Slowly expanding/evolving lesions as a magnetic resonance imaging marker of chronic active multiple sclerosis lesions.

BACKGROUND:Chronic lesion activity driven by smoldering inflammation is a pathological hallmark of progressive forms of multiple sclerosis (MS). OBJECTIVE:To develop a method for automatic detection of slowly expanding/evolving lesions (SELs) on conventional brain magnetic resonance imaging (MRI) and characterize such SELs in primary progressive MS (PPMS) and relapsing MS (RMS) populations. METHODS:We defined SELs as contiguous regions of existing T2 lesions showing local expansion assessed by the Jacobian determinant of the deformation between reference and follow-up scans. SEL candidates were assigned a heuristic score based on concentricity and constancy of change in T2- and T1-weighted MRIs. SELs were examined in 1334 RMS patients and 555 PPMS patients. RESULTS:Compared with RMS patients, PPMS patients had higher numbers of SELs (p = 0.002) and higher T2 volumes of SELs (p < 0.001). SELs were devoid of gadolinium enhancement. Compared with areas of T2 lesions not classified as SEL, SELs had significantly lower T1 intensity at baseline and larger decrease in T1 intensity over time. CONCLUSION:We suggest that SELs reflect chronic tissue loss in the absence of ongoing acute inflammation. SELs may represent a conventional brain MRI correlate of chronic active MS lesions and a candidate biomarker for smoldering inflammation in MS

Chronic white matter lesion activity predicts clinical progression in primary progressive multiple sclerosis.

Chronic active and slowly expanding lesions with smouldering inflammation are neuropathological correlates of progressive multiple sclerosis pathology. T1 hypointense volume and signal intensity on T1-weighted MRI reflect brain tissue damage that may develop within newly formed acute focal inflammatory lesions or in chronic pre-existing lesions without signs of acute inflammation. Using a recently developed method to identify slowly expanding/evolving lesions in vivo from longitudinal conventional T2- and T1-weighted brain MRI scans, we measured the relative amount of chronic lesion activity as measured by change in T1 volume and intensity within slowly expanding/evolving lesions and non-slowly expanding/evolving lesion areas of baseline pre-existing T2 lesions, and assessed the effect of ocrelizumab on this outcome in patients with primary progressive multiple sclerosis participating in the phase III, randomized, placebo-controlled, double-blind ORATORIO study (n = 732, NCT01194570). We also assessed the predictive value of T1-weighted measures of chronic lesion activity for clinical multiple sclerosis progression as reflected by a composite disability measure including the Expanded Disability Status Scale, Timed 25-Foot Walk and 9-Hole Peg Test. We observed in this clinical trial population that most of total brain non-enhancing T1 hypointense lesion volume accumulation was derived from chronic lesion activity within pre-existing T2 lesions rather than new T2 lesion formation. There was a larger decrease in mean normalized T1 signal intensity and greater relative accumulation of T1 hypointense volume in slowly expanding/evolving lesions compared with non-slowly expanding/evolving lesions. Chronic white matter lesion activity measured by longitudinal T1 hypointense lesion volume accumulation in slowly expanding/evolving lesions and in non-slowly expanding/evolving lesion areas of pre-existing lesions predicted subsequent composite disability progression with consistent trends on all components of the composite. In contrast, whole brain volume loss and acute lesion activity measured by longitudinal T1 hypointense lesion volume accumulation in new focal T2 lesions did not predict subsequent composite disability progression in this trial at the population level. Ocrelizumab reduced longitudinal measures of chronic lesion activity such as T1 hypointense lesion volume accumulation and mean normalized T1 signal intensity decrease both within regions of pre-existing T2 lesions identified as slowly expanding/evolving and in non-slowly expanding/evolving lesions. Using conventional brain MRI, T1-weighted intensity-based measures of chronic white matter lesion activity predict clinical progression in primary progressive multiple sclerosis and may qualify as a longitudinal in vivo neuroimaging correlate of smouldering demyelination and axonal loss in chronic active lesions due to CNS-resident inflammation and/or secondary neurodegeneration across the multiple sclerosis disease continuum

