Accurate simultaneous quantification of liver steatosis and iron overload in diffuse liver diseases with MRI

Purpose: To evaluate the diagnostic performances of 3 Tesla multi-echo chemical shift-encoded gradient echo magnetic resonance (MECSE-MR) imaging to simultaneously quantify liver steatosis and iron overload in a wide spectrum of diffuse liver diseases having biopsy as reference standard. Methods: MECSE-MR-acquired images were used to calculate fat fraction and iron content in a single breath-hold in 109 adult patients. Proton density fat fraction (PDFF) was prospectively estimated using complex-based data reconstruction with multipeak fat modeling. Water R2* was used to estimate iron content. Biopsy was obtained in all cases, grading liver steatosis, siderosis, inflammation, and fibrosis. Differences in PDFF and R2* values across histopathological grades were analyzed, and ROC curves analyses evaluated the MR diagnostic performance. Results: Calculated fat fraction measurements showed significant differences (p < 0.001) among steatosis grades, being unaffected by the presence of inflammation or fibrosis (p ≥ 0.05). A strong correlation was found between fat fraction and steatosis grade (R S = 0.718, p < 0.001). Iron deposits did not affect fat fraction quantitation (p ≥ 0.05), except in cases with severe iron overload (grade 4). A strong positive correlation was also observed between R2* measurements and iron grades (R S = 0.704, p < 0.001). Calculated R2* values were not different across grades of steatosis, inflammation, and fibrosis (p ≥ 0.05). Conclusion: A MECSE-MR sequence simultaneously quantifies liver steatosis and siderosis, regardless coexisting liver inflammation or fibrosis, with high accuracy in a wide spectrum of diffuse liver disorders. This sequence can be acquired within a single breath-hold and can be implemented in the routine MR evaluation of the liver.This work was partially funded by a research grant from the Teaching and Research Department of Centro Hospitalar do Porto (DEFI:309/12(213-DEFI/251-CES)) and from a Spanish Ministry of Health and Carlos III Health Institute funding grant (PI12/01262). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Numerical Study of Aging in the Generalized Random Energy Model

Magnetizations are introduced to the Generalized Random Energy Model (GREM) and numerical simulations on ac susceptibility is made for direct comparison with experiments in glassy materials. Prominent dynamical natures of spin glasses, {\it i.e.}, {\em memory} effect and {\em reinitialization}, are reproduced well in the GREM. The existence of many layers causing continuous transitions is very important for the two natures. Results of experiments in other glassy materials such as polymers, supercooled glycerol and orientational glasses, which are contrast to those in spin glasses, are interpreted well by the Single-layer Random Energy Model.Comment: 8 pages, 9 figures, to be submitted to J. Phys. Soc. Jp

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions

Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse single modality multicentre datasets. However, these surveys rarely focused on evaluation metrics and lacked a checklist for computational data harmonisation studies. In this systematic review, we summarise the computational data harmonisation approaches for multi-modality data in the digital healthcare field, including harmonisation strategies and evaluation metrics based on different theories. In addition, a comprehensive checklist that summarises common practices for data harmonisation studies is proposed to guide researchers to report their research findings more effectively. Last but not least, flowcharts presenting possible ways for methodology and metric selection are proposed and the limitations of different methods have been surveyed for future research

Interacting Preformed Cooper Pairs in Resonant Fermi Gases

We consider the normal phase of a strongly interacting Fermi gas, which can have either an equal or an unequal number of atoms in its two accessible spin states. Due to the unitarity-limited attractive interaction between particles with different spin, noncondensed Cooper pairs are formed. The starting point in treating preformed pairs is the Nozi\`{e}res-Schmitt-Rink (NSR) theory, which approximates the pairs as being noninteracting. Here, we consider the effects of the interactions between the Cooper pairs in a Wilsonian renormalization-group scheme. Starting from the exact bosonic action for the pairs, we calculate the Cooper-pair self-energy by combining the NSR formalism with the Wilsonian approach. We compare our findings with the recent experiments by Harikoshi {\it et al.} [Science {\bf 327}, 442 (2010)] and Nascimb\`{e}ne {\it et al.} [Nature {\bf 463}, 1057 (2010)], and find very good agreement. We also make predictions for the population-imbalanced case, that can be tested in experiments.Comment: 10 pages, 6 figures, accepted version for PRA, discussion of the imbalanced Fermi gas added, new figure and references adde

BDNF and NGF signalling in early phases of psychosis: relationship with inflammation and response to antipsychotics after a 1 year

