Automated identification of Myxobacterial genera using Convolutional Neural Network.

The Myxococcales order consist of eleven families comprising30 genera, and are featured by the formation of the highest level of differential structure aggregations called fruiting bodies. These multicellular structures are essential for their resistance in ecosystems and is used in the primitive identification of these bacteria while their accurate taxonomic position is confirmed by the nucleotide sequence of 16SrRNA gene. Phenotypic classification of these structures is currently performed based on the stereomicroscopic observations that demand personal experience. The detailed phenotypic features of the genera with similar fruiting bodies are not readily distinctive by not particularly experienced researchers. The human examination of the fruiting bodies requires high skill and is error-prone. An image pattern analysis of schematic images of these structures conducted us to the construction of a database, which led to an extractable recognition of the unknown fruiting bodies. In this paper, Convolutional Neural Network (CNN) was considered as a baseline for recognition of fruiting bodies. In addition, to enhance the result the classifier, part of CNN is replaced with other classifiers. By employing the introduced model, all 30 genera of this order could be recognized based on stereomicroscopic images of the fruiting bodies at the genus level that not only does not urge us to amplify and sequence gene but also can be attained without preparation of microscopic slides of the vegetative cells or myxospores. The accuracy of 77.24% in recognition of genera and accuracy of 88.92% in recognition of suborders illustrate the applicability property of the proposed machine learning model.

Universal atrial coordinates applied to visualisation, registration and construction of patient specific meshes.

Integrating spatial information about atrial physiology and anatomy in a single patient from multimodal datasets, as well as generalizing these data across patients, requires a common coordinate system. In the atria, this is challenging due to the complexity and variability of the anatomy. We aimed to develop and validate a Universal Atrial Coordinate (UAC) system for the following applications: combination and assessment of multimodal data; comparison of spatial data across patients; 2D visualization; and construction of patient specific geometries to test mechanistic hypotheses. Left and right atrial LGE-MRI data were segmented and meshed. Two coordinates were calculated for each atrium by solving Laplace's equation, with boundary conditions assigned using five landmark points. The coordinate system was used to map spatial information between atrial meshes, including scalar fields measured using different mapping modalities, and atrial anatomic structures and fibre directions from a reference geometry. Average error in point transfer from a source mesh to a destination mesh and back again was less than 0.1 mm for the left atrium and 0.02 mm for the right atrium. Patient specific meshes were constructed using the coordinate system and phase singularity density maps from arrhythmia simulations were visualised in 2D. In conclusion, we have developed a universal atrial coordinate system allowing automatic registration of imaging and electroanatomic mapping data, 2D visualisation, and patient specific model creation.

Compartmentalized Structure of the Moderator Band Provides a Unique Substrate for Macroreentrant Ventricular Tachycardia.

Background Papillary muscles are an important source of ventricular tachycardia (VT). Yet little is known about the role of the right ventricular (RV) endocavity structure, the moderator band (MB). The aim of this study was to determine the characteristics of the MB that may predispose to arrhythmia substrates. Methods Ventricular wedge preparations with intact MBs were studied from humans (n=2) and sheep (n=15; 40-50 kg). RV endocardium was optically mapped, and electrical recordings were measured along the MB and septum. S1S2 pacing of the RV free wall, MB, or combined S1-RV S2-MB sites were assessed. Human (n=2) and sheep (n=4) MB tissue constituents were assessed histologically. Results The MB structure was remarkably organized as 2 excitable, yet uncoupled compartments of myocardium and Purkinje. In humans, action potential duration heterogeneity between MB and RV myocardium was found (324.6±12.0 versus 364.0±8.4 ms; P<0.0001). S1S2-MB pacing induced unidirectional propagation via MB myocardium, permitting sustained macroreentrant VT. In sheep, the incidence of VT for RV, MB, and S1-RV S2-MB pacing was 1.3%, 5.1%, and 10.3%. Severing the MB led to VT termination, confirming a primary arrhythmic role. Inducible preparations had shorter action potential duration in the MB than RV (259.3±45.2 versus 300.7±38.5 ms; P<0.05), whereas noninducible preparations showed no difference (312.0±30.3 versus 310.0±24.6 ms, respectively). Conclusions The MB presents anatomic and electrical compartmentalization between myocardium and Purkinje fibers, providing a substrate for macroreentry. The vulnerability to sustain VT via this mechanism is dependent on MB structure and action potential duration gradients between the RV free wall and MB.

Universal ventricular coordinates: A generic framework for describing position within the heart and transferring data.

