Design of a minimally invasive single port HDR brachytherapy applicator for the treatment of lung cancer

Cancer has become the number one cause of death in Canada and lung cancer is its deadliest form. Surgical resection remains as the treatment of choice for most patients; however, in many cases a less aggressive alternative such as brachytherapy may be preferable. Today, HDR brachytherapy is a relatively common procedure but with current techniques and equipment only tumours close to the main bronchi can be reached. This project describes the design, development and validation of a first prototype of an ultrasound-guided needle guidance system that would enable physicians to perform HDR brachytherapy for the treatment of lung cancer in a minimally invasive manner through the intercostal spaces. The development of the mechanical components is thoroughly described followed by the description of the electronic control system that was developed for this novel mechatronic medical tool. Finally through validation experiments, the approach was shown to be an accurate and viable approach for precisely reaching desired targets with a wide yet flexible needle

Design and Development of a Surgical Robot for Needle-Based Medical Interventions

Lung cancer is the leading cause of cancer related deaths. If diagnosed in a timely manner, the treatment of choice is surgical resection of the cancerous lesions followed by radiotherapy. However, surgical resection may be too invasive for some patients due to old age or weakness. An alternative is minimally invasive needle-based interventions for cancer diagnosis and treatment. This project describes the design, analysis, development and experimental evaluation of a modular, compact, patient-mounted robotic manipulator for lung cancer diagnosis and treatment. In this regard, a novel parallel Remote Centre of Motion (RCM) mechanism is proposed for minimally invasive delivery of needle-based interventions. The proposed robot provides four degrees of freedom (DOFs) to orient and move a surgical needle within a spherical coordinate system. There is an analytical solution for the kinematics of the proposed parallel mechanism and the end-effectors motion is well-conditioned within the required workspace. The RCM is located beneath the skin surface to minimize the invasiveness of the surgical procedure while providing the required workspace to target the cancerous lesions. In addition, the proposed robot benefits from a design capable of measuring the interaction forces between the needle and the tissue. The experimental evaluation of the robot has proved its capability to accurately orient and move a surgical needle within the required workspace. Although this robotic system has been designed for the treatment of lung cancer, it is capable of performing other procedures in the thoracic or abdominal cavity such as liver cancer diagnosis and treatment

InterNAV3D: A Navigation Tool for Robot-Assisted Needle-Based Intervention for the Lung

Lung cancer is one of the leading causes of cancer deaths in North America. There are recent advances in cancer treatment techniques that can treat cancerous tumors, but require a real-time imaging modality to provide intraoperative assistive feedback. Ultrasound (US) imaging is one such modality. However, while its application to the lungs has been limited because of the deterioration of US image quality (due to the presence of air in the lungs); recent work has shown that appropriate lung deflation can help to improve the quality sufficiently to enable intraoperative, US-guided robotics-assisted techniques to be used. The work described in this thesis focuses on this approach. The thesis describes a project undertaken at Canadian Surgical Technologies and Advanced Robotics (CSTAR) that utilizes the image processing techniques to further enhance US images and implements an advanced 3D virtual visualization software approach. The application considered is that for minimally invasive lung cancer treatment using procedures such as brachytherapy and microwave ablation while taking advantage of the accuracy and teleoperation capabilities of surgical robots, to gain higher dexterity and precise control over the therapy tools (needles and probes). A number of modules and widgets are developed and explained which improve the visibility of the physical features of interest in the treatment and help the clinician to have more reliable and accurate control of the treatment. Finally the developed tools are validated with extensive experimental evaluations and future developments are suggested to enhance the scope of the applications

On the Application of Mechanical Vibration in Robotics-Assisted Soft Tissue Intervention

