Planning and Sizing with OsiriX/Horos

It is known that endovascular aneurysm repair (EVAR) requires a precise deployment of the graft and so the anatomical and morphological characteristic study of the aorta and its branches is mandatory. The increase of endovascular surgeons’ interest on tomography image edition through software is marked specially when the increasing frequency of these procedures and its complexity have impelled surgeons to face additional and successive risk to occupational radiation exposure. Thus, a meticulous study of the angio-CT during EVAR preparation allows the reduction of unnecessary radiation exposure, as it also reduces consecutive image acquisition and contrast use (that may be related to renal overload in susceptible patients). Although some studies propose effective strategies to optimize the procedure, they rely on the use of additional specific and advanced equipment, available only in major centers. As an alternative, a simpler technique through image manipulation on the software OsiriX/Horos, aiming to reduce both exposures, is presented

Towards real-time cardiovascular magnetic resonance guided transarterial CoreValve implantation: in vivo evaluation in swine

<p>Abstract</p> <p>Background</p> <p>Real-time cardiovascular magnetic resonance (rtCMR) is considered attractive for guiding TAVI. Owing to an unlimited scan plane orientation and an unsurpassed soft-tissue contrast with simultaneous device visualization, rtCMR is presumed to allow safe device navigation and to offer optimal orientation for precise axial positioning. We sought to evaluate the preclinical feasibility of rtCMR-guided transarterial aortic valve implatation (TAVI) using the nitinol-based Medtronic CoreValve bioprosthesis.</p> <p>Methods</p> <p>rtCMR-guided transfemoral (n = 2) and transsubclavian (n = 6) TAVI was performed in 8 swine using the original CoreValve prosthesis and a modified, CMR-compatible delivery catheter without ferromagnetic components.</p> <p>Results</p> <p>rtCMR using TrueFISP sequences provided reliable imaging guidance during TAVI, which was successful in 6 swine. One transfemoral attempt failed due to unsuccessful aortic arch passage and one pericardial tamponade with subsequent death occurred as a result of ventricular perforation by the device tip due to an operating error, this complication being detected without delay by rtCMR. rtCMR allowed for a detailed, simultaneous visualization of the delivery system with the mounted stent-valve and the surrounding anatomy, resulting in improved visualization during navigation through the vasculature, passage of the aortic valve, and during placement and deployment of the stent-valve. Post-interventional success could be confirmed using ECG-triggered time-resolved cine-TrueFISP and flow-sensitive phase-contrast sequences. Intended valve position was confirmed by ex-vivo histology.</p> <p>Conclusions</p> <p>Our study shows that rtCMR-guided TAVI using the commercial CoreValve prosthesis in conjunction with a modified delivery system is feasible in swine, allowing improved procedural guidance including immediate detection of complications and direct functional assessment with reduction of radiation and omission of contrast media.</p

“Redo” 2D–3D Fusion Technique during Endovascular Redo Aortic Repair

Purpose: The present study aims to describe a new 2D–3D fusion registration method in the case of endovascular redo aortic repair and compare the accuracy of the registration using the previously implanted devices vs. bones as landmarks. Materials and Methods: This single-center study prospectively analyzed all the patients that underwent elective endovascular re-interventions using the Redo Fusion technique between January 2016 and December 2021 at the Vascular Surgery Unit of the Fondazione Policlinico Universitario A. Gemelli (FPUG)—IRCCS in Rome, Italy. The fusion overlay was performed twice, first using bone landmarks (bone fusion) and the second using radiopaque markers of a previous endovascular device (redo fusion). The pre-operative 3D model was fused with live fluoroscopy to create a roadmap. Longitudinal distances between the inferior margin of the target vessel in live fluoroscopy and the inferior margin of the target vessel in bone fusion and redo fusion were measured. Results: This single-center study prospectively analyzed 20 patients. There were 15 men and five women, with a median age of 69.7 (IQR 42) years. The median distance between the inferior margin of the target vessel ostium in digital subtraction angiography and the inferior margin of the target vessel ostium in bone fusion and redo fusion was 5.35 mm and 1.35 mm, respectively (p ≤ 0.0001). Conclusions: The redo fusion technique is accurate and allows the optimization of X-ray working views, supporting the endovascular navigation and vessel catheterization in case of endovascular redo aortic repair

Standard of Practice for the Endovascular Treatment of Thoracic Aortic Aneurysms and Type B Dissections

