Biomechanical modelling of probe to tissue interaction during ultrasound scanning

Purpose: Biomechanical simulation of anatomical deformations caused by ultrasound probe pressure is of outstanding importance for several applications, from the testing of robotic acquisition systems to multi-modal image fusion and development of ultrasound training platforms. Different approaches can be exploited for modelling the probe-tissue interaction, each achieving different trade-offs among accuracy, computation time and stability. Methods: We assess the performances of different strategies based on the finite element method for modelling the interaction between the rigid probe and soft tissues. Probe\u2013tissue contact is modelled using (i) penalty forces, (ii) constraint forces, and (iii) by prescribing the displacement of the mesh surface nodes. These methods are tested in the challenging context of ultrasound scanning of the breast, an organ undergoing large nonlinear deformations during the procedure. Results: The obtained results are evaluated against those of a non-physically based method. While all methods achieve similar accuracy, performance in terms of stability and speed shows high variability, especially for those methods modelling the contacts explicitly. Overall, prescribing surface displacements is the approach with best performances, but it requires prior knowledge of the contact area and probe trajectory. Conclusions: In this work, we present different strategies for modelling probe\u2013tissue interaction, each able to achieve different compromises among accuracy, speed and stability. The choice of the preferred approach highly depends on the requirements of the specific clinical application. Since the presented methodologies can be applied to describe general tool\u2013tissue interactions, this work can be seen as a reference for researchers seeking the most appropriate strategy to model anatomical deformation induced by the interaction with medical tools

Soft Tissue Simulation Environment to Learn Manipulation Tasks in Autonomous Robotic Surgery

Reinforcement Learning (RL) methods have demonstrated promising results for the automation of subtasks in surgical robotic systems. Since many trial and error attempts are required to learn the optimal control policy, RL agent training can be performed in simulation and the learned behavior can be then deployed in real environments. In this work, we introduce an open-source simulation environment providing support for position based dynamics soft bodies simulation and state-of-the-art RL methods. We demonstrate the capabilities of the proposed framework by training an RL agent based on Proximal Policy Optimization in fat tissue manipulation for tumor exposure during a nephrectomy procedure. Leveraging on a preliminary optimization of the simulation parameters, we show that our agent is able to learn the task on a virtual replica of the anatomical environment. The learned behavior is robust to changes in the initial end-effector position. Furthermore, we show that the learned policy can be directly deployed on the da Vinci Research Kit, which is able to execute the trajectories generated by the RL agent. The proposed simulation environment represents an essential component for the development of next-generation robotic systems, where the interaction with the deformable anatomical environment is involved

Listeria monocytogenes in Ready-to-Eat Seafood and Potential Hazards for the Consumers

The risk of exposure to Listeria monocytogenes (L. monocytogenes) when consuming Ready-to-Eat (RTE) seafood was assessed in the Veneto Region (Italy). Thirty-eight samples were analyzed, each sample consisted of three subunits belonging to the same batches. The first of the three units was examined immediately, the second was stored at +4°C (for all of its shelf-life) and the third at +10°C (for the latter third of its shelf-life) before the analysis. Chemical-physical and microbiological parameters were tested simultaneously. Culture results showed the presence of viable L. monocytogenes in 9 (23,68%) of the 38 samples analysed, 3 (33,33%) of which with a concentration >100 cfu/g. PCR tests yielded 12 L. monocytogenes positive samples. Semipreserves with aw (water activity) and pH values that favour L. monocytogenes growth were the only ones to result positive to microbiological and PCR tests. Temperature proved to be an important factor as it limits the growth of L. monocytogenes, including products with potentially high competitive microbial charges. Four different serotypes were recovered and ribotyping has helped to highlight the genomic variability of L. monocytogenes strains in food. This supports the hypothesis that L. monocytogenes continues to evolve genetically to the detriment of phenotypic conservation

Position-based modeling of lesion displacement in Ultrasound-guided breast biopsy

International audiencePurpose Although ultrasound (US) images represent the most popular modality for guiding breast biopsy, malignant regions are often missed by sonography, thus preventing accurate lesion localization which is essential for a successful procedure. Biomechanical models can support the localization of suspicious areas identified on a pre-operative image during US scanning since they are able to account for anatomical deformations resulting from US probe pressure. We propose a deformation model which relies on position-based dynamics (PBD) approach to predict the displacement of internal targets induced by probe interaction during US acquisition. Methods The PBD implementation available in NVIDIA FleX is exploited to create an anatomical model capable of deforming online. Simulation parameters are initialized on a calibration phantom under different levels of probe-induced deformations, then they are fine-tuned by minimizing the localization error of a US-visible landmark of a realistic breast phantom. The updated model is used to estimate the displacement of other internal lesions due to probe-tissue interaction. Results The localization error obtained when applying the PBD model remains below 11 mm for all the tumors even for input displacements in the order of 30 mm. This proposed method obtains results aligned with FE models with faster computational performance, suitable for real-time applications. In addition, it outperforms rigid model used to track lesion position in US-guided breast biopsies, at least halving the localization error for all the displacement ranges considered. 2 Eleonora Tagliabue et al. Conclusions Position-based dynamics approach has proved to be successful in modeling breast tissue deformations during US acquisition. Its stability, accuracy and real-time performance make such model suitable for tracking lesions displacement during US-guided breast biopsy

Correction to: Position-based modeling of lesion displacement in ultrasound-guided breast biopsy

Comparison and metrics for medical simulation

ViTAS Gaming Suite: Virtual Therapy Against Stroke

Stroke is the leading cause of disability in Western Society, and rehabilitation is a fundamental support to ensure the best possible recovery of stroke patients after acute disease. To support and enhance conventional therapies we have developed a virtual rehabilitation gaming suite called ViTAS. ViTAS replicates some of the tests performed in clinical contexts, thus making the integration between virtual and traditional rehabilitation completely straightforward. We have collected the opinion of 35 clinicians with different degree of experience, following a customized self-report questionnaire. The results showed high acceptance of clinicians to use ViTAS system in rehabilitation. We conclude that ViTAS could become an essential supplement to standard post-stroke rehabilitatio

Effect of Surface Chemistry on Incorporation of Nanoparticles within Calcite Single Crystals

Inclusion of additives into calcite crystals allows one to embed non-native proprieties into the inorganic matrix and obtain new functional materials. Up to now, few parameters have been taken into account to evaluate the efficiency of inclusion of an additive. Taking inspiration from Nature, we grew calcite crystals in the presence of fluorescent silica nanoparticles carrying different functional groups (PluS-X) to investigate the effect of surface chemistry on the inclusion of additives. PluS-X allowed us to keep constant all the particle characteristics, including size and morphology, while changing exposed functional groups and thus zeta potential. The effect on crystal morphology and structure, the loading, and distribution of PluS-X within the crystals have been evaluated with different microscopy and diffractometric techniques. Our data indicate that hydroxyl functionalized particles are entrapped more efficiently inside calcite single crystals without distortion of the crystal structure and inhibition of the growth

A multi-element psychosocial intervention for early psychosis (GET UP PIANO TRIAL) conducted in a catchment area of 10 million inhabitants: study protocol for a pragmatic cluster randomized controlled trial

Multi-element interventions for first-episode psychosis (FEP) are promising, but have mostly been conducted in non-epidemiologically representative samples, thereby raising the risk of underestimating the complexities involved in treating FEP in 'real-world' services