Navigation system based in motion tracking sensor for percutaneous renal access

Tese de Doutoramento em Engenharia BiomédicaMinimally-invasive kidney interventions are daily performed to diagnose and treat several renal diseases. Percutaneous renal access (PRA) is an essential but challenging stage for most of these procedures, since its outcome is directly linked to the physician’s ability to precisely visualize and reach the anatomical target. Nowadays, PRA is always guided with medical imaging assistance, most frequently using X-ray based imaging (e.g. fluoroscopy). Thus, radiation on the surgical theater represents a major risk to the medical team, where its exclusion from PRA has a direct impact diminishing the dose exposure on both patients and physicians. To solve the referred problems this thesis aims to develop a new hardware/software framework to intuitively and safely guide the surgeon during PRA planning and puncturing. In terms of surgical planning, a set of methodologies were developed to increase the certainty of reaching a specific target inside the kidney. The most relevant abdominal structures for PRA were automatically clustered into different 3D volumes. For that, primitive volumes were merged as a local optimization problem using the minimum description length principle and image statistical properties. A multi-volume Ray Cast method was then used to highlight each segmented volume. Results show that it is possible to detect all abdominal structures surrounding the kidney, with the ability to correctly estimate a virtual trajectory. Concerning the percutaneous puncturing stage, either an electromagnetic or optical solution were developed and tested in multiple in vitro, in vivo and ex vivo trials. The optical tracking solution aids in establishing the desired puncture site and choosing the best virtual puncture trajectory. However, this system required a line of sight to different optical markers placed at the needle base, limiting the accuracy when tracking inside the human body. Results show that the needle tip can deflect from its initial straight line trajectory with an error higher than 3 mm. Moreover, a complex registration procedure and initial setup is needed. On the other hand, a real-time electromagnetic tracking was developed. Hereto, a catheter was inserted trans-urethrally towards the renal target. This catheter has a position and orientation electromagnetic sensor on its tip that function as a real-time target locator. Then, a needle integrating a similar sensor is used. From the data provided by both sensors, one computes a virtual puncture trajectory, which is displayed in a 3D visualization software. In vivo tests showed a median renal and ureteral puncture times of 19 and 51 seconds, respectively (range 14 to 45 and 45 to 67 seconds). Such results represent a puncture time improvement between 75% and 85% when comparing to state of the art methods. 3D sound and vibrotactile feedback were also developed to provide additional information about the needle orientation. By using these kind of feedback, it was verified that the surgeon tends to follow a virtual puncture trajectory with a reduced amount of deviations from the ideal trajectory, being able to anticipate any movement even without looking to a monitor. Best results show that 3D sound sources were correctly identified 79.2 ± 8.1% of times with an average angulation error of 10.4º degrees. Vibration sources were accurately identified 91.1 ± 3.6% of times with an average angulation error of 8.0º degrees. Additionally to the EMT framework, three circular ultrasound transducers were built with a needle working channel. One explored different manufacture fabrication setups in terms of the piezoelectric materials, transducer construction, single vs. multi array configurations, backing and matching material design. The A-scan signals retrieved from each transducer were filtered and processed to automatically detect reflected echoes and to alert the surgeon when undesirable anatomical structures are in between the puncture path. The transducers were mapped in a water tank and tested in a study involving 45 phantoms. Results showed that the beam cross-sectional area oscillates around the ceramics radius and it was possible to automatically detect echo signals in phantoms with length higher than 80 mm. Hereupon, it is expected that the introduction of the proposed system on the PRA procedure, will allow to guide the surgeon through the optimal path towards the precise kidney target, increasing surgeon’s confidence and reducing complications (e.g. organ perforation) during PRA. Moreover, the developed framework has the potential to make the PRA free of radiation for both patient and surgeon and to broad the use of PRA to less specialized surgeons.Intervenções renais minimamente invasivas são realizadas diariamente para o tratamento e diagnóstico de