An artificial intelligence natural language processing pipeline for information extraction in neuroradiology

The use of electronic health records in medical research is difficult because of the unstructured format. Extracting information within reports and summarising patient presentations in a way amenable to downstream analysis would be enormously beneficial for operational and clinical research. In this work we present a natural language processing pipeline for information extraction of radiological reports in neurology. Our pipeline uses a hybrid sequence of rule-based and artificial intelligence models to accurately extract and summarise neurological reports. We train and evaluate a custom language model on a corpus of 150000 radiological reports from National Hospital for Neurology and Neurosurgery, London MRI imaging. We also present results for standard NLP tasks on domain-specific neuroradiology datasets. We show our pipeline, called `neuroNLP', can reliably extract clinically relevant information from these reports, enabling downstream modelling of reports and associated imaging on a heretofore unprecedented scale.Comment: 20 pages, 2 png image figure

Orienting to fear under transient focal disruption of the human amygdala

Responding to threat is under strong survival pressure, promoting the evolution of systems highly optimised for the task. Though the amygdala is implicated in detecting threat, its role in the action that immediately follows-orienting-remains unclear. Critical to mounting a targeted response, such early action requires speed, accuracy, and resilience optimally achieved through conserved, parsimonious, dedicated systems, insured against neural loss by a parallelized functional organisation. These characteristics tend to conceal the underlying substrate not only from correlative methods but also from focal disruption over time scales long enough for compensatory adaptation to take place. In a study of six patients with intracranial electrodes temporarily implanted for the clinical evaluation of focal epilepsy, here we investigate gaze orienting to fear during focal, transient, unilateral direct electrical disruption of the amygdala. We show that the amygdala is necessary for rapid gaze shifts towards faces presented in the contralateral hemifield regardless of their emotional expression, establishing its functional lateralisation. Behaviourally dissociating the location of presented fear from the direction of the response, we implicate the amygdala not only in detecting contralateral faces, but also in automatically orienting specifically towards fearful ones. This salience-specific role is demonstrated within a drift-diffusion model of action to manifest as an orientation bias towards the location of potential threat. Pixel-wise analysis of target facial morphology reveals scleral exposure as its primary driver, and induced gamma oscillations-obtained from intracranial local field potentials-as its time-locked electrophysiological correlate. The amygdala is here re-conceptualised as a functionally lateralised instrument of early action, reconciling previous conflicting accounts confined to detection, and revealing a neural organisation analogous to the superior colliculus, with which it is phylogenetically kin. Greater clarity on its role has the potential to guide therapeutic resection, still frequently complicated by impairments of cognition and behaviour related to threat, and inform novel focal stimulation techniques for the management of neuropsychiatric conditions

GeoSPM: Geostatistical parametric mapping for medicine

The characteristics and determinants of health and disease are often organised in space, reflecting our spatially extended nature. Understanding the influence of such factors requires models capable of capturing spatial relations. Though a mature discipline, spatial analysis is comparatively rare in medicine, arguably a consequence of the complexity of the domain and the inclemency of the data regimes that govern it. Drawing on statistical parametric mapping, a framework for topological inference well-established in the realm of neuroimaging, we propose and validate a novel approach to the spatial analysis of diverse clinical data - GeoSPM - based on differential geometry and random field theory. We evaluate GeoSPM across an extensive array of synthetic simulations encompassing diverse spatial relationships, sampling, and corruption by noise, and demonstrate its application on large-scale data from UK Biobank. GeoSPM is transparently interpretable, can be implemented with ease by non-specialists, enables flexible modelling of complex spatial relations, exhibits robustness to noise and under-sampling, offers well-founded criteria of statistical significance, and is through computational efficiency readily scalable to large datasets. We provide a complete, open-source software implementation of GeoSPM, and suggest that its adoption could catalyse the wider use of spatial analysis across the many aspects of medicine that urgently demand it.Comment: 29 pages, 22 figure

