Clinical Applications of T1 Mapping

Feb 13, 2015   |  Erik B. Schelbert, MD, FACC; Timothy C. Wong, MD, FACC

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T1 mapping and extracellular volume fraction (ECV) measures enable clinicians and researchers to noninvasively measure changes in myocardial tissue composition that have important implications for both diagnosis and prognosis. Historically, clinicians have relied on changes in cardiac function and shape to distinguish health and disease given the technical limitations of cardiac imaging.1 Now, with the evolution of technology, T1 mapping and ECV mapping can quantify global and regional perturbations in myocardial structure occurring at the microscopic level that offer new dimensions to distinguish health and disease, especially when the context of a clinical scenario is known.2 Advances in knowledge about myocardial tissue composition could ultimately change paradigms of cardiac vulnerability.3 Yet, despite the recent rapid and encouraging progress in the field, the role of T1 mapping in clinical care is still evolving which has been reviewed in several publications.2-13

Definitions

T1 is a parameter that describes how quickly protons recover in the z-axis after being "flipped" by a radiofrequency pulse ("longitudinal" or "spin-lattice" recovery of magnetization). This process is summarized by an exponential time constant, T1, that governs the nonlinear rate of recovery. The T1 value is derived from the mathematical fitting of curve of the individual data points, which are specifically the changes in image signal intensity that vary with the time interval between RF pulse and image acquisition. The general term T1 "mapping" specifically refers to information derived from the ability of cardiovascular magnetic resonance (CMR) to measure myocardial T1 relaxation time (and whole blood T1) on a pixelwise basis. Thus, every pixel on a T1 map encodes an absolute T1 value. This feature is distinct from T1 weighted imaging. T1 weighted imaging detects only regional differences (i.e., spatial heterogeneity) in myocardial tissue composition,4,14 a limitation that also applies to late gadolinium enhancement imaging (LGE). In contrast, any abnormality on T1 mapping – whether global or regional – is determined by comparison to reference values expressed in units of time (e.g., milliseconds), not solely by regional heterogeneity of bright versus dark areas within the weighted image that are expressed in arbitrary units. The "ideal" method to measure T1 remains a subject of active investigation.2

Increased Native T1

A key advantage of native T1 mapping (without the use of gadolinium [Gd] contrast) is that one can exploit its "parametric" nature to detect focal and diffuse disease processes, intracellular or interstitial, whether acute or chronic. Myocardial "native T1" increases with myocardial water content or edema. Such changes may follow acute insults such as recent myocardial infarction or acute myocarditis which can mimic myocardial infarction in terms of its clinical presentation. Native T1 can be useful in the evaluation of chest pain syndromes and identify focal areas of acute myocardial injury without the need for Gd.

T1 mapping can also detect more diffuse disease processes, whether acute or chronic. If reference ranges are carefully established for a given T1 mapping protocol, native T1 can detect global myocardial injury (e.g., diffuse acute myocarditis or even chronic systemic capillary leak syndrome), which is generally not possible with T1 weighted or T2 weighted imaging.4,14 Beyond acute myocardial insults, native T1 may also increase with chronic conditions such as fibrosis15,16 or amyloidosis.17,18 Although edema is challenging to validate histologically, preliminary data suggest that native T1 mapping appears just as robust as T2 mapping19 or T2 weighted imaging20 for the detection and quantification of myocardial edema.

Like many cardiac parameters, abnormalities in native T1 need to be interpreted within the clinical context, because edema, fibrosis, and amyloidosis can all increase native T1 values. Nonetheless, T1 mapping appears promising because the clinical context is usually known. Investigation into the diagnostic and prognostic performance of native T1 is ongoing.

Decreased Native T1

Novel, landmark work suggests that low T1 appears sensitive and specific for detecting myocardial accumulation of iron in siderotic disease21 or glycosphyngolipid in Anderson-Fabry disease.22,23 These advances appear to advance diagnostic capabilities of CMR significantly. Given their ability to diagnose and quantify disease burden, native T1 mapping data in this population may refine prognostic capabilities, but such data have not yet been published. Yet, T1 mapping may follow the precedent set by T2* (star) measurement techniques for myocardial iron quantification that appear to have lowered mortality in thallasemia patients. The introduction of T2* CMR in 1999 allowed one to identify myocardial siderosis and adjust iron chelation treatment, with resultant improvement of mortality rates from due to cardiac iron overload.24 This scenario illustrates a case in which the fundamental promise of CMR – to match the right treatment to the right patient – appears to have been realized. T1 mapping might have the potential to deliver similar results in the future.

Extracellular Volume Fraction (EVC)

Beyond native T1 mapping, one can use Gd contrast as an extracellular space or interstitial space marker to compute the ECV. ECV measures require myocardial T1 and whole blood T1 before and after administration of Gd contrast agents (of note, an off label use) as well as the hematocrit.25-27 ECV is a quantitative measure of the volume percent of interstitial space that also includes the intramyocardial vasculature which is estimated to be ~4.5%.28 ECV simply reflects the relative myocardial uptake of contrast relative to plasma. ECV measures assume equilibration of Gd between extravascular interstitial fluid and intravascular plasma without any intravascular protein binding that would prevent free dispersion of contrast between these extracellular compartments.

