Fast 4D Ultrasound Registration for Image Guided Liver Interventions

Liver problems are a serious health issue. The common liver problems are hepatitis, fatty liver, liver cancer and liver damage caused by alcohol abuse. Continuous, long term disease may cause a condition of the liver known as the Liver Cirrhosis. Liver cirrhosis makes the liver scarred and hardened up causing portal hypertension. In such a situation the collateral vessels try to bypass the liver as blood cannot freely flow through the liver; causing internal bleeding. One of the treatments of portal hypertension is Transjugular intrahepatic portosystemic shunt (TIPS). In a TIPS procedure a tract in the liver is created that shortcuts two veins in the liver, reducing the portal hypertension. Radiofrequency ablation (RFA) is use for the treatment of liver cancer. In RFA, a needle electrode is placed through the skin into the liver tumor. High-frequency electrical currents are passed through the electrode, creating heat that destroys the cancer cells, without damaging the surrounding liver tissues. TIPS and RFA are minimally invasive procedures, where small incisions are made to perform the surgery and are alternative to open surgery. A minimally invasive alternative has large potential in reducing complication rates, minimizing surgical trauma and reducing hospital stay. However, in these procedures, due to lack of direct eyesight, three-dimensional imaging information about the anatomy and instruments during the intervention is required. The most difficult part of these procedures is the interpretation and selection of oblique views for needle/instrument insertion and target visualization. In our work we develop and evaluate techniques that enable the effective use of 3D ultrasound for image guided interventions. Ultrasound is low cost, mobile and unlike CT and X-rays does not use any harmful radiation in the imaging process. During these procedures, breathing shifts the region of interest and makes it difficult to constantly focus on a region of interest. We provide an approach to correct for the motion due to breathing. Additionally, we propose a method for image fusion of interventional ultrasound and preoperative imaging modalities such as CT for cases where the lesions are visible in CT but not visible in ultrasound. Incorporating CT data during intervention additionally adds greater definition and precision to the ultrasound based navigation system. Concluding, in this thesis, we presented methods and evaluated their accuracies that demonstrate the use of real-time 3D US and its fusion with CT in potentially improving image guidance in minimally invasive US guided liver interventions

マーカーレス腫瘍位置決めを目的とした深層学習に基づく患者固有標的輪郭予測モデルの開発

京都大学新制・課程博士博士(人間健康科学)甲第24542号人健博第113号新制||人健||8(附属図書館)京都大学大学院医学研究科人間健康科学系専攻(主査)教授 中尾 恵, 教授 杉本 直三, 教授 黒田 知宏学位規則第4条第1項該当Doctor of Human Health SciencesKyoto UniversityDFA

Advances in real-time thoracic guidance systems

Substantial tissue motion: \u3e1cm) arises in the thoracic/abdominal cavity due to respiration. There are many clinical applications in which localizing tissue with high accuracy: \u3c1mm) is important. Potential applications include radiation therapy, radio frequency ablation, lung/liver biopsies, and brachytherapy seed placement. Recent efforts have made highly accurate sub-mm 3D localization of discrete points available via electromagnetic: EM) position monitoring. Technology from Calypso Medical allows for simultaneous tracking of up to three implanted wireless transponders. Additionally, Medtronic Navigation uses wired electromagnetic tracking to guide surgical tools for image guided surgery: IGS). Utilizing real-time EM position monitoring, a prototype system was developed to guide a therapeutic linear accelerator to follow a moving target: tumor) within the lung/abdomen. In a clinical setting, electromagnetic transponders would be bronchoscopically implanted into the lung of the patient in or near the tumor. These transponders would ax to the lung tissue in a stable manner and allow real-time position knowledge throughout a course of radiation therapy. During each dose of radiation, the beam is either halted when the target is outside of a given threshold, or in a later study the beam follows the target in real-time based on the EM position monitoring. We present quantitative analysis of the accuracy and efficiency of the radiation therapy tumor tracking system. EM tracking shows promise for IGS applications. Tracking the position of the instrument tip allows for minimally invasive intervention and alleviates the trauma associated with conventional surgery. Current clinical IGS implementations are limited to static targets: e.g. craniospinal, neurological, and orthopedic intervention. We present work on the development of a respiratory correlated image guided surgery: RCIGS) system. In the RCIGS system, target positions are modeled via respiratory correlated imaging: 4DCT) coupled with a breathing surrogate representative of the patient\u27s respiratory phase/amplitude. Once the target position is known with respect to the surrogate, intervention can be performed when the target is in the correct location. The RCIGS system consists of imaging techniques and custom developed software to give visual and auditory feedback to the surgeon indicating both the proper location and time for intervention. Presented here are the details of the IGS lung system along with quantitative results of the system accuracy in motion phantom, ex-vivo porcine lung, and human cadaver environments

A Novel System and Image Processing for Improving 3D Ultrasound-guided Interventional Cancer Procedures

