Factorised spatial representation learning: application in semi-supervised myocardial segmentation

The success and generalisation of deep learning algorithms heavily depend on learning good feature representations. In medical imaging this entails representing anatomical information, as well as properties related to the specific imaging setting. Anatomical information is required to perform further analysis, whereas imaging information is key to disentangle scanner variability and potential artefacts. The ability to factorise these would allow for training algorithms only on the relevant information according to the task. To date, such factorisation has not been attempted. In this paper, we propose a methodology of latent space factorisation relying on the cycle-consistency principle. As an example application, we consider cardiac MR segmentation, where we separate information related to the myocardium from other features related to imaging and surrounding substructures. We demonstrate the proposed method's utility in a semi-supervised setting: we use very few labelled images together with many unlabelled images to train a myocardium segmentation neural network. Specifically, we achieve comparable performance to fully supervised networks using a fraction of labelled images in experiments on ACDC and a dataset from Edinburgh Imaging Facility QMRI. Code will be made available at https://github.com/agis85/spatial_factorisation.Comment: Accepted in MICCAI 201

Severe head injury in children - a preventable but forgotten epidemic

No Abstract

Fronto-medial electrode placement for electroconvulsive treatment of depression

Electroconvulsive therapy (ECT) is the most effective treatment for severe treatment-resistant depression but concern about cognitive side-effects, particularly memory loss, limits its use. Recent observational studies on large groups of patients who have received ECT report that cognitive side-effects were associated with electric field (EF) induced increases in hippocampal volume, whereas therapeutic efficacy was associated with EF induced increases in sagittal brain structures. The aim in the present study was to determine whether a novel fronto-medial (FM) ECT electrode placement would minimize electric fields in bilateral hippocampi (HIP) whilst maximizing electric fields in dorsal sagittal cortical regions. An anatomically detailed computational head model was used with finite element analysis, to calculate ECT-induced electric fields in specific brain regions identified by translational neuroimaging studies of treatment-resistant depressive illness, for a range of electrode placements. As hypothesized, compared to traditional bitemporal (BT) electrode placement, a specific FM electrode placement reduced bilateral hippocampal electric fields two-to-three-fold, whilst the electric fields in the dorsal anterior cingulate (dAC) were increased by approximately the same amount. We highlight the clinical relevance of this specific FM electrode placement for ECT, which may significantly reduce cognitive and non-cognitive side-effects and suggest a clinical trial is indicated

Diagnosis of insulin autoimmune syndrome using polyethylene glycol precipitation and gel filtration chromatography with ex vivo insulin exchange.

CONTEXT: Insulin-binding antibodies may produce severe dysglycaemia in insulin-naïve patients ('insulin autoimmune syndrome' (IAS) or Hirata disease), while rendering routine insulin assays unreliable. OBJECTIVE: To assess the performance of clinically used insulin assays and an optimal analytical approach in the context of IAS. DESIGN: Observational biochemical study of selected patients with hyperinsulinaemic hypoglycaemia. PATIENTS: Three patients without diabetes with recurrent spontaneous hyperinsulinaemic hypoglycaemia and 'positive' insulin antibodies. MEASUREMENTS: A panel of clinically used insulin assays (Siemens ADVIA® Centaur, Siemens Immulite® 2000, DiaSorin LIAISON® XL, PE AutoDELFIA® and the Beckman Coulter Access® 2) were used before and after plasma dilution or polyethylene glycol (PEG) precipitation. Anti-insulin IgG antibodies were measured by Isletest™ -IAA ELISA. Gel filtration chromatography (GFC) was undertaken with and without preincubation of plasma with exogenous insulin. RESULTS: Dilution of IAS plasma with assay-specific buffer increased insulin recovery, supporting negative immunoassay interference by antibodies. PEG precipitation of IAS plasma decreased insulin recovery using all assays except the Immulite® 2000. GFC discriminated high molecular weight and monomeric insulin, while ex vivo addition of exogenous insulin to plasma increased insulin bound to antibody, thereby improving the sensitivity of detection of insulin immunocomplexes. CONCLUSIONS: Immunoprecipitation with PEG must be used with caution in screening for insulin-antibody complexes as results are assay dependent. GFC with addition of exogenous insulin can identify significant insulin immunocomplexes with enhanced sensitivity, with attendant greater clinical utility and avoidance of radiolabelled reagents.Diabetes Research & Wellness Foundation Sutherland-Earl Clinical Fellowship (Grant ID: RG68554), Wellcome Trust (Grant ID: WT098498), Medical Research Council (Grant ID: MRC_MC_UU_12012/5), National Institute for Health Research (NIHR), Cambridge Biomedical Research CentreThis is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1111/cen.1317

Risk of transition to schizophrenia following first admission with substance-induced psychotic disorder: a population-based longitudinal cohort study

The potential for drugs of abuse to induce acute psychotic symptoms is well recognised. However, the likelihood of transition from initial substance-induced psychotic disorder (SIPD) to chronic psychosis is much less well understood. This study investigated the rate of SIPD transition to schizophrenia (F20), the time to conversion and other possible related factors. Using data from the Scottish Morbidity Record, we examined all patients (n = 3486) since their first admission to psychiatric hospital with a diagnosis of SIPD [International Classification of Diseases, Tenth Revision (ICD-10) codes F10-F19, with third digit five] from January 1997 to July 2012. Patients were followed until first episode of schizophrenia (ICD-10 code F20, with any third digit) or July 2012. Any change in diagnosis was noted in the follow-up period, which ranged from 1 day to 15.5 years across the groups. The 15.5-year cumulative hazard rate was 17.3% (s.e. = 0.007) for a diagnosis of schizophrenia. Cannabis, stimulant, opiate and multiple drug-induced psychotic disorder were all associated with similar hazard rates. The mean time to transition to a diagnosis of schizophrenia was around 13 years, although over 50% did so within 2 years and over 80% of cases presented within 5 years of SIPD diagnosis. Risk factors included male gender, younger age and longer first admission. SIPD episodes requiring hospital admission for more than 2 weeks are more likely to be associated with later diagnosis of schizophrenia. Follow-up periods of more than 2 years are needed to detect the majority of those individuals who will ultimately develop schizophrenia