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Methadone, a widely-prescribed medication for chronic pain and opioid addiction, is associated with respiratory depression and increased predisposition for torsades de pointes, a potentially fatal arrhythmia. Most methadone-related deaths occur during sleep. The objective of this study was to determine whether methadone’s arrhythmogenic effects increase during sleep, with a focus on cardiac repolarization instability using QT variability index (QTVI), a measure shown to predict arrhythmias and mortality. Sleep study data of 24 patients on chronic methadone therapy referred to a tertiary clinic for overnight polysomnography were compared with two matched groups not on methadone: 24 patients referred for overnight polysomnography to the same clinic (Clinic group), and 24 volunteers who had overnight polysomnography at home (Community group). Despite similar values for heart rate, heart rate variability, corrected QT interval, QTVI and oxygen saturation (SpO(2)) when awake, patients on methadone had larger QTVI (p=0.015 vs Clinic, p1000 premature beats per median sleep period), a precursor for torsades de pointes, was uncommon but more frequent in patients on methadone (p=0.039). This study demonstrates that chronic methadone use is associated with increased cardiac repolarization instability. Methadone’s pro-arrhythmic impact may be mediated by sleep-related hypoxemia which could explain the increased nocturnal mortality associated with this opioid.

Large-scale data obtained from aggregation of already collected multi-site neuroimaging datasets has brought benefits such as higher statistical power, reliability, and robustness to the studies. Despite these promises from growth in sample size, substantial technical variability stemming from differences in scanner specifications exists in the aggregated data and could inadvertently bias any downstream analyses on it. Such a challenge calls for data normalization and/or harmonization frameworks, in addition to comprehensive criteria to estimate the scanner-related variability and evaluate the harmonization frameworks. In this study, we propose MISPEL (Multi-scanner Image harmonization via Structure Preserving Embedding Learning), a supervised multi-scanner harmonization method that is naturally extendable to more than two scanners. We also designed a set of criteria to investigate the scanner-related technical variability and evaluate the harmonization techniques. As an essential requirement of our criteria, we introduced a multi-scanner matched dataset of 3T T1 images across four scanners, which, to the best of our knowledge is one of the few datasets of this kind. We also investigated our evaluations using two popular segmentation frameworks: FSL and segmentation in statistical parametric mapping (SPM). Lastly, we compared MISPEL to popular methods of normalization and harmonization, namely White Stripe, RAVEL, and CALAMITI. MISPEL outperformed these methods and is promising for many other neuroimaging modalities.

ObjectiveTo evaluate whether a retinal spectral-domain optical coherence tomography (SD-OCT) assessment at baseline is associated with long-term disability worsening in people with multiple sclerosis (PwMS), we performed SD-OCT and Expanded Disability Status Scale (EDSS) assessments among 132 PwMS at baseline and at a median of 10 years later.MethodsIn this prospective, longitudinal study, participants underwent SD-OCT, EDSS, and visual acuity (VA) assessments at baseline and at follow-up. Statistical analyses were performed using generalized linear regression models, adjusted for age, sex, race, multiple sclerosis (MS) subtype, and baseline disability. We defined clinically meaningful EDSS worsening as an increase of ≥2.0 if baseline EDSS score was ResultsA total of 132 PwMS (mean age 43 years; 106 patients with relapsing-remitting MS) were included in analyses. Median duration of follow-up was 10.4 years. In multivariable models excluding eyes with prior optic neuritis, relative to patients with an average baseline ganglion cell + inner plexiform layer (GCIPL) thickness ≥70 µm (the mean GCIPL thickness of all eyes at baseline), an average baseline GCIPL thickness p = 0.02) and an almost 3-fold increased odds of low-contrast VA worsening (adjusted OR 2.93, 95% CI 1.40–6.13; p = 0.04).ConclusionsLower baseline GCIPL thickness on SD-OCT is independently associated with long-term disability worsening in MS. Accordingly, SD-OCT at a single time point may help guide therapeutic decision-making among individual PwMS.Classification of EvidenceThis study provides Class I evidence that lower baseline GCIPL thickness on SD-OCT is independently associated with long-term disability worsening in MS.