Being able to map a particular set of cardiac ventricles to a generic topologically equivalent representation has many applications, including facilitating comparison of different hearts, as well as mapping quantities and structures of interest between them. In this paper we describe Universal Ventricular Coordinates (UVC), which can be used to describe position within any biventricular heart. UVC comprise four unique coordinates that we have chosen to be intuitive, well defined, and relevant for physiological descriptions. We describe how to determine these coordinates for any volumetric mesh by illustrating how to properly assign boundary conditions and utilize solutions to Laplace's equation. Using UVC, we transferred scalar, vector, and tensor data between four unstructured ventricular meshes from three different species. Performing the mappings was very fast, on the order of a few minutes, since mesh nodes were searched in a KD tree. Distance errors in mapping mesh nodes back and forth between meshes were less than the size of an element. Analytically derived fiber directions were also mapped across meshes and compared, showing  < 5° difference over most of the ventricles. The ability to transfer gradients was also demonstrated. Topologically variable structures, like papillary muscles, required further definition outside of the UVC framework. In conclusion, UVC can aid in transferring many types of data between different biventricular geometries.

Novel Radiofrequency Ablation Strategies for Terminating Atrial Fibrillation in the Left Atrium: A Simulation Study.

Pulmonary vein isolation (PVI) with radiofrequency ablation (RFA) is the cornerstone of atrial fibrillation (AF) therapy, but few strategies exist for when it fails. To guide RFA, phase singularity (PS) mapping locates reentrant electrical waves (rotors) that perpetuate AF. The goal of this study was to test existing and develop new RFA strategies for terminating rotors identified with PS mapping. It is unsafe to test experimental RFA strategies in patients, so they were evaluated in silico using a bilayer computer model of the human atria with persistent AF (pAF) electrical (ionic) and structural (fibrosis) remodeling. pAF was initiated by rapidly pacing the right (RSPV) and left (LSPV) superior pulmonary veins during sinus rhythm, and rotor dynamics quantified by PS analysis. Three RFA strategies were studied: (i) PVI, roof, and mitral lines; (ii) circles, perforated circles, lines, and crosses 0.5-1.5 cm in diameter/length administered near rotor locations/pathways identified by PS mapping; and (iii) 4-8 lines streamlining the sequence of electrical activation during sinus rhythm. As in pAF patients, 2 ± 1 rotors with cycle length 185 ± 4 ms and short PS duration 452 ± 401 ms perpetuated simulated pAF. Spatially, PS density had weak to moderate positive correlations with fibrosis density (RSPV: r = 0.38, p = 0.35, LSPV: r = 0.77, p = 0.02). RFA PVI, mitral, and roof lines failed to terminate pAF, but RFA perforated circles and lines 1.5 cm in diameter/length terminated meandering rotors from RSPV pacing when placed at locations with high PS density. Similarly, RFA circles, perforated circles, and crosses 1.5 cm in diameter/length terminated stationary rotors from LSPV pacing. The most effective strategy for terminating pAF was to streamline the sequence of activation during sinus rhythm with >4 RFA lines. These results demonstrate that co-localizing 1.5 cm RFA lesions with locations of high PS density is a promising strategy for terminating pAF rotors. For patients immune to PVI, roof, mitral, and PS guided RFA strategies, streamlining patient-specific activation sequences during sinus rhythm is a robust but challenging alternative.

Percolation as a mechanism to explain atrial fractionated electrograms and reentry in a fibrosis model based on imaging data.

BACKGROUND: Complex fractionated atrial electrograms (CFAEs) have long been associated with proarrhythmic alterations in atrial structure or electrophysiology. Structural alterations disrupt and slow smoothly propagating wavefronts, leading to wavebreaks and electrogram (EGM) fractionation, but the exact nature and characteristics for arrhythmia remain unknown. Clinically, in atrial fibrillation (AF) patients, increases in frequency, whether by pacing or fibrillation, increase EGM fractionation and duration, and reentry can occur in relation with the conduction disturbance. Recently, percolation has been proposed as an arrhythmogenic mechanism, but its role in AF has not been investigated. OBJECTIVE: We sought to determine if percolation can explain reentry formation and EGM behavior observed in AF patients. METHODS: Computer models of fibrotic tissue with different densities were generated based on late gadolinium-enhanced magnetic resonance images, using pixel intensity as a fibrosis probability to avoid an arbitrary binary threshold. Clinical pacing protocols were followed to induce AF, and EGMs were computed. RESULTS: Reentry could be elicited, with a biphasic behavior dependent on fibrotic density. CFAEs were recorded above fibrotic regions, and consistent with clinical data, EGM duration and fractionation increased with more rapid pacing. CONCLUSION: These findings confirm percolation as a potential mechanism to explain AF in humans and give new insights into dynamics underlying conduction distortions and fractionated signals in excitable media, which correlate well with the experimental findings in fibrotic regions. The greater understanding of the different patterns of conduction changes and related EGMs could lead to more individualized and effective approaches to AF ablation therapy.

