Surgical Augmented Reality with Topological Changes

International audienceThe visualization of internal structures of organs in minimally invasive surgery is an important avenue for improving the perception of the surgeon, or for supporting planning and decision systems. However, current methods dealing with non-rigid augmented reality only provide augmentation when the topology of the organ is not modified. In this paper we solve this shortcoming by introducing a method for physics-based non-rigid augmented reality. Singularities caused by topo-logical changes are detected and propagated to the pre-operative model. This significantly improves the coherence between the actual laparascopic view and the model, and provides added value in terms of navigation and decision making. Our real time augmentation algorithm is assessed on a video showing the cut of a porcine liver's lobe in minimal invasive surgery

Face-based Smoothed Finite Element Method for Real-time Simulation of soft tissue

International audienceIn soft tissue surgery, a tumor and other anatomical structures are usually located using the preoperative CT or MR images. However, due to the deformation of the concerned tissues, this information suffers from inaccuracy when employed directly during the surgery. In order to account for these deformations in the planning process, the use of a bio-mechanical model of the tissues is needed. Such models are often designed using the finite element method (FEM), which is, however, computationally expensive, in particular when a high accuracy of the simulation is required. In our work, we propose to use a smoothed finite element method (S-FEM) in the context of modeling of the soft tissue deformation. This numerical technique has been introduced recently to overcome the overly stiff behavior of the standard FEM and to improve the solution accuracy and the convergence rate in solid mechanics problems. In this paper, a face-based smoothed finite element method (FS-FEM) using 4-node tetrahedral elements is presented. We show that in some cases, the method allows for reducing the number of degrees of freedom, while preserving the accuracy of the discretization. The method is evaluated on a simulation of a cantilever beam loaded at the free end and on a simulation of a 3D cube under traction and compression forces. Further, it is applied to the simulation of the brain shift and of the kidney's deformation. The results demonstrate that the method outperforms the standard FEM in a bending scenario and that has similar accuracy as the standard FEM in the simulations of brain shift and kidney deformation

Handling Topological Changes during Elastic Registration: Application to Augmented Reality in Laparoscopic Surgery

International audiencePurpose: Locating the internal structures of an organ is a critical aspect of many surgical procedures. Minimally invasive surgery, associated with augmented reality techniques, offers the potential to visualize inner structures, allowing for improved analysis, depth perception or for supporting planning and decision systems.Methods: Most of the current methods dealing with rigid or non-rigid augmented reality make the assumption that the topology of the organ is not modified. As surgery relies essentially on cutting and dissection of anatomical structures, such methods are limited to the early stages of the surgery.We solve this shortcoming with the introduction of a method for physics-based elastic registration using a single view from a monocular camera.Singularities caused by topological changes are detected and propagated to the pre-operative model. This significantly improves the coherence between the actual laparoscopic view and the model, and provides added value in terms of navigation and decision-making, e.g. by overlaying the internal structures of an organ on the laparoscopic view.Results: Our real time augmentation method is assessed on several scenarios, using synthetic objects and real organs. In all cases, the impact of our approach is demonstrated, both qualitatively and quantitatively.Conclusion: The presented approach tackles the challenge of localizing internal structures throughout a complete surgical procedure, even after surgical cuts. This information is crucial for surgeons to improve the outcome for their surgical procedure and avoid complications

Biomarker-guided duration of Antibiotic Treatment in Children Hospitalised with confirmed or suspected bacterial infection (BATCH): Protocol for a randomised controlled trial

Introduction Procalcitonin (PCT) is a biomarker more specific for bacterial infection and responds quicker than other commonly used biomarkers such as C reactive protein, but is not routinely used in the National Health Service (NHS). Studies mainly in adults show that using PCT to guide clinicians may reduce antibiotic use, reduce hospital stay, with no associated adverse effects such as increased rates of hospital re-admission, incomplete treatment of infections, relapse or death. A review conducted for National Institute for Health and Care Excellence recommends further research on PCT testing to guide antibiotic use in children.Methods and analysis Biomarker-guided duration of Antibiotic Treatment in Children Hospitalised with confirmed or suspected bacterial infection is a multi-centre, prospective, two-arm, individually Randomised Controlled Trial (RCT) with a 28-day follow-up and internal pilot. The intervention is a PCT-guided algorithm used in conjunction with best practice. The control arm is best practice alone. We plan to recruit 1942 children, aged between 72 hours and up to 18 years old, who are admitted to the hospital and being treated with intravenous antibiotics for suspected or confirmed bacterial infection. Coprimary outcomes are duration of antibiotic use and a composite safety measure. Secondary outcomes include time to switch from broad to narrow spectrum antibiotics, time to discharge, adverse drug reactions, health utility and cost-effectiveness. We will also perform a qualitative process evaluation. Recruitment commenced in June 2018 and paused briefly between March and May 2020 due to the COVID-19 pandemic

