Clinical Applications of T1 Mapping

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


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.


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.


  1. Friedrich MG. There is more than shape and function. J Am Coll Cardiol 2008;52:1581-3.
  2. Moon JC, Messroghli DR, Kellman P, et al. Myocardial T1 mapping and extracellular volume quantification: a Society for Cardiovascular Magnetic Resonance (SCMR) and CMR Working Group of the European Society of Cardiology consensus statement. J Cardiovasc Magn Reson 2013;15:92.
  3. Schelbert EB, Fonarow GC, Bonow RO, Butler J, Gheorghiade M. Therapeutic targets in heart failure: refocusing on the myocardial interstitium. J Am Coll Cardiol 2014;63:2188-98.
  4. Kellman P, Wilson JR, Xue H et al. Extracellular volume fraction mapping in the myocardium, part 2: initial clinical experience. J Cardiovasc Magn Reson 2012;14:64.
  5. Treibel TA, White SK, Moon JC. Myocardial tissue characterization: histological and pathophysiological correlation. Curr Cardiovasc Imaging Rep 2014;7:9254.
  6. Salerno M, Kramer CM. Advances in parametric mapping with CMR imaging. JACC Cardiovasc Imag 2013;6:806-22.
  7. Ambale-Venkatesh B, Lima JA. Cardiac MRI: a central prognostic tool in myocardial fibrosis. Nat Rev Cardiol 2015;12:18-29.
  8. Maestrini V, Treibel TA, White SK, Fontana M, Moon JC. T1 mapping for characterization of intracellular and extracellular myocardial diseases in heart failure. Curr Cardiovasc Imaging Rep 2014;7:9287.
  9. Jellis CL, Kwon DH. Myocardial T1 mapping: modalities and clinical applications. Cardiovasc Diagn Ther 2014;4:126-37.
  10. Sado DM, Flett AS, Banypersad SM, et al. Cardiovascular magnetic resonance measurement of myocardial extracellular volume in health and disease. Heart 2012;98:1436-41.
  11. Rogers T, Yap ML, Puntmann VO. Myocardial T1 mapping: a non-invasive alternative to tissue diagnosis? Eur Heart J Cardiovasc Imaging 2015;16:108-9.
  12. Mewton N, Liu CY, Croisille P, Bluemke D, Lima JA. Assessment of myocardial fibrosis with cardiovascular magnetic resonance. J Am Coll Cardiol 2011;57:891-903.
  13. h-Ici DO, Jeuthe S, Al-Wakeel N, et al. T1 mapping in ischaemic heart disease. Eur Heart J Cardiovasc Imaging 2014;15:597-602.
  14. Ferreira VM, Piechnik SK, Dall'armellina E et al. T Mapping for the diagnosis of acute myocarditis using CMR: comparison to T-weighted and late gadolinium enhanced imaging. JACC Cardiovasc Imaging 2013;6:1048-58..
  15. Bull S, White SK, Piechnik SK, et al. Human non-contrast T1 values and correlation with histology in diffuse fibrosis. Heart 2013;99:932-7.
  16. Lee SP, Lee W, Lee JM, et al. Assessment of diffuse myocardial fibrosis by using MR imaging in asymptomatic patients with aortic stenosis. Radiology 2014;2015;274:359-69.
  17. Fontana M, Banypersad SM, Treibel TA, et al. Native T1 mapping in transthyretin amyloidosis. JACC Cardiovasc Imaging 2014;7:157-65.
  18. Karamitsos TD, Piechnik SK, Banypersad SM, et al. Noncontrast t1 mapping for the diagnosis of cardiac amyloidosis. JACC Cardiovasc Imaging 2013;6:488-97.
  19. Ugander M, Bagi PS, Oki AJ, et al. Myocardial edema as detected by pre-contrast T1 and T2 CMR delineates area at risk associated with acute myocardial infarction. JACC Cardiovasc Imaging 2012;5:596-603.
  20. Ferreira VM, Piechnik SK, Dall'Armellina E et al. Non-contrast T1-mapping detects acute myocardial edema with high diagnostic accuracy: a comparison to T2-weighted cardiovascular magnetic resonance. J Cardiovasc Magn Reson 2012;14:42.