Image-guided medical interventions are diagnostic and therapeutic procedures that focus on minimizing surgical incisions for improving disease management and reducing patient burden relative to conventional techniques. Interventional approaches, such as biopsy, brachytherapy, and ablation procedures, have been used in the management of cancer for many anatomical regions, including the prostate and liver. Needles and needle-like tools are often used for achieving planned clinical outcomes, but the increased dependency on accurate targeting, guidance, and verification can limit the widespread adoption and clinical scope of these procedures. Image-guided interventions that incorporate 3D information intraoperatively have been shown to improve the accuracy and feasibility of these procedures, but clinical needs still exist for improving workflow and reducing physician variability with widely applicable cost-conscience approaches. The objective of this thesis was to incorporate 3D ultrasound (US) imaging and image processing methods during image-guided cancer interventions in the prostate and liver to provide accessible, fast, and accurate approaches for clinical improvements. An automatic 2D-3D transrectal ultrasound (TRUS) registration algorithm was optimized and implemented in a 3D TRUS-guided system to provide continuous prostate motion corrections with sub-millimeter and sub-degree error in 36 ± 4 ms. An automatic and generalizable 3D TRUS prostate segmentation method was developed on a diverse clinical dataset of patient images from biopsy and brachytherapy procedures, resulting in errors at gold standard accuracy with a computation time of 0.62 s. After validation of mechanical and image reconstruction accuracy, a novel 3D US system for focal liver tumor therapy was developed to guide therapy applicators with 4.27 ± 2.47 mm error. The verification of applicators post-insertion motivated the development of a 3D US applicator segmentation approach, which was demonstrated to provide clinically feasible assessments in 0.246 ± 0.007 s. Lastly, a general needle and applicator tool segmentation algorithm was developed to provide accurate intraoperative and real-time insertion feedback for multiple anatomical locations during a variety of clinical interventional procedures. Clinical translation of these developed approaches has the potential to extend the overall patient quality of life and outcomes by improving detection rates and reducing local cancer recurrence in patients with prostate and liver cancer

Advancements and Breakthroughs in Ultrasound Imaging

Ultrasonic imaging is a powerful diagnostic tool available to medical practitioners, engineers and researchers today. Due to the relative safety, and the non-invasive nature, ultrasonic imaging has become one of the most rapidly advancing technologies. These rapid advances are directly related to the parallel advancements in electronics, computing, and transducer technology together with sophisticated signal processing techniques. This book focuses on state of the art developments in ultrasonic imaging applications and underlying technologies presented by leading practitioners and researchers from many parts of the world

A biomechanical approach for real-time tracking of lung tumors during External Beam Radiation Therapy (EBRT)

Lung cancer is the most common cause of cancer related death in both men and women. Radiation therapy is widely used for lung cancer treatment. However, this method can be challenging due to respiratory motion. Motion modeling is a popular method for respiratory motion compensation, while biomechanics-based motion models are believed to be more robust and accurate as they are based on the physics of motion. In this study, we aim to develop a biomechanics-based lung tumor tracking algorithm which can be used during External Beam Radiation Therapy (EBRT). An accelerated lung biomechanical model can be used during EBRT only if its boundary conditions (BCs) are defined in a way that they can be updated in real-time. As such, we have developed a lung finite element (FE) model in conjunction with a Neural Networks (NNs) based method for predicting the BCs of the lung model from chest surface motion data. To develop the lung FE model for tumor motion prediction, thoracic 4D CT images of lung cancer patients were processed to capture the lung and diaphragm geometry, trans-pulmonary pressure, and diaphragm motion. Next, the chest surface motion was obtained through tracking the motion of the ribcage in 4D CT images. This was performed to simulate surface motion data that can be acquired using optical tracking systems. Finally, two feedforward NNs were developed, one for estimating the trans-pulmonary pressure and another for estimating the diaphragm motion from chest surface motion data. The algorithm development consists of four steps of: 1) Automatic segmentation of the lungs and diaphragm, 2) diaphragm motion modelling using Principal Component Analysis (PCA), 3) Developing the lung FE model, and 4) Using two NNs to estimate the trans-pulmonary pressure values and diaphragm motion from chest surface motion data. The results indicate that the Dice similarity coefficient between actual and simulated tumor volumes ranges from 0.76±0.04 to 0.91±0.01, which is favorable. As such, real-time lung tumor tracking during EBRT using the proposed algorithm is feasible. Hence, further clinical studies involving lung cancer patients to assess the algorithm performance are justified

Focal Spot, Summer 2002

https://digitalcommons.wustl.edu/focal_spot_archives/1091/thumbnail.jp

Virtual and Augmented Reality Techniques for Minimally Invasive Cardiac Interventions: Concept, Design, Evaluation and Pre-clinical Implementation

While less invasive techniques have been employed for some procedures, most intracardiac interventions are still performed under cardiopulmonary bypass, on the drained, arrested heart. The progress toward off-pump intracardiac interventions has been hampered by the lack of adequate visualization inside the beating heart. This thesis describes the development, assessment, and pre-clinical implementation of a mixed reality environment that integrates pre-operative imaging and modeling with surgical tracking technologies and real-time ultrasound imaging. The intra-operative echo images are augmented with pre-operative representations of the cardiac anatomy and virtual models of the delivery instruments tracked in real time using magnetic tracking technologies. As a result, the otherwise context-less images can now be interpreted within the anatomical context provided by the anatomical models. The virtual models assist the user with the tool-to-target navigation, while real-time ultrasound ensures accurate positioning of the tool on target, providing the surgeon with sufficient information to ``see\u27\u27 and manipulate instruments in absence of direct vision. Several pre-clinical acute evaluation studies have been conducted in vivo on swine models to assess the feasibility of the proposed environment in a clinical context. Following direct access inside the beating heart using the UCI, the proposed mixed reality environment was used to provide the necessary visualization and navigation to position a prosthetic mitral valve on the the native annulus, or to place a repair patch on a created septal defect in vivo in porcine models. Following further development and seamless integration into the clinical workflow, we hope that the proposed mixed reality guidance environment may become a significant milestone toward enabling minimally invasive therapy on the beating heart