Personalized Prediction of Future Lesion Activity and Treatment Effect in Multiple Sclerosis from Baseline MRI

Precision medicine for chronic diseases such as multiple sclerosis (MS) involves choosing a treatment which best balances efficacy and side effects/preferences for individual patients. Making this choice as early as possible is important, as delays in finding an effective therapy can lead to irreversible disability accrual. To this end, we present the first deep neural network model for individualized treatment decisions from baseline magnetic resonance imaging (MRI) (with clinical information if available) for MS patients. Our model (a) predicts future new and enlarging T2 weighted (NE-T2) lesion counts on follow-up MRI on multiple treatments and (b) estimates the conditional average treatment effect (CATE), as defined by the predicted future suppression of NE-T2 lesions, between different treatment options relative to placebo. Our model is validated on a proprietary federated dataset of 1817 multi-sequence MRIs acquired from MS patients during four multi-centre randomized clinical trials. Our framework achieves high average precision in the binarized regression of future NE-T2 lesions on five different treatments, identifies heterogeneous treatment effects, and provides a personalized treatment recommendation that accounts for treatment-associated risk (e.g. side effects, patient preference, administration difficulties).Comment: Accepted to MIDL 202

Spatial and temporal variability of cadmium in Gulf Stream warm-core rings and associated waters

Seawater samples were collected and analyzed for cadmium during four cruises studying Gulf Stream warm-core rings and associated waters. Warm-core ring (WCR) 82-B was sampled in April (approximately two months after formation), in June (after seasonal stratification), and in August (during its interaction with the Gulf Stream). The September–October cruise studied closure and separation of a meander that formed ring 82-H. The depth of the cadmium maximum varied with the depth of the main thermocline; the maximum occurred at a potential temperature of 7.8 ± 0.5°C and sigma-theta 27.4 ± 0.05 in the Slope Water, Gulf Stream, and Sargasso Sea stations. As the upper 100 m of the ring progressed from vertically well-mixed in April to seasonally stratified in June, the mole-ratios of cadmium/nutrient removal in the mixed layer were similar to the calculated slopes of the linear regressions of cadmium with phosphate, nitrate and silicate calculated from spatial distributions. Lateral mixing processes near the boundaries of WCR 82-B markedly influenced the vertical cadmium distribution via intrusions of Shelf/Slope water containing elevated levels of cadmium. Comparison of ASV-labile and total dissolvable cadmium from the August WCR 82-B station indicated essentially 100% ASV-labile cadmium in the waters within and below the main thermocline but non-detectable (\u3c0.010 nmol kg−1) ASV-labile cadmium in the waters above the thermocline

Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models

Image-based precision medicine aims to personalize treatment decisions based on an individual's unique imaging features so as to improve their clinical outcome. Machine learning frameworks that integrate uncertainty estimation as part of their treatment recommendations would be safer and more reliable. However, little work has been done in adapting uncertainty estimation techniques and validation metrics for precision medicine. In this paper, we use Bayesian deep learning for estimating the posterior distribution over factual and counterfactual outcomes on several treatments. This allows for estimating the uncertainty for each treatment option and for the individual treatment effects (ITE) between any two treatments. We train and evaluate this model to predict future new and enlarging T2 lesion counts on a large, multi-center dataset of MR brain images of patients with multiple sclerosis, exposed to several treatments during randomized controlled trials. We evaluate the correlation of the uncertainty estimate with the factual error, and, given the lack of ground truth counterfactual outcomes, demonstrate how uncertainty for the ITE prediction relates to bounds on the ITE error. Lastly, we demonstrate how knowledge of uncertainty could modify clinical decision-making to improve individual patient and clinical trial outcomes

Supraglacial lakes on the Larsen B ice shelf, Antarctica, and at Paakitsoq, West Greenland:A Comparative Study

