Constructing personalized characterizations of structural brain aberrations in patients with dementia using explainable artificial intelligence

Deep learning approaches for clinical predictions based on magnetic resonance imaging data have shown great promise as a translational technology for diagnosis and prognosis in neurological disorders, but its clinical impact has been limited. This is partially attributed to the opaqueness of deep learning models, causing insufficient understanding of what underlies their decisions. To overcome this, we trained convolutional neural networks on structural brain scans to differentiate dementia patients from healthy controls, and applied layerwise relevance propagation to procure individual-level explanations of the model predictions. Through extensive validations we demonstrate that deviations recognized by the model corroborate existing knowledge of structural brain aberrations in dementia. By employing the explainable dementia classifier in a longitudinal dataset of patients with mild cognitive impairment, we show that the spatially rich explanations complement the model prediction when forecasting transition to dementia and help characterize the biological manifestation of disease in the individual brain. Overall, our work exemplifies the clinical potential of explainable artificial intelligence in precision medicine.

Predictive Clinical Neuroscience Portal (PCNportal): instant online access to research-grade normative models for clinical neuroscientists

Background

The neurobiology of mental disorders remains poorly understood despite substantial scientific efforts, due to large clinical heterogeneity and to a lack of tools suitable to map individual variability. Normative modeling is one recently successful framework that can address these problems by comparing individuals to a reference population. The methodological underpinnings of normative modelling are, however, relatively complex and computationally expensive. Our research group has developed the python-based normative modelling package Predictive Clinical Neuroscience toolkit (PCNtoolkit) which provides access to many validated algorithms for normative modelling. PCNtoolkit has since proven to be a strong foundation for large scale normative modelling, but still requires significant computation power, time and technical expertise to develop.

Methods

To address these problems, we introduce PCNportal. PCNportal is an online platform integrated with PCNtoolkit that offers access to pre-trained research-grade normative models estimated on tens of thousands of participants, without the need for computation power or programming abilities. PCNportal is an easy-to-use web interface that is highly scalable to large user bases as necessary. Finally, we demonstrate how the resulting normalized deviation scores can be used in a clinical application through a schizophrenia classification task applied to cortical thickness and volumetric data from the longitudinal Northwestern University Schizophrenia Data and Software Tool (NUSDAST) dataset.

Results

At each longitudinal timepoint, the transferred normative models achieved a mean[std. dev.] explained variance of 9.4[8.8]%, 9.2[9.2]%, 5.6[7.4]% respectively in the control group and 4.7[5.5]%, 6.0[6.2]%, 4.2[6.9]% in the schizophrenia group. Diagnostic classifiers achieved AUC of 0.78, 0.76 and 0.71 respectively.

Conclusions

This replicates the utility of normative models for diagnostic classification of schizophrenia and showcases the use of PCNportal for clinical neuroimaging. By facilitating and speeding up research with high-quality normative models, this work contributes to research in inter-individual variability, clinical heterogeneity and precision medicine.

Effects of urban living environments on mental health in adults

Urban-living individuals are exposed to many environmental factors that may combine and interact to influence mental health. While individual factors of an urban environment have been investigated in isolation, no attempt has been made to model how complex, real-life exposure to living in the city relates to brain and mental health, and how this is moderated by genetic factors. Using the data of 156,075 participants from the UK Biobank, we carried out sparse canonical correlation analyses to investigate the relationships between urban environments and psychiatric symptoms. We found an environmental profile of social deprivation, air pollution, street network and urban land-use density that was positively correlated with an affective symptom group (r = 0.22, Pperm < 0.001), mediated by brain volume differences consistent with reward processing, and moderated by genes enriched for stress response, including CRHR1, explaining 2.01% of the variance in brain volume differences. Protective factors such as greenness and generous destination accessibility were negatively correlated with an anxiety symptom group (r = 0.10, Pperm < 0.001), mediated by brain regions necessary for emotion regulation and moderated by EXD3, explaining 1.65% of the variance. The third urban environmental profile was correlated with an emotional instability symptom group (r = 0.03, Pperm < 0.001). Our findings suggest that different environmental profiles of urban living may influence specific psychiatric symptom groups through distinct neurobiological pathways.

Multivariate brain-based dimensions of child psychiatric problems: degrees of generalizability

Multivariate machine learning techniques are a promising set of tools for identifying complex brain-behavior associations. However, failure to replicate results from these methods across samples has hampered their clinical relevance. This study aimed to delineate dimensions of brain functional connectivity that are associated with child psychiatric symptoms in two large and independent cohorts: the Adolescent Brain Cognitive Development (ABCD) Study and the Generation R Study (total n =8,605). Using sparse canonical correlations analysis, we identified three brain-behavior dimensions in ABCD: attention problems, aggression and rule-breaking behaviors, and withdrawn behaviors. Importantly, out-of-sample generalizability of these dimensions was consistently observed in ABCD, suggesting robust multivariate brain-behavior associations. Despite this, out-of-study generalizability in Generation R was limited. These results highlight that the degree of generalizability can vary depending on the external validation methods employed as well as the datasets used, emphasizing that biomarkers will remain elusive until models generalize better in true external settings.

Sensory salience processing moderates attenuated gazes on faces in autism spectrum disorder: a case-control study

BACKGROUND

Attenuated social attention is a key marker of autism spectrum disorder (ASD). Recent neuroimaging findings also emphasize an altered processing of sensory salience in ASD. The locus coeruleus-norepinephrine system (LC-NE) has been established as a modulator of this sensory salience processing (SSP). We tested the hypothesis that altered LC-NE functioning contributes to different SSP and results in diverging social attention in ASD.

METHODS

We analyzed the baseline eye-tracking data of the EU-AIMS Longitudinal European Autism Project (LEAP) for subgroups of autistic participants (n = 166, age = 6-30 years, IQ = 61-138, gender [female/male] = 41/125) or neurotypical development (TD; n = 166, age = 6-30 years, IQ = 63-138, gender [female/male] = 49/117) that were matched for demographic variables and data quality. Participants watched brief movie scenes (k = 85) depicting humans in social situations (human) or without humans (non-human). SSP was estimated by gazes on physical and motion salience and a corresponding pupillary response that indexes phasic activity of the LC-NE. Social attention is estimated by gazes on faces via manual areas of interest definition. SSP is compared between groups and related to social attention by linear mixed models that consider temporal dynamics within scenes. Models are controlled for comorbid psychopathology, gaze behavior, and luminance.

RESULTS

We found no group differences in gazes on salience, whereas pupillary responses were associated with altered gazes on physical and motion salience. In ASD compared to TD, we observed pupillary responses that were higher for non-human scenes and lower for human scenes. In ASD, we observed lower gazes on faces across the duration of the scenes. Crucially, this different social attention was influenced by gazes on physical salience and moderated by pupillary responses.

LIMITATIONS

The naturalistic study design precluded experimental manipulations and stimulus control, while effect sizes were small to moderate. Covariate effects of age and IQ indicate that the findings differ between age and developmental subgroups.

CONCLUSIONS

Pupillary responses as a proxy of LC-NE phasic activity during visual attention are suggested to modulate sensory salience processing and contribute to attenuated social attention in ASD.

