Improving The Robustness Of Interventional 4D Ultrasound Segmentation Through The Use Of Personalized Shape Priors

While fluoroscopy is still the most widely used imaging modality to guide cardiac interventions, the fusion of pre-operative Magnetic Resonance Imaging (MRI) with real-time intra-operative ultrasound (US) is rapidly gaining clinical acceptance as a viable, radiation-free alternative. In order to improve the detection of the left ventricular (LV) surface in 4D ultrasound, we propose to take advantage of the pre-operative MRI scans to extract a realistic geometrical model representing the patients cardiac anatomy. This could serve as prior information in the interventional setting, allowing to increase the accuracy of the anatomy extraction step in US data. We have made use of a real-time 3D segmentation framework used in the recent past to solve the LV segmentation problem in MR and US data independently and we take advantage of this common link to introduce the prior information as a soft penalty term in the ultrasound segmentation algorithm. We tested the proposed algorithm in a clinical dataset of 38 patients undergoing both MR and US scans. The introduction of the personalized shape prior improves the accuracy and robustness of the LV segmentation, as supported by the error reduction when compared to core lab manual segmentation of the same US sequences.

Validation of percutaneous puncture trajectory during renal access using 4D ultrasound reconstruction

Background: An accurate percutaneous puncture is essential for disintegration and removal of renal stones. Although this procedure has proven to be safe, some organs surrounding the renal target might be accidentally perforated. This work describes a new intraoperative framework where tracked surgical tools are superimposed within 4D ultrasound imaging for security assessment of the percutaneous puncture trajectory (PPT). Methods: A PPT is first generated from the skin puncture site towards an anatomical target, using the information retrieved by electromagnetic motion tracking sensors coupled to surgical tools. Then, 2D ultrasound images acquired with a tracked probe are used to reconstruct a 4D ultrasound around the PPT under GPU processing. Volume hole-filling was performed in different processing time intervals by a tri-linear interpolation method. At spaced time intervals, the volume of the anatomical structures was segmented to ascertain if any vital structure is in between PPT and might compromise the surgical success. To enhance the volume visualization of the reconstructed structures, different render transfer functions were used. Results: Real-time US volume reconstruction and rendering with more than 25 frames/s was only possible when rendering only three orthogonal slice views. When using the whole reconstructed volume one achieved 8-15 frames/s. 3 frames/s were reached when one introduce the segmentation and detection if some structure intersected the PPT. Conclusions: The proposed framework creates a virtual and intuitive platform that can be used to identify and validate a PPT to safely and accurately perform the puncture in percutaneous nephrolithotomy.

Multi-centre validation of an automatic algorithm for fast 4D myocardial segmentation in cine CMR datasets

Quantitative analysis of cine cardiac magnetic resonance (CMR) images for the assessment of global left ventricular morphology and function remains a routine task in clinical cardiology practice. To date, this process requires user interaction and therefore prolongs the examination (i.e. cost) and introduces observer variability. In this study, we sought to validate the feasibility, accuracy, and time efficiency of a novel framework for automatic quantification of left ventricular global function in a clinical setting.

Fast left ventricle tracking in CMR images using localized anatomical affine optical flow

In daily cardiology practice, assessment of left ventricular (LV) global function using non-invasive imaging remains central for the diagnosis and follow-up of patients with cardiovascular diseases. Despite the different methodologies currently accessible for LV segmentation in cardiac magnetic resonance (CMR) images, a fast and complete LV delineation is still limitedly available for routine use. In this study, a localized anatomically constrained affine optical flow method is proposed for fast and automatic LV tracking throughout the full cardiac cycle in short-axis CMR images. Starting from an automatically delineated LV in the end-diastolic frame, the endocardial and epicardial boundaries are propagated by estimating the motion between adjacent cardiac phases using optical flow. In order to reduce the computational burden, the motion is only estimated in an anatomical region of interest around the tracked boundaries and subsequently integrated into a local affine motion model. Such localized estimation enables to capture complex motion patterns, while still being spatially consistent. The method was validated on 45 CMR datasets taken from the 2009 MICCAI LV segmentation challenge. The proposed approach proved to be robust and efficient, with an average distance error of 2.1 mm and a correlation with reference ejection fraction of 0.98 (1.9 ± 4.5%). Moreover, it showed to be fast, taking 5 seconds for the tracking of a full 4D dataset (30 ms per image). Overall, a novel fast, robust and accurate LV tracking methodology was proposed, enabling accurate assessment of relevant global function cardiac indices, such as volumes and ejection fraction.

Sistema eletromecânico para controlo intuitivo dos movimentos de uma sonda transesofágica

O ser humano realiza uma alimentação pouco variada, com grandes teores de açúcar e gorduras saturadas, ao mesmo tempo, está sujeito a profissões cada vez mais competitivas aonde passa longos períodos sentados sem qualquer esforço físico. Estes aspetos levam à acumulação de gorduras em redor de todos os órgãos, que promovem o aparecimento de problemas cardiovascular, que são atualmente, a principal causa de morte no mundo. O tratamento das doenças cardiovasculares é em muitas situações realizado por procedimentos minimamente-invasivos, que são guiados através de imagem médica. Contudo, a utilização de radiação durante a navegação é normalmente requerida o que tem consequências para o paciente e para a equipa médica. Nesta dissertação, focamo-nos nos recentes sistemas de aquisição de imagem sem radiação e no desenvolvimento de sistemas mais inteligentes para facilitar o controlo destes equipamentos durante o procedimento. Assim, pretendemos desenvolver um robô que apoie na aquisição de imagens de ultrassons através de uma sonda transesofágica. O robô desenvolvido possui um conjunto de engrenagens que fazem a transferência de movimento para as rodas dos manípulos da sonda e um encoder magnético que proporciona uma leitura rápida e de alta precisão dos movimentos da sonda. De forma a automaticamente adaptar a posição da sonda na direção do alvo anatómico, um sistema de motion tracking foi acoplado ao robô e ao instrumento cirúrgico utilizado durante o procedimento. Assim, todos os movimentos realizados pelo intervencionista são repetidos pela sonda, permitindo assim adquirir uma imagem de ultrassom sempre centrada no instrumento cirúrgico. Para avaliar a performance do robô foram realizados testes em laboratório. mais concretamente: 1) controlo do robô sem sonda acoplada e 2) controlo do robô com sonda acoplada. Os testes foram realizados com diferentes posições angulares, em todas as gamas de funcionamento do robô, avaliando o erro da posição final em relação posição desejada e o tempo de resposta. Os resultados demonstraram que um erro médio de 2º foi observado para as diferentes situações com um tempo médio de resposta de 300 ms. Os resultados alcançados demonstraram uma boa resposta do sistema, pelo que se espera que sistema desenvolvido venha ser capaz de reduzir o tempo de intervenção, aumentando a qualidade da intervenção e minimizando possíveis erros.