AI-based detection of contrast-enhancing MRI lesions in patients with multiple sclerosis.

BACKGROUND Contrast-enhancing (CE) lesions are an important finding on brain magnetic resonance imaging (MRI) in patients with multiple sclerosis (MS) but can be missed easily. Automated solutions for reliable CE lesion detection are emerging; however, independent validation of artificial intelligence (AI) tools in the clinical routine is still rare. METHODS A three-dimensional convolutional neural network for CE lesion segmentation was trained externally on 1488 datasets of 934 MS patients from 81 scanners using concatenated information from FLAIR and T1-weighted post-contrast imaging. This externally trained model was tested on an independent dataset comprising 504 T1-weighted post-contrast and FLAIR image datasets of MS patients from clinical routine. Two neuroradiologists (R1, R2) labeled CE lesions for gold standard definition in the clinical test dataset. The algorithmic output was evaluated on both patient- and lesion-level. RESULTS On a patient-level, recall, specificity, precision, and accuracy of the AI tool to predict patients with CE lesions were 0.75, 0.99, 0.91, and 0.96. The agreement between the AI tool and both readers was within the range of inter-rater agreement (Cohen's kappa; AI vs. R1: 0.69; AI vs. R2: 0.76; R1 vs. R2: 0.76). On a lesion-level, false negative lesions were predominately found in infratentorial location, significantly smaller, and at lower contrast than true positive lesions (p < 0.05). CONCLUSIONS AI-based identification of CE lesions on brain MRI is feasible, approaching human reader performance in independent clinical data and might be of help as a second reader in the neuroradiological assessment of active inflammation in MS patients. CRITICAL RELEVANCE STATEMENT Al-based detection of contrast-enhancing multiple sclerosis lesions approaches human reader performance, but careful visual inspection is still needed, especially for infratentorial, small and low-contrast lesions

Insular dysfunction reflects altered between-network connectivity and severity of negative symptoms in schizophrenia during psychotic remission

Schizophrenia is characterized by aberrant intrinsic functional connectivity (iFC) within and between intrinsic connectivity networks (ICNs), including the Default Mode- (DMN), Salience- (SN), and Central Executive Network (CEN). The anterior insula (AI) of the SN has been demonstrated to modulate DMN/CEN interactions. Recently, we found that the dependence of DMN/CEN interactions on SN's right AI activity is altered in patients with schizophrenia in acute psychosis and related to psychotic symptoms, indicating a link between aberrant AI, DMN, CEN, and psychosis. However, since structural alterations of the insula are also present during psychotic remission and associated with negative symptoms, impaired AI interaction might be relevant even for psychotic remission and corresponding symptoms. Twelve patients with schizophrenia during psychotic remission (SR) and 12 healthy controls were assessed using resting-state fMRI and psychometric examination. High-model-order independent component analysis of fMRI data revealed ICNs including DMN, SN, and CEN. Scores of iFC within (intra-iFC) and between (inter-iFC) distinct subsystems of the DMN, SN, and CEN were calculated, compared between groups and correlated with the severity of symptoms. Intra-iFC was altered in patients SN, DMN, and CEN, including decreased intra-iFC in the left AI within the SN. Patients' inter-iFC between SN and CEN was increased and correlated with the severity of negative symptoms. Furthermore, decreased intra-iFC of the left AI correlated with both severity of negative symptoms and increased inter-iFC between SN and CEN. Our result provides first evidence for a relationship between AI dysfunction and altered between-network interactions in schizophrenia during psychotic remission, which is related to the severity of negative symptoms. Together with our previous results, data suggest specific SN/DMN/CEN reorganization in schizophrenia with distinct insular pathways for distinct symptom dimensions

Novel multiple sclerosis susceptibility loci implicated in epigenetic regulation

We conducted a genome-wide association study (GWAS) on multiple sclerosis (MS) susceptibility in German cohorts with 4888 cases and 10,395 controls. In addition to associations within the major histocompatibility complex (MHC) region, 15 non-MHC loci reached genome-wide significance. Four of these loci are novel MS susceptibility loci. They map to the genes L3MBTL3, MAZ, ERG, and SHMT1. The lead variant at SHMT1 was replicated in an independent Sardinian cohort. Products of the genes L3MBTL3, MAZ, and ERG play important roles in immune cell regulation. SHMT1 encodes a serine hydroxymethyltransferase catalyzing the transfer of a carbon unit to the folate cycle. This reaction is required for regulation of methylation homeostasis, which is important for establishment and maintenance of epigenetic signatures. Our GWAS approach in a defined population with limited genetic substructure detected associations not found in larger, more heterogeneous cohorts, thus providing new clues regarding MS pathogenesis

Clinical implications of serum neurofilament in newly diagnosed MS patients: a longitudinal multicentre cohort study