Development and external validation of predictive models for prevalent and recurrent atrial fibrillation: a protocol for the analysis of the CATCH ME combined dataset

Background: Atrial fibrillation (AF) is caused by different mechanisms but current treatment strategies do not target these mechanisms. Stratified therapy based on mechanistic drivers and biomarkers of AF have the potential to improve AF prevention and management outcomes. We will integrate mechanistic insights with known pathophysiological drivers of AF in models predicting recurrent AF and prevalent AF to test hypotheses related to AF mechanisms and response to rhythm control therapy. Methods: We will harmonise and combine baseline and outcome data from 12 studies collected by six centres from the United Kingdom, Germany, France, Spain, and the Netherlands which assess prevalent AF or recurrent AF. A Delphi process and statistical selection will be used to identify candidate clinical predictors. Prediction models will be developed in patients with AF for AF recurrence and AF-related outcomes, and in patients with or without AF at baseline for prevalent AF. Models will be used to test mechanistic hypotheses and investigate the predictive value of plasma biomarkers. Discussion: This retrospective, harmonised, individual patient data analysis will use information from 12 datasets collected in five European countries. It is envisioned that the outcome of this analysis would provide a greater understanding of the factors associated with recurrent and prevalent AF, potentially allowing development of stratified approaches to prevention and therapy management

Heart Failure, Female Sex, and Atrial Fibrillation Are the Main Drivers of Human Atrial Cardiomyopathy: Results From the CATCH ME Consortium

Background: Atrial cardiomyopathy (atCM) is an emerging prognostic factor in cardiovascular disease. Fibrotic remodeling, cardiomyocyte hypertrophy, and capillary density are hallmarks of atCM. The contribution of etiological factors and atrial fibrillation (AF) to the development of differential atCM phenotypes has not been quantified. This study aimed to evaluate the association between histological features of atCM and the clinical phenotype. Methods and results: We examined left atrial (LA, n=95) and right atrial (RA, n=76) appendages from a European cohort of patients undergoing cardiac surgery. Quantification of histological atCM features was performed following wheat germ agglutinin/CD31/vimentin staining. The contributions of AF, heart failure, sex, and age to histological characteristics were determined with multiple linear regression models. Persistent AF was associated with increased endomysial fibrosis (LA: +1.13±0.47 μm, P=0.038; RA: +0.94±0.38 μm, P=0.041), whereas total extracellular matrix content was not. Men had larger cardiomyocytes (LA: +1.92±0.72 μm, P<0.001), while women had more endomysial fibrosis (LA: +0.99±0.56 μm, P=0.003). Patients with heart failure showed more endomysial fibrosis (LA: +1.85±0.48 μm, P<0.001) and extracellular matrix content (LA: +3.07±1.29%, P=0.016), and a higher capillary density (LA: +0.13±0.06, P=0.007) and size (LA: +0.46±0.22 μm, P=0.044). Fuzzy k-means clustering of histological features identified 2 subtypes of atCM: 1 characterized by enhanced endomysial fibrosis (LA: +3.17 μm, P<0.001; RA: +2.86 μm, P<0.001), extracellular matrix content (LA: +3.53%, P<0.001; RA: +6.40%, P<0.001) and fibroblast density (LA: +4.38%, P<0.001), and 1 characterized by cardiomyocyte hypertrophy (LA: +1.16 μm, P=0.008; RA: +2.58 μm, P<0.001). Patients with fibrotic atCM were more frequently female (LA: odds ratio [OR], 1.33, P=0.002; RA: OR, 1.54, P=0.004), with persistent AF (LA: OR, 1.22, P=0.036) or heart failure (LA: OR, 1.62, P<0.001). Hypertrophic features were more common in men (LA: OR=1.33, P=0.002; RA: OR, 1.54, P=0.004). Conclusions: Fibrotic atCM is associated with female sex, persistent AF, and heart failure, while hypertrophic features are more common in men

An angiopoietin 2, FGF23, and BMP10 biomarker signature differentiates atrial fibrillation from other concomitant cardiovascular conditions