várias doenças renais. O acesso renal percutâneo (ARP) é uma etapa essencial e desafiante na maior parte destes procedimentos. O seu resultado encontra-se diretamente relacionado com a capacidade do cirurgião visualizar e atingir com precisão o alvo anatómico. Hoje em dia, o ARP é sempre guiado com recurso a sistemas imagiológicos, na maior parte das vezes baseados em raios-X (p.e. a fluoroscopia). A radiação destes sistemas nas salas cirúrgicas representa um grande risco para a equipa médica, aonde a sua remoção levará a um impacto direto na diminuição da dose exposta aos pacientes e cirurgiões. De modo a resolver os problemas existentes, esta tese tem como objetivo o desenvolvimento de uma framework de hardware/software que permita, de forma intuitiva e segura, guiar o cirurgião durante o planeamento e punção do ARP. Em termos de planeamento, foi desenvolvido um conjunto de metodologias de modo a aumentar a eficácia com que o alvo anatómico é alcançado. As estruturas abdominais mais relevantes para o procedimento de ARP, foram automaticamente agrupadas em volumes 3D, através de um problema de optimização global com base no princípio de “minimum description length” e propriedades estatísticas da imagem. Por fim, um procedimento de Ray Cast, com múltiplas funções de transferência, foi utilizado para enfatizar as estruturas segmentadas. Os resultados mostram que é possível detetar todas as estruturas abdominais envolventes ao rim, com a capacidade para estimar corretamente uma trajetória virtual. No que diz respeito à fase de punção percutânea, foram testadas duas soluções de deteção de movimento (ótica e eletromagnética) em múltiplos ensaios in vitro, in vivo e ex vivo. A solução baseada em sensores óticos ajudou no cálculo do melhor ponto de punção e na definição da melhor trajetória a seguir. Contudo, este sistema necessita de uma linha de visão com diferentes marcadores óticos acoplados à base da agulha, limitando a precisão com que a agulha é detetada no interior do corpo humano. Os resultados indicam que a agulha pode sofrer deflexões à medida que vai sendo inserida, com erros superiores a 3 mm. Por outro lado, foi desenvolvida e testada uma solução com base em sensores eletromagnéticos. Para tal, um cateter que integra um sensor de posição e orientação na sua ponta, foi colocado por via trans-uretral junto do alvo renal. De seguida, uma agulha, integrando um sensor semelhante, é utilizada para a punção percutânea. A partir da diferença espacial de ambos os sensores, é possível gerar uma trajetória de punção virtual. A mediana do tempo necessário para puncionar o rim e ureter, segundo esta trajetória, foi de 19 e 51 segundos, respetivamente (variações de 14 a 45 e 45 a 67 segundos). Estes resultados representam uma melhoria do tempo de punção entre 75% e 85%, quando comparados com o estado da arte dos métodos atuais. Além do feedback visual, som 3D e feedback vibratório foram explorados de modo a fornecer informações complementares da posição da agulha. Verificou-se que com este tipo de feedback, o cirurgião tende a seguir uma trajetória de punção com desvios mínimos, sendo igualmente capaz de antecipar qualquer movimento, mesmo sem olhar para o monitor. Fontes de som e vibração podem ser corretamente detetadas em 79,2 ± 8,1% e 91,1 ± 3,6%, com erros médios de angulação de 10.4º e 8.0 graus, respetivamente. Adicionalmente ao sistema de navegação, foram também produzidos três transdutores de ultrassom circulares com um canal de trabalho para a agulha. Para tal, foram exploradas diferentes configurações de fabricação em termos de materiais piezoelétricos, transdutores multi-array ou singulares e espessura/material de layers de suporte. Os sinais originados em cada transdutor foram filtrados e processados de modo a detetar de forma automática os ecos refletidos, e assim, alertar o cirurgião quando existem variações anatómicas ao longo do caminho de punção. Os transdutores foram mapeados num tanque de água e testados em 45 phantoms. Os resultados mostraram que o feixe de área em corte transversal oscila em torno do raio de cerâmica, e que os ecos refletidos são detetados em phantoms com comprimentos superiores a 80 mm. Desta forma, é expectável que a introdução deste novo sistema a nível do ARP permitirá conduzir o cirurgião ao longo do caminho de punção ideal, aumentado a confiança do cirurgião e reduzindo possíveis complicações (p.e. a perfuração dos órgãos). Além disso, de realçar que este sistema apresenta o potencial de tornar o ARP livre de radiação e alarga-lo a cirurgiões menos especializados.The present work was only possible thanks to the support by the Portuguese Science and Technology Foundation through the PhD grant with reference SFRH/BD/74276/2010 funded by FCT/MEC (PIDDAC) and by Fundo Europeu de Desenvolvimento Regional (FEDER), Programa COMPETE - Programa Operacional Factores de Competitividade (POFC) do QREN