This is the accepted manuscript. The final version is available from Ingenta Connect at http://www.ingentaconnect.com/content/igsoc/agl/2014/00000055/00000066/art00001.Supraglacial meltwater lakes trigger ice-shelf break-up and modulate seasonal ice\ud sheet flow, and are thus agents by which warming is transmitted to the Antarctic\ud and Greenland ice sheets. To characterize supraglacial lake variability we perform a\ud comparative analysis of lake geometry and depth in two distinct regions, one on the\ud pre-collapse (2002) Larsen B Ice Shelf, and the other in the ablation zone of\ud Paakitsoq, a land-terminating region of the Greenland Ice Sheet. Compared to\ud Paakitsoq, lakes on the Larsen B Ice Shelf cover a greater proportion of surface area\ud (5.3% vs. 1%), but are shallower and more uniform in area. Other aspects of lake\ud geometry, such as eccentricity, degree of convexity (solidity) and orientation, are\ud relatively similar between the two regions. We attribute the notable difference in\ud lake density and depth between ice-shelf and grounded ice to the fact that ice shelves\ud have flatter surfaces and less distinct drainage basins. Ice shelves also possess more\ud stimuli to small-scale, localized surface elevation variability due to the various\ud structural features that yield small variations in thickness and which float at\ud different levels by Archimedes? principle.We acknowledge the support of the U.S. National Science Foundation under grant ANT-0944248

Placebo-controlled trial of an oral BTK inhibitor in multiple sclerosis

Evobrutinib; Multiple sclerosis; Receptors in B cells; Receptors in myeloid cellsEvobrutinib; Esclerosis múltiple; Receptores en células B; Receptores en células mieloidesEvobrutinib; Esclerosi múltiple; Receptors en cèl·lules B; Receptors en cèl·lules mieloidesBACKGROUND: Bruton's tyrosine kinase (BTK) regulates the functions of B cells and myeloid cells that are implicated in the pathogenesis of multiple sclerosis. Evobrutinib is a selective oral BTK inhibitor that has been shown to inhibit B-cell activation both in vitro and in vivo. METHODS: In this double-blind, randomized, phase 2 trial, we assigned patients with relapsing multiple sclerosis to one of five groups: placebo, evobrutinib (at a dose of 25 mg once daily, 75 mg once daily, or 75 mg twice daily), or open-label dimethyl fumarate (DMF) as a reference. The primary end point was the total (cumulative) number of gadolinium-enhancing lesions identified on T1-weighted magnetic resonance imaging at weeks 12, 16, 20, and 24. Key secondary end points included the annualized relapse rate and change from baseline in the score on the Expanded Disability Status Scale (EDSS). RESULTS: A total of 267 patients were randomly assigned to a trial group. The mean (±SD) total number of gadolinium-enhancing lesions during weeks 12 through 24 was 3.85±5.44 in the placebo group, 4.06±8.02 in the evobrutinib 25-mg group, 1.69±4.69 in the evobrutinib 75-mg once-daily group, 1.15±3.70 in the evobrutinib 75-mg twice-daily group, and 4.78±22.05 in the DMF group. The baseline adjusted rate ratios for the total number of lesions over time as compared with placebo were 1.45 in the evobrutinib 25-mg group (P = 0.32), 0.30 in the evobrutinib 75-mg once-daily group (P = 0.005), and 0.44 in the evobrutinib 75-mg twice-daily group (P = 0.06). The unadjusted annualized relapse rate at week 24 was 0.37 in the placebo group, 0.57 in the evobrutinib 25-mg group, 0.13 in the evobrutinib 75-mg once-daily group, 0.08 in the evobrutinib 75-mg twice-daily group, and 0.20 in the DMF group. There was no significant effect of trial group on the change from baseline in the EDSS score. Elevations in liver aminotransferase values were observed with evobrutinib. CONCLUSIONS: Patients with relapsing multiple sclerosis who received 75 mg of evobrutinib once daily had significantly fewer enhancing lesions during weeks 12 through 24 than those who received placebo. There was no significant difference with placebo for either the 25-mg once-daily or 75-mg twice-daily dose of evobrutinib, nor in the annualized relapse rate or disability progression at any dose. Longer and larger trials are required to determine the effect and risks of evobrutinib in patients with multiple sclerosis.Funded by EMD Serono; ClinicalTrials.gov number, NCT02975349