Deep Anatomical Federated Network (Dafne): an open client/server framework for the continuous collaborative improvement of deep-learning-based medical image segmentation

Semantic segmentation is a crucial step to extract quantitative information from medical (and, specifically, radiological) images to aid the diagnostic process, clinical follow-up. and to generate biomarkers for clinical research. In recent years, machine learning algorithms have become the primary tool for this task. However, its real-world performance is heavily reliant on the comprehensiveness of training data. Dafne is the first decentralized, collaborative solution that implements continuously evolving deep learning models exploiting the collective knowledge of the users of the system. In the Dafne workflow, the result of each automated segmentation is refined by the user through an integrated interface, so that the new information is used to continuously expand the training pool via federated incremental learning. The models deployed through Dafne are able to improve their performance over time and to generalize to data types not seen in the training sets, thus becoming a viable and practical solution for real-life medical segmentation tasks.Comment: 10 pages (main body), 5 figures. Work partially presented at the 2021 RSNA conference and at the 2023 ISMRM conference In this new version: added author and change in the acknowledgmen

Specific sequence determinants of miR-15/107 microRNA gene group targets

MicroRNAs (miRNAs) target mRNAs in human cells via complex mechanisms that are still incompletely understood. Using anti-Argonaute (anti-AGO) antibody co-immunoprecipitation, followed by microarray analyses and downstream bioinformatics, ‘RIP-Chip’ experiments enable direct analyses of miRNA targets. RIP-Chip studies (and parallel assessments of total input mRNA) were performed in cultured H4 cells after transfection with miRNAs corresponding to the miR-15/107 gene group (miR-103, miR-107, miR-16 and miR-195), and five control miRNAs. Three biological replicates were run for each condition with a total of 54 separate human Affymetrix Human Gene 1.0 ST array replicates. Computational analyses queried for determinants of miRNA:mRNA binding. The analyses support four major findings: (i) RIP-Chip studies correlated with total input mRNA profiling provides more comprehensive information than using either RIP-Chip or total mRNA profiling alone after miRNA transfections; (ii) new data confirm that miR-107 paralogs target coding sequence (CDS) of mRNA; (iii) biochemical and computational studies indicate that the 3′ portion of miRNAs plays a role in guiding miR-103/7 to the CDS of targets; and (iv) there are major sequence-specific targeting differences between miRNAs in terms of CDS versus 3′-untranslated region targeting, and stable AGO association versus mRNA knockdown. Future studies should take this important miRNA-to-miRNA variability into account

Ventilation Strategies During Extracorporeal Membrane Oxygenation for Neonatal Respiratory Failure: Current Approaches Among Level IV Neonatal ICUs

To describe ventilation strategies used during extracorporeal membrane oxygenation (ECMO) for neonatal respiratory failure among level IV neonatal ICUs (NICUs). Design: Cross-sectional electronic survey. Setting: Email-based Research Electronic Data Capture survey. Patients: Neonates undergoing ECMO for respiratory failure at level IV NICUs. Interventions: A 40-question survey was sent to site sponsors of regional referral neonatal ECMO centers participating in the Children\u27s Hospitals Neonatal Consortium. Reminder emails were sent at 2- and 4-week intervals. Measurements and main results: Twenty ECMO centers responded to the survey. Most primarily use venoarterial ECMO (65%); this percentage is higher (90%) for congenital diaphragmatic hernia. Sixty-five percent reported following protocol-based guidelines, with neonatologists primarily responsible for ventilator management (80%). The primary mode of ventilation was pressure control (90%), with synchronized intermittent mechanical ventilation (SIMV) comprising 80%. Common settings included peak inspiratory pressure (PIP) of 16-20 cm H2O (55%), positive end-expiratory pressure (PEEP) of 9-10 cm H2O (40%), I-time 0.5 seconds (55%), rate of 10-15 (60%), and Fio2 22-30% (65%). A minority of sites use high-frequency ventilation (HFV) as the primary mode (5%). During ECMO, 55% of sites target some degree of lung aeration to avoid complete atelectasis. Fifty-five percent discontinue inhaled nitric oxide (iNO) during ECMO, while 60% use iNO when trialing off ECMO. Nonventilator practices to facilitate decannulation include bronchoscopy (50%), exogenous surfactant (25%), and noninhaled pulmonary vasodilators (50%). Common ventilator thresholds for decannulation include PEEP of 6-7 (45%), PIP of 21-25 (55%), and tidal volume 5-5.9 mL/kg (50%). Conclusions: The majority of level IV NICUs follow internal protocols for ventilator management during neonatal respiratory ECMO, and neonatologists primarily direct management in the NICU. While most centers use pressure-controlled SIMV, there is considerable variability in the range of settings used, with few centers using HFV primarily. Future studies should focus on identifying respiratory management practices that improve outcomes for neonatal ECMO patients

