Automatic Emphysema Detection using Weakly Labeled HRCT Lung Images

A method for automatically quantifying emphysema regions using High-Resolution Computed Tomography (HRCT) scans of patients with chronic obstructive pulmonary disease (COPD) that does not require manually annotated scans for training is presented. HRCT scans of controls and of COPD patients with diverse disease severity are acquired at two different centers. Textural features from co-occurrence matrices and Gaussian filter banks are used to characterize the lung parenchyma in the scans. Two robust versions of multiple instance learning (MIL) classifiers, miSVM and MILES, are investigated. The classifiers are trained with the weak labels extracted from the forced expiratory volume in one minute (FEV$_1$) and diffusing capacity of the lungs for carbon monoxide (DLCO). At test time, the classifiers output a patient label indicating overall COPD diagnosis and local labels indicating the presence of emphysema. The classifier performance is compared with manual annotations by two radiologists, a classical density based method, and pulmonary function tests (PFTs). The miSVM classifier performed better than MILES on both patient and emphysema classification. The classifier has a stronger correlation with PFT than the density based method, the percentage of emphysema in the intersection of annotations from both radiologists, and the percentage of emphysema annotated by one of the radiologists. The correlation between the classifier and the PFT is only outperformed by the second radiologist. The method is therefore promising for facilitating assessment of emphysema and reducing inter-observer variability.Comment: Accepted at PLoS ON

Transfer learning for multicenter classification of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a lung disease which can be quantified using chest computed tomography (CT) scans. Recent studies have shown that COPD can be automatically diagnosed using weakly supervised learning of intensity and texture distributions. However, up till now such classifiers have only been evaluated on scans from a single domain, and it is unclear whether they would generalize across domains, such as different scanners or scanning protocols. To address this problem, we investigate classification of COPD in a multi-center dataset with a total of 803 scans from three different centers, four different scanners, with heterogenous subject distributions. Our method is based on Gaussian texture features, and a weighted logistic classifier, which increases the weights of samples similar to the test data. We show that Gaussian texture features outperform intensity features previously used in multi-center classification tasks. We also show that a weighting strategy based on a classifier that is trained to discriminate between scans from different domains, can further improve the results. To encourage further research into transfer learning methods for classification of COPD, upon acceptance of the paper we will release two feature datasets used in this study on http://bigr.nl/research/projects/copdComment: Accepted at Journal of Biomedical and Health Informatic

Clustering treatment outcomes in women with gambling disorder

The rising prevalence of gambling disorder (GD) among women has awakened considerable interest in the study of therapeutic outcomes in females. This study aimed to explore profles of women seeking treatment for GD based on a set of indicators including sociodemographic features, personality traits, clinical state at baseline, and cognitive behavioral therapy (CBT) outcomes. Two-step clustering, an agglomerative hierarchical classifcation system, was applied to a sample of n=163 women of ages ranging from 20 to 73 yearsold, consecutively attended to by a clinical unit specialized in the treatment of G. Three mutually exclusive clusters were identifed. Cluster C1 (n=67, 41.1%) included the highest proportion of married, occupationally active patients within the highest social status index. This cluster was characterized by medium GD severity levels, the best psychopathological functioning, and the highest mean in the self-directedness trait. C1 registered 0% dropouts and only 14.9% relapse. Cluster C2 (n=63; 38.7%) was characterized by the lowest GD severity, medium scores for psychopathological measures and a high risk of dropout during CBT. Cluster C3 (n=33; 20.2%) registered the highest GD severity, the worst psychopathological state, the lowest self-directedness level and the highest harm-avoidance level, as well as the highest risk of relapse. These results provide new evidence regarding the heterogeneity of women diagnosed with GD and treated with CBT, based on the profle at preand post-treatment. Person-centered treatments should include specifc strategies aimed at increasing self-esteem, emotional regulation capacities and self-control of GD women

Does Confinement Affect Treatment Dropout Rates in Patients With Gambling Disorder? A Nine-Month Observational Study

