Conveying clinical reasoning based on visual observation via eye-movement modelling examples

Jarodzka, H., Balslev, T., Holmqvist, K., Nyström, M., Scheiter, K., Gerjets, P., & Eika, B. (2012). Conveying clinical reasoning based on visual observation via eye-movement modelling examples. Instructional Science, 40(5), 813-827. doi:10.1007/s11251-012-9218-5Complex perceptual tasks, like clinical reasoning based on visual observations of patients, require not only conceptual knowledge about diagnostic classes but also the skills to visually search for symptoms and interpret these observations. However, medical education so far has focused very little on how visual observation skills can be efficiently conveyed to novices. The current study applied a novel instructional method to teach these skills by showing the learners how an expert model visually searches and interprets symptoms (i.e., eye-movement modelling examples; EMMEs). Case videos of patients were verbally explained by a model (control condition) and presented to students. In the experimental conditions, the participants received a recording of the model’s eye movements superimposed on the case videos. The eye movements were displayed by either highlighting the features the model focused on with a circle (the circle condition) or by blurring the features the model did not focus on (the spotlight condition). Compared to the other two conditions, results show that a spotlight on the case videos better guides the students’ attention towards the relevant features. Moreover, when testing the students’ clinical reasoning skills with videos of new patient cases without any guidance participants studying EMMEs with a spotlight showed improved their visual search and enhanced interpretation performance of the symptoms in contrast to participants in either the circle or the control condition. These findings show that a spotlight EMME can successfully convey clinical reasoning based on visual observations

Epilepsy

Epilepsy is the most common neurological disorder globally, affecting approximately 50 million people of all ages. It is one of the oldest diseases described in literature from remote ancient civilizations 2000-3000 years ago. Despite its long history and wide spread, epilepsy is still surrounded by myth and prejudice, which can only be overcome with great difficulty. The term epilepsy is derived from the Greek verb epilambanein, which by itself means to be seized and to be overwhelmed by surprise or attack. Therefore, epilepsy is a condition of getting over, seized, or attacked. The twelve very interesting chapters of this book cover various aspects of epileptology from the history and milestones of epilepsy as a disease entity, to the most recent advances in understanding and diagnosing epilepsy

The Value of Seizure Semiology in Epilepsy Surgery: Epileptogenic-Zone Localisation in Presurgical Patients using Machine Learning and Semiology Visualisation Tool

Background Eight million individuals have focal drug resistant epilepsy worldwide. If their epileptogenic focus is identified and resected, they may become seizure-free and experience significant improvements in quality of life. However, seizure-freedom occurs in less than half of surgical resections. Seizure semiology - the signs and symptoms during a seizure - along with brain imaging and electroencephalography (EEG) are amongst the mainstays of seizure localisation. Although there have been advances in algorithmic identification of abnormalities on EEG and imaging, semiological analysis has remained more subjective. The primary objective of this research was to investigate the localising value of clinician-identified semiology, and secondarily to improve personalised prognostication for epilepsy surgery. Methods I data mined retrospective hospital records to link semiology to outcomes. I trained machine learning models to predict temporal lobe epilepsy (TLE) and determine the value of semiology compared to a benchmark of hippocampal sclerosis (HS). Due to the hospital dataset being relatively small, we also collected data from a systematic review of the literature to curate an open-access Semio2Brain database. We built the Semiology-to-Brain Visualisation Tool (SVT) on this database and retrospectively validated SVT in two separate groups of randomly selected patients and individuals with frontal lobe epilepsy. Separately, a systematic review of multimodal prognostic features of epilepsy surgery was undertaken. The concept of a semiological connectome was devised and compared to structural connectivity to investigate probabilistic propagation and semiology generation. Results Although a (non-chronological) list of patients’ semiologies did not improve localisation beyond the initial semiology, the list of semiology added value when combined with an imaging feature. The absolute added value of semiology in a support vector classifier in diagnosing TLE, compared to HS, was 25%. Semiology was however unable to predict postsurgical outcomes. To help future prognostic models, a list of essential multimodal prognostic features for epilepsy surgery were extracted from meta-analyses and a structural causal model proposed. Semio2Brain consists of over 13000 semiological datapoints from 4643 patients across 309 studies and uniquely enabled a Bayesian approach to localisation to mitigate TLE publication bias. SVT performed well in a retrospective validation, matching the best expert clinician’s localisation scores and exceeding them for lateralisation, and showed modest value in localisation in individuals with frontal lobe epilepsy (FLE). There was a significant correlation between the number of connecting fibres between brain regions and the seizure semiologies that can arise from these regions. Conclusions Semiology is valuable in localisation, but multimodal concordance is more valuable and highly prognostic. SVT could be suitable for use in multimodal models to predict the seizure focus