Canine models of Duchenne muscular dystrophy and their use in therapeutic strategies

Duchenne muscular dystrophy (DMD) is an X-linked recessive disorder in which the loss of dystrophin causes progressive degeneration of skeletal and cardiac muscle. Potential therapies that carry substantial risk, such as gene and cell-based approaches, must first be tested in animal models, notably the mdx mouse and several dystrophin-deficient breeds of dogs, including golden retriever muscular dystrophy (GRMD). Affected dogs have a more severe phenotype, in keeping with that of DMD, so may better predict disease pathogenesis and treatment efficacy. We and others have developed various phenotypic tests to characterize disease progression in the GRMD model. These biomarkers range from measures of strength and joint contractures to magnetic resonance imaging. Some of these tests are routinely used in clinical veterinary practice, while others require specialized equipment and expertise. By comparing serial measurements from treated and untreated groups, one can document improvement or delayed progression of disease. Potential treatments for DMD may be broadly categorized as molecular, cellular, or pharmacologic. The GRMD model has increasingly been used to assess efficacy of a range of these therapies. While some of these studies have largely provided general proof-of-concept for the treatment under study, others have demonstrated efficacy using the biomarkers discussed. Importantly, just as symptoms in DMD vary among patients, GRMD dogs display remarkable phenotypic variation. While confounding statistical analysis in preclinical trials, this variation offers insight regarding the role that modifier genes play in disease pathogenesis. By correlating functional and mRNA profiling results, gene targets for therapy development can be identified

Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development

Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson’s r=0.77 and 0.76, respectively, across SNPs with p &lt; 4.4 × 10−4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45×10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p &gt; 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec

Repetitive ocular vestibular evoked myogenic potentials in myasthenia gravis

OBJECTIVE To validate the repetitive ocular vestibular evoked myogenic potentials (RoVEMP) test for diagnostic use in myasthenia gravis (MG) and to investigate its value in diagnostically challenging subgroups. METHODS The RoVEMP test was performed in 92 patients with MG, 22 healthy controls, 33 patients with a neuromuscular disease other than MG (neuromuscular controls), 4 patients with Lambert-Eaton myasthenic syndrome, and 2 patients with congenital myasthenic syndrome. RESULTS Mean decrement was significantly higher in patients with MG (28.4% ± 32.2) than in healthy controls (3.2% ± 13.9; p < 0.001) or neuromuscular controls (3.8% ± 26.9; p < 0.001). With neuromuscular controls as reference, a cutoff of ≥14.3% resulted in a sensitivity of 67% and a specificity of 82%. The sensitivity of the RoVEMP test was 80% in ocular MG and 63% in generalized MG. The RoVEMP test was positive in 6 of 7 patients with seronegative MG (SNMG) with isolated ocular weakness. Of 10 patients with SNMG with negative repetitive nerve stimulation (RNS) results, 73% had an abnormal RoVEMP test. The magnitude of decrement was correlated with the time since the last intake of pyridostigmine (B = 5.40; p = 0.019). CONCLUSIONS The RoVEMP test is a new neurophysiologic test that, in contrast to RNS and single-fiber EMG, is able to measure neuromuscular transmission of extraocular muscles, which are the most affected muscles in MG. Especially in diagnostically challenging patients with negative antibody tests, negative RNS results, and isolated ocular muscle weakness, the RoVEMP test has a clear added value in supporting the diagnosis of MG. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that RoVEMP distinguishes MG from other neuromuscular diseases

Baseline fat fraction is a strong predictor of disease progression in Becker muscular dystrophy