Decrement Evoked Potential Mapping: Basis of a Mechanistic Strategy for Ventricular Tachycardia Ablation.

BACKGROUND: Substrate-based mapping for ventricular tachycardia (VT) ablation is hampered by its inability to determine critical sites of the VT circuit. We hypothesized that those potentials, which delay with a decremental extrastimulus (decrement evoked potentials or DEEPs), are more likely to colocalize with the diastolic pathways of VT circuits. METHODS AND RESULTS: DEEPs were identified in intraoperative left ventricular maps from 6 patients with ischemic cardiomyopathy (total 9 VTs) and were compared with late potential (LP) and activation maps of the diastolic pathway for each VT. Mathematical modeling was also used to further validate and elucidate the mechanisms of DEEP mapping. All patients demonstrated regions of DEEPs and LPs. The mean endocardial surface area of these potentials was 18±4% and 21±6%, respectively (P=0.13). The mean sensitivity for identifying the diastolic pathway in VT was 50±23% for DEEPs and 36±32% for LPs (P=0.31). The mean specificity was 43±23% versus 20±8% for DEEP and LP mapping, respectively (P=0.031). The electrograms that displayed the greatest decrement in each case had a sensitivity and specificity for the VT isthmus of 29±10% and 95±1%, respectively. Mathematical modeling studies recapitulated DEEPs at the VT isthmus and demonstrated their role in VT initiation with a critical degree of decrement. CONCLUSIONS: In this preliminary study, DEEP mapping was more specific than LP mapping for identifying the critical targets of VT ablation. The mechanism of DEEPs relates to conduction velocity restitution magnified by zigzag conduction within scar channels.

Computation and projection of spiral wave trajectories during atrial fibrillation: a computational study.

To show how atrial fibrillation rotor activity on the heart surface manifests as phase on the torso, fibrillation was induced on a geometrically accurate computer model of the human atria. The Hilbert transform, time embedding, and filament detection were compared. Electrical activity on the epicardium was used to compute potentials on different surfaces from the atria to the torso. The Hilbert transform produces erroneous phase when pacing for longer than the action potential duration. The number of phase singularities, frequency content, and the dominant frequency decreased with distance from the heart, except for the convex hull.

Evaluation of Gastric Lesions Based on Helicobacter pylori and Helicobacter-Like Organisms (HLOs) in Cats; A Histopathological and Bacteriological Study.

BACKGROUND: The lesions induced by Helicobacter pylori in a candidate animal model should always be examined thoroughly. The resemblance of these lesions to those observed in humans can indicate whether the usage of this model will contribute to the understanding of the various pathogenic mechanisms involved in the development of human H. pylori-associated diseases. OBJECTIVES: The aim of this study was to perform a histopathological and bacteriological evaluation of gastric lesions based on H. pylori and Helicobacter-like organisms (HLOs) in cats. MATERIALS AND METHODS: The present study was carried out on 28 cat's (13 male and 15 female cases) gastric mucosae, which were tested by bacteriological and histopathological methods. Biochemical tests such as catalase, oxidase and urease were utilized in addition to Gram and Giemsa staining. RESULTS: This research demonstrated that solely one case of H. pylori was isolated by gastric mucosal culture. Microscopically, the infected stomachs by HLOs comprised a mild to severe diffuse lymphoplasmacytic infiltration into the subglandular and gastric mucosa. Lymphoid follicles were also marked, particularly within pyloric tissues and mostly in displaced mucosal glands. For 75% of the gastritis cases, both HLOs and rapid urease tests were positive, whereas 83% of cases were more than one-year-old with gastritis. Furthermore, 75% of cats indicated gastritis, though 25% encompassed no gastritis; hence 20% had negative results for the rapid urease test and 25% for the Giemsa staining test. Such results may indicate that cats without gastritis were considered as free of HLOs pathogenic bacteria. CONCLUSIONS: These results suggest that most cases of gastritis were located in the antral region. Additionally, the isolation of H. pylori from domestic cats raises the possibility of zoonotic characteristics for the slightly pathogen; therefore transmission occurs from cats to human and vice versa.