Patterns of connectome variability in autism across five functional activation tasks: findings from the LEAP project

BACKGROUND

Autism spectrum disorder (autism) is a complex neurodevelopmental condition with pronounced behavioral, cognitive, and neural heterogeneities across individuals. Here, our goal was to characterize heterogeneity in autism by identifying patterns of neural diversity as reflected in BOLD fMRI in the way individuals with autism engage with a varied array of cognitive tasks.

METHODS

All analyses were based on the EU-AIMS/AIMS-2-TRIALS multisite Longitudinal European Autism Project (LEAP) with participants with autism (n = 282) and typically developing (TD) controls (n = 221) between 6 and 30 years of age. We employed a novel task potency approach which combines the unique aspects of both resting state fMRI and task-fMRI to quantify task-induced variations in the functional connectome. Normative modelling was used to map atypicality of features on an individual basis with respect to their distribution in neurotypical control participants. We applied robust out-of-sample canonical correlation analysis (CCA) to relate connectome data to behavioral data.

RESULTS

Deviation from the normative ranges of global functional connectivity was greater for individuals with autism compared to TD in each fMRI task paradigm (all tasks p < 0.001). The similarity across individuals of the deviation pattern was significantly increased in autistic relative to TD individuals (p < 0.002). The CCA identified significant and robust brain-behavior covariation between functional connectivity atypicality and autism-related behavioral features.

CONCLUSIONS

Individuals with autism engage with tasks in a globally atypical way, but the particular spatial pattern of this atypicality is nevertheless similar across tasks. Atypicalities in the tasks originate mostly from prefrontal cortex and default mode network regions, but also speech and auditory networks. We show how sophisticated modeling methods such as task potency and normative modeling can be used toward unravelling complex heterogeneous conditions like autism.

Accommodating site variation in neuroimaging data using normative and hierarchical Bayesian models

The potential of normative modeling to make individualized predictions from neuroimaging data has enabled inferences that go beyond the case-control approach. However, site effects are often confounded with variables of interest in a complex manner and can bias estimates of normative models, which has impeded the application of normative models to large multi-site neuroimaging data sets. In this study, we suggest accommodating for these site effects by including them as random effects in a hierarchical Bayesian model. We compared the performance of a linear and a non-linear hierarchical Bayesian model in modeling the effect of age on cortical thickness. We used data of 570 healthy individuals from the ABIDE (autism brain imaging data exchange) data set in our experiments. In addition, we used data from individuals with autism to test whether our models are able to retain clinically useful information while removing site effects. We compared the proposed single stage hierarchical Bayesian method to several harmonization techniques commonly used to deal with additive and multiplicative site effects using a two stage regression, including regressing out site and harmonizing for site with ComBat, both with and without explicitly preserving variance caused by age and sex as biological variation of interest, and with a non-linear version of ComBat. In addition, we made predictions from raw data, in which site has not been accommodated for. The proposed hierarchical Bayesian method showed the best predictive performance according to multiple metrics. Beyond that, the resulting z-scores showed little to no residual site effects, yet still retained clinically useful information. In contrast, performance was particularly poor for the regression model and the ComBat model in which age and sex were not explicitly modeled. In all two stage harmonization models, predictions were poorly scaled, suffering from a loss of more than 90% of the original variance. Our results show the value of hierarchical Bayesian regression methods for accommodating site variation in neuroimaging data, which provides an alternative to harmonization techniques. While the approach we propose may have broad utility, our approach is particularly well suited to normative modeling where the primary interest is in accurate modeling of inter-subject variation and statistical quantification of deviations from a reference model.

Accommodating site variation in neuroimaging data using normative and hierarchical Bayesian models

The potential of normative modeling to make individualized predictions from neuroimaging data has enabled inferences that go beyond the case-control approach. However, site effects are often confounded with variables of interest in a complex manner and can bias estimates of normative models, which has impeded the application of normative models to large multi-site neuroimaging data sets. In this study, we suggest accommodating for these site effects by including them as random effects in a hierarchical Bayesian model. We compared the performance of a linear and a non-linear hierarchical Bayesian model in modeling the effect of age on cortical thickness. We used data of 570 healthy individuals from the ABIDE (autism brain imaging data exchange) data set in our experiments. In addition, we used data from individuals with autism to test whether our models are able to retain clinically useful information while removing site effects. We compared the proposed single stage hierarchical Bayesian method to several harmonization techniques commonly used to deal with additive and multiplicative site effects using a two stage regression, including regressing out site and harmonizing for site with ComBat, both with and without explicitly preserving variance caused by age and sex as biological variation of interest, and with a non-linear version of ComBat. In addition, we made predictions from raw data, in which site has not been accommodated for. The proposed hierarchical Bayesian method showed the best predictive performance according to multiple metrics. Beyond that, the resulting z-scores showed little to no residual site effects, yet still retained clinically useful information. In contrast, performance was particularly poor for the regression model and the ComBat model in which age and sex were not explicitly modeled. In all two stage harmonization models, predictions were poorly scaled, suffering from a loss of more than 90% of the original variance. Our results show the value of hierarchical Bayesian regression methods for accommodating site variation in neuroimaging data, which provides an alternative to harmonization techniques. While the approach we propose may have broad utility, our approach is particularly well suited to normative modeling where the primary interest is in accurate modeling of inter-subject variation and statistical quantification of deviations from a reference model.

Site effects how-to and when: An overview of retrospective techniques to accommodate site effects in multi-site neuroimaging analyses

Site differences, or systematic differences in feature distributions across multiple data-acquisition sites, are a known source of heterogeneity that may adversely affect large-scale meta- and mega-analyses of independently collected neuroimaging data. They influence nearly all multi-site imaging modalities and biomarkers, and methods to compensate for them can improve reliability and generalizability in the analysis of genetics, omics, and clinical data. The origins of statistical site effects are complex and involve both technical differences (scanner vendor, head coil, acquisition parameters, imaging processing) and differences in sample characteristics (inclusion/exclusion criteria, sample size, ancestry) between sites. In an age of expanding international consortium research, there is a growing need to disentangle technical site effects from sample characteristics of interest. Numerous statistical and machine learning methods have been developed to control for, model, or attenuate site effects - yet to date, no comprehensive review has discussed the benefits and drawbacks of each for different use cases. Here, we provide an overview of the different existing statistical and machine learning methods developed to remove unwanted site effects from independently collected neuroimaging samples. We focus on linear mixed effect models, the ComBat technique and its variants, adjustments based on image quality metrics, normative modeling, and deep learning approaches such as generative adversarial networks. For each method, we outline the statistical foundation and summarize strengths and weaknesses, including their assumptions and conditions of use. We provide information on software availability and comment on the ease of use and the applicability of these methods to different types of data. We discuss validation and comparative reports, mention caveats and provide guidance on when to use each method, depending on context and specific research questions.

Interindividual Differences in Cortical Thickness and Their Genomic Underpinnings in Autism Spectrum Disorder

OBJECTIVE

Autism spectrum disorder (ASD) is accompanied by highly individualized neuroanatomical deviations that potentially map onto distinct genotypes and clinical phenotypes. This study aimed to link differences in brain anatomy to specific biological pathways to pave the way toward targeted therapeutic interventions.

METHODS

The authors examined neurodevelopmental differences in cortical thickness and their genomic underpinnings in a large and clinically diverse sample of 360 individuals with ASD and 279 typically developing control subjects (ages 6-30 years) within the EU-AIMS Longitudinal European Autism Project (LEAP). The authors also examined neurodevelopmental differences and their potential pathophysiological mechanisms between clinical ASD subgroups that differed in the severity and pattern of sensory features.

