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.