Previous studies have indicated systemic deregulation of the proinflammatory or anti-inflammatory balance in individuals with first-episode psychosis (FEP) that persists 12 months later. To identify potential risk/protective factors and associations with symptom severity, we assessed possible changes in plasma levels of neurotrophins (brain-derived neurotrophic factor [BDNF] and nerve growth factor [NGF]) and their receptors in peripheral blood mononuclear cells (PBMCs). Expression of the 2 forms of BDNF receptors (active TrkB-FL and inactiveTrkB-T1) in PBMCs of FEP patients changed over time, TrkB-FL expression increasing by 1 year after diagnosis, while TrkB-T1 expression decreased. The TrkB-FL/TrkB-T1 ratio (hereafter FL/T1 ratio) increased during follow-up in the nonaffective psychosis group only, suggesting different underlying pathophysiological mechanisms in subgroups of FEP patients. Further, the expression of the main NGF receptor, TrkA, generally increased in patients at follow-up. After adjusting for potential confounders, baseline levels of inducible isoforms of nitric oxide synthase, cyclooxygenase, and nuclear transcription factor were significantly associated with the FL/T1 ratio, suggesting that more inflammation is associated with higher values of this ratio. Interestingly, the FL/T1 ratio might have a role as a predictor of functioning, a regression model of functioning at 1 year suggesting that the effect of the FL/T1 ratio at baseline on functioning at 1 year depended on whether patients were treated with antipsychotics. These findings may have translational relevance; specifically, it might be useful to assess the expression of TrkB receptor isoforms before initiating antipsychotic treatment in FEP

BDNF and NGF Signalling in Early Phases of Psychosis: Relationship with Inflammation and Response to Antipsychotics after 1 Year

Previous studies have indicated systemic deregulation of the proinflammatory or anti-inflammatory balance in individuals with first-episode psychosis (FEP) that persists 12 months later. To identify potential risk/protective factors and associations with symptom severity, we assessed possible changes in plasma levels of neurotrophins (brain-derived neurotrophic factor BDNF] and nerve growth factor NGF]) and their receptors in peripheral blood mononuclear cells (PBMCs). Expression of the 2 forms of BDNF receptors (active TrkB-FL and inactiveTrkB-T1) in PBMCs of FEP patients changed over time, TrkB-FL expression increasing by 1 year after diagnosis, while TrkB-T1 expression decreased. The TrkB-FL/TrkB-T1 ratio (hereafter FL/T1 ratio) increased during follow-up in the nonaffective psychosis group only, suggesting different underlying pathophysiological mechanisms in subgroups of FEP patients. Further, the expression of the main NGF receptor, TrkA, generally increased in patients at follow-up. After adjusting for potential confounders, baseline levels of inducible isoforms of nitric oxide synthase, cyclooxygenase, and nuclear transcription factor were significantly associated with the FL/T1 ratio, suggesting that more inflammation is associated with higher values of this ratio. Interestingly, the FL/T1 ratio might have a role as a predictor of functioning, a regression model of functioning at 1 year suggesting that the effect of the FL/T1 ratio at baseline on functioning at 1 year depended on whether patients were treated with antipsychotics. These findings may have translational relevance; specifically, it might be useful to assess the expression of TrkB receptor isoforms before initiating antipsychotic treatment in FEPs

Prostate Diffusion Weighted-Magnetic Resonance Image analysis using Multivariate Curve Resolution methods

[EN] Multivariate Curve Resolution (MCR) has been applied on prostate Diffusion Weighted-Magnetic Resonance Images (DW-MRI). Different physiological-based modeling approaches of the diffusion process have been submitted to validation by sequentially incorporating prior knowledge on the MCR constraints. Results validate the biexponential diffusion modeling approach and show the capability of the MCR models to find, characterize and locate the behaviors related to the presence of an early prostate tumor.The authors want to thank prof. Anna de Juan for her comments and help in using the software for this study. This research work was partially supported by the Spanish Ministry of Economy and Competitiveness under the project DPI 2011-28112-004-02.Aguado Sarrió, E.; Prats-Montalbán, JM.; Sanz Requena, R.; Marti Bonmati, L.; Alberich Bayarri, Á.; Ferrer Riquelme, AJ. (2015). Prostate Diffusion Weighted-Magnetic Resonance Image analysis using Multivariate Curve Resolution methods. Chemometrics and Intelligent Laboratory Systems. 140:43-48. https://doi.org/10.1016/j.chemolab.2014.11.002S434814

PRIMAGE project : predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers

PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, artificial intelligence and cancer treatment in children. It is a 4-year European Commission-financed project that has 16 European partners in the consortium, including the European Society for Paediatric Oncology, two imaging biobanks, and three prominent European paediatric oncology units. The project is constructed as an observational in silico study involving high-quality anonymised datasets (imaging, clinical, molecular, and genetics) for the training and validation of machine learning and multiscale algorithms. The open cloud-based platform will offer precise clinical assistance for phenotyping (diagnosis), treatment allocation (prediction), and patient endpoints (prognosis), based on the use of imaging biomarkers, tumour growth simulation, advanced visualisation of confidence scores, and machine-learning approaches. The decision support prototype will be constructed and validated on two paediatric cancers: neuroblastoma and diffuse intrinsic pontine glioma. External validation will be performed on data recruited from independent collaborative centres. Final results will be available for the scientific community at the end of the project, and ready for translation to other malignant solid tumours

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR)

Abstract: Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions