No abstract

No abstract

Modern approaches to modelling cardiac perfusion now commonly describe the myocardium using the framework of poroelasticity. Cardiac tissue can be described as a saturated porous medium composed of the pore fluid (blood) and the skeleton (myocytes and collagen scaffold). In previous studies fluid–structure interaction in the heart has been treated in a variety of ways, but in most cases, the myocardium is assumed to be a hyperelastic fibre‐reinforced material. Conversely, models that treat the myocardium as a poroelastic material typically neglect interactions between the myocardium and intracardiac blood flow. This work presents a poroelastic immersed finite element framework to model left ventricular dynamics in a three‐phase poroelastic system composed of the pore blood fluid, the skeleton, and the chamber fluid. We benchmark our approach by examining a pair of prototypical poroelastic formations using a simple cubic geometry considered in the prior work by Chapelle et al (2010). This cubic model also enables us to compare the differences between system behaviour when using isotropic and anisotropic material models for the skeleton. With this framework, we also simulate the poroelastic dynamics of a three‐dimensional left ventricle, in which the myocardium is described by the Holzapfel–Ogden law. Results obtained using the poroelastic model are compared to those of a corresponding hyperelastic model studied previously. We find that the poroelastic LV behaves differently from the hyperelastic LV model. For example, accounting for perfusion results in a smaller diastolic chamber volume, agreeing well with the well‐known wall‐stiffening effect under perfusion reported previously. Meanwhile differences in systolic function, such as fibre strain in the basal and middle ventricle, are found to be comparatively minor.

A comprehensive search of published literature in brain volumetry was conducted in three autoimmune diseases — systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and ulcerative colitis (UC) — with the intention of performing a meta-analysis of published data. Due to the lack of data in RA and UC, the reported meta-analysis was limited to SLE. The MEDLINE database was searched for studies from 1988 to March 2022. A total of 175 papers met the initial inclusion criteria, and 16 were included in a random-effects meta-analysis. The reduction in the number of papers included in the final analysis is primarily due to the lack of overlap in measured and reported brain regions. A significantly lower volume was seen in patients with SLE in the hippocampus, corpus callosum, and total gray matter volume measurements as compared to age- and sex-matched controls. There were not enough studies to perform a meta-analysis for RA and UC; instead, we include a summary of published volumetric studies. The meta-analyses revealed structural brain abnormalities in patients with SLE, suggesting that lower global brain volumes are associated with disease status. This volumetric difference was seen in both the hippocampus and corpus callosum and total gray matter volume measurements. These results indicate both gray and white matter involvements in SLE and suggest there may be both localized and global reductions in brain volume.

ObjectiveA comprehensive search of published literature in brain volumetry was conducted in three autoimmune diseases – Systemic Lupus Erythematosus (SLE), Rheumatoid Arthritis (RA), and Ulcerative Colitis (UC) with the intention of performing a meta-analysis of published data. Due to lack of data in RA and UC the reported meta-analysis was limited to SLE.MethodsThe MEDLINE database was searched for studies from 1988 through March 2022. A total of 175 papers met the initial inclusion criteria and 16 were included in a random effects meta-analysis. The reduction in the number of papers included in the final analysis is primarily due to the lack of overlap in measured and reported brain regions.ResultsA significantly lower volume was seen in patients with SLE in the hippocampus, corpus callosum and total gray matter volume measurements as compared to age and sex matched controls. There were not enough studies to perform a meta-analysis for RA and UC; instead we include a summary of published volumetric studies.ConclusionsThe meta-analyses revealed structural brain abnormalities in patients with SLE suggesting that lower global brain volumes are associated with disease status. This volumetric difference was seen in both the hippocampus and corpus callosum and total gray matter volume measurements. These results indicate both gray and white matter involvement in SLE and suggest there may be both localised and global reductions in brain volume.KEY MESSAGESWhat’s already known on this topicCentral nervous system effects of lupus are common, however, agreement on principally affected neuroanatomical regions is lacking.What this study addsThis study combines the volumetric neuroimaging data from previously published SLE literature in a meta-analysis. The hippocampus, corpus callosum and total gray matter volume in patients with SLE is smaller than in age and sex matched controls. Additionally, a summary of published data in RA and UC is provided.How this study might affect research, practice or policyThis is the first meta-analysis on neuroimaging studies of volume differences in SLE. The regions identified can inform further research on disease progression and therapy evaluation targeted at brain volumetric changes in SLE.These results provide specific regions of interest to further explore in the central treatment and management of SLE. While these regions are shown to be directly affected, additional brain regions may be implicated. Further research to understand the potential link between these volumetric measurements and behavioural/cognitive changes observed in patients with lupus is warranted.

Deposition of amyloid in the heart can lead to cardiac dilation and impair its pumping ability. This ultimately leads to heart failure with worsening symptoms of breathlessness and fatigue due to the progressive loss of elasticity of the myocardium. Biomarkers linked to the clinical deterioration can be crucial in developing effective treatments. However, to date the progression of cardiac amyloidosis is poorly characterized. There is an urgent need to identify key predictors for disease progression and cardiac tissue function. In this proof of concept study, we estimate a group of new markers based on mathematical models of the left ventricle derived from routine clinical magnetic resonance imaging and follow-up scans from the National Amyloidosis Center at the Royal Free in London. Using mechanical modeling and statistical classification, we show that it is possible to predict disease progression. Our predictions agree with clinical assessments in a double-blind test in six out of the seven sample cases studied. Importantly, we find that multiple factors need to be used in the classification, which includes mechanical, geometrical and shape features. No single marker can yield reliable prediction given the complexity of the growth and remodeling process of diseased hearts undergoing high-dimensional shape changes. Our approach is promising in terms of clinical translation but the results presented should be interpreted with caution due to the small sample size.

Objectives: Rheumatoid arthritis (RA) and ulcerative colitis (UC) are two autoimmune diseases where patients report high levels of fatigue, pain, and depression. The effect of systemic inflammation from these diseases is likely affecting the brain, however, it is unknown whether there are measurable neuroanatomical changes and whether these are a contributing factor to these central symptoms. Methods: We included 258 RA patients with 774 age and sex matched controls and 249 UC patients with 747 age and sex matched controls in a case control study utilising the UK Biobank dataset. We used imaging derived phenotypes (IDPs) to determine whether there were differences in (1) hippocampal volume and (2) additional subcortical brain volumes between patients compared to controls and if there were common regions affected between these two diseases. Results: Patients with UC had moderately smaller hippocampi compared to age and sex matched controls (difference: 134.15 mm3, SD ± 64.76, p = 0.035). This result was not seen in RA patients. RA patients had a significantly smaller amygdala volume than age and sex matched controls (difference: 91.27 mm3, SD ± 30.85, p = 0.0021, adjusted p value = 0.012). This result was not seen in UC patients. All other subcortical structures analysed were comparable between the patients and control groups. Conclusion: These results indicate there are subcortical brain differences between UC, RA and controls but different regions of the limbic system are preferentially affected by UC and RA. This study may provide evidence for different neurodegenerative mechanisms in distinct autoimmune diseases.

No abstract