Effect of statistically derived fiber models on the estimation of cardiac electrical activation.

Myocardial fiber orientation plays a critical role in the electrical activation and subsequent contraction of the heart. To increase the clinical potential of electrophysiological (EP) simulation for the study of cardiac phenomena and the planning of interventions, accurate personalization of the fibers is a necessary yet challenging task. Due to the difficulties associated with the in vivo imaging of cardiac fiber structure, researchers have developed alternative techniques to personalize fibers. Thus far, cardiac simulation was performed mainly based on rule-based fiber models. More recently, there has been a significant interest in data-driven and statistically derived fiber models. In particular, our predictive method in [1] allows us to estimate the unknown subject-specific fiber orientation based on the more easily available shape information. The aim of this work is to estimate the effect of using such statistical predictive models for the estimation of cardiac electrical activation times and patterns. To this end, we perform EP simulations based on a database of ten canine ex vivo diffusion tensor imaging (DTI) datasets that include normal and failing cases. To assess the strength of the fiber models under varying conditions, we consider both sinus rhythm and biventricular pacing simulations. The results show that 1) the statistically derived fibers improve the estimation of the local activation times by an average of 53.7% over traditional rule-based models, and that 2) the obtained electrical activations are consistently similar to those of the DTI-based fibers.

Statistical personalization of ventricular fiber orientation using shape predictors.

This paper presents a predictive framework for the statistical personalization of ventricular fibers. To this end, the relationship between subject-specific geometry of the left (LV) and right ventricles (RV) and fiber orientation is learned statistically from a training sample of ex vivo diffusion tensor imaging datasets. More specifically, the axes in the shape space which correlate most with the myocardial fiber orientations are extracted and used for prediction in new subjects. With this approach and unlike existing fiber models, inter-subject variability is taken into account to generate latent shape predictors that are statistically optimal to estimate fiber orientation at each individual myocardial location. The proposed predictive model was applied to the task of personalizing fibers in 10 canine subjects. The results indicate that the ventricular shapes are good predictors of fiber orientation, with an improvement of 11.4% in accuracy over the average fiber model.

Numerical simulation of blood flow in the left ventricle and aortic sinus using magnetic resonance imaging and computational fluid dynamics.

Understanding cardiac blood flow patterns has many applications in analysing haemodynamics and for the clinical assessment of heart function. In this study, numerical simulations of blood flow in a patient-specific anatomical model of the left ventricle (LV) and the aortic sinus are presented. The realistic 3D geometry of both LV and aortic sinus is extracted from the processing of magnetic resonance imaging (MRI). Furthermore, motion of inner walls of LV and aortic sinus is obtained from cine-MR image analysis and is used as a constraint to a numerical computational fluid dynamics (CFD) model based on the moving boundary approach. Arbitrary Lagrangian-Eulerian finite element method formulation is used for the numerical solution of the transient dynamic equations of the fluid domain. Simulation results include detailed flow characteristics such as velocity, pressure and wall shear stress for the whole domain. The aortic outflow is compared with data obtained by phase-contrast MRI. Good agreement was found between simulation results and these measurements.

Model generation of coronary artery bifurcations from CTA and single plane angiography.

PURPOSE: To generate accurate and realistic models of coronary artery bifurcations before and after percutaneous coronary intervention (PCI), using information from two image modalities. Because bifurcations are regions where atherosclerotic plaque appears frequently and intervention is more challenging, generation of such realistic models could be of high value to predict the risk of restenosis or thrombosis after stent implantation, and to study geometrical and hemodynamical changes. METHODS: Two image modalities have been employed to generate the bifurcation models: computer tomography angiography (CTA) to obtain the 3D trajectory of vessels, and 2D conventional coronary angiography (CCA) to obtain radius information of the vessel lumen, due to its better contrast and image resolution. In addition, CCA can be acquired right before and after the intervention in the operation room; therefore, the combination of CTA and CCA allows the generation of realistic preprocedure and postprocedure models of coronary bifurcations. The method proposed is semiautomatic, based on landmarks manually placed on both image modalities. RESULTS: A comparative study of the models obtained with the proposed method with models manually obtained using only CTA, shows more reliable results when both modalities are used together. The authors show that using preprocedure CTA and postprocedure CCA, realistic postprocedure models can be obtained. Analysis carried out of the Murray's law in all patient bifurcations shows the geometric improvement of PCI in our models, better than using manual models from CTA alone. An experiment using a cardiac phantom also shows the feasibility of the proposed method. CONCLUSIONS: The authors have shown that fusion of CTA and CCA is feasible for realistic generation of coronary bifurcation models before and after PCI. The method proposed is efficient, and relies on minimal user interaction, and therefore is of high value to study geometric and hemodynamic changes of treated patients.