RESULTS

In addition to significant between-group differences in "core" ASD brain regions (i.e., fronto-temporal and cingulate regions), individuals with ASD manifested as neuroanatomical outliers within the neurotypical cortical thickness range in a wider neural system, which was enriched for genes known to be implicated in ASD on the genetic and/or transcriptomic level. Within these regions, the individuals' total (i.e., accumulated) degree of neuroanatomical atypicality was significantly correlated with higher polygenic scores for ASD and other psychiatric conditions, and it scaled with measures of symptom severity. Differences in cortical thickness deviations were also associated with distinct sensory subgroups, especially in brain regions expressing genes involved in excitatory rather than inhibitory neurotransmission.

CONCLUSIONS

The study findings corroborate the link between macroscopic differences in brain anatomy and the molecular mechanisms underpinning heterogeneity in ASD, and provide future targets for stratification and subtyping.

Global urbanicity is associated with brain and behaviour in young people

Urbanicity is a growing environmental challenge for mental health. Here, we investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe (total n = 3,867). We developed a remote-sensing satellite measure (UrbanSat) to quantify population density at any point on Earth. UrbanSat estimates of urbanicity were correlated with brain volume, cortical surface area and brain network connectivity in the medial prefrontal cortex and cerebellum. UrbanSat was also associated with perspective-taking and depression symptoms, and this was mediated by neural variables. Urbanicity effects were greatest when urban exposure occurred in childhood for the cerebellum, and from childhood to adolescence for the prefrontal cortex. As UrbanSat can be generalized to different geographies, it may enable assessments of correlations of urbanicity with mental illness and resilience globally.

Prediction of transition to psychosis from an at-risk mental state using structural neuroimaging, genetic, and environmental data

INTRODUCTION

Psychosis is usually preceded by a prodromal phase in which patients are clinically identified as being at in an "At Risk Mental State" (ARMS). A few studies have demonstrated the feasibility of predicting psychosis transition from an ARMS using structural magnetic resonance imaging (sMRI) data and machine learning (ML) methods. However, the reliability of these findings is unclear due to possible sampling bias. Moreover, the value of genetic and environmental data in predicting transition to psychosis from an ARMS is yet to be explored.

METHODS

In this study we aimed to predict transition to psychosis from an ARMS using a combination of ML, sMRI, genome-wide genotypes, and environmental risk factors as predictors, in a sample drawn from a pool of 246 ARMS subjects (60 of whom later transitioned to psychosis). First, the modality-specific values in predicting transition to psychosis were evaluated using several: (a) feature types; (b) feature manipulation strategies; (c) ML algorithms; (d) cross-validation strategies, as well as sample balancing and bootstrapping. Subsequently, the modalities whose at least 60% of the classification models showed an balanced accuracy (BAC) statistically better than chance level were included in a multimodal classification model.

RESULTS AND DISCUSSION

Results showed that none of the modalities alone, i.e., neuroimaging, genetic or environmental data, could predict psychosis from an ARMS statistically better than chance and, as such, no multimodal classification model was trained/tested. These results suggest that the value of structural MRI data and genome-wide genotypes in predicting psychosis from an ARMS, which has been fostered by previous evidence, should be reconsidered.

Atypical Brain Asymmetry in Autism-A Candidate for Clinically Meaningful Stratification

BACKGROUND

Autism spectrum disorder ("autism") is a highly heterogeneous neurodevelopmental condition with few effective treatments for core and associated features. To make progress we need to both identify and validate neural markers that help to parse heterogeneity to tailor therapies to specific neurobiological profiles. Atypical hemispheric lateralization is a stable feature across studies in autism, but its potential as a neural stratification marker has not been widely examined.

METHODS

In order to dissect heterogeneity in lateralization in autism, we used the large EU-AIMS (European Autism Interventions-A Multicentre Study for Developing New Medications) Longitudinal European Autism Project dataset comprising 352 individuals with autism and 233 neurotypical control subjects as well as a replication dataset from ABIDE (Autism Brain Imaging Data Exchange) (513 individuals with autism, 691 neurotypical subjects) using a promising approach that moves beyond mean group comparisons. We derived gray matter voxelwise laterality values for each subject and modeled individual deviations from the normative pattern of brain laterality across age using normative modeling.

RESULTS

Individuals with autism had highly individualized patterns of both extreme right- and leftward deviations, particularly in language, motor, and visuospatial regions, associated with symptom severity. Language delay explained most variance in extreme rightward patterns, whereas core autism symptom severity explained most variance in extreme leftward patterns. Follow-up analyses showed that a stepwise pattern emerged, with individuals with autism with language delay showing more pronounced rightward deviations than individuals with autism without language delay.

CONCLUSIONS

Our analyses corroborate the need for novel (dimensional) approaches to delineate the heterogeneous neuroanatomy in autism and indicate that atypical lateralization may constitute a neurophenotype for clinically meaningful stratification in autism.

Fractionating autism based on neuroanatomical normative modeling

Autism is a complex neurodevelopmental condition with substantial phenotypic, biological, and etiologic heterogeneity. It remains a challenge to identify biomarkers to stratify autism into replicable cognitive or biological subtypes. Here, we aim to introduce a novel methodological framework for parsing neuroanatomical subtypes within a large cohort of individuals with autism. We used cortical thickness (CT) in a large and well-characterized sample of 316 participants with autism (88 female, age mean: 17.2 ± 5.7) and 206 with neurotypical development (79 female, age mean: 17.5 ± 6.1) aged 6-31 years across six sites from the EU-AIMS multi-center Longitudinal European Autism Project. Five biologically based putative subtypes were derived using normative modeling of CT and spectral clustering. Three of these clusters showed relatively widespread decreased CT and two showed relatively increased CT. These subtypes showed morphometric differences from one another, providing a potential explanation for inconsistent case-control findings in autism, and loaded differentially and more strongly onto symptoms and polygenic risk, indicating a dilution of clinical effects across heterogeneous cohorts. Our results provide an important step towards parsing the heterogeneous neurobiology of autism.

Modelling brain development to detect white matter injury in term and preterm born neonates

Premature birth occurs during a period of rapid brain growth. In this context, interpreting clinical neuroimaging can be complicated by the typical changes in brain contrast, size and gyrification occurring in the background to any pathology. To model and describe this evolving background in brain shape and contrast, we used a Bayesian regression technique, Gaussian process regression, adapted to multiple correlated outputs. Using MRI, we simultaneously estimated brain tissue intensity on T1- and T2-weighted scans as well as local tissue shape in a large cohort of 408 neonates scanned cross-sectionally across the perinatal period. The resulting model provided a continuous estimate of brain shape and intensity, appropriate to age at scan, degree of prematurity and sex. Next, we investigated the clinical utility of this model to detect focal white matter injury. In individual neonates, we calculated deviations of a neonate's observed MRI from that predicted by the model to detect punctate white matter lesions with very good accuracy (area under the curve > 0.95). To investigate longitudinal consistency of the model, we calculated model deviations in 46 neonates who were scanned on a second occasion. These infants' voxelwise deviations from the model could be used to identify them from the other 408 images in 83% (T2-weighted) and 76% (T1-weighted) of cases, indicating an anatomical fingerprint. Our approach provides accurate estimates of non-linear changes in brain tissue intensity and shape with clear potential for radiological use.

