Beyond Simpson's Rule: Accounting for Orientation and Ellipticity Assumptions.

Simpson's biplane rule (SBR) is considered the gold standard method for left ventricle (LV) volume quantification from echocardiography but relies on a summation-of-disks approach that makes assumptions about LV orientation and cross-sectional shape. We aim to identify key limiting factors in SBR and to develop a new robust standard for volume quantification. Three methods for computing LV volume were studied: (i) SBR, (ii) addition of a truncated basal cone (TBC) to SBR and (iii) a novel method of basal-oriented disks (BODs). Three retrospective cohorts representative of the young, adult healthy and heart failure populations were used to study the impact of anatomical variations in volume computations. Results reveal how basal slanting can cause over- and underestimation of volume, with errors by SBR and TBC >10 mL for slanting angles >6°. Only the BOD method correctly accounted for basal slanting, reducing relative volume errors by SBR from -2.23 ± 2.21% to -0.70 ± 1.91% in the adult population and similar qualitative performance in the other two cohorts. In conclusion, the summation of basal oriented disks, a novel interpretation of SBR, is a more accurate and precise method for estimating LV volume.

Automated Echocardiographic Detection of Severe Coronary Artery Disease Using Artificial Intelligence.

OBJECTIVES: The purpose of this study was to establish whether an artificially intelligent (AI) system can be developed to automate stress echocardiography analysis and support clinician interpretation. BACKGROUND: Coronary artery disease is the leading global cause of mortality and morbidity and stress echocardiography remains one of the most commonly used diagnostic imaging tests. METHODS: An automated image processing pipeline was developed to extract novel geometric and kinematic features from stress echocardiograms collected as part of a large, United Kingdom-based prospective, multicenter, multivendor study. An ensemble machine learning classifier was trained, using the extracted features, to identify patients with severe coronary artery disease on invasive coronary angiography. The model was tested in an independent U.S. STUDY: How availability of an AI classification might impact clinical interpretation of stress echocardiograms was evaluated in a randomized crossover reader study. RESULTS: Acceptable classification accuracy for identification of patients with severe coronary artery disease in the training data set was achieved on cross-fold validation based on 31 unique geometric and kinematic features, with a specificity of 92.7% and a sensitivity of 84.4%. This accuracy was maintained in the independent validation data set. The use of the AI classification tool by clinicians increased inter-reader agreement and confidence as well as sensitivity for detection of disease by 10% to achieve an area under the receiver-operating characteristic curve of 0.93. CONCLUSIONS: Automated analysis of stress echocardiograms is possible using AI and provision of automated classifications to clinicians when reading stress echocardiograms could improve accuracy, inter-reader agreement, and reader confidence.

Exploring the Role of Self-Motives in Postgraduate Trainees' Feedback-Seeking Behavior in the Clinical Workplace: A Multicenter Study of Workplace-Based Assessments From the United Kingdom.

PURPOSE: To explore trainees' feedback-seeking behavior in the postgraduate surgical workplace using a self-motives framework. Self-motives include self-assessment "to obtain accurate information about the self," self-improvement "to improve one's traits, abilities, and skills," self-enhancement "to enhance the favorability of self views," and self-verification "to maintain consistency between one's central self-view and new self-relevant information." METHOD: This project constituted a further framework analysis of previously obtained qualitative focus group data that originally explored trainees' perceptions and use of workplace-based assessment (WBA). Data were collected from multiple centers in the United Kingdom from 2012 to 2013. Content was analyzed to identify references in the data that reflected the above self-motives and in relation to contextual themes identified from within the data. RESULTS: Trainees' motivations for seeking feedback broadly fit within a self-motives framework. Trainees' feedback seeking using WBA related to self-enhancement and self-verification, whereas outside WBA trainees reported self-improvement and self-assessment motives. Where trainees perceived WBA represented an opportunity to learn, they described a self-improvement motive toward seeking feedback, whereas when WBA represented an assessment of learning, trainees described tensions between self-enhancement and self-improvement motives. CONCLUSIONS: Surgical trainees' motivations for seeking feedback can be explained using a conceptual self-motives framework. Trainees need to be motivated to seek accurate informational feedback so they can improve their performance within the clinical workplace. To achieve this, trainees need training; current assessment systems must change to allow trainees to seek such feedback without fear and concern about this information being used as an assessment of learning.