NOVEL COMPUTATIONAL ELECTROENCEPHALOGRAPHIC (EEG) METHODOLOGIES FOR AUTISM MANAGEMENT AND EPILEPTIC SEIZURE PREDICTION

The doctoral thesis deals with a novel methodology of looking and processing electroencephalographic (EEG) data. The first part deals with real-time brain stimulation in the form of a sonified neurofeedback therapy derived from a clinically comparable portable, 4-channel EEG system. The therapy aims to provide an effective management for symptoms of the Autism Spectrum Disorder (ASD). ASD is characterized with a high level of delta electroencephalographic waveform levels, while alpha and beta prove to be present at lower levels especially in the frontal-temporal regions. The treatment aims at lowering delta waves and promoting alpha and beta waveforms. The second part of the thesis focuses on using EEG data in the prediction of epileptic seizures. With the help of custom built algorithms and neural networks, an effective prediction of an epileptic seizure can be achieved

An exploration of epileptic and nonepileptic seizures : an interpretative phenomenological analytic study

Background Differentiating epileptic seizures from non epileptic seizures (NES) has always been difficult. Seizures can look very similar, substantial physical injury and incontinence can occur in both conditions and people can have both conditions simultaneously. Treatment for each condition is very different however, epilepsy needing anti epileptic medication whereas NES is a psychologically rooted condition. Aims To develop previous work To document a number of detailed seizures descriptions and to analyse these using Interpretative Phenomenological Analysis (IPA) To identify linguistic markers to differentiate NES from epilepsy Methodology This project used IPA as a more expansive method of 'history taking' being completely patient led. The approach and its theoretical antecedents have been described in depth in the thesis. Four newly referred patients with uncertain diagnoses were interviewed once, three twice. There was additional, contextual data. Results The interpretation illustrated that subjective seizure experiences using IPA can contribute to previous work: It heralded the potential beginnings of the development of an alternative 'seizure discourse' for lay and professionals. It had the potential to contribute to patient information material and a screening tool. It offered new ideas for clinical practice and research. Discussion As an approach, IPA has the potential to combine its findings with those in the field of neurophenomenology in terms of expanding knowledge of corresponding subjective experiences. Conclusions Given that subjective experiences of people can help locate seizure foci, IPA has the potential for establishing itself as a qualitative scientific research approach in the area of seizure experiences

Autism Spectrum Disorder Symptomatology in Children with Neurofibromatosis Type 1

Social problems are a common concern of parents of children with Neurofibromatosis type 1 (NF1). There has been a recent surge of research examining the prevalence of autism spectrum disorders (ASD) and ASD symptomatology in children with NF1. Findings from this relatively new body of research are mixed. The primary aim of this study was to examine ASD symptomatology in children with NF1 using a comprehensive assessment of ASD symptoms. A second aim was to examine possible variables that may contribute to socio-communicative difficulties. Participants included 25 children with NF1 between the ages of 9 and 13, along with their parent. Standardized parent-report questionnaires were used to assess social responsiveness and restrictive and repetitive behaviors (RRB; Social Responsiveness Scale, Second Edition: SRS-2) and ASD symptomatology (Social Communication Questionnaire: SCQ). Diagnostic assessment measures for ASD were used to examine the frequency and severity of ASD symptomatology (Autism Screening Interview: ASI, and Autism Diagnostic Observation Scale, Second Edition: ADOS-2). Selected measures were used to assess intellectual functioning, attention, social cognition, and pragmatic language. Overall, results indicate that 30% of parents observed mild to moderate social responsiveness difficulties and RRB on the SRS-2. However, no children met diagnostic criteria for ASD based on the combination of ASI and ADOS-2 classifications and very few RRB were reported by parents or observed by clinicians. Relations between social responsiveness and intellectual functioning, social information processing, and pragmatic language were found. Performance on a pragmatic language task uniquely explained 38% of the social responsiveness difficulties reported by parents. Results indicate that children with NF1 are demonstrating elevated ASD symptomatology per parent and clinician report; however, those difficulties are largely not severe nor pervasive enough to meet criteria for ASD

Neuroimaging - Clinical Applications

Modern neuroimaging tools allow unprecedented opportunities for understanding brain neuroanatomy and function in health and disease. Each available technique carries with it a particular balance of strengths and limitations, such that converging evidence based on multiple methods provides the most powerful approach for advancing our knowledge in the fields of clinical and cognitive neuroscience. The scope of this book is not to provide a comprehensive overview of methods and their clinical applications but to provide a "snapshot" of current approaches using well established and newly emerging techniques