Abstract Early detection of atrial fibrillation (AF) enables initiation of anticoagulation and early rhythm control therapy to reduce stroke, cardiovascular death, and heart failure. In a cross-sectional, observational study, we aimed to identify a combination of circulating biomolecules reflecting different biological processes to detect prevalent AF in patients with cardiovascular conditions presenting to hospital. Twelve biomarkers identified by reviewing literature and patents were quantified on a high-precision, high-throughput platform in 1485 consecutive patients with cardiovascular conditions (median age 69 years [Q1, Q3 60, 78]; 60% male). Patients had either known AF (45%) or AF ruled out by 7-day ECG-monitoring. Logistic regression with backward elimination and a neural network approach considering 7 key clinical characteristics and 12 biomarker concentrations were applied to a randomly sampled discovery cohort (n = 933) and validated in the remaining patients (n = 552). In addition to age, sex, and body mass index (BMI), BMP10, ANGPT2, and FGF23 identified patients with prevalent AF (AUC 0.743 [95% CI 0.712, 0.775]). These circulating biomolecules represent distinct pathways associated with atrial cardiomyopathy and AF. Neural networks identified the same variables as the regression-based approach. The validation using regression yielded an AUC of 0.719 (95% CI 0.677, 0.762), corroborated using deep neural networks (AUC 0.784 [95% CI 0.745, 0.822]). Age, sex, BMI and three circulating biomolecules (BMP10, ANGPT2, FGF23) are associated with prevalent AF in unselected patients presenting to hospital. Findings should be externally validated. Results suggest that age and different disease processes approximated by these three biomolecules contribute to AF in patients. Our findings have the potential to improve screening programs for AF after external validation

Diagnosis of childhood febrile illness using a multi-class blood RNA molecular signature

Background: Appropriate treatment and management of children presenting with fever depend on accurate and timely diagnosis, but current diagnostic tests lack sensitivity and specificity and are frequently too slow to inform initial treatment. As an alternative to pathogen detection, host gene expression signatures in blood have shown promise in discriminating several infectious and inflammatory diseases in a dichotomous manner. However, differential diagnosis requires simultaneous consideration of multiple diseases. Here, we show that diverse infectious and inflammatory diseases can be discriminated by the expression levels of a single panel of genes in blood. Methods: A multi-class supervised machine-learning approach, incorporating clinical consequence of misdiagnosis as a ‘‘cost’’ weighting, was applied to a whole-blood transcriptomic microarray dataset, incorporating 12 publicly available datasets, including 1,212 children with 18 infectious or inflammatory diseases. The transcriptional panel identifiedwas further validated in a new RNA sequencing dataset comprising 411 febrile children. Findings: We identified 161 transcripts that classified patients into 18 disease categories, reflecting individual causative pathogen and specific disease, as well as reliable prediction of broad classes comprising bacterial infection, viral infection, malaria, tuberculosis, or inflammatory disease. The transcriptional panel was validated in an independent cohort andbenchmarked against existingdichotomousRNA signatures. Conclusions: Our data suggest that classification of febrile illness can be achieved with a single blood sample and opens the way for a new approach for clinical diagnosis. Funding: European Union’s Seventh Framework no. 279185; Horizon2020 no. 668303 PERFORM; Wellcome Trust (206508/Z/17/Z); Medical Research Foundation (MRF-160-0008-ELP-KAFO-C0801); NIHR Imperial BRC

Relationship between molecular pathogen detection and clinical disease in febrile children across Europe:a multicentre, prospective observational study

Background: The PERFORM study aimed to understand causes of febrile childhood illness by comparing molecular pathogen detection with current clinical practice. Methods: Febrile children and controls were recruited on presentation to hospital in 9 European countries 2016–2020. Each child was assigned a standardized diagnostic category based on retrospective review of local clinical and microbiological data. Subsequently, centralised molecular tests (CMTs) for 19 respiratory and 27 blood pathogens were performed. Findings: Of 4611 febrile children, 643 (14%) were classified as definite bacterial infection (DB), 491 (11%) as definite viral infection (DV), and 3477 (75%) had uncertain aetiology. 1061 controls without infection were recruited. CMTs detected blood bacteria more frequently in DB than DV cases for N. meningitidis (OR: 3.37, 95% CI: 1.92–5.99), S. pneumoniae (OR: 3.89, 95% CI: 2.07–7.59), Group A streptococcus (OR 2.73, 95% CI 1.13–6.09) and E. coli (OR 2.7, 95% CI 1.02–6.71). Respiratory viruses were more common in febrile children than controls, but only influenza A (OR 0.24, 95% CI 0.11–0.46), influenza B (OR 0.12, 95% CI 0.02–0.37) and RSV (OR 0.16, 95% CI: 0.06–0.36) were less common in DB than DV cases. Of 16 blood viruses, enterovirus (OR 0.43, 95% CI 0.23–0.72) and EBV (OR 0.71, 95% CI 0.56–0.90) were detected less often in DB than DV cases. Combined local diagnostics and CMTs respectively detected blood viruses and respiratory viruses in 360 (56%) and 161 (25%) of DB cases, and virus detection ruled-out bacterial infection poorly, with predictive values of 0.64 and 0.68 respectively. Interpretation: Most febrile children cannot be conclusively defined as having bacterial or viral infection when molecular tests supplement conventional approaches. Viruses are detected in most patients with bacterial infections, and the clinical value of individual pathogen detection in determining treatment is low. New approaches are needed to help determine which febrile children require antibiotics. Funding: EU Horizon 2020 grant 668303.</p