Augmenting CT cardiac roadmaps with segmented streaming ultrasound

Static X-ray computed tomography (CT) volumes are often used as anatomic roadmaps during catheter-based cardiac interventions performed under X-ray fluoroscopy guidance. These CT volumes provide a high-resolution depiction of soft-tissue structures, but at only a single point within the cardiac and respiratory cycles. Augmenting these static CT roadmaps with segmented myocardial borders extracted from live ultrasound (US) provides intra-operative access to real-time dynamic information about the cardiac anatomy. In this work, using a customized segmentation method based on a 3D active mesh, endocardial borders of the left ventricle were extracted from US image streams (4D data sets) at a frame rate of approximately 5 frames per second. The coordinate systems for CT and US modalities were registered using rigid body registration based on manually selected landmarks, and the segmented endocardial surfaces were overlaid onto the CT volume. The root-mean squared fiducial registration error was 3.80 mm. The accuracy of the segmentation was quantitatively evaluated in phantom and human volunteer studies via comparison with manual tracings on 9 randomly selected frames using a finite-element model (the US image resolutions of the phantom and volunteer data were 1.3 x 1.1 x 1.3 mm and 0.70 x 0.82 x 0.77 mm, respectively). This comparison yielded 3.70±2.5 mm (approximately 3 pixels) root-mean squared error (RMSE) in a phantom study and 2.58±1.58 mm (approximately 3 pixels) RMSE in a clinical study. The combination of static anatomical roadmap volumes and dynamic intra-operative anatomic information will enable better guidance and feedback for image-guided minimally invasive cardiac interventions

Improved Image Guidance in TACE Procedures

Purpose of the work in this thesis is to improve the image guidance in TACE procedures. More specifically, we intend to develop and evaluate technology that permits dynamic roadmapping based on a 3D model of the liver vasculature

Medical SLAM in an autonomous robotic system

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-operative morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilities by observing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted instruments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This thesis addresses the ambitious goal of achieving surgical autonomy, through the study of the anatomical environment by Initially studying the technology present and what is needed to analyze the scene: vision sensors. A novel endoscope for autonomous surgical task execution is presented in the first part of this thesis. Which combines a standard stereo camera with a depth sensor. This solution introduces several key advantages, such as the possibility of reconstructing the 3D at a greater distance than traditional endoscopes. Then the problem of hand-eye calibration is tackled, which unites the vision system and the robot in a single reference system. Increasing the accuracy in the surgical work plan. In the second part of the thesis the problem of the 3D reconstruction and the algorithms currently in use were addressed. In MIS, simultaneous localization and mapping (SLAM) can be used to localize the pose of the endoscopic camera and build ta 3D model of the tissue surface. Another key element for MIS is to have real-time knowledge of the pose of surgical tools with respect to the surgical camera and underlying anatomy. Starting from the ORB-SLAM algorithm we have modified the architecture to make it usable in an anatomical environment by adding the registration of the pre-operative information of the intervention to the map obtained from the SLAM. Once it has been proven that the slam algorithm is usable in an anatomical environment, it has been improved by adding semantic segmentation to be able to distinguish dynamic features from static ones. All the results in this thesis are validated on training setups, which mimics some of the challenges of real surgery and on setups that simulate the human body within Autonomous Robotic Surgery (ARS) and Smart Autonomous Robotic Assistant Surgeon (SARAS) projects

Medical SLAM in an autonomous robotic system

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-operative morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilities by observing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted instruments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This thesis addresses the ambitious goal of achieving surgical autonomy, through the study of the anatomical environment by Initially studying the technology present and what is needed to analyze the scene: vision sensors. A novel endoscope for autonomous surgical task execution is presented in the first part of this thesis. Which combines a standard stereo camera with a depth sensor. This solution introduces several key advantages, such as the possibility of reconstructing the 3D at a greater distance than traditional endoscopes. Then the problem of hand-eye calibration is tackled, which unites the vision system and the robot in a single reference system. Increasing the accuracy in the surgical work plan. In the second part of the thesis the problem of the 3D reconstruction and the algorithms currently in use were addressed. In MIS, simultaneous localization and mapping (SLAM) can be used to localize the pose of the endoscopic camera and build ta 3D model of the tissue surface. Another key element for MIS is to have real-time knowledge of the pose of surgical tools with respect to the surgical camera and underlying anatomy. Starting from the ORB-SLAM algorithm we have modified the architecture to make it usable in an anatomical environment by adding the registration of the pre-operative information of the intervention to the map obtained from the SLAM. Once it has been proven that the slam algorithm is usable in an anatomical environment, it has been improved by adding semantic segmentation to be able to distinguish dynamic features from static ones. All the results in this thesis are validated on training setups, which mimics some of the challenges of real surgery and on setups that simulate the human body within Autonomous Robotic Surgery (ARS) and Smart Autonomous Robotic Assistant Surgeon (SARAS) projects

Development of a Surgical Assistance System for Guiding Transcatheter Aortic Valve Implantation