Summary We introduce a multilevel functional Beta model to quantify the blood glucose levels measured by continuous glucose monitors for multiple days in study participants with type 2 diabetes mellitus. The model estimates the subject-specific marginal quantiles, quantifies the within- and between-subject variability, and produces interpretable parameters of blood glucose dynamics as a function of time from the actigraphy-estimated sleep onset. Results are validated via simulations and by studying the association between the estimated model parameters and hemoglobin A1c, the gold standard for assessing glucose control in diabetes.

Harmonization of magnetic resonance imaging (MRI) and positron emission tomography (PET) scans from multi-scanner and multi-site studies presents a challenging problem. We applied the Removal of Artificial Voxel Effect by Linear regression (RAVEL) method to normalize T1-MRI intensities collected on two different scanners across two different sites as part of the Neurodegeneration in Aging Down syndrome (NiAD) study. The effects on FreeSurfer regional cortical thickness and volume outcome measures, in addition to FreeSurfer-based regional quantification of amyloid PET standardized uptake value ratio (SUVR) outcomes, were evaluated. A neuroradiologist visually assessed the accuracy of FreeSurfer hippocampus segmentations with and without the application of RAVEL. Quantitative results demonstrated that the application of RAVEL intensity normalization prior to running FreeSurfer significantly impacted both FreeSurfer volume and cortical thickness outcome measures. Visual assessment demonstrated that the application of RAVEL significantly improved FreeSurfer hippocampal segmentation accuracy. The RAVEL intensity normalization had little impact on PET SUVR measures.

Summary Our main goal is to study and quantify the evolution of multiple sclerosis lesions observed longitudinally over many years in multi-sequence structural magnetic resonance imaging (sMRI). To achieve that, we propose a class of functional models for capturing the temporal dynamics and spatial distribution of the voxel-specific intensity trajectories in all sMRI sequences. To accommodate the hierarchical data structure (observations nested within voxels, which are nested within lesions, which, in turn, are nested within study participants), we use structured functional principal component analysis. We propose and evaluate the finite sample properties of hypothesis tests of therapeutic intervention effects on lesion evolution while accounting for the multilevel structure of the data. Using this novel testing strategy, we found statistically significant differences in lesion evolution between treatment groups.

Background: Studies evaluating associations between body mass index (BMI) and optical coherence tomography (OCT) measures in multiple sclerosis (MS) are lacking. Objective: To assess whether elevated BMI is associated with accelerated retinal atrophy. Methods: In this observational study, 513 MS patients were followed with serial spectral-domain OCT for a median of 4.4 years. Participants were categorized as normal weight (BMI: 18.5–24.9 kg/m2), overweight (BMI: 25–29.9 kg/m2), and obese (BMI: ⩾30 kg/m2). Participants with diabetes mellitus or uncontrolled hypertension and eyes with optic neuritis (ON) ⩽6 months prior to baseline OCT or during follow-up were excluded. Statistical analyses were performed with mixed-effects linear regression. Results: Obese patients ( n = 146) exhibited accelerated rates of ganglion cell + inner plexiform layer (GCIPL) atrophy relative to normal weight patients ( n = 214; –0.57%/year (95% confidence interval (CI): –0.65% to –0.48%) versus –0.42%/year (95% CI: –0.49% to –0.35%); p = 0.012). GCIPL atrophy rate did not differ between overweight ( n = 153) and normal weight patients (–0.47%/year vs –0.42%/year; p = 0.41). Each 1 kg/m2 higher BMI was associated with accelerated GCIPL (–0.011%/year; 95% CI: –0.019% to –0.004%; p = 0.003) atrophy. Multivariable analyses accounting for age, sex, race, MS subtype, and ON history did not alter the above findings. Conclusions: Elevated BMI, in the absence of overt metabolic comorbidities, may be associated with accelerated GCIPL atrophy. Obesity, a modifiable risk factor, may be associated with accelerated neurodegeneration in MS.