncture events. The outputs from these perception modules are then combined with a motion planning framework that uses visual-servoing and optimal control to cannulate the target vein, while respecting kinematic constraints that consider the safety of the procedure. We demonstrate that we can reliably and consistently perform needle insertion in the domain of retinal surgery, specifically in performing retinal vein cannulation. Using cadaveric pig eyes, we demonstrate that our system can navigate to target veins within 22μm\mu m XY accuracy and perform the entire procedure in less than 35 seconds on average, and all 24 trials performed on 4 pig eyes were successful. Preliminary comparison study against a human operator show that our system is consistently more accurate and safer, especially during safety-critical needle-tissue interactions. To the best of the authors' knowledge, this work accomplishes a first demonstration of autonomous retinal vein cannulation at a clinically-relevant setting using animal tissues

    An Optimization-based Approach to Dosimetry Planning for Brachytherapy

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    Prostate cancer is the second leading cause of death from cancer in North American men, with a reported 32,050 deaths in the U.S. alone for 2010; lung cancer is reported as the number one leading cause of death from cancer in both men and women in North America, its estimated death toll in the U.S. alone in 2010 is over 157,000. One method of treating prostate cancer patients nowadays is by Low Dose Rate Brachytherapy, a process where radioactive seeds are placed in or near the tumor site to kill cancerous cells. For lung cancer, brachytherapy has begun to attract attention due to the advent of robotics assistance and there is increasing research currently in the area. While brachytherapy is gaining popularity as a commonly practiced method for treating cancer patients, the procedure itself has several drawbacks that require further research. One such drawback is that the dosimetry plan created based on the pre-operative imaging may not be accurate due to (a) the change in the tumor’s size as a result of the time elapsed between pre-operative imaging and seed implantation; and (b) movement of the organ under treatment from the position and orientation in pre­ operative imaging; this is particularly important in the case of lung brachytherapy as it would have to take into account lung deflation and respiratory and cardiac motions as well. In addition, seeds may be misplaced during implantation as a result of limitation of the manual or robotic procedures. When this happens, the final dose coverage of the tumor is no longer the same as the intended coverage in the dosimetry plan. In this thesis, the development, implementation and evaluation of two algorithms are presented.The first algorithm is the pre-planning algorithm, which aims to reduce the errors in the dosimetry plan caused by the change in the tumor’s size by providing a mechanism to perform dosimetry planning on-line. By doing this, the first algorithm can also eliminate the need for the patient to be imaged twice, so that the same set of images can be used for dosimetry planning as well as seed implantation. The second algorithm deals with intra-operative dynamic dose optimization, where real­ time seed compensation is performed to compensate for any seed misplacements so that an optimal final coverage can be achieved. The results of the experimental evaluation performed in this project indicate that these algorithms are feasible and have the potential to be applied in the operating room following appropriate animal and clinical validation

    Robotics-Assisted Needle Steering for Percutaneous Interventions: Modeling and Experiments

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    Needle insertion and guidance plays an important role in medical procedures such as brachytherapy and biopsy. Flexible needles have the potential to facilitate precise targeting and avoid collisions during medical interventions while reducing trauma to the patient and post-puncture issues. Nevertheless, error introduced during guidance degrades the effectiveness of the planned therapy or diagnosis. Although steering using flexible bevel-tip needles provides great mobility and dexterity, a major barrier is the complexity of needle-tissue interaction that does not lend itself to intuitive control. To overcome this problem, a robotic system can be employed to perform trajectory planning and tracking by manipulation of the needle base. This research project focuses on a control-theoretic approach and draws on the rich literature from control and systems theory to model needle-tissue interaction and needle flexion and then design a robotics-based strategy for needle insertion/steering. The resulting solutions will directly benefit a wide range of needle-based interventions. The outcome of this computer-assisted approach will not only enable us to perform efficient preoperative trajectory planning, but will also provide more insight into needle-tissue interaction that will be helpful in developing advanced intraoperative algorithms for needle steering. Experimental validation of the proposed methodologies was carried out on a state of-the-art 5-DOF robotic system designed and constructed in-house primarily for prostate brachytherapy. The system is equipped with a Nano43 6-DOF force/torque sensor (ATI Industrial Automation) to measure forces and torques acting on the needle shaft. In our setup, an Aurora electromagnetic tracker (Northern Digital Inc.) is the sensing device used for measuring needle deflection. A multi-threaded application for control, sensor readings, data logging and communication over the ethernet was developed using Microsoft Visual C 2005, MATLAB 2007 and the QuaRC Toolbox (Quanser Inc.). Various artificial phantoms were developed so as to create a realistic medium in terms of elasticity and insertion force ranges; however, they simulated a uniform environment without exhibiting complexities of organic tissues. Experiments were also conducted on beef liver and fresh chicken breast, beef, and ham, to investigate the behavior of a variety biological tissues