Importantly, in the absence of edema or amyloidosis, ECV is a robust measure of myocardial fibrosis. ECV exhibits high agreement with histologic measures of myocardial collagen content, which have been validated repeatedly.29-33 ECV is also reproducible34-37 although cross vendor issues and varying degrees of Gd dose dependence have been observed.30,34,38,39 ECV measures are more reproducible37 and exhibits better agreement with histologic measures of the collagen volume fraction than isolated post contrast T1 measures. ECV–histology R2 values29,30,32,33,40 range between 0.69-0.90 compared to R2 ranges of 0.32-0.61 for isolated post contrast T1 measures.41-43 These results are not surprising given that post contrast T1 values may be confounded by variations in weight based gadolinium contrast dosing (e.g., obesity), renal clearance, time elapsed between contrast bolus and T1 measurement, and displacement of contrast by the hematocrit (e.g., anemia).

Conceptually, ECV allows one to dichotomize the myocardium into its cellular compartment (mostly myocytes) and interstitial compartment (mostly collagen, but also amyloid protein or edema depending on the clinical scenario). Myocardial fibrosis is an important modifiable "intermediate phenotype" of pathologic remodeling44-48 that indicates vulnerability to adverse outcomes49-52 and potentially treatable interstitial heart disease.53-56 Antifibrotic medications appear to improve outcomes.23 Myocardial fibrosis is a final common disease pathway from a variety of potential insults. Preliminary ECV outcomes data, where ECV measures fibrosis in noninfarcted myocardium, provide intriguing results about the ability of ECV to improve risk stratification57 and identify therapeutic targets.3 Based on single-center data, ECV is associated with mortality or hospitalization for heart failure more so than ejection fraction or disease exposure category (e.g., diabetes).49,50 Myocardial ECV appears to predict outcomes better than left ventricular mass (i.e., a left ventricular myocardial "quality versus quantity" issue).58 ECV appears more strongly associated with outcomes than LGE measures of nonischemic myocardial scar.50 ECV may improve the classification of individual patients at risk and provided added prognostic value beyond age, gender, renal function, myocardial infarction size, ejection fraction, and heart failure stage.57 Interestingly, cardiac amyloidosis yields higher values of ECV than myocardial fibrosis which renders it a promising diagnostic tool and potential prognostic tool for cardiac amyloidosis.32,59-62

Overlap of T1 or ECV Across Patient Groups for Diagnosis vs. Prognosis

Despite the promise of emerging native T1 and ECV data, concern may arise when the distributions of ECV or other T1 data overlap according to a disease classification scheme (e.g., dilated cardiomyopathy33,63) or a disease "exposure variable" such as aortic stenosis,37,64 diabetes,50 heart failure with or without preserved ejection fraction,65,66 etc. For diagnostic purposes, this concern is valid, and overlapping distributions pose limitations for use of native T1 or ECV as a diagnostic tool specifically for that the classification scheme or disease "exposure variable" in which distributions overlap. To put this issue into context, it is expected that the myocardial "response" to a given stimulus or disease state measured by T1 mapping may overlap across disease categories. As an example, the spectrum of myocardial fibrosis measured by histology, is known to vary across individuals,30,33,64,67 reflected in the robust histologic validation data for ECV.29-33 Indeed, the regulation of myocardial collagen metabolism is not well understood.3

For prognostic purposes, however, it must be emphasized that outcomes data are the final arbiter of what constitutes eventual vulnerability to the patient among the various parameters that become deranged in the genesis of various disease states. One might be misled to assume that any overlap of ECV (or other T1 data) between disease categories limits its clinical assessment of vulnerability, but such an assumption is false without ascertainment of subsequent event rates, which undoubtedly represent the gold standard for vulnerability. Overlap of myocardial fibrosis across disease categories does not relegate its status as a biologically and prognostically meaningful biomarker – especially given the robust histological validation29-33 and high reproducibility.34-36 On the contrary, it may be that ECV measures of myocardial fibrosis may be the critical determinant of vulnerability rather than a patient's disease category or classification (e.g., diabetes50). Outcomes data are necessary to understand these issues, and ultimately inform paradigms of disease. Preliminary data demonstrating that ECV can improve the classification of individual patients at risk and provide added prognostic value beyond age, gender, renal function, myocardial infarction size, ejection fraction, and heart failure stage suggest added prognostic value, despite any overlap in disease category or classification scheme.57 Outcomes T1 mapping and ECV mapping data are undoubtedly forthcoming in emerging work.

Conclusion

T1 and ECV mapping are providing new insights into myocardial disease. T1 is sensitive to myocardial processes that can affect the myocyte or interstitial compartment. ECV detects expansion of the extracellular compartment (typically fibrosis but also amyloidosis and edema, depending on the clinical context). Emerging work suggests that T1 mapping and ECV mapping have the potential to improve the diagnosis of disease and refine risk stratification. Ultimately, T1 mapping and ECV mapping may improve care by matching the right therapy to each patient, but further work is needed.

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Keywords: Amyloidogenic Proteins, Amyloidosis, Anemia, Aortic Valve Stenosis, Biomarkers, Capillary Leak Syndrome, Cardiomyopathies, Cardiomyopathy, Dilated, Chest Pain, Cicatrix, Collagen, Contrast Media, Cost of Illness, Cost of Illness, Diabetes Mellitus, Edema, Extracellular Fluid, Extracellular Space, Fabry Disease, Gadolinium, Heart Failure, Hematocrit, Iron, Iron Overload, Magnetic Resonance Spectroscopy, Myocardial Infarction, Myocarditis, Myocardium, Obesity, Off-Label Use, Phenotype, Protein Binding, Protons, Siderosis, Water, Reproducibility of Results, Reference Values


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