Identification of neurobehavioural symptom groups based on shared brain mechanisms

Most psychopathological disorders develop in adolescence. The biological basis for this development is poorly understood. To enhance diagnostic characterization and develop improved targeted interventions, it is critical to identify behavioural symptom groups that share neural substrates. We ran analyses to find relationships between behavioural symptoms and neuroimaging measures of brain structure and function in adolescence. We found two symptom groups, consisting of anxiety/depression and executive dysfunction symptoms, respectively, that correlated with distinct sets of brain regions and inter-regional connections, measured by structural and functional neuroimaging modalities. We found that the neural correlates of these symptom groups were present before behavioural symptoms had developed. These neural correlates showed case-control differences in corresponding psychiatric disorders, depression and attention deficit hyperactivity disorder in independent clinical samples. By characterizing behavioural symptom groups based on shared neural mechanisms, our results provide a framework for developing a classification system for psychiatric illness that is based on quantitative neurobehavioural measures.

In Vivo Evidence of Reduced Integrity of the Gray-White Matter Boundary in Autism Spectrum Disorder

Atypical cortical organization and reduced integrity of the gray–white matter boundary have been reported by postmortem studies in individuals with autism spectrum disorder (ASD). However, there are no in vivo studies that examine these particular features of cortical organization in ASD. Hence, we used structural magnetic resonance imaging to examine differences in tissue contrast between gray and white matter in 98 adults with ASD and 98 typically developing controls, to test the hypothesis that individuals with ASD have significantly reduced tissue contrast. More specifically, we examined contrast as a percentage between gray and white matter tissue signal intensities (GWPC) sampled at the gray–white matter boundary, and across different cortical layers. We found that individuals with ASD had significantly reduced GWPC in several clusters throughout the cortex (cluster, P < 0.05). As expected, these reductions were greatest when tissue intensities were sampled close to gray–white matter interface, which indicates a less distinct gray–white matter boundary in ASD. Our in vivo findings of reduced GWPC in ASD are therefore consistent with prior postmortem findings of a less well-defined gray–white matter boundary in ASD. Taken together, these results indicate that GWPC might be utilized as an in vivo proxy measure of atypical cortical microstructural organization in future studies.

Using Pattern Classification to Identify Brain Imaging Markers in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social interaction and communication, as well as repetitive and restrictive behaviours. The etiological and phenotypic complexity of ASD has so far hindered the development of clinically useful biomarkers for the condition. Neuroimaging studies have been valuable in establishing a biological basis for ASD. Increasingly, neuroimaging has been combined with 'machine learning'-based pattern classification methods to make individual diagnostic predictions. Moving forward, the hope is that these techniques may not only facilitate the diagnostic process but may also aid in fractionating the ASD phenotype into more biologically homogeneous sub-groups, with defined pathophysiology, predictable outcomes and/or responses to targeted treatments and/or interventions. This review chapter will first introduce 'machine learning' and pattern recognition methods in general, with a focus on their application to diagnostic classification. It will highlight why such approaches to biomarker discovery may have advantages over more conventional analytical methods. Magnetic resonance imaging (MRI) findings of atypical brain structure, function and connectivity in ASD will be briefly reviewed before we describe how pattern recognition has been applied to generate predictive models for ASD. Last, we will discuss some limitations and pitfalls of pattern recognition analyses in ASD and consider how the field can advance beyond the prediction of binary outcomes.

Novel genetic loci underlying human intracranial volume identified through genome-wide association

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.

Multivariate decoding of cerebral blood flow measures in a clinical model of on-going postsurgical pain

Recent reports of multivariate machine learning (ML) techniques have highlighted their potential use to detect prognostic and diagnostic markers of pain. However, applications to date have focussed on acute experimental nociceptive stimuli rather than clinically relevant pain states. These reports have coincided with others describing the application of arterial spin labeling (ASL) to detect changes in regional cerebral blood flow (rCBF) in patients with on-going clinical pain. We combined these acquisition and analysis methodologies in a well-characterized postsurgical pain model. The principal aims were (1) to assess the classification accuracy of rCBF indices acquired prior to and following surgical intervention and (2) to optimise the amount of data required to maintain accurate classification. Twenty male volunteers, requiring bilateral, lower jaw third molar extraction (TME), underwent ASL examination prior to and following individual left and right TME, representing presurgical and postsurgical states, respectively. Six ASL time points were acquired at each exam. Each ASL image was preceded by visual analogue scale assessments of alertness and subjective pain experiences. Using all data from all sessions, an independent Gaussian Process binary classifier successfully discriminated postsurgical from presurgical states with 94.73% accuracy; over 80% accuracy could be achieved using half of the data (equivalent to 15 min scan time). This work demonstrates the concept and feasibility of time-efficient, probabilistic prediction of clinically relevant pain at the individual level. We discuss the potential of ML techniques to impact on the search for novel approaches to diagnosis, management, and treatment to complement conventional patient self-reporting.

Pattern recognition analysis of anterior cingulate cortex blood flow to classify depression polarity

Differentiating bipolar from recurrent unipolar depression is a major clinical challenge. In 18 healthy females and 36 females in a depressive episode--18 with bipolar disorder type I, 18 with recurrent unipolar depression--we applied pattern recognition analysis using subdivisions of anterior cingulate cortex (ACC) blood flow at rest, measured with arterial spin labelling. Subgenual ACC blood flow classified unipolar v. bipolar depression with 81% accuracy (83% sensitivity, 78% specificity).

Pattern recognition and functional neuroimaging help to discriminate healthy adolescents at risk for mood disorders from low risk adolescents

Introduction

There are no known biological measures that accurately predict future development of psychiatric disorders in individual at-risk adolescents. We investigated whether machine learning and fMRI could help to: 1. differentiate healthy adolescents genetically at-risk for bipolar disorder and other Axis I psychiatric disorders from healthy adolescents at low risk of developing these disorders; 2. identify those healthy genetically at-risk adolescents who were most likely to develop future Axis I disorders.

Methods

16 healthy offspring genetically at risk for bipolar disorder and other Axis I disorders by virtue of having a parent with bipolar disorder and 16 healthy, age- and gender-matched low-risk offspring of healthy parents with no history of psychiatric disorders (12–17 year-olds) performed two emotional face gender-labeling tasks (happy/neutral; fearful/neutral) during fMRI. We used Gaussian Process Classifiers (GPC), a machine learning approach that assigns a predictive probability of group membership to an individual person, to differentiate groups and to identify those at-risk adolescents most likely to develop future Axis I disorders.

Results

Using GPC, activity to neutral faces presented during the happy experiment accurately and significantly differentiated groups, achieving 75% accuracy (sensitivity = 75%, specificity = 75%). Furthermore, predictive probabilities were significantly higher for those at-risk adolescents who subsequently developed an Axis I disorder than for those at-risk adolescents remaining healthy at follow-up.

Conclusions

We show that a combination of two promising techniques, machine learning and neuroimaging, not only discriminates healthy low-risk from healthy adolescents genetically at-risk for Axis I disorders, but may ultimately help to predict which at-risk adolescents subsequently develop these disorders.

Subregional hippocampal deformations in major depressive disorder

BACKGROUND

Hippocampal atrophy is a well reported feature of major depressive disorder, although the evidence has been mixed. The present study sought to examine hippocampal volume and subregional morphology in patients with major depressive disorder, who were all medication-free and in an acute depressive episode of moderate severity.