    Targeted prostate biopsy using statistical image analysis

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    Abstract-In this paper, a method for maximizing the probability of prostate cancer detection via biopsy is presented, by combining image analysis and optimization techniques. This method consists of three major steps. First, a statistical atlas of the spatial distribution of prostate cancer is constructed from histological images obtained from radical prostatectomy specimen. Second, a probabilistic optimization framework is employed to optimize the biopsy strategy, so that the probability of cancer detection is maximized under needle placement uncertainties. Finally, the optimized biopsy strategy generated in the atlas space is mapped to a specific patient space using an automated segmentation and elastic registration method. Cross-validation experiments showed that the predictive power of the optimized biopsy strategy for cancer detection reached the 94%-96% levels for 6-7 biopsy cores, which is significantly better than standard random-systematic biopsy protocols, thereby encouraging further investigation of optimized biopsy strategies in prospective clinical studies. Index Terms-Biopsy optimization, prostate cancer, spatial normalization, statistical image analysis

    Prostate biopsy tracking with deformation estimation

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    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±\pm0.52mm using manually segmented fiducials on 687 registered volumes stemming from 40 patients. A clinical protocol for assisted biopsy acquisition was designed and implemented as a biopsy assistance system, which allows to overcome the draw-backs of the standard biopsy procedure.Comment: Medical Image Analysis (2011) epub ahead of prin

    Thoracoscopic detection of occult indeterminate pulmonary nodules using bronchoscopic pleural dye marking

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    Background: The annual incidence of a small indeterminate pulmonary nodule (IPN) on computed tomography (CT) scan remains high. While traditional paradigms exist, the integration of new technologies into these diagnostic and treatment algorithms can result in alternative, potentially more efficient methods of managing these findings. Methods: We report on an alternative diagnostic and therapeutic strategy for the management of an IPN. This approach combines electromagnetic navigational bronchoscopy (ENB) with an updated approach to placement of a pleural dye marker. This technique lends itself to a minimally invasive wedge resection via either video-assisted thoracoscopic surgery (VATS) or a robotic approach. Results: Subsequent to alterations in the procedure, a cohort of 22 patients with an IPN was reviewed. Navigation was possible in 21 out of 22 patients with one patient excluded based on airway anatomy. The remaining 21 patients underwent ENB with pleural dye marking followed by minimally invasive wedge resection. The median size of the nodules was 13.4 mm (range: 7–29). There were no complications from the ENB procedure. Indigo carmine dye was used in ten patients. Methylene blue was used in the remaining 11 patients. In 81% of cases, the visceral pleural marker was visible at the time of surgery. In one patient, there was diffuse staining of the parietal pleura. In three additional patients, no dye was identified within the hemithorax. In all cases where dye marker was present on the visceral pleural surface, it was in proximity to the IPN and part of the excised specimen. Conclusions: ENB with pleural dye marking can provide a safe and effective method to localize an IPN and can allow for subsequent minimally invasive resection. Depending on the characteristics and location of the nodule, this method may allow more rapid identification intraoperatively

    New Technology and Techniques for Needle-Based Magnetic Resonance Image-Guided Prostate Focal Therapy

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    The most common diagnosis of prostate cancer is that of localized disease, and unfortunately the optimal type of treatment for these men is not yet certain. Magnetic resonance image (MRI)-guided focal laser ablation (FLA) therapy is a promising potential treatment option for select men with localized prostate cancer, and may result in fewer side effects than whole-gland therapies, while still achieving oncologic control. The objective of this thesis was to develop methods of accurately guiding needles to the prostate within the bore of a clinical MRI scanner for MRI-guided FLA therapy. To achieve this goal, a mechatronic needle guidance system was developed. The system enables precise targeting of prostate tumours through angulated trajectories and insertion of needles with the patient in the bore of a clinical MRI scanner. After confirming sufficient accuracy in phantoms, and good MRI-compatibility, the system was used to guide needles for MRI-guided FLA therapy in eight patients. Results from this case series demonstrated an improvement in needle guidance time and ease of needle delivery compared to conventional approaches. Methods of more reliable treatment planning were sought, leading to the development of a systematic treatment planning method, and Monte Carlo simulations of needle placement uncertainty. The result was an estimate of the maximum size of focal target that can be confidently ablated using the mechatronic needle guidance system, leading to better guidelines for patient eligibility. These results also quantified the benefit that could be gained with improved techniques for needle guidance
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