GeoSPM: Geostatistical parametric mapping for medicine

The characteristics and determinants of health and disease are often organised in space, reflecting our spatially extended nature. Understanding the influence of such factors requires models capable of capturing spatial relations. Though a mature discipline, spatial analysis is comparatively rare in medicine, arguably a consequence of the complexity of the domain and the inclemency of the data regimes that govern it. Drawing on statistical parametric mapping, a framework for topological inference well-established in the realm of neuroimaging, we propose and validate a novel approach to the spatial analysis of diverse clinical data - GeoSPM - based on differential geometry and random field theory. We evaluate GeoSPM across an extensive array of synthetic simulations encompassing diverse spatial relationships, sampling, and corruption by noise, and demonstrate its application on large-scale data from UK Biobank. GeoSPM is transparently interpretable, can be implemented with ease by non-specialists, enables flexible modelling of complex spatial relations, exhibits robustness to noise and under-sampling, offers well-founded criteria of statistical significance, and is through computational efficiency readily scalable to large datasets. We provide a complete, open-source software implementation of GeoSPM, and suggest that its adoption could catalyse the wider use of spatial analysis across the many aspects of medicine that urgently demand it

A framework for focal and connectomic mapping of transiently disrupted brain function

The distributed nature of the neural substrate, and the difficulty of establishing necessity from correlative data, combine to render the mapping of brain function a far harder task than it seems. Methods capable of combining connective anatomical information with focal disruption of function are needed to disambiguate local from global neural dependence, and critical from merely coincidental activity. Here we present a comprehensive framework for focal and connective spatial inference based on sparse disruptive data, and demonstrate its application in the context of transient direct electrical stimulation of the human medial frontal wall during the pre-surgical evaluation of patients with focal epilepsy. Our framework formalizes voxel-wise mass-univariate inference on sparsely sampled data within the statistical parametric mapping framework, encompassing the analysis of distributed maps defined by any criterion of connectivity. Applied to the medial frontal wall, this transient dysconnectome approach reveals marked discrepancies between local and distributed associations of major categories of motor and sensory behaviour, revealing differentiation by remote connectivity to which purely local analysis is blind. Our framework enables disruptive mapping of the human brain based on sparsely sampled data with minimal spatial assumptions, good statistical efficiency, flexible model formulation, and explicit comparison of local and distributed effects

Subthalamic nucleus phase-amplitude coupling correlates with motor impairment in Parkinson's disease

Objective High-amplitude beta band oscillations within the subthalamic nucleus are frequently associated with Parkinson’s disease but it is unclear how they might lead to motor impairments. Here we investigate a likely pathological coupling between the phase of beta band oscillations and the amplitude of high-frequency oscillations around 300Hz. Methods We analysed an extensive data set comprising resting-state recordings obtained from deep brain stimulation electrodes in 33 patients before and/or after taking dopaminergic medication. We correlated mean values of spectral power and phase-amplitude coupling with severity of hemibody bradykinesia/rigidity. In addition, we used simultaneously recorded magneto-encephalography to look at functional interactions between the subthalamic nucleus and ipsilateral motor cortex. Results We analysed an extensive data set comprising resting-state recordings obtained from deep brain stimulation electrodes in 33 patients before and/or after taking dopaminergic medication. We correlated mean values of spectral power and phase-amplitude coupling with severity of hemibody bradykinesia/rigidity. In addition, we used simultaneously recorded magneto-encephalography to look at functional interactions between the subthalamic nucleus and ipsilateral motor cortex. Conclusions We speculate that the beta band might impede pro-kinetic high-frequency activity patterns when phase-amplitude coupling is prominent. Furthermore, results provide evidence for a functional subdivision of the beta band into low and high frequencies. Significance Our findings contribute to the interpretation of oscillatory activity within the cortico-basal ganglia circuit

Disruption of APOL1-miR193a Axis Induces Disorganization of Podocyte Actin Cytoskeleton