METHODS

Structural magnetic resonance imaging scans were acquired in 37 patients (mean age 42 years) and 37 age, gender and IQ-matched healthy individuals. Hippocampal volume and subregional structural differences were measured by manual tracings and identification of homologous surface points to the central core of each hippocampus.

RESULTS

Both right (P=0.001) and left (P=0.005) hippocampal volumes were reduced in patients relative to healthy controls (n=37 patients and n=37 controls), while only the right hippocampus (P=0.016) showed a reduced volume in a subgroup of first-episode depression patients (n=13) relative to healthy controls. Shape analysis localised the subregional deformations to the subiculum and CA1 subfield extending into the CA2-3 subfields predominantly in the tail regions in the right (P=0.017) and left (P=0.011) hippocampi.

LIMITATIONS

As all patients were in an acute depressive episode, effects associated with depressive state cannot be distinguished from trait effects.

CONCLUSIONS

Subregional hippocampal deficits are present early in the course of major depression. The deformations may reflect structural correlates underlying functional memory impairments and distinguish depression from other psychiatric disorders.

Quantitative prediction of subjective pain intensity from whole-brain fMRI data using Gaussian processes

Supervised machine learning (ML) algorithms are increasingly popular tools for fMRI decoding due to their predictive capability and their ability to capture information encoded by spatially correlated voxels. In addition, an important secondary outcome is a multivariate representation of the pattern underlying the prediction. Despite an impressive array of applications, most fMRI applications are framed as classification problems and predictions are limited to categorical class decisions. For many applications, quantitative predictions are desirable that more accurately represent variability within subject groups and that can be correlated with behavioural variables. We evaluate the predictive capability of Gaussian process (GP) models for two types of quantitative prediction (multivariate regression and probabilistic classification) using whole-brain fMRI volumes. As a proof of concept, we apply GP models to an fMRI experiment investigating subjective responses to thermal pain and show GP models predict subjective pain ratings without requiring anatomical hypotheses about functional localisation of relevant brain processes. Even in the case of pain perception, where strong hypotheses do exist, GP predictions were more accurate than any region previously demonstrated to encode pain intensity. We demonstrate two brain mapping methods suitable for GP models and we show that GP regression models outperform state of the art support vector- and relevance vector regression. For classification, GP models perform categorical prediction as accurately as a support vector machine classifier and furnish probabilistic class predictions.

Investigating the predictive value of whole-brain structural MR scans in autism: a pattern classification approach

Autistic spectrum disorder (ASD) is accompanied by subtle and spatially distributed differences in brain anatomy that are difficult to detect using conventional mass-univariate methods (e.g., VBM). These require correction for multiple comparisons and hence need relatively large samples to attain sufficient statistical power. Reports of neuroanatomical differences from relatively small studies are thus highly variable. Also, VBM does not provide predictive value, limiting its diagnostic value. Here, we examined neuroanatomical networks implicated in ASD using a whole-brain classification approach employing a support vector machine (SVM) and investigated the predictive value of structural MRI scans in adults with ASD. Subsequently, results were compared between SVM and VBM. We included 44 male adults; 22 diagnosed with ASD using "gold-standard" research interviews and 22 healthy matched controls. SVM identified spatially distributed networks discriminating between ASD and controls. These included the limbic, frontal-striatal, fronto-temporal, fronto-parietal and cerebellar systems. SVM applied to gray matter scans correctly classified ASD individuals at a specificity of 86.0% and a sensitivity of 88.0%. Cases (68.0%) were correctly classified using white matter anatomy. The distance from the separating hyperplane (i.e., the test margin) was significantly related to current symptom severity. In contrast, VBM revealed few significant between-group differences at conventional levels of statistical stringency. We therefore suggest that SVM can detect subtle and spatially distributed differences in brain networks between adults with ASD and controls. Also, these differences provide significant predictive power for group membership, which is related to symptom severity.

[Home blood pressure monitoring in addition to office blood pressure determination is useful in patients with systolic hypertension before their inclusion into a drug trial]

OBJECTIVE

In patients with uncontrolled systolic hypertension, to estimate the value of home blood pressure monitoring in addition to office blood pressure for inclusion in a trial.

METHODS

80 patients with systolic hypertension, defined as SBP > or =140 mmHg and pulse pressure > or =60 mmHg, were treated for 4 weeks with a thiazide diuretic at usual dose (25 mg HCTZ or 1.5 mg indapamide or methyclothiazide 5 mg). Blood pressure was measured using an automatic monitor (Omron M6) at office and at home in the 3 days prior the visit. Subjects with an uncontrolled hypertension were included in the second part of the trial only if there fulfilled inclusion criteria: office SBP > or =140 mmHg and home SBP > or =135 mmHg (mean of 18 measurements obtained on 3 consecutive days) and office pulse pressure > or =60 mmHg.

RESULTS

After 4 weeks with diuretic treatment, 62% of patients fulfilled 3 criteria and were included in the second part of the trial. It was observed 76% of patients with office SBP > or =140 mmHg, 72% with office pulse pressure > or =60 mmHg and 70% with both office SBP and PP criteria. However, only 67% of patients had home SBP > or =135 mmHg. Discrepancy between office and home SBP was observed and subjects with a white coat hypertension was noticed in 14% and masked hypertension in 5%.

CONCLUSION

If patients with systolic hypertension have to be included into a drug trial because there are uncontrolled, home blood pressure monitoring in addition to office blood pressure is a very useful criteria for inclusion because misclassifications due to white coat or masked hypertension is frequent in these patients.

[Systolic blood pressures are not comparable when home blood pressure is measured with a wrist or an arm validated monitor]

OBJECTIVES

To compare home blood pressure values obtained with two validated OMRON (wrist or arm) monitors used sequentially in the same subject.

METHODS

In 265 hypertensive subjects referred to hypertension specialists, a self measurement of blood pressure was performed sequentially with an OMRON M4-I (arm cuff, A/A, BHS validation) or OMRON RX-I (wrist cuff, B/B, BHS validation). Each patient recorded home blood pressure during two periods of 4 days with 3 measures in the morning and 3 in the evening. Order for use of each monitor was randomised. With wrist devices, subjects were advised to keep the arm at heart level during measurements. BP values were reported on a standardized document. Patients were asked by a questionnaire about the tolerance and feasibility of the 2 methods.

RESULTS

In this population, aged 59 +/- 14 years, with 60% of men and a mean blood pressure of 152 +/- 21 / 86 +/- 14 mmHg, the home blood pressure values were 143 +/- 20/81 +/- 11 mmHg with the arm monitor and 135 +/- 10 / 80 +/- 11 mmHg with the wrist monitor. Mean SBP adjusted on age, initial blood pressure level and period order was significantly lower when home blood pressure monitoring has been recorded with a wrist monitor as compared to an arm monitor (p < 0.001). Self measurement of blood pressure was felt as easy in 92% with the arm monitor and in 96% with the wrist monitor (p < 0.05). Self measurement of blood pressure was felt as constraining in 14% with the arm monitor and in 7% with the wrist monitor (p < 0.01). The feasibility between the two devices was good with none of the value missing in 86% with the arm monitor and in 85% with the wrist monitor. The missing values were in 56% the fourth day.