Development of image-guided interventional systems is growing up rapidly in the recent years. These new systems become an essential part of the modern minimally invasive surgical procedures, especially for the cardiac surgery. Transcatheter aortic valve implantation (TAVI) is a recently developed surgical technique to treat severe aortic valve stenosis in elderly and high-risk patients. The placement of stented aortic valve prosthesis is crucial and typically performed under live 2D fluoroscopy guidance. To assist the placement of the prosthesis during the surgical procedure, a new fluoroscopy-based TAVI assistance system has been developed. The developed assistance system integrates a 3D geometrical aortic mesh model and anatomical valve landmarks with live 2D fluoroscopic images. The 3D aortic mesh model and landmarks are reconstructed from interventional angiographic and fluoroscopic C-arm CT system, and a target area of valve implantation is automatically estimated using these aortic mesh models. Based on template-based tracking approach, the overlay of visualized 3D aortic mesh model, landmarks and target area of implantation onto fluoroscopic images is updated by approximating the aortic root motion from a pigtail catheter motion without contrast agent. A rigid intensity-based registration method is also used to track continuously the aortic root motion in the presence of contrast agent. Moreover, the aortic valve prosthesis is tracked in fluoroscopic images to guide the surgeon to perform the appropriate placement of prosthesis into the estimated target area of implantation. An interactive graphical user interface for the surgeon is developed to initialize the system algorithms, control the visualization view of the guidance results, and correct manually overlay errors if needed. Retrospective experiments were carried out on several patient datasets from the clinical routine of the TAVI in a hybrid operating room. The maximum displacement errors were small for both the dynamic overlay of aortic mesh models and tracking the prosthesis, and within the clinically accepted ranges. High success rates of the developed assistance system were obtained for all tested patient datasets. The results show that the developed surgical assistance system provides a helpful tool for the surgeon by automatically defining the desired placement position of the prosthesis during the surgical procedure of the TAVI.Die Entwicklung bildgeführter interventioneller Systeme wächst rasant in den letzten Jahren. Diese neuen Systeme werden zunehmend ein wesentlicher Bestandteil der technischen Ausstattung bei modernen minimal-invasiven chirurgischen Eingriffen. Diese Entwicklung gilt besonders für die Herzchirurgie. Transkatheter Aortenklappen-Implantation (TAKI) ist eine neue entwickelte Operationstechnik zur Behandlung der schweren Aortenklappen-Stenose bei alten und Hochrisiko-Patienten. Die Platzierung der Aortenklappenprothese ist entscheidend und wird in der Regel unter live-2D-fluoroskopischen Bildgebung durchgeführt. Zur Unterstützung der Platzierung der Prothese während des chirurgischen Eingriffs wurde in dieser Arbeit ein neues Fluoroskopie-basiertes TAKI Assistenzsystem entwickelt. Das entwickelte Assistenzsystem überlagert eine 3D-Geometrie des Aorten-Netzmodells und anatomischen Landmarken auf live-2D-fluoroskopische Bilder. Das 3D-Aorten-Netzmodell und die Landmarken werden auf Basis der interventionellen Angiographie und Fluoroskopie mittels eines C-Arm-CT-Systems rekonstruiert. Unter Verwendung dieser Aorten-Netzmodelle wird das Zielgebiet der Klappen-Implantation automatisch geschätzt. Mit Hilfe eines auf Template Matching basierenden Tracking-Ansatzes wird die Überlagerung des visualisierten 3D-Aorten-Netzmodells, der berechneten Landmarken und der Zielbereich der Implantation auf fluoroskopischen Bildern korrekt überlagert. Eine kompensation der Aortenwurzelbewegung erfolgt durch Bewegungsverfolgung eines Pigtail-Katheters in Bildsequenzen ohne Kontrastmittel. Eine starrere Intensitätsbasierte Registrierungsmethode wurde verwendet, um kontinuierlich die Aortenwurzelbewegung in Bildsequenzen mit Kontrastmittelgabe zu detektieren. Die Aortenklappenprothese wird in die fluoroskopischen Bilder eingeblendet und dient dem Chirurg als Leitfaden für die richtige Platzierung der realen Prothese. Eine interaktive Benutzerschnittstelle für den Chirurg wurde zur Initialisierung der Systemsalgorithmen, zur Steuerung der Visualisierung und für manuelle Korrektur eventueller Überlagerungsfehler entwickelt. Retrospektive Experimente wurden an mehreren Patienten-Datensätze aus der klinischen Routine der TAKI in einem Hybrid-OP durchgeführt. Hohe Erfolgsraten des entwickelten Assistenzsystems wurden für alle getesteten Patienten-Datensätze erzielt. Die Ergebnisse zeigen, dass das entwickelte chirurgische Assistenzsystem ein hilfreiches Werkzeug für den Chirurg bei der Platzierung Position der Prothese während des chirurgischen Eingriffs der TAKI bietet