Thoracic endovascular aortic repair (TEVAR) represents a minimally invasive technique alternative to conventional open surgical reconstruction for the treatment of thoracic aortic pathologies. Rapid advances in endovascular technology and procedural breakthroughs have contributed to a dramatic transformation of the entire field of thoracic aortic surgery. TEVAR procedures can be challenging and, at times, extraordinarily difficult. They require seasoned endovascular experience and refined skills. Of all endovascular procedures, meticulous assessment of anatomy and preoperative procedure planning are absolutely paramount to produce optimal outcomes. These guidelines are intended for use in quality-improvement programs that assess the standard of care expected from all physicians who perform TEVAR procedures

Evaluation of robotic catheter technology in complex endovascular intervention

The past four decades have witnessed tremendous strides in the evolution of endovascular devices and techniques. Catheter-based intervention has revolutionized the management of arterial disease allowing treatment of aortic and peripheral pathologies via a minimally invasive approach. Despite the exponential advances in endovascular equipment, devices and techniques, catheter-based endovascular intervention has certain morphological and technological constraints. Complex patient anatomy, technological impediments and suboptimal fluoroscopic imaging, can make endovascular intervention challenging using traditional endovascular means. Conventional endovascular catheters lack active manoeuvrability of the tip. Manual control can hinder overall stability and control at key target areas, leading to significantly prolonged overall procedure and fluoroscopic times. Repeated instrumentation increases the risk of vessel trauma and distal embolization. More importantly, guidewire-catheter skills are not necessarily intuitive but must be developed and are highly dependent on operator skill with long training pathways as a result. Recognizing the pressing need to address some of the limitations of standard catheter technology this thesis aims to evaluate the role of advanced robotic endovascular catheters in the aortic arch and the visceral segment. Clinical use of this technology is currently limited to transvenous cardiac mapping and ablation procedures. A comprehensive pre-clinical comparison and analysis of robotic versus manual catheter techniques is presented to reveal both their advantages and limitations, with particular emphasis on the potential of robotic catheter technology to reduce the manual skill required for complex tasks, improve stability at key target areas, reduce the risk of vessel trauma, embolization and radiation exposure, whilst improving overall operator performance. The worlds first clinical report of robot-assisted aortic aneurysm repair, a “proof - of - concept” resulting from this research, is also presented, and the potential for future advanced applications in order to increase the applicability of endovascular therapy to a larger cohort of patients discussed

Apport de l'assistance par ordinateur lors de la pose d'endoprothèse aortique

The development of endovascular aortic procedures is growing. These mini-invasive techniques allow a reduction of surgical trauma, usually important in conventional open surgery. The technical limitations of endovascular repair are pushed to special aortic localizations which were in the past decade indication for open repair. Success and efficiency of such procedures are based on the development and the implementation of decision-making tools. This work aims to improve endovascular procedures thanks to a better utilization of pre and intraoperative imaging. This approach is in the line with the framework of computer-assisted surgery whose concepts are applied to vascular surgery. The optimization of endograft deployment is considered in three steps. The first part is dedicated to preoperative imaging analysis and shows the limits of the current sizing tools. The accuracy of a new measurement criterion is assessed (outer curvature length). The second part deals with intraoperative imaging and shows the contribution of augmented reality in endovascular aortic repair. In the last part, image guided surgery on soft tissues is addressed, especially the arterial deformations occurring during endovascular procedures which disprove rigid registration in fusion imaging. The use of finite element simulation to deal with this issue is presented. We report an original approach based on a predictive model of deformations using finite element simulation with geometrical and anatomo-mechanical patient specific parameters extracted from the preoperative CT-scan.Les techniques endovasculaires, particulièrement pour l’aorte, sont en plein essor en chirurgie vasculaire. Ces techniques mini-invasives permettent de diminuer l’agression chirurgicale habituellement importante lors de la chirurgie conventionnelle. Les limites techniques sont repoussées à certaines localisations de l’aorte qui étaient il y a encore peu de temps inaccessibles aux endoprothèses. Le succès et l’efficience de ces interventions reposent en partie sur l'élaboration et la mise en œuvre de nouveaux outils d'aide à la décision. Ce travail entend contribuer à l’amélioration des procédures interventionnelles aortiques grâce à une meilleure exploitation de l’imagerie pré et peropératoire. Cette démarche s’inscrit dans le cadre plus général des Gestes Médico-Chirurgicaux Assistés par Ordinateur, dont les concepts sont revisités pour les transposer au domaine de la chirurgie endovasculaire. Trois axes sont développés afin de sécuriser et optimiser la pose d'endoprothèse. Le premier est focalisé sur l’analyse préopératoire du scanner (sizing) et montre les limites des outils de mesure actuels et évalue la précision d’un nouveau critère de mesure des longueurs de l’aorte (courbure externe). Le deuxième axe se positionne sur le versant peropératoire et montre la contribution de la réalité augmentée dans la pose d’une endoprothèse aortique. Le troisième axe s’intéresse au problème plus général des interventions sur les tissus mous et particulièrement aux déformations artérielles qui surviennent au cours des procédures interventionnelles qui mettent en défaut le recalage rigide lors de la fusion d’images. Nous présentons une approche originale basée sur un modèle numérique de prédiction des déformations qui utilise la simulation par éléments finis en y intégrant des paramètres géométriques et anatomo-mécaniques spécifique-patient extraits du scanner préopératoire