CONCLUSION

Despite the use of two validated monitors, mean SBP is significantly lower when home blood pressure monitoring is recorded with a wrist monitor as compared to an arm monitor. Uncertainty in the arm position with the use of wrist device could explain these results. When advising home blood pressure monitoring, care should be taken to recommend only the use of validated devices and to prefer the use of arm devices in order to avoid the uncertainty of an inadequate utilisation.

How to limit screening of patients for atheromatous renal artery stenosis in two-drug resistant hypertension?

BACKGROUND

The DRASTIC model based on nine variables (age, gender, recent onset of hypertension, smoking status, body mass index (BMI), abdominal bruit, atherosclerosis, dyslipidemia and creatininemia) has been proposed to predict renal artery stenosis (RAS) occurrence.

METHODS

In a prospective multicenter study, the clinical usefulness of the DRASTIC model was checked in 336 patients with two-drug resistant hypertension. RAS was excluded using at least color Doppler sonography. RAS was diagnosed using at least renal angiography. The statistical dependence (Z(Rho)) analysis was applied to investigate further the relationships between each variable and presence of RAS.

RESULTS

The prevalence of RAS (n=51) was 15%. The goodness-of-fit test that compared observed RAS to predicted RAS using the DRASTIC model was not significant. Accordingly, the multivariate logistic regression indicated that only three parameters (abdominal bruit, atherosclerotic vascular disease and BMI <25 kg/m2) were significantly linked to RAS. The Z(Rho) methodology revealed that calculated renal function <60 ml/min and age >58 yrs (median) were also significantly linked to RAS. No variable or combination of variables offered satisfactory positive predictive values for the RAS diagnosis. The combination of the five significantly linked variables had a negative predictive value of 98%, and allowed RAS detection with a sensitivity of 96%. In our population, RAS screening could have been avoided in 30% of our patients screened.

CONCLUSIONS

The DRASTIC model was unsuitable for clinical use in our sample population. In our population, renal arteries were considered stenosis free with a probability of 98% in refractory hypertensive overweight patients, aged < or = 58 yrs, with satisfactory renal function and without both abdominal bruit and atherosclerotic vascular disease.

[Association between blood pressure level and the follow up of the guidelines concerning the use of self blood pressure measurement]

OBJECTIVES

To evaluate the characteristics of hypertensive subjects who practise self measurement of blood pressure (SMBP) and their conditions of use, and to identify the properties of subjects using SMBP according the usual guidelines.

METHODS

In 531 consecutive hypertensive subjects, referred to hypertension specialists, possessing a SMBP a questionnaire evaluating the condition of use of SMBP was given. Subjects following the guidelines about the use of SMBP have been compared to those using SMBP without specific design of supervision.

RESULTS

In this population, aged 62 +/- 14 years, with 57% of men and a mean blood pressure of 147 +/- 23/82 +/- 12 mmHg, the SMBP devices have been bought without medical advice in 50% of cases (265/531). In 45% of cases (239/531), SMBP were made at the wrist. SMBP device was used every days in 26% of cases, every weeks in 27% of cases, every month or more in 22% of cases and only in case of uneasiness in 25% of cases. Blood pressure was measured only in the morning in 25% of cases, in the morning and evening in 31%, only the evening in 8% and at any time of the day in 36% of cases. More frequently 2 BP measurements were realized (47%) and in 19% of cases 3 measurements have been performed. In 15% of cases, the measurements were performed on 3 or 4 days consecutively, more frequently (85%) the measurements were realized without specific design ("once in awhile"). The data of SMBP were noted and showed to the doctor in 34% of cases. Only 12% (64/531) of subjects followed the usual guidelines concerning the use of SMBP (2 or 3 measurements, in the morning and the evening, during 3 or 4 consecutive days). Subjects following the guidelines for SMBP use have a higher SBP at the office than those using SMBP without specific design of supervision (155 +/- 25 mmHg vs 146 +/- 22 mmHg; p<0.01).

CONCLUSION

Among hypertensives referred to hypertension specialists most of subjects use SMBP device without a specific design of supervision. Subjects with the most severe hypertension are those who have the best formation for SMBP.

[Medical management of libido disturbances in treated hypertensive patients: differences between men and women]

Decrease in sexual desire is a disturbance affecting treated hypertensive subjects of both sexes. In contrast with erection problems, this abnormality has rarely been studied in hypertensives treated with antihypertensive drugs.

OBJECTIVES

To evaluate, using a self-administered questionnaire, the prevalence of sexual disturbance (decrease in sexual desire) in treated hypertensive subjects and to determine the management of these troubles.

METHODS

In 428 hypertensive subjects, living in France and referred to hypertension specialists, a self-administered questionnaire evaluating the quality of sexual activity was given before the consultation. Nine specific questions focused on the quality of sexual function for the last 6 months in men or women (interest for sexuality, sexual desire, sexual pleasure). Secondly, the doctors were questioned about their management of these sexual disturbances.

RESULTS

In this population of treated hypertensives, including 270 men and 158 women, with a blood pressure level of 139 +/- 20/84 +/- 13 mmHg, a decrease in sexual desire was reported by 47% of men (127/270) and 48% of women (76/158). Sexual disturbance was related to antihypertensive drugs in 46% of cases (93/203), more often in men (59% [75/127]) than in women (24%, [18/76]), p < 0.001). In subjects with sexual disturbance, a specific medical management has been proposed in 35% of cases (71/203), especially in men (in 46% of cases [58/127], and consisted in a specialized consultation for 34% (43/127) and/or the prescription of Sildenafil for 20% (26/127). In women, the lack of management of these troubles was more often observed than in men (82% vs 54%; p < 0.01). Modifications of antihypertensive treatments were rarely observed in 15% of cases (30/203) comparatively in men and women.

CONCLUSIONS

Men and women with treated hypertension are at "high risk" of sexual disturbance. Management of sexual dysfunction in these subjects concerns only 35% of cases, especially men, including specific treatments and/or consultations, but changing in antihypertensive drugs still remains rare.

[Sexual dysfunction in treated hypertensive patients. Results of a national survey]

OBJECTIVES

To evaluate, using an self-administered questionnaire, the characteristics of sexual function in treated hypertensives.

METHODS

In 459 hypertensive subjects, aged of 59 +/- 12 years, living in France and referred to hypertension specialists, a self-administered questionnaire evaluating quality of life and antihypertensive treatment was given before the consultation. Several questions focused on the quality of sexual function since the last 12 months (interest for sexuality, sexual pleasure, quality of erection). Details on antihypertensive treatments and cardiovascular characteristics were obtained from medical records. Antihypertensive treatments were prescribed since more than 10 years for 39% of subjects, since 5-10 years for 25%, since 1-5 years for 26%, and since less than 1 year for 10%.

RESULTS

In this population of treated hypertensives, blood pressure level was higher in men than in women (145 +/- 22/86 +/- 13 vs 135 +/- 25/76 +/- 15; p < 0.01). In the questionnaire, the section with sexual function questions was filled out extensively in 92% of men (248/268), but only in 74% of women (142/191). Sexual disturbance was declared by 38% of cases (148/390), but rate was significantly higher in men as compared to women (49% vs 18%; p < 0.01). In men, these modifications were characterised by an interest for sexuality decreased for 58%, unchanged for 41% and increased for 1%. Sexual pleasure was decreased for 49%, unchanged for 50%, and increased for 1%. Quality of erection was modified in 45%. The erections were less frequent for 31%, less durable for 19% and impossible for 11%. In women, interest for sexuality was decreased for 41% and unchanged for 59%, sexual pleasure was decreased for 34% and unchanged for 66%. Logistic regression analysis indicates that gender (p < 0.001), greater number of antihypertensive tablets (p < 0.01), prescription of diuretics (p = 0.03) and presence of coronaropathy (p = 0.01) were independent determinants for sexual disturbance in treated hypertensives.