'Playing the game': How do surgical trainees seek feedback using workplace-based assessment?

OBJECTIVES: Although trainees and trainers find feedback interactions beneficial, difficulties in giving and receiving feedback are reported. Few studies have explored what drives trainees to seek feedback. This study explores how workplace-based assessments (WBAs) influence the ways surgical trainees seek feedback and feedback interactions. METHODS: Utilising a template analysis approach, we conducted 10 focus groups with 42 surgical trainees from four regions across the UK. Data were independently coded by three researchers, incorporating three a priori themes identified from a previous quantitative study. Further themes emerged from exploration of these data. The final template, agreed by the three researchers, was applied to all focus group transcripts. The themes were linked in a diagrammatical form to allow critical exploration of the data. RESULTS: Trainees' perceptions of the purpose of WBA for learning or an assessment of learning, and their relationship with their trainer impacted upon how trainees chose to use WBA. Perceiving WBA as a test led trainees to 'play the game': seek positive and avoid negative feedback through WBA. Perceiving WBA as a chance to learn led trainees to seek negative feedback. Some trainees sought negative feedback outside WBA. Negative feedback was more important for changing practice compared with positive feedback, which enabled trainees to 'look good' but had less of an effect on changing clinical practice. The timing of feedback relative to WBA was also important, with immediate feedback being more beneficial for learning; however, delayed feedback was still sought using WBA. DISCUSSION: Trainees' perceptions of the purpose of WBA and their relationship with their trainer informed when they chose to seek feedback. Trainees who perceived WBA as a test were led to 'play the game' by seeking positive and avoiding negative feedback. Outside of WBA, trainees sought negative feedback, which was most important for change in practice.

Surgical Trainee Feedback-Seeking Behavior in the Context of Workplace-Based Assessment in Clinical Settings.

PURPOSE: To investigate surgical trainee feedback-seeking behaviors-directly asking for feedback (inquiry) and observing and responding to situational clues (monitoring)-in the context of workplace-based assessment (WBA). METHOD: A hypothetical model of trainee feedback-seeking behavior was developed using existing literature. A questionnaire, incorporating previously validated instruments from organizational psychology, was distributed to general surgical trainees at 23 U.K. hospitals in 2012-2013. Statistical modeling techniques compared the data with 12 predetermined hypothetical relationships between feedback-seeking behaviors and predictive variables (goal orientation, supervisory style) through mediating variables (perceptions of personal benefits and costs of feedback) to develop a final model. RESULTS: Of 235 trainees invited, 178 (76%) responded. Trainees completed 48 WBAs/year on average, and 73% reported receiving feedback via WBA. The final model was of good fit (chi-square/degree of freedom ratio = 1.620, comparative fit index = 0.953, root mean square error of approximation = 0.059). Modeled data showed trainees who perceive personal benefits to feedback use both feedback inquiry and monitoring to engage in feedback interactions. Trainees who seek feedback engage in using WBA. Trainees' goal orientations and perceptions of trainers' supervisory styles as supportive and instrumental are associated with perceived benefits and costs to feedback. CONCLUSIONS: Trainees actively engage in seeking feedback and using WBA. Their perceptions of feedback benefits and costs and supervisory style play a role in their feedback-seeking behavior. Encouraging trainees to actively seek feedback by providing specific training and creating a supportive environment for feedback interactions could positively affect their ability to seek feedback.

Choosing an Appropriate Modelling Framework for Analysing Multispecies Co-culture Cell Biology Experiments.

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insufficient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

Comparing methods for modelling spreading cell fronts.