Mechanical vibration as a way of transmitting energy has been an interesting subject to study. While cyclic oscillation is usually associated with fatigue effect, and hence a detrimental factor in failure of structures and machineries, by controlled transmission of vibration, energy can be transferred from the source to the target. In this thesis, the application of such mechanical vibration in a few surgical procedures is demonstrated. Three challenges associated with lung cancer diagnosis and treatment are chosen for this purpose, namely, Motion Compensation, tumor targeting in lung Needle Insertion and Soft Tissue Dissection: A robotic solution is proposed for compensating for the undesirable oscillatory motion of soft tissue (caused by heart beat and respiration) during needle insertion in the lung. An impedance control strategy based on a mechanical vibratory system is implemented to minimize the tissue deformation during needle insertion. A prototype was built to evaluate the proposed approach using: 1) two Mitsubishi PA10-7C robots, one for manipulating the macro part and the other for mimicking the tissue motion, 2) one motorized linear stage to handle the micro part, and 3) a Phantom Omni haptic device for remote manipulation. Experimental results are given to demonstrate the performance of the motion compensation system. A vibration-assisted needle insertion technique has been proposed in order to reduce needle–tissue friction. The LuGre friction model is employed as a basis for the study and the model is extended and analyzed to include the impact of high-frequency vibration on translational friction. Experiments are conducted to evaluate the role of insertion speed as well as vibration frequency on frictional effects. In the experiments conducted, an 18 GA brachytherapy needle was vibrated and inserted into an ex-vivo soft tissue sample using a pair of amplified piezoelectric actuators. Analysis demonstrates that the translational friction can be reduced by introducing a vibratory low-amplitude motion onto a regular insertion profile, which is usually performed at a constant rate. A robotics-assisted articulating ultrasonic surgical scalpel for minimally invasive soft tissue cutting and coagulation is designed and developed. For this purpose, the optimal design of a Langevin transducer with stepped horn profile is presented for internal-body applications. The modeling, optimization and design of the ultrasonic scalpel are performed through equivalent circuit theory and verified by finite element analysis. Moreover, a novel surgical wrist, compatible with the da Vinci® surgical system, with decoupled two degrees-of-freedom (DOFs) is developed that eliminates the strain of pulling cables and electrical wires. The developed instrument is then driven using the dVRK (da Vinci® research kit) and the Classic da Vinci® surgical system

Tactile Sensing System for Lung Tumour Localization during Minimally Invasive Surgery

Video-assisted thoracoscopie surgery (VATS) is becoming a prevalent method for lung cancer treatment. However, VATS suffers from the inability to accurately relay haptic information to the surgeon, often making tumour localization difficult. This limitation was addressed by the design of a tactile sensing system (TSS) consisting of a probe with a tactile sensor and interfacing visualization software. In this thesis, TSS performance was tested to determine the feasibility of implementing the system in VATS. This was accomplished through a series of ex vivo experiments in which the tactile sensor was calibrated and the visualization software was modified to provide haptic information visually to the user, and TSS performance was compared using human and robot palpation methods, and conventional VATS instruments. It was concluded that the device offers the possibility of providing to the surgeon the haptic information lost during surgery, thereby mitigating one of the current limitations of VATS

Computer- and robot-assisted Medical Intervention

Medical robotics includes assistive devices used by the physician in order to make his/her diagnostic or therapeutic practices easier and more efficient. This chapter focuses on such systems. It introduces the general field of Computer-Assisted Medical Interventions, its aims, its different components and describes the place of robots in that context. The evolutions in terms of general design and control paradigms in the development of medical robots are presented and issues specific to that application domain are discussed. A view of existing systems, on-going developments and future trends is given. A case-study is detailed. Other types of robotic help in the medical environment (such as for assisting a handicapped person, for rehabilitation of a patient or for replacement of some damaged/suppressed limbs or organs) are out of the scope of this chapter.Comment: Handbook of Automation, Shimon Nof (Ed.) (2009) 000-00

CRANE: A Redundant, Multi-Degree-of-Freedom Computed Tomography Robot for Heightened Needle Dexterity within a Medical Imaging Bore

Computed Tomography (CT) image guidance enables accurate and safe minimally invasive treatment of diseases, including cancer and chronic pain, with needle-like tools via a percutaneous approach. The physician incrementally inserts and adjusts the needle with intermediate images due to the accuracy limitation of free-hand adjustment and patient physiological motion. Scanning frequency is limited to minimize ionizing radiation exposure for the patient and physician. Robots can provide high positional accuracy and compensate for physiological motion with fewer scans. To accomplish this, the robots must operate within the confined imaging bore while retaining sufficient dexterity to insert and manipulate the needle. This paper presents CRANE: CT Robotic Arm and Needle Emplacer, a CT-compatible robot with a design focused on system dexterity that enables physicians to manipulate and insert needles within the scanner bore as naturally as they would be able to by hand. We define abstract and measurable clinically motivated metrics for in-bore dexterity applicable to general-purpose intra-bore image-guided needle placement robots, develop an automatic robot planning and control method for intra-bore needle manipulation and device setup, and demonstrate the redundant linkage design provides dexterity across various human morphology and meets the clinical requirements for target accuracy during an in-situ evaluation.Comment: 20 pages, 13 figures, Transactions on Robotic

Biomechanical Modeling for Lung Tumor Motion Prediction during Brachytherapy and Radiotherapy