Background and Aims: COVID-19 pandemic and confinement have represented a challenge for patients with gambling disorder (GD). Regarding treatment outcome, dropout may have been influenced by these adverse circumstances. The aims of this study were: (a) to analyze treatment dropout rates in patients with GD throughout two periods: during and after the lockdown and (b) to assess clinical features that could represent vulnerability factors for treatment dropout. Methods: The sample consisted of n=86 adults, mostly men (n=79, 91.9%) and with a mean age of 45years old (SD=16.85). Patients were diagnosed with GD according to DSM-5 criteria and were undergoing therapy at a Behavioral Addiction Unit when confinement started. Clinical data were collected through a semi-structured interview and protocolized psychometric assessment. A brief telephone survey related to COVID-19 concerns was also administered at the beginning of the lockdown. Dropout data were evaluated at two moments throughout a nine-month observational period (T1: during the lockdown, and T2: after the lockdown). Results: The risk of dropout during the complete observational period was R=32/86=0.372 (37.2%), the Incidence Density Rate (IDR) ratio T2/T1 being equal to 0.052/0.033=1.60 (p=0.252). Shorter treatment duration (p=0.007), lower anxiety (p=0.025), depressive symptoms (p=0.045) and lower use of adaptive coping strategies (p=0.046) characterized patients who abandoned treatment during the lockdown. Briefer duration of treatment Baenas et al. Lockdown and GD: Treatment Dropout Frontiers in Psychology | www.frontiersin.org 2 December 2021 | Volume 12 | Article 761802 (p=0.001) and higher employment concerns (p=0.044) were highlighted in the individuals who dropped out after the lockdown. Treatment duration was a predictor of dropout in both periods (p=0.005 and p<0.001, respectively). Conclusion: The present results suggest an impact of the COVID-19 pandemic on treatment dropout among patients with GD during and after the lockdown, being treatment duration a predictor of dropout. Assessing vulnerability features in GD may help clinicians identify high-risk individuals and enhance prevention and treatment approaches in future similar situations

The influence of chronological age on cognitive biases and impulsivity levels in male patients with gambling disorder

Background and aims: due to the contribution of age to the etiology of gambling disorder (GD), there is a need to assess the moderator effect of the aging process with other features that are highly related with the clinical profile. The objective of this study is to examine the role of the chronological age into the relationships between cognitive biases, impulsivity levels and gambling preference with the GD profile during adulthood. Methods: sample included n = 209 patients aged 18-77 years-old recruited from a Pathological Gambling Outpatients Unit. Orthogonal contrasts explored polynomial patterns in data, and path analysis implemented through structural equation modeling assessed the underlying mechanisms between the study variables. Results: compared to middle-age patients, younger and older age groups reported more impairing irrational beliefs (P = 0.005 for interpretative control and P = 0.043 for interpretative bias). A linear trend showed that as people get older sensation seeking (P = 0.006) and inability to stop gambling (P = 0.018) increase. Path analysis showed a direct effect between the cognitive bias and measures of gambling severity (standardized effects [SE] between 0.12 and 0.17) and a direct effect between impulsivity levels and cumulated debts due to gambling (SE = 0.22). Conclusion: screening tools and intervention plans should consider the aging process. Specific programs should be developed for younger and older age groups, since these are highly vulnerable to the consequences of gambling activities and impairment levels of impulsivity and cognitive biases

Suicidal behavior in patients with gambling disorder and their response to psychological treatment: The roles of gender and gambling preference

Suicidal ideation and attempts are prevalent among patients with gambling disorder (GD). However, patients with GD and a history of lifetime suicidal events are not a homogeneous group. The main objective of this study was to compare sociodemographic, clinical, personality, and psychopathological features among different profiles of adults with GD with and without a history of suicidal behavior, taking into account two relevant variables: gender and gambling preference. The second aim was to examine how the different profiles of patients with a history of suicidal events responded to cognitive-behavioral therapy (CBT). A total of 1112 treatment-seeking adults who met the criteria for GD were assessed at a hospital specialized unit for the treatment of behavioral addictions. The participants completed self-reported questionnaires to explore GD, personality traits, and psychopathological symptomatology. The lifetime histories of suicidal ideation and attempts, and gambling preferences, were assessed during semi-structured face-to-face clinical interviews. Of the total sample, 229 patients (26.6%) reported suicidal ideation and 74 patients (6.7%), suicide attempts. The likelihood of presenting suicidal ideation was higher for women than men, but no differences were observed based on gambling preference. Regarding suicide attempts, the odds were higher among women with non-strategic forms of gambling. Suicidal ideation and attempts were associated with higher GD severity, a worse psychopathological state and higher self-transcendence levels. In terms of treatment outcomes, neither gambling preference nor past suicidal behavior had an influence on dropouts and relapses. Nevertheless, female gender and a lack of family support constitute two good predictors of a worse treatment outcome