Relationship between endocardial activation sequences defined by high-density mapping to early septal contraction (septal flash) in patients with left bundle branch block undergoing cardiac resynchronization therapy.

AIMS: Early inward motion and thickening/thinning of the ventricular septum associated with left bundle branch block is known as the septal flash (SF). Correction of SF corresponds to response to cardiac resynchronization therapy (CRT). We hypothesized that SF was associated with a specific left ventricular (LV) activation pattern predicting a favourable response to CRT. We sought to characterize the spatio-temporal relationship between electrical and mechanical events by directly comparing non-contact mapping (NCM), acute haemodynamics, and echocardiography. METHODS AND RESULTS: Thirteen patients (63 ± 10 years, 10 men) with severe heart failure (ejection fraction 22.8 ± 5.8%) awaiting CRT underwent echocardiography and NCM pre-implant. Presence and extent of SF defined visually and with M-mode was fused with NCM bull's eye plots of endocardial activation patterns. LV-dP/dt(max) was measured during different pacing modes. Five patients had a large SF, four small SF, and four no SF. Large SF patients had areas of conduction block in non-infarcted regions, whereas those with small or no SF did not. Patients with large SF had greater acute response to LV and biventricular (BIV) pacing vs. those with small/no SF (% increase dP/dt 28 ± 14 vs. 11 ± 19% for LV pacing and 42 ± 28 vs. 22 ± 21% for BIV pacing) (P < 0.05). This translated into a more favourable chronic response to CRT. The lines of conduction block disappeared with LV/BIV pacing while remaining with right ventricle pacing. CONCLUSION: A strong association exists between electrical activation and mechanical deformation of the septum. Correction of both mechanical synchrony and the functional conduction block by CRT may explain the favourable response in patients with SF.

Fast multiscale modeling of cardiac electrophysiology including Purkinje system.

In this paper, we present a modeling methodology to couple the cardiac conduction system to cardiac myocytes through a model of Purkinje-ventricular junctions to yield fast and realistic electrical activation of the ventricles. A patient-specific biventricular geometry is obtained from processing computed tomography scan data. A one-manifold implementation of the fast marching method based on Eikonal-type equations is used for modeling heart electrophysiology, which facilitates the multiscale 1-D-3-D coupling at very low computational costs. The method is illustrated in in-silico experiments where we analyze and compare alternative pacing strategies on the same patient-specific anatomy. We also show very good agreement between the results from the proposed approach and more detailed and comprehensive biophysical models for modeling cardiac electrophysiology. The effect of atrioventricular delay on the distribution of activation time in myocardium is studied with two experiments. Given the reasonable computational times and realistic activation sequences provided by our method, it can have an important clinical impact on the selection of optimal implantation sites of pacing leads or placement of ablation catheter's tip in the context of cardiac rhythm management therapies.

OpenCMISS: a multi-physics & multi-scale computational infrastructure for the VPH/Physiome project.

The VPH/Physiome Project is developing the model encoding standards CellML (cellml.org) and FieldML (fieldml.org) as well as web-accessible model repositories based on these standards (models.physiome.org). Freely available open source computational modelling software is also being developed to solve the partial differential equations described by the models and to visualise results. The OpenCMISS code (opencmiss.org), described here, has been developed by the authors over the last six years to replace the CMISS code that has supported a number of organ system Physiome projects. OpenCMISS is designed to encompass multiple sets of physical equations and to link subcellular and tissue-level biophysical processes into organ-level processes. In the Heart Physiome project, for example, the large deformation mechanics of the myocardial wall need to be coupled to both ventricular flow and embedded coronary flow, and the reaction-diffusion equations that govern the propagation of electrical waves through myocardial tissue need to be coupled with equations that describe the ion channel currents that flow through the cardiac cell membranes. In this paper we discuss the design principles and distributed memory architecture behind the OpenCMISS code. We also discuss the design of the interfaces that link the sets of physical equations across common boundaries (such as fluid-structure coupling), or between spatial fields over the same domain (such as coupled electromechanics), and the concepts behind CellML and FieldML that are embodied in the OpenCMISS data structures. We show how all of these provide a flexible infrastructure for combining models developed across the VPH/Physiome community.