3D shape instantiation for intra-operative navigation from a single 2D projection

Unlike traditional open surgery where surgeons can see the operation area clearly, in robot-assisted Minimally Invasive Surgery (MIS), a surgeon’s view of the region of interest is usually limited. Currently, 2D images from fluoroscopy, Magnetic Resonance Imaging (MRI), endoscopy or ultrasound are used for intra-operative guidance as real-time 3D volumetric acquisition is not always possible due to the acquisition speed or exposure constraints. 3D reconstruction, however, is key to navigation in complex in vivo geometries and can help resolve this issue. Novel 3D shape instantiation schemes are developed in this thesis, which can reconstruct the high-resolution 3D shape of a target from limited 2D views, especially a single 2D projection or slice. To achieve a complete and automatic 3D shape instantiation pipeline, segmentation schemes based on deep learning are also investigated. These include normalization schemes for training U-Nets and network architecture design of Atrous Convolutional Neural Networks (ACNNs). For U-Net normalization, four popular normalization methods are reviewed, then Instance-Layer Normalization (ILN) is proposed. It uses a sigmoid function to linearly weight the feature map after instance normalization and layer normalization, and cascades group normalization after the weighted feature map. Detailed validation results potentially demonstrate the practical advantages of the proposed ILN for effective and robust segmentation of different anatomies. For network architecture design in training Deep Convolutional Neural Networks (DCNNs), the newly proposed ACNN is compared to traditional U-Net where max-pooling and deconvolutional layers are essential. Only convolutional layers are used in the proposed ACNN with different atrous rates and it has been shown that the method is able to provide a fully-covered receptive field with a minimum number of atrous convolutional layers. ACNN enhances the robustness and generalizability of the analysis scheme by cascading multiple atrous blocks. Validation results have shown the proposed method achieves comparable results to the U-Net in terms of medical image segmentation, whilst reducing the trainable parameters, thus improving the convergence and real-time instantiation speed. For 3D shape instantiation of soft and deforming organs during MIS, Sparse Principle Component Analysis (SPCA) has been used to analyse a 3D Statistical Shape Model (SSM) and to determine the most informative scan plane. Synchronized 2D images are then scanned at the most informative scan plane and are expressed in a 2D SSM. Kernel Partial Least Square Regression (KPLSR) has been applied to learn the relationship between the 2D and 3D SSM. It has been shown that the KPLSR-learned model developed in this thesis is able to predict the intra-operative 3D target shape from a single 2D projection or slice, thus permitting real-time 3D navigation. Validation results have shown the intrinsic accuracy achieved and the potential clinical value of the technique. The proposed 3D shape instantiation scheme is further applied to intra-operative stent graft deployment for the robot-assisted treatment of aortic aneurysms. Mathematical modelling is first used to simulate the stent graft characteristics. This is then followed by the Robust Perspective-n-Point (RPnP) method to instantiate the 3D pose of fiducial markers of the graft. Here, Equally-weighted Focal U-Net is proposed with a cross-entropy and an additional focal loss function. Detailed validation has been performed on patient-specific stent grafts with an accuracy between 1-3mm. Finally, the relative merits and potential pitfalls of all the methods developed in this thesis are discussed, followed by potential future research directions and additional challenges that need to be tackled.Open Acces