CONCLUSION

This study indicates that sexual disturbance is declared by 38% of patients treated for hypertension. Because complaints are more frequent in men, treated with multiple medications including a diuretic, a specific interrogation should be proposed more regularly in these patients in order to detect and to deal with, if possible, sexual disability.

[Blood pressure self-monitoring contributes to improved patient education among hypertensive subjects]

Education of hypertensive subject must sensitize the patient to its pathway and to the prescribed treatment. Self-measurement of blood pressure, which directly implicates the patient, should ameliorate the education of hypertensive subject.

OBJECTIVES

To evaluate if the possession of a self-measurement blood pressure device improves patients' knowledge of hypertension.

METHODS

In 484 treated hypertensive subjects referred to hypertension specialists, a questionnaire evaluating patients knowledge of hypertension and its treatment was given before the consultation. During this consultation, the practitioner evaluated the concordance between antihypertensive treatments declared by the patient and those effectively prescribed.

RESULTS

In this population, aged 61 +/- 12 years, with 55% of men, a self-measurement blood pressure device was possessed by 165 subjects (34%). These devices have been bought without medical advice by 83 patients. For a minority of subjects (n = 41), self-measurements of blood pressure were made at the wrist. Blood pressure level was similar in subjects with (141 +/- 19/80 +/- 10 mmHg) or without (140 +/- 19/80 +/- 10 mmHg) self-measurement devices. Subjects possessing a self measurement device had a better knowledge of their usual blood pressure level and of the normal blood pressure values (< 140/90 mmHg), than subjects without self measurement device (93% vs 77%, p < 0.01, and 56% vs 33%, p < 0.01, respectively). Moreover, subjects in possession of self-measurement devices had a better knowledge of their antihypertensive treatment than those without device (83% vs 70%, p < 0.05). Logistic regression analysis including age, sex, smoking, education level, blood pressure level and the number of antihypertensive tablets confirm the statistical differences observed.

CONCLUSION

Hypertensive subjects who possess a self-measurement blood pressure device have a better knowledge of their hypertension. These results indicate that the possession of a self-measurement device contributes to the education of hypertensive patients.

[So-called spontaneous intramural dissection of the esophagus]

We report two cases of spontaneous esophageal intramural dissection in two women aged 65 and 79 years. Initial symptoms were a constrictive retrosternal thoracic pain during a meal. Minor hematemesis accompanied by dysphagia or odynophagia appeared during the following hours. After excluding a cardiovascular emergency, diagnosis was confirmed by upper GI endoscopy that found a large mucosal longitudinal dissection; the lesion extended from mid-esophagus until short above the gastro-esophageal junction. Intramural parietal dissection characteristically appeared on barium swallow as a "double-barrelled" esophagus related to a thin radiolucent mucosal membrane separating the false and true lumens. Medical treatment with total parenteral nutrition, intravenous gastric antisecretory drugs, antibiotics in 1 patient was continued until symptoms disappeared; oral feeding was then started without incident. Follow-up endoscopic examinations confirmed complete healing. Regardless of etiology which remains speculative, spontaneous intramural dissection of the esophagus probably results from an intramural hematoma in most cases.

[Validity of the clinical prediction rule for the diagnosis of renal arterial stenosis in hypertensive patients resistant to treatment]

PURPOSE

To perform an external validation of the clinical prediction rule established by Krijnen et al. (Ann Intern Med 1998; 129: 705-11) designed to identify renal artery stenoses (RAS) in hypertensive patients.

METHODS

We included 102 patients with a refractory hypertension treated with at least two antihypertensive drugs. All subjects had the research of RAS by renal angiography, or angio-computed tomography, or doppler ultrasound. Probability to detect RAS was calculated with Krijnen's algorithm (Pre-test probability) from the following parameters: age, smoking status, diffuse atherosclerosis, recent hypertension (< 2 y), obesity (BMI > 25), abdominal bruit, hypercholesterolemia (> 6.5 mmol/L), creatinine. ROC curves were plotted for each pre-test probability value. A "post-test probability" was obtained from the likelihood ratio calculated at each pre-test probability level.

RESULTS

RAS prevalence in this population was 49%. Area under the ROC curve was 0.79 and Youden index was maximal for a pre-test probability of 15%. Maximal likelihood ratio was obtained for a pre-test probability of 46%. Table shows post-test probability as a function of pre-test probability obtained with Krijnen's algorithm. [table: see text]

CONCLUSION

Krijnen's algorithm is valid in a population of resistant hypertensives treated with a bi-therapy. This external validation obtained on a population with a high prevalence of RAS should also be tested on a population with a lower prevalence of SAR.

[What tests should be conducted for secondary arterial hypertension in hypertensive patients resistant to treatment?]

The aim of this study was to determine the prevalence of secondary hypertension in a population of refractory hypertension without initial clinical or biological findings suggesting identifiable causes of hypertension.

METHODS

A survey included 200 consecutive hypertensive patients referred to hypertension specialists for refractory hypertension (BP > 140/90 mmHg on at least two antihypertensive drugs). Prior inclusion, the permanent elevation of blood pressure was confirmed by ambulatory monitoring. In each subject an extensive work-up was performed to detect a secondary cause for hypertension.

RESULTS

An essential hypertension was confirmed in 61% of this cohort. A secondary hypertension was detected in 20% of the patients; 8.5% with a primary hyperaldosteronism, 8% with a reno-vascular hypertension and 3% with a nephropathy. Moreover, 18.5% had a low renin hypertension. Thus, 27% of these patients had an abnormality of the renin-aldosterone axis.

CONCLUSION

Patients with refractory hypertension should be explored to detect secondary hypertension even without findings suggesting such causes. This additional diagnostic procedure must include at least renovascular investigations and plasma renin/aldosterone level determinations in appropriate conditions.

[Comparative study of bisoprolol and celiprolol in to moderate hypertension using casual as well as ambulatory blood pressure measurements]

A randomised, parallel, double-blind trial was undertaken in 80 patients to compare the efficacy of bisoprolol with that of celiprolol, using causal (BPc) as well as ambulatory (AMBP) blood pressure measurement. After a two week wash-out and two week placebo run-in, patients in whom diastolic blood pressure (DBP) was between 95 and 114 mmHg were given either bisoprolol (10 mg/day) or celiprolol (200 mg/day) for 12 weeks. When efficacy was insufficient (DBP > 95 mmHg), the dose could be doubled after 4 weeks and a diuretic added after 8 weeks. BPc was measured at each visit and an AMBP obtained the day before the start of active treatment and at its end. Six patients dropped out of the trial because of adverse events. Clinical safety/acceptability of both drugs was good. Demographic data, and blood pressure and heart rate figures in both groups were comparable at the end of the placebo period. Mean fall in BPc in the bisoprolol group was 32.5/20.3 mmHg and 23/17.4 mmHg in the celiprolol group, with a significant difference between the two groups concerning systolic pressure (SBP). Ambulatory measurement showed evidence during the periods 24 hours (H), day and night, of a greater fall with bisoprolol (10.7/8.9 mmHg; 13.9/10.8 mmHg; 7.3/7.2 mmHg) than in the celiprolol group (4.9/21.6; 7.3/3.8; 2.9/2 mmHg), the difference being significant for diastolic blood pressure (DBP: p < 0.01; p < 0.05; p < 0.05. Thus bisoprolol was more effective than celiprolol in mild to moderate hypertension, but the difference was significant for SBP by casual measurement and for DBP by ambulatory measurement.

