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.

Rapid innovations in cardiovascular magnetic resonance (CMR) now permit the routine acquisition of quantitative measures of myocardial and blood T1 which are key tissue characteristics. These capabilities introduce a new frontier in cardiology, enabling the practitioner/investigator to quantify biologically important myocardial properties that otherwise can be difficult to ascertain clinically. CMR may be able to track biologically important changes in the myocardium by: a) native T1 that reflects myocardial disease involving the myocyte and interstitium without use of gadolinium based contrast agents (GBCA), or b) the extracellular volume fraction (ECV)–a direct GBCA-based measurement of the size of the extracellular space, reflecting interstitial disease. The latter technique attempts to dichotomize the myocardium into its cellular and interstitial components with estimates expressed as volume fractions. This document provides recommendations for clinical and research T1 and ECV measurement, based on published evidence when available and expert consensus when not. We address site preparation, scan type, scan planning and acquisition, quality control, visualisation and analysis, technical development. We also address controversies in the field. While ECV and native T1 mapping appear destined to affect clinical decision making, they lack multi-centre application and face significant challenges, which demand a community-wide approach among stakeholders. At present, ECV and native T1 mapping appear sufficiently robust for many diseases; yet more research is required before a large-scale application for clinical decision-making can be recommended.

A number of different methods have been demonstrated which increase the speed of MR acquisition by decreasing the number of sequential phase encodes. The UNFOLD technique is based on time interleaving of k‐space lines in sequential images and exploits the property that the outer portion of the field‐of‐view is relatively static. The differences in spatial sensitivity of multiple receiver coils may be exploited using SENSE or SMASH techniques to eliminate the aliased component that results from undersampling k‐space. In this article, an adaptive method of sensitivity encoding is presented which incorporates both spatial and temporal filtering. Temporal filtering and spatial encoding may be combined by acquiring phase encodes in an interleaved manner. In this way the aliased components are alternating phase. The SENSE formulation is not altered by the phase of the alias artifact; however, for imperfect estimates of coil sensitivities the residual artifact will have alternating phase using this approach. This is the essence of combining temporal filtering (UNFOLD) with spatial sensitivity encoding (SENSE). Any residual artifact will be temporally frequency‐shifted to the band edge and thus may be further suppressed by temporal low‐pass filtering. By combining both temporal and spatial filtering a high degree of alias artifact rejection may be achieved with less stringent requirements on accuracy of coil sensitivity estimates and temporal low‐pass filter selectivity than would be required using each method individually. Experimental results that demonstrate the adaptive spatiotemporal filtering method (adaptive TSENSE) with acceleration factor R = 2, for real‐time nonbreath‐held cardiac MR imaging during exercise induced stress are presented. Magn Reson Med 45:846–852, 2001. Published 2001 Wiley‐Liss, Inc.

The longitudinal relaxation time constant (T1) of the myocardium is altered in various disease states due to increased water content or other changes to the local molecular environment. Changes in both native T1 and T1 following administration of gadolinium (Gd) based contrast agents are considered important biomarkers and multiple methods have been suggested for quantifying myocardial T1 in vivo. Characterization of the native T1 of myocardial tissue may be used to detect and assess various cardiomyopathies while measurement of T1 with extracellular Gd based contrast agents provides additional information about the extracellular volume (ECV) fraction. The latter is particularly valuable for more diffuse diseases that are more challenging to detect using conventional late gadolinium enhancement (LGE). Both T1 and ECV measures have been shown to have important prognostic significance. T1-mapping has the potential to detect and quantify diffuse fibrosis at an early stage provided that the measurements have adequate reproducibility. Inversion recovery methods such as MOLLI have excellent precision and are highly reproducible when using tightly controlled protocols. The MOLLI method is widely available and is relatively mature. The accuracy of inversion recovery techniques is affected significantly by magnetization transfer (MT). Despite this, the estimate of apparent T1 using inversion recovery is a sensitive measure, which has been demonstrated to be a useful tool in characterizing tissue and discriminating disease. Saturation recovery methods have the potential to provide a more accurate measurement of T1 that is less sensitive to MT as well as other factors. Saturation recovery techniques are, however, noisier and somewhat more artifact prone and have not demonstrated the same level of reproducibility at this point in time. This review article focuses on the technical aspects of key T1-mapping methods and imaging protocols and describes their limitations including the factors that influence their accuracy, precision, and reproducibility.

The method for phased array image reconstruction of uniform noise images may be used in conjunction with proper image scaling as a means of reconstructing images directly in SNR units. This facilitates accurate and precise SNR measurement on a per pixel basis. This method is applicable to root‐sum‐of‐squares magnitude combining, B₁‐weighted combining, and parallel imaging such as SENSE. A procedure for image reconstruction and scaling is presented, and the method for SNR measurement is validated with phantom data. Alternative methods that rely on noise only regions are not appropriate for parallel imaging where the noise level is highly variable across the field‐of‐view. The purpose of this article is to provide a nuts and bolts procedure for calculating scale factors used for reconstructing images directly in SNR units. The procedure includes scaling for noise equivalent bandwidth of digital receivers, FFTs and associated window functions (raw data filters), and array combining. Magn Reson Med, 2005. Published 2005 Wiley‐Liss, Inc.

Myocardial infarction (MI) documented by late gadolinium enhancement (LGE) has clinical and prognostic importance, but its detection is sometimes compromised by poor contrast between blood and MI. MultiContrast Delayed Enhancement (MCODE) is a technique that helps discriminate subendocardial MI from blood pool by simultaneously providing a T2-weighted image with a PSIR (phase sensitive inversion recovery) LGE image. In this clinical validation study, our goal was to prospectively compare standard LGE imaging to MCODE in the detection of MI. Imaging was performed on a 1.5 T scanner on patients referred for CMR including a LGE study. Prospective comparisons between MCODE and standard PSIR LGE imaging were done by targeted, repeat imaging of slice locations. Clinical data were used to determine MI status. Images at each of multiple time points were read on separate days and categorized as to whether or not MI was present and whether an infarction was transmural or subendocardial. The extent of infarction was scored on a sector-by-sector basis. Seventy-three patients were imaged with the specified protocol. The majority were referred for vasodilator perfusion exams and viability assessment (37 ischemia assessment, 12 acute MI, 10 chronic MI, 12 other diagnoses). Forty-six patients had a final diagnosis of MI (30 subendocardial and 16 transmural). MCODE had similar specificity compared to LGE at all time points but demonstrated better sensitivity compared to LGE performed early and immediately before and after the MCODE (p = 0.008 and 0.02 respectively). Conventional LGE only missed cases of subendocardial MI. Both LGE and MCODE identified all transmural MI. Based on clinical determination of MI, MCODE had three false positive MI’s; LGE had two false positive MI’s including two of the three MCODE false positives. On a per sector basis, MCODE identified more infarcted sectors compared to LGE performed immediately prior to MCODE (p < 0.001). While both PSIR LGE and MCODE were good in identifying MI, MCODE demonstrated more subendocardial MI’s than LGE and identified a larger number of infarcted sectors. The simultaneous acquisition of T1 and T2-weighted images improved differentiation of blood pool from enhanced subendocardial MI.