Abstract APOL1-miR193a axis participates in the preservation of molecular phenotype of differentiated podocytes (DPDs). We examined the hypothesis that APOL1 (G0) preserves, but APOL1 risk alleles (G1 and G2) disrupt APOL1-miR193a axis in DPDs. DPDG0s displayed down-regulation of miR193a, but upregulation of nephrin expression. DPDG1s/G2s exhibited an increase in miR193a and down-regulation of the expression of adherens complex’s constituents (CD2AP, nephrin, and dendrin). DPDG0s showed decreased Cathepsin L, enhanced dynamin expressions, and the intact actin cytoskeleton. On the contrary, DPDG1s/G2s displayed an increase in Cathepsin L, but down-regulation of dynamin expressions and disorganization of the actin cytoskeleton. APOL1 silencing enhanced miR193a and Cathepsin L, but down-regulated dynamin expressions. DPDG1s/G2s displayed nuclear import of dendrin, indicating an occurrence of destabilization of adherens complexes in APOL1 risk milieu. These findings suggest that DPDG1s and DPDG2s developed disorganized actin cytoskeleton as a consequence of disrupted APOL1-miR193a axis. Interestingly, docking and co-labeling studies suggested an interaction between APOL1 and CD2AP. APOL1 G1/G1 and APOL1 G1/G2 transgenic mice displayed nuclear import of dendrin indicating destabilization of adherens complexes in podocytes; moreover, these mice showed a four-fold increase in urinary albumin to creatinine ratio and development of focal segmental glomerular lesions

Outcome Measures for Disease-Modifying Trials in Parkinson's Disease:Consensus Paper by the EJS ACT-PD Multi-Arm Multi-Stage Trial Initiative

BACKGROUND: Multi-arm, multi-stage (MAMS) platform trials can accelerate the identification of disease-modifying treatments for Parkinson's disease (PD) but there is no current consensus on the optimal outcome measures (OM) for this approach.OBJECTIVE: To provide an up-to-date inventory of OM for disease-modifying PD trials, and a framework for future selection of OM for such trials.METHODS: As part of the Edmond J Safra Accelerating Clinical Trials in Parkinson Disease (EJS ACT-PD) initiative, an expert group with Patient and Public Involvement and Engagement (PPIE) representatives' input reviewed and evaluated available evidence on OM for potential use in trials to delay progression of PD. Each OM was ranked based on aspects such as validity, sensitivity to change, participant burden and practicality for a multi-site trial. Review of evidence and expert opinion led to the present inventory.RESULTS: An extensive inventory of OM was created, divided into: general, motor and non-motor scales, diaries and fluctuation questionnaires, cognitive, disability and health-related quality of life, capability, quantitative motor, wearable and digital, combined, resource use, imaging and wet biomarkers, and milestone-based. A framework for evaluation of OM is presented to update the inventory in the future. PPIE input highlighted the need for OM which reflect their experience of disease progression and are applicable to diverse populations and disease stages.CONCLUSION: We present a range of OM, classified according to a transparent framework, to aid selection of OM for disease-modifying PD trials, whilst allowing for inclusion or re-classification of relevant OM as new evidence emerges.</p

Outcome Measures for Disease-Modifying Trials in Parkinson's Disease: Consensus Paper by the EJS ACT-PD Multi-Arm Multi-Stage Trial Initiative

BACKGROUND: Multi-arm, multi-stage (MAMS) platform trials can accelerate the identification of disease-modifying treatments for Parkinson's disease (PD) but there is no current consensus on the optimal outcome measures (OM) for this approach. OBJECTIVE: To provide an up-to-date inventory of OM for disease-modifying PD trials, and a framework for future selection of OM for such trials. METHODS: As part of the Edmond J Safra Accelerating Clinical Trials in Parkinson Disease (EJS ACT-PD) initiative, an expert group with Patient and Public Involvement and Engagement (PPIE) representatives' input reviewed and evaluated available evidence on OM for potential use in trials to delay progression of PD. Each OM was ranked based on aspects such as validity, sensitivity to change, participant burden and practicality for a multi-site trial. Review of evidence and expert opinion led to the present inventory. RESULTS: An extensive inventory of OM was created, divided into: general, motor and non-motor scales, diaries and fluctuation questionnaires, cognitive, disability and health-related quality of life, capability, quantitative motor, wearable and digital, combined, resource use, imaging and wet biomarkers, and milestone-based. A framework for evaluation of OM is presented to update the inventory in the future. PPIE input highlighted the need for OM which reflect their experience of disease progression and are applicable to diverse populations and disease stages. CONCLUSION: We present a range of OM, classified according to a transparent framework, to aid selection of OM for disease-modifying PD trials, whilst allowing for inclusion or re-classification of relevant OM as new evidence emerges