GPU-based 3D iceball modeling for fast cryoablation simulation and planning

Purpose The elimination of abdominal tumors by percutaneous cryoablation has been shown to be an effective and less invasive alternative to open surgery. Cryoablation destroys malignant cells by freezing them with one or more cryoprobes inserted into the tumor through the skin. Alternating cycles of freezing and thawing produce an enveloping iceball that causes the tumor necrosis. Planning such a procedure is difficult and time-consuming, as it is necessary to plan the number and cryoprobe locations and predict the iceball shape which is also influenced by the presence of heating sources, e.g., major blood vessels and warm saline solution, injected to protect surrounding structures from the cold. Methods This paper describes a method for fast GPU-based iceball modeling based on the simulation of thermal propagation in the tissue. Our algorithm solves the heat equation within a cube around the cryoprobes tips and accounts for the presence of heating sources around the iceball. Results Experimental results of two studies have been obtained: an ex vivo warm gel setup and simulation on five retrospective patient cases of kidney tumors cryoablation with various levels of complexity of the vascular structure and warm saline solution around the tumor tissue. The experiments have been conducted in various conditions of cube size and algorithm implementations. Results show that it is possible to obtain an accurate result within seconds. Conclusion The promising results indicate that our method yields accurate iceball shape predictions in a short time and is suitable for surgical planning

Hybrid Simulation and Planning Platform for Cryosurgery with Microsoft HoloLens

Cryosurgery is a technique of growing popularity involving tissue ablation under controlled freezing. Technological advancement of devices along with surgical technique improvements have turned cryosurgery from an experimental to an established option for treating several diseases. However, cryosurgery is still limited by inaccurate planning based primarily on 2D visualization of the patient's preoperative images. Several works have been aimed at modelling cryoablation through heat transfer simulations; however, most software applications do not meet some key requirements for clinical routine use, such as high computational speed and user-friendliness. This work aims to develop an intuitive platform for anatomical understanding and pre-operative planning by integrating the information content of radiological images and cryoprobe specifications either in a 3D virtual environment (desktop application) or in a hybrid simulator, which exploits the potential of the 3D printing and augmented reality functionalities of Microsoft HoloLens. The proposed platform was preliminarily validated for the retrospective planning/simulation of two surgical cases. Results suggest that the platform is easy and quick to learn and could be used in clinical practice to improve anatomical understanding, to make surgical planning easier than the traditional method, and to strengthen the memorization of surgical planning

Image Guided Robots for Urology

This dissertation addresses the development of medical image-guided robots and their applications in urology. Image-guided robots integrate medical image information with robotic precision to assist the planning and execution of the image-guided interventions. Robots guided by two different image modalities, ultrasound and MR image, were developed. Ultrasound image-guided robots manipulate an ultrasound probe and a needle-guide that are calibrated with respect to the robot for image-guided targeting. A method for calibration was developed and verified through the image-guided targeting experiments. Robotic manipulation of the calibrated probe allows acquisition of image slices at precise location, which can be combined to generate a 3D ultrasound image. Software for 3D ultrasound image acquisition, processing, and segmentation was developed as a part of the image-guided robot system. The feasibility of several image-guided intervention procedures using the ultrasound image-guided robot system was tested. The robot was used in a clinical trial of intraoperative transrectal ultrasound (TRUS) guided prostatectomy. The accuracy of TRUS-guided prostate biopsy using the robot was evaluated in a comparative study versus the classic human operation of the probe. Robot controlled palpation and image processing methods were developed for ultrasound elastography imaging of the prostate. An ultrasound to CT image-fusion method using the robot as a common reference was developed for percutaneous access of the kidney. MRI-guided robots were developed for transrectal and transperineal prostate biopsy. Extensive in-vitro tests were performed to ensure MRI compatibility and image-guided accuracy of the robots. The transrectal robot was evaluated in an animal study and the transperineal robot is undergoing a clinical trial. The collection of methods and algorithms presented in this dissertation can contribute to the development of image-guided robots that may provide less invasive and more precise interventions in urology, interventional radiology, and other fields