BACKGROUND: We aim to evaluate serum neurofilament light chain (sNfL), indicating neuroaxonal damage, as a biomarker at diagnosis in a large cohort of early multiple sclerosis (MS) patients. METHODS: In a multicentre prospective longitudinal observational cohort, patients with newly diagnosed relapsing-remitting MS (RRMS) or clinically isolated syndrome (CIS) were recruited between August 2010 and November 2015 in 22 centers. Clinical parameters, MRI, and sNfL levels (measured by single molecule array) were assessed at baseline and up to four-year follow-up. FINDINGS: Of 814 patients, 54.7% (445) were diagnosed with RRMS and 45.3% (369) with CIS when applying 2010 McDonald criteria (RRMS[2010] and CIS[2010]). After reclassification of CIS[2010] patients with existing CSF analysis, according to 2017 criteria, sNfL levels were lower in CIS[2017] than RRMS[2017] patients (9.1 pg/ml, IQR 6.2-13.7 pg/ml, n = 45; 10.8 pg/ml, IQR 7.4-20.1 pg/ml, n = 213; p = 0.036). sNfL levels correlated with number of T2 and Gd+ lesions at baseline and future clinical relapses. Patients receiving disease-modifying therapy (DMT) during the first four years had higher baseline sNfL levels than DMT-naïve patients (11.8 pg/ml, IQR 7.5-20.7 pg/ml, n = 726; 9.7 pg/ml, IQR 6.4-15.3 pg/ml, n = 88). Therapy escalation decisions within this period were reflected by longitudinal changes in sNfL levels. INTERPRETATION: Assessment of sNfL increases diagnostic accuracy, is associated with disease course prognosis and may, particularly when measured longitudinally, facilitate therapeutic decisions

Women's job quality across family life stages: An analysis of female employees across 27 European countries

There is little empirical evidence on how working conditions affect women’s employment and fertility choices, despite a number of studies on the impact of individual-level and institutional factors. The article addresses this gap by examining how family life stages are related to particular aspects of job quality among employed women in 27 European countries. The central argument of the analysis is that high-quality jobs are conducive to both transitions to motherhood and employment after childbirth as women select into these roles. Accordingly, mothers of young children, if employed, are expected to have relatively better quality jobs. Four dimensions of job quality are considered: job security, career progression, working time and intrinsic job quality. The results indicate that mothers with young children are more likely to hold high-quality jobs than women at other life stages with respect to working time quality and job security, but with some variation across countries for job security. The findings highlight the importance of high-quality jobs for women’s fertility decisions and labour market attachment after childbirth, with implications for European employment policy

Variation within the Huntington's Disease Gene Influences Normal Brain Structure

Genetics of the variability of normal and diseased brain structure largely remains to be elucidated. Expansions of certain trinucleotide repeats cause neurodegenerative disorders of which Huntington's disease constitutes the most common example. Here, we test the hypothesis that variation within the IT15 gene on chromosome 4, whose expansion causes Huntington's disease, influences normal human brain structure. In 278 normal subjects, we determined CAG repeat length within the IT15 gene on chromosome 4 and analyzed high-resolution T1-weighted magnetic resonance images by the use of voxel-based morphometry. We found an increase of GM with increasing long CAG repeat and its interaction with age within the pallidum, which is involved in Huntington's disease. Our study demonstrates that a certain trinucleotide repeat influences normal brain structure in humans. This result may have important implications for the understanding of both the healthy and diseased brain

Examining ecological validity in social interaction: problems of visual fidelity, gaze, and social potential

Social interaction is an essential part of the human experience, and much work has been done to study it. However, several common approaches to examining social interactions in psychological research may inadvertently either unnaturally constrain the observed behaviour by causing it to deviate from naturalistic performance, or introduce unwanted sources of variance. In particular, these sources are the differences between naturalistic and experimental behaviour that occur from changes in visual fidelity (quality of the observed stimuli), gaze (whether it is controlled for in the stimuli), and social potential (potential for the stimuli to provide actual interaction). We expand on these possible sources of extraneous variance and why they may be important. We review the ways in which experimenters have developed novel designs to remove these sources of extraneous variance. New experimental designs using a ‘two-person’ approach are argued to be one of the most effective ways to develop more ecologically valid measures of social interaction, and we suggest that future work on social interaction should use these designs wherever possible

Effect of HLA-DRB1 alleles and genetic variants on the development of neutralizing antibodies to interferon beta in the BEYOND and BENEFIT trials

BACKGROUND: Treatment of multiple sclerosis (MS) with interferon β can lead to the development of antibodies directed against interferon β that interfere with treatment efficacy. Several observational studies have proposed different HLA alleles and genetic variants associated with the development of antibodies against interferon β. OBJECTIVE: To validate the proposed genetic markers and to identify new markers. METHODS: Associations of genetic candidate markers with antibody presence and development were examined in a post hoc analysis in 941 patients treated with interferon β-1b in the Betaferon® Efficacy Yielding Outcomes of a New Dose (BEYOND) and BEtaseron®/BEtaferon® in Newly Emerging multiple sclerosis For Initial Treatment (BENEFIT) prospective phase III trials. All patients were treated with interferon β-1b for at least 6 months. In addition, a genome-wide association study was conducted to identify new genetic variants. RESULTS: We confirmed an increased risk for carriers of HLA-DRB1*04:01 (odds ratio (OR) = 3.3, p = 6.9 × 10-4) and HLA-DRB1*07:01 (OR = 1.8, p = 3.5 × 10-3) for developing neutralizing antibodies (NAbs). Several additional, previously proposed HLA alleles and genetic variants showed nominally significant associations. In the exploratory analysis, variants in the HLA region were associated with NAb development at genome-wide significance (OR = 2.6, p = 2.30 × 10-15). CONCLUSION: The contribution of HLA alleles and HLA-associated single-nucleotide polymorphisms (SNPs) to the development and titer of antibodies against interferon β was confirmed in the combined analysis of two multi-national, multi-center studies

Power estimation for non-standardized multisite studies

AbstractA concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer's segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions