Parametric mapping techniques provide a non-invasive tool for quantifying tissue alterations in myocardial disease in those eligible for cardiovascular magnetic resonance (CMR). Parametric mapping with CMR now permits the routine spatial visualization and quantification of changes in myocardial composition based on changes in T1, T2, and T2*(star) relaxation times and extracellular volume (ECV). These changes include specific disease pathways related to mainly intracellular disturbances of the cardiomyocyte (e.g., iron overload, or glycosphingolipid accumulation in Anderson-Fabry disease); extracellular disturbances in the myocardial interstitium (e.g., myocardial fibrosis or cardiac amyloidosis from accumulation of collagen or amyloid proteins, respectively); or both (myocardial edema with increased intracellular and/or extracellular water). Parametric mapping promises improvements in patient care through advances in quantitative diagnostics, inter- and intra-patient comparability, and relatedly improvements in treatment. There is a multitude of technical approaches and potential applications. This document provides a summary of the existing evidence for the clinical value of parametric mapping in the heart as of mid 2017, and gives recommendations for practical use in different clinical scenarios for scientists, clinicians, and CMR manufacturers.

Background Measurement of myocardial iron is key to the clinical management of patients at risk of siderotic cardiomyopathy. The cardiovascular magnetic resonance (CMR) relaxation parameter R2* (assessed clinically via its reciprocal T2*) measured in the ventricular septum is used to assess cardiac iron, but iron calibration and distribution data in humans is limited. Methods and Results Twelve human hearts were studied from transfusion dependent patients following either death (heart failure n=7, stroke n=1) or transplantation for end-stage heart failure (n=4). After CMR R2* measurement, tissue iron concentration was measured in multiple samples of each heart using inductively coupled plasma atomic emission spectroscopy. Iron distribution throughout the heart showed no systematic variation between segments, but epicardial iron concentration was higher than in the endocardium. The mean (±SD) global myocardial iron causing severe heart failure in 10 patients was 5.98 ±2.42mg/g dw (range 3.19–9.50), but in 1 outlier case of heart failure was 25.9mg/g dw. Myocardial ln[R2*] was strongly linearly correlated with ln[Fe] (R2=0.910, p<0.001) leading to [Fe]=45.0•(T2*)−1.22 for the clinical calibration equation with [Fe] in mg/g dw and T2* in ms. Mid-ventricular septal iron concentration and R2* were both highly representative of mean global myocardial iron. Conclusions These data detail the iron distribution throughout the heart in iron overload and provide calibration in humans for CMR R2* against myocardial iron concentration. The iron values are of considerable interest with regard to the level of cardiac iron associated with iron-related death and indicate that the heart is more sensitive to iron loading than the liver. The results also validate the current clinical practice of monitoring cardiac iron in-vivo by CMR of the mid septum.

BackgroundThere is a need to standardise non-invasive measurements of liver iron concentrations (LIC) so clear inferences can be drawn about body iron levels that are associated with hepatic and extra-hepatic complications of iron overload. Since the first demonstration of an inverse relationship between biopsy LIC and liver magnetic resonance (MR) using a proof-of-concept T2* sequence, MR technology has advanced dramatically with a shorter minimum echo-time, closer inter-echo spacing and constant repetition time. These important advances allow more accurate calculation of liver T2* especially in patients with high LIC.MethodsHere, we used an optimised liver T2* sequence calibrated against 50 liver biopsy samples on 25 patients with transfusional haemosiderosis using ordinary least squares linear regression, and assessed the method reproducibility in 96 scans over an LIC range up to 42 mg/g dry weight (dw) using Bland-Altman plots. Using mixed model linear regression we compared the new T2*-LIC with R2-LIC (Ferriscan) on 92 scans in 54 patients with transfusional haemosiderosis and examined method agreement using Bland-Altman approach.ResultsStrong linear correlation between ln(T2*) and ln(LIC) led to the calibration equation LIC = 31.94(T2*)-1.014. This yielded LIC values approximately 2.2 times higher than the proof-of-concept T2* method. Comparing this new T2*-LIC with the R2-LIC (Ferriscan) technique in 92 scans, we observed a close relationship between the two methods for values up to 10 mg/g dw, however the method agreement was poor.ConclusionsNew calibration of T2* against liver biopsy estimates LIC in a reproducible way, correcting the proof-of-concept calibration by 2.2 times. Due to poor agreement, both methods should be used separately to diagnose or rule out liver iron overload in patients with increased ferritin.