Spreading cell fronts play an essential role in many physiological processes. Classically, models of this process are based on the Fisher-Kolmogorov equation; however, such continuum representations are not always suitable as they do not explicitly represent behaviour at the level of individual cells. Additionally, many models examine only the large time asymptotic behaviour, where a travelling wave front with a constant speed has been established. Many experiments, such as a scratch assay, never display this asymptotic behaviour, and in these cases the transient behaviour must be taken into account. We examine the transient and the asymptotic behaviour of moving cell fronts using techniques that go beyond the continuum approximation via a volume-excluding birth-migration process on a regular one-dimensional lattice. We approximate the averaged discrete results using three methods: (i) mean-field, (ii) pair-wise, and (iii) one-hole approximations. We discuss the performance of these methods, in comparison to the averaged discrete results, for a range of parameter space, examining both the transient and asymptotic behaviours. The one-hole approximation, based on techniques from statistical physics, is not capable of predicting transient behaviour but provides excellent agreement with the asymptotic behaviour of the averaged discrete results, provided that cells are proliferating fast enough relative to their rate of migration. The mean-field and pair-wise approximations give indistinguishable asymptotic results, which agree with the averaged discrete results when cells are migrating much more rapidly than they are proliferating. The pair-wise approximation performs better in the transient region than does the mean-field, despite having the same asymptotic behaviour. Our results show that each approximation only works in specific situations, thus we must be careful to use a suitable approximation for a given system, otherwise inaccurate predictions could be made.

Incorporating spatial correlations into multispecies mean-field models.

In biology, we frequently observe different species existing within the same environment. For example, there are many cell types in a tumour, or different animal species may occupy a given habitat. In modeling interactions between such species, we often make use of the mean-field approximation, whereby spatial correlations between the locations of individuals are neglected. Whilst this approximation holds in certain situations, this is not always the case, and care must be taken to ensure the mean-field approximation is only used in appropriate settings. In circumstances where the mean-field approximation is unsuitable, we need to include information on the spatial distributions of individuals, which is not a simple task. In this paper, we provide a method that overcomes many of the failures of the mean-field approximation for an on-lattice volume-excluding birth-death-movement process with multiple species. We explicitly take into account spatial information on the distribution of individuals by including partial differential equation descriptions of lattice site occupancy correlations. We demonstrate how to derive these equations for the multispecies case and show results specific to a two-species problem. We compare averaged discrete results to both the mean-field approximation and our improved method, which incorporates spatial correlations. We note that the mean-field approximation fails dramatically in some cases, predicting very different behavior from that seen upon averaging multiple realizations of the discrete system. In contrast, our improved method provides excellent agreement with the averaged discrete behavior in all cases, thus providing a more reliable modeling framework. Furthermore, our method is tractable as the resulting partial differential equations can be solved efficiently using standard numerical techniques.

Simplified method for including spatial correlations in mean-field approximations.

Biological systems involving proliferation, migration, and death are observed across all scales. For example, they govern cellular processes such as wound healing, as well as the population dynamics of groups of organisms. In this paper, we provide a simplified method for correcting mean-field approximations of volume-excluding birth-death-movement processes on a regular lattice. An initially uniform distribution of agents on the lattice may give rise to spatial heterogeneity, depending on the relative rates of proliferation, migration, and death. Many frameworks chosen to model these systems neglect spatial correlations, which can lead to inaccurate predictions of their behavior. For example, the logistic model is frequently chosen, which is the mean-field approximation in this case. This mean-field description can be corrected by including a system of ordinary differential equations for pairwise correlations between lattice site occupancies at various lattice distances. In this work we discuss difficulties with this method and provide a simplification in the form of a partial differential equation description for the evolution of pairwise spatial correlations over time. We test our simplified model against the more complex corrected mean-field model, finding excellent agreement. We show how our model successfully predicts system behavior in regions where the mean-field approximation shows large discrepancies. Additionally, we investigate regions of parameter space where migration is reduced relative to proliferation, which has not been examined in detail before and find our method is successful at correcting the deviations observed in the mean-field model in these parameter regimes.