A novel technique is proposed to develop a biomechanical model for estimating lung’s tumor position as a function of respiration cycle time. Continuous tumor motion is a major challenge in lung cancer treatment techniques where the tumor needs to be targeted; e.g. in external beam radiotherapy and brachytherapy. If not accounted for, this motion leads to areas of radiation over and/or under dosage for normal tissue and tumors. In this thesis, biomechanical models were developed for lung tumor motion predication in two distinct cases of lung brachytherapy and lung external beam radiotherapy. The lung and other relevant surrounding organs geometries, loading, boundary conditions and mechanical properties were considered and incorporated properly for each case. While using material model with constant incompressibility is sufficient to model the lung tissue in the brachytherapy case, in external beam radiation therapy the tissue incompressibility varies significantly due to normal breathing. One of the main issues tackled in this research is characterizing lung tissue incompressibility variations and measuring its corresponding parameters as a function of respiration cycle time. Results obtained from an ex-vivo porcine deflated lung indicated feasibility and reliability of using the developed biomechanical model to predict tumor motion during brachytherapy. For external beam radiotherapy, in-silico studies indicated very significant impact of considering the lung tissue incompressibility on the accuracy of predicting tumor motion. Furthermore, ex-vivo porcine lung experiments demonstrated the capability and reliability of the proposed approach for predicting tumor motion as a function of cyclic time. As such, the proposed models have a good potential to be incorporated effectively in computer assisted lung radiotherapy treatment systems

Robotically Steered Needles: A Survey of Neurosurgical Applications and Technical Innovations

This paper surveys both the clinical applications and main technical innovations related to steered needles, with an emphasis on neurosurgery. Technical innovations generally center on curvilinear robots that can adopt a complex path that circumvents critical structures and eloquent brain tissue. These advances include several needle-steering approaches, which consist of tip-based, lengthwise, base motion-driven, and tissue-centered steering strategies. This paper also describes foundational mathematical models for steering, where potential fields, nonholonomic bicycle-like models, spring models, and stochastic approaches are cited. In addition, practical path planning systems are also addressed, where we cite uncertainty modeling in path planning, intraoperative soft tissue shift estimation through imaging scans acquired during the procedure, and simulation-based prediction. Neurosurgical scenarios tend to emphasize straight needles so far, and span deep-brain stimulation (DBS), stereoelectroencephalography (SEEG), intracerebral drug delivery (IDD), stereotactic brain biopsy (SBB), stereotactic needle aspiration for hematoma, cysts and abscesses, and brachytherapy as well as thermal ablation of brain tumors and seizure-generating regions. We emphasize therapeutic considerations and complications that have been documented in conjunction with these applications

A Framework for Tumor Localization in Robot-Assisted Minimally Invasive Surgery

Manual palpation of tissue is frequently used in open surgery, e.g., for localization of tumors and buried vessels and for tissue characterization. The overall objective of this work is to explore how tissue palpation can be performed in Robot-Assisted Minimally Invasive Surgery (RAMIS) using laparoscopic instruments conventionally used in RAMIS. This thesis presents a framework where a surgical tool is moved teleoperatively in a manner analogous to the repetitive pressing motion of a finger during manual palpation. We interpret the changes in parameters due to this motion such as the applied force and the resulting indentation depth to accurately determine the variation in tissue stiffness. This approach requires the sensorization of the laparoscopic tool for force sensing. In our work, we have used a da Vinci needle driver which has been sensorized in our lab at CSTAR for force sensing using Fiber Bragg Grating (FBG). A computer vision algorithm has been developed for 3D surgical tool-tip tracking using the da Vinci \u27s stereo endoscope. This enables us to measure changes in surface indentation resulting from pressing the needle driver on the tissue. The proposed palpation framework is based on the hypothesis that the indentation depth is inversely proportional to the tissue stiffness when a constant pressing force is applied. This was validated in a telemanipulated setup using the da Vinci surgical system with a phantom in which artificial tumors were embedded to represent areas of different stiffnesses. The region with high stiffness representing tumor and region with low stiffness representing healthy tissue showed an average indentation depth change of 5.19 mm and 10.09 mm respectively while maintaining a maximum force of 8N during robot-assisted palpation. These indentation depth variations were then distinguished using the k-means clustering algorithm to classify groups of low and high stiffnesses. The results were presented in a colour-coded map. The unique feature of this framework is its use of a conventional laparoscopic tool and minimal re-design of the existing da Vinci surgical setup. Additional work includes a vision-based algorithm for tracking the motion of the tissue surface such as that of the lung resulting from respiratory and cardiac motion. The extracted motion information was analyzed to characterize the lung tissue stiffness based on the lateral strain variations as the surface inflates and deflates