Exploring the Association between Gambling-Related Offenses, Substance Use, Psychiatric Comorbidities, and Treatment Outcome

Several studies have explored the association between gambling disorder (GD) and gambling-related crimes. However, it is still unclear how the commission of these offenses influences treatment outcomes. In this longitudinal study we sought: (1) to explore sociodemographic and clinical differences (e.g., psychiatric comorbidities) between individuals with GD who had committed gambling-related illegal acts (differentiating into those who had had legal consequences (n = 31) and those who had not (n = 55)), and patients with GD who had not committed crimes (n = 85); and (2) to compare the treatment outcome of these three groups, considering dropouts and relapses. Several sociodemographic and clinical variables were assessed, including the presence of substance use, and comorbid mental disorders. Patients received 16 sessions of cognitive-behavioral therapy. Patients who reported an absence of gambling-related illegal behavior were older, and showed the lowest GD severity, the most functional psychopathological state, the lowest impulsivity levels, and a more adaptive personality profile. Patients who had committed offenses with legal consequences presented the highest risk of dropout and relapses, higher number of psychological symptoms, higher likelihood of any other mental disorders, and greater prevalence of tobacco and illegal drugs use. Our findings uphold that patients who have committed gambling-related offenses show a more complex clinical profile that may interfere with their adherence to treatment

Differences in Emotion Regulation Considering Gender, Age, and Gambling Preferences in a Sample of Gambling Disorder Patients

Impairments in emotion regulation are understood to be a transdiagnostic risk factor of suffering from compulsive and addictive behaviors. The aim of this study was to investigate the role of emotion regulation deficits in gambling disorder and to analyze these differences taking gender, age, and gambling activity preferences into account. Methods: The sample included n = 484 patients seeking treatment for gambling disorder at a specialized outpatient service. Main outcomes were sociodemographic variables, emotion regulation, and gambling severity. Results: Differences between sexes were found in non-acceptance of emotions. Older patients obtained higher levels in non-acceptance of emotions, lack of emotion regulation strategies, emotional clarity, and global emotion regulation scores. No differences were found in emotion scores considering gambling preferences (non-strategic versus strategic). Path analysis showed that emotion regulation scores and age had a direct effect on gambling disorder severity, while emotion regulation and gambling preference were not mediational variables in the relationships of gender and age with gambling severity. Conclusions: Emotion regulation impairments differ in patients seeking treatment for gambling problems. Early prevention and intervention programs should incorporate the different dimensions of this process, taking into account clinical phenotypes

The prevalence and features of schizophrenia among individuals with gambling disorder

Background-objectives: Few studies have analyzed the comorbid presence of gambling disorder (GD) with schizophrenia, its sociodemographic correlates and clinical implications. This study estimated the prevalence of the dual diagnosis (GD with schizophrenia) and the differences in the profiles of patients with and without the dual condition. Method: The sample included n = 3,754 patients consecutively accepted for treatment for GD. Sociodemographics, gambling-related variables, psychopathological state and personality traits were assessed and compared between the groups. Results: The prevalence of schizophrenia within patients who met clinical criteria for GD was 4.4% (95% confidence interval: 3.8%-5.1%). Variables related to the dual presence of GD with schizophrenia were single marital status, lower education level, inactive working status, socioeconomic disadvantage, younger age, earlier onset of gambling problems, worse global psychopathological state and more dysfunctional personality profile (higher level in harm avoidance and lower level in cooperativeness, reward dependence, persistence and selfdirectedness). Conclusion: The presence of schizophrenia among patients with GD was around 4 times higher than the prevalence rate estimated in the reference general population. The differences in the profiles of GD patients with and without schizophrenia suggest that individuals with the dual diagnosis condition require unique assessment considerations and tailored treatment interventions specifically designed for the clinical and functioning higher risk