In Becker muscular dystrophy (BMD), muscle weakness progresses relatively slowly, with a highly variable rate among patients. This complicates clinical trials, as clinically relevant changes are difficult to capture within the typical duration of a trial. Therefore, predictors for disease progression are needed. We assessed if temporal increase of fat fraction (FF) in BMD follows a sigmoidal trajectory and whether fat fraction at baseline (FFbase) could therefore predict FF increase after 2 years (ΔFF). Thereafter, for two different MR-based parameters, we tested the additional predictive value to FFbase. We used 3-T Dixon data from the upper and lower leg, and multiecho spin-echo MRI and 7-T 31P MRS datasets from the lower leg, acquired in 24 BMD patients (age: 41.4 [SD 12.8] years). We assessed the pattern of increase in FF using mixed-effects modelling. Subsequently, we tested if indicators of muscle damage like standard deviation in water T2 (stdT2) and the phosphodiester (PDE) over ATP ratio at baseline had additional value to FFbase for predicting ∆FF. The association between FFbase and ΔFF was described by the derivative of a sigmoid function and resulted in a peak ΔFF around 0.45 FFbase (fourth-order polynomial term: t = 3.7, p <.001). StdT2 and PDE/ATP were not significantly associated with ∆FF if FFbase was included in the model. The relationship between FFbase and ∆FF suggests a sigmoidal trajectory of the increase in FF over time in BMD, similar to that described for Duchenne muscular dystrophy. Our results can be used to identify muscles (or patients) that are in the fast progressing stage of the disease, thereby facilitating the conduct of clinical trials

T 2

Purpose: Multi-echo spin-echo (MSE) transverse relaxometry mapping using multi-component models is used to study disease activity in neuromuscular disease by assessing the T2 of the myocytic component (T2water). Current extended phase graph algorithms are not optimized for fat fractions above 50% and the effects of inaccuracies in the T2fat calibration remain unexplored. Hence, we aimed to improve the performance of extended phase graph fitting methods over a large range of fat fractions, by including the slice-selection flip angle profile, a through-plane chemical-shift displacement correction, and optimized calibration of T2fat. Methods: Simulation experiments were used to study the influence of the slice flip-angle profile with chemical-shift and T2fat estimations. Next, in vivo data from four neuromuscular disease cohorts were studied for different T2fat calibration methods and T2water estimations. Results: Excluding slice flip-angle profiles or chemical-shift displacement resulted in a bias in T2water up to 10 ms. Furthermore, a wrongly calibrated T2fat caused a bias of up to 4 ms in T2water. For the in vivo data, one-component calibration led to a lower T2fat compared with a two-component method, and T2water decreased with increasing fat fractions. Conclusion: In vivo data showed a decline in T2water for increasing fat fractions, which has important implications for clinical studies, especially in multicenter settings. We recommend using an extended phase graph–based model for fitting T2water from MSE sequences with two-component T2fat calibration. Moreover, we recommend including the slice flip-angle profile in the model with correction for through-plane chemical-shift displacements

T2 relaxation-time mapping in healthy and diseased skeletal muscle using extended phase graph algorithms

Purpose: Multi-echo spin-echo (MSE) transverse relaxometry mapping using multi-component models is used to study disease activity in neuromuscular disease by assessing the T2 of the myocytic component (T2water). Current extended phase graph algorithms are not optimized for fat fractions above 50% and the effects of inaccuracies in the T2fat calibration remain unexplored. Hence, we aimed to improve the performance of extended phase graph fitting methods over a large range of fat fractions, by including the slice-selection flip angle profile, a through-plane chemical-shift displacement correction, and optimized calibration of T2fat. Methods: Simulation experiments were used to study the influence of the slice flip-angle profile with chemical-shift and T2fat estimations. Next, in vivo data from four neuromuscular disease cohorts were studied for different T2fat calibration methods and T2water estimations. Results: Excluding slice flip-angle profiles or chemical-shift displacement resulted in a bias in T2water up to 10 ms. Furthermore, a wrongly calibrated T2fat caused a bias of up to 4 ms in T2water. For the in vivo data, one-component calibration led to a lower T2fat compared with a two-component method, and T2water decreased with increasing fat fractions. Conclusion: In vivo data showed a decline in T2water for increasing fat fractions, which has important implications for clinical studies, especially in multicenter settings. We recommend using an extended phase graph–based model for fitting T2water from MSE sequences with two-component T2fat calibration. Moreover, we recommend including the slice flip-angle profile in the model with correction for through-plane chemical-shift displacements