Routinely recorded electrocardiograms (ECGs) are often corrupted by different types of artefacts and many efforts have been made to enhance their quality by reducing the noise or artefacts. This paper addresses the problem of removing noise and artefacts from ECGs using independent component analysis (ICA). An ICA algorithm is tested on three-channel ECG recordings taken from human subjects, mostly in the coronary care unit. Results are presented that show that ICA can detect and remove a variety of noise and artefact sources in these ECGs. One difficulty with the application of ICA is the determination of the order of the independent components. A new technique based on simple statistical parameters is proposed to solve this problem in this application. The developed technique is successfully applied to the ECG data and offers potential for online processing of ECG using ICA.

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Previous studies have evaluated gene expression in Alzheimer’s disease (AD) brains to identify mechanistic processes, but have been limited by the size of the datasets studied. Here we have implemented a novel meta-analysis approach to identify differentially expressed genes (DEGs) in published datasets comprising 450 late onset AD (LOAD) brains and 212 controls. We found 3124 DEGs, many of which were highly correlated with Braak stage and cerebral atrophy. Pathway Analysis revealed the most perturbed pathways to be (a) nitric oxide and reactive oxygen species in macrophages (NOROS), (b) NFkB and (c) mitochondrial dysfunction. NOROS was also up-regulated, and mitochondrial dysfunction down-regulated, in healthy ageing subjects. Upstream regulator analysis predicted the TLR4 ligands, STAT3 and NFKBIA, for activated pathways and RICTOR for mitochondrial genes. Protein-protein interaction network analysis emphasised the role of NFKB; identified a key interaction of CLU with complement; and linked TYROBP, TREM2 and DOK3 to modulation of LPS signalling through TLR4 and to phosphatidylinositol metabolism. We suggest that NEUROD6, ZCCHC17, PPEF1 and MANBAL are potentially implicated in LOAD, with predicted links to calcium signalling and protein mannosylation. Our study demonstrates a highly injurious combination of TLR4-mediated NFKB signalling, NOROS inflammatory pathway activation, and mitochondrial dysfunction in LOAD.

Reproducible and accurate myocardial T* 2 measurements are required for the quantification of iron in heart tissue in transfused thalassemia. The aim of this study was to determine the best method to measure the myocardial T* 2 from multi-gradientecho data acquired both with and without black-blood preparation. Sixteen thalassemia patients from six centers were scanned twice locally, within 1 week, using an optimized brightblood T* 2 sequence and then subsequently scanned at the standardization center in London within 4 weeks, using a T* 2 sequence both with and without black-blood preparation. Different curve-fitting models (monoexponential, truncation, and offset) were applied to the data and the results were compared by means of reproducibility. T* 2 measurements obtained using the bright-and black-blood techniques. The black-blood data were well fitted by the monoexponential model, which suggests that a more accurate measure of T* 2 can be obtained by removing the main source of errors in the bright-blood data. For bright-blood data, the offset model appeared to underestimate T* 2 values substantially and was less reproducible. The truncation model gave rise to more reproducible T* 2 measurements, which were also closer to the values obtained from the blackblood data. Magn Reson Med 60:1082-1089, 2008.

Purpose: To examine the reproducibility of the single breathhold T2* technique from different scanners, after installation of standard methodology in five international centers. Materials and Methods:Up to 10 patients from each center were scanned twice locally for local interstudy reproducibility of heart and liver T2*, and then flown to a central MR facility to be rescanned on a reference scanner for intercenter reproducibility. Interobserver reproducibility for all scans was also assessed. Results:Of the 49 patients scanned, the intercenter reproducibility for T2* was 5.9% for the heart and 5.8% for the liver. Local interstudy reproducibility for T2* was 7.4% for the heart and 4.6% for the liver. Interobserver reproducibility for T2* was 5.4% for the heart and 4.4% for the liver. Conclusion:These data indicate that T2* MR may be developed into a widespread test for tissue siderosis providing that well-defined and approved imaging and analysis techniques are used.