[Arterial thromboses and essential thrombocythemia in young patients]

The authors report two cases of essential thrombocythemia (ET) which occurred in young subjects (25 and 33 years) and revealed by arterial thromboses. The first case was one of myocardial infarction: in the second case, ischemic signs in the left leg led to cutaneous necrosis. Thrombotic signs are commonplace in ET and are generally considered to be attributable to an impaired underlying vascular territory. The cases reported by the authors conflict with these data and it would seem, therefore, that the onset of thrombosis in the absence of any associated cardiovascular risk can be envisaged. With regard to therapy, if thrombotic signs occur, myelosuppressive treatment must be undertaken; in asymptomatic patients, due to the potential and unpredictable risk of thrombosis, this treatment should be initiated if the platelet count rises above 800 x 10(9)/l. Hydroxyurea is generally prescribed (particularly in young patients) since it is generally considered to be devoid of any leukemogenic potential.

[Heart valve involvement in lupus erythematosus disseminatus. Apropos of 2 cases. Review of the literature]

Regarding two cases of idiopathic lupus valvulopathy, the authors review the various mechanisms responsible for the endocardial lesions in disseminated lupus erythematosus. In addition to the classic Libman-Sachs endocarditis, there are sclerous forms, ruptures of the chords, thromboses and bacterial superinfections. The role of steroid therapy in the genesis of valvular stenosis is not always determined. A surgical treatment, effective and without major risk, must be advocated at an early stage in the presence of poorly tolerated forms.

[Nitroglycerin and angina with angiographically normal coronary vessels. Clinical effects and effects on esophageal motility]

In order to determine whether the presence of a retrosternal pain sensitive to nitroglycerin is predictive of the finding of esophageal dyskinesia in patients with normal coronary angiography and negative methylergonovine test, we administered 0.8 mg of a nitroglycerin spray during esophageal manometry and after a methylergonovine or edrophonium provocation test. The effects of nitroglycerin on esophageal motility were recorded and compared with clinical data. Forty patients (21 men, 19 women, mean age 54 +/- 8 years) entered the study. In 22 of them (55 p. 100) the retrosternal pain was relieved by nitroglycerin within less than 5 minutes; the provocation test was positive in 10 cases (25 p. 100). In all patients nitroglycerin produced a highly significant decrease in the duration and amplitude of esophageal contractions. Among the 10 patients with esophageal dyskinesia, the duration of contractions was significantly more reduced (p less than 0.005) in those with nitroglycerin-sensitive pain (6 patients) than in those with nitroglycerin-resistant pain. These 6 patients, therefore, could be regarded clinically and manometrically as "responders" to nitroglycerin. Two of them had gastro-esophageal reflux. In contrast, among patients without induced esophageal dyskinesia the effects of nitroglycerin on manometry were the same irrespective of whether or not pain was usually relieved by nitroglycerin. The fact that pain was nitroglycerin-sensitive had no predictive value concerning the finding of esophageal dyskinesia by the provocation test (non-significant X2 test). We conclude that the clinical and manometric effects of nitroglycerin were concordant only in patients with induced esophageal dyskinesia; patients who responded to nitroglycerin could have a gastro-esophageal reflux.(ABSTRACT TRUNCATED AT 250 WORDS)

[Chronic aortic dissection disclosed by pericardial effusion. Apropos of 3 cases]

Three exceptional cases of chronic aortic dissection revealed by a pericardial effusion are reported. The patients were two men and a woman admitted for thoracic pain or fever. Initial diagnoses were myocardial infarction, infective endocarditis and tuberculous pericarditis. The effusions were drained on two occasions. Because the pericardial fluid was a mixture of serum and blood, computerized tomography of the thorax and abdomen was performed. All three cases were then diagnosed as aortic dissection (type II in two cases and type III in one case, with retrograde extension to the ascending aorta). The authors underline the utility of drainage and the need for systematic CT scans in patients with sero-haematic pericardial effusion of uncertain origin.

[Value of pericardioscopy in pericardial effusion. Apropos of 20 patients]

The value of pericardioscopy in pericardial effusion of uncertain origin was evaluated in 20 patients, aged from 18 to 77 years, whose pericardial effusion had been diagnosed by ultrasonography; 2 patients presented with clinical signs of tamponade. The cause of the pericarditis was unknown, but the clinical context suggested a malignant disease in 13 patients, tuberculosis in 5 patients and another cause in 2 patients. The pericardium was explored by means of a direct vision, cold-light endoscope, usually a mediastinoscope, introduced by the retroxiphoidal route under general of local anaesthesia. This method made it possible to study the pericardial fluid, examine the pericardial serous membrane, perform biopsies at a distance from the orifice of entry and cleanse the pericardium thoroughly in cases with blood or pus collection. Apart from 2 cases where the examination could not be completed because of an anterior mediastinal mass and a pericardial symphysis, valuable information could be obtained in purulent pericarditis (n = 1), chronic radiation induced lesions (n = 2), metastases (n = 2), haemopericardium (n = 2), and biopsies could be performed in tumoral or suspicious areas. These guided biopsies revealed a metastasis in 3 cases where the pericardial window was negative. No sign of tuberculosis was found in the 5 cases where the disease was suspected. The final diagnoses were: neoplastic pericarditis in 4 cases, radiation-induced pericarditis in 2 cases, purulent pericarditis in 2 cases, haemopericardium in 3 cases and idiopathic or reactive pericarditis in 9 cases. The post-operative period was uneventful, with no major complication ascribable to the procedure.(ABSTRACT TRUNCATED AT 250 WORDS)

[Reproducibility of the exercise test and coronary vasomotor tonus]

The effect of coronary vasomotor tone on exercise test reproducibility was evaluated in two groups of patients. All had an apparently stable angina, a positive first exercise test and at least one significant stenosis at coronary arteriography. Group A patients (n = 30) had a positive ergonovine test (dynamic stenosis) whereas this test was negative (fixed stenosis) in group B patients (n = 29). Patients of both groups underwent two exercise tests without treatment, each of these tests being performed on a different day of the same week, at the same time and according to Bruce's procedure. The reproducibility of angina was poor in group A patients: 6/15 (40 p. 100) as against 18/20 (90 p. 100) in group B patients (p less than 0.05). Moreover, the initially positive exercise test subsequently become negative in 6 of the group A patients and in none of the group B patients (p less than 0.05). The time elapsed before ischaemia appeared was globally increased to the same extent in both groups, but individual variations were more pronounced in group A: a more than 1 minute variation was noted in 63 p. 100 of group A patients and in 18 p. 100 of group B patients (p less than 0.01). Similarly, the double product of ischaemia (-1 mm) varied by more than 20 p. 100 in 37 p. 100 of group A patients and in 14 p. 100 of group B patients. In contrast, the maximum stress parameters were increased to the same degree in both groups, including the double product duration.(ABSTRACT TRUNCATED AT 250 WORDS)