  21. Sado DM, Maestrini V, Piechnik SK, et al. Noncontrast myocardial T mapping using cardiovascular magnetic resonance for iron overload. J Magn Reson Imaging 2014 Aug 8. [Epub ahead of print]
  22. Sado DM, White SK, Piechnik SK, et al. The identification and assessment of Anderson-Fabry disease by cardiovascular magnetic resonance non-contrast myocardial T1 mapping. Circ Cardiovasc Imaging 2013;6:392-8.
  23. Thompson RB, Chow K, Khan A, et al. T1 Mapping with CMR is highly sensitive for Fabry disease independent of hypertrophy and gender. Circ Cardiovasc Imaging 2013;6:637-45.
  24. Modell B, Khan M, Darlison M, Westwood MA, Ingram D, Pennell DJ. Improved survival of thalassaemia major in the UK and relation to T2* cardiovascular magnetic resonance. J Cardiovasc Magn Reson 2008;10:42.
  25. Arheden H, Saeed M, Higgins CB, et al. Measurement of the distribution volume of gadopentetate dimeglumine at echo-planar MR imaging to quantify myocardial infarction: comparison with 99mTc-DTPA autoradiography in rats. Radiology 1999;211:698-708.
  26. Poole-Wilson PA. The Intracellular pH, Potassium and Electrolyte Content of Heart Muscle in Acidosis and Alkalosis. London: University of Cambridge, 1975.
  27. Brading AF, Jones AW. Distribution and kinetics of CoEDTA in smooth muscle, and its use as an extracellular marker. J Physiol 1969;200:387-401.
  28. Jerosch-Herold M, Sheridan DC, Kushner JD, et al. Cardiac magnetic resonance imaging of myocardial contrast uptake and blood flow in patients affected with idiopathic or familial dilated cardiomyopathy. Am J Physiol Heart Circ Physiol 2008;295:H1234-H1242.
  29. Flett AS, Hayward MP, Ashworth MT, et al. Equilibrium contrast cardiovascular magnetic resonance for the measurement of diffuse myocardial fibrosis: preliminary validation in humans. Circulation 2010;122:138-44.
  30. Miller CA, Naish J, Bishop P, et al. Comprehensive validation of cardiovascular magnetic resonance techniques for the assessment of myocardial extracellular volume. Circ Cardiovasc Imaging 2013;6:373-83.
  31. Fontana M, White SK, Banypersad SM, et al. Comparison of T1 mapping techniques for ECV quantification. Histological validation and reproducibility of ShMOLLI versus multibreath-hold T1 quantification equilibrium contrast CMR. J Cardiovasc Magn Reson 2012;14:88.
  32. White SK, Sado DM, Fontana M et al. T1 Mapping for myocardial extracellular volume measurement by CMR: bolus only versus primed infusion technique. JACC Cardiovasc Imaging 2013;6:955-62.
  33. Aus dem Siepen F, Buss SJ, Messroghli D, et al. T1 mapping in dilated cardiomyopathy with cardiac magnetic resonance: quantification of diffuse myocardial fibrosis and comparison with endomyocardial biopsy. Eur Heart J Cardiovasc Imaging 2015;16:210-6.
  34. Schelbert EB, Testa SM, Meier CG, et al. Myocardial extravascular extracellular volume fraction measurement by gadolinium cardiovascular magnetic resonance in humans: slow infusion versus bolus. J Cardiovasc Magn Reson 2011;13:16.
  35. Liu S, Han J, Nacif MS et al. Diffuse myocardial fibrosis evaluation using cardiac magnetic resonance T1 mapping: sample size considerations for clinical trials. J Cardiovasc Magn Reson 2012;14:90.
  36. Kawel N, Nacif M, Zavodni A, et al. T1 mapping of the myocardium: Intra-individual assessment of the effect of field strength, cardiac cycle and variation by myocardial region. J Cardiovasc Magn Reson 2012;14:27.
  37. Chin CW, Semple S, Malley T, et al. Optimization and comparison of myocardial T1 techniques at 3T in patients with aortic stenosis. Eur Heart J Cardiovasc Imaging 2014;15:556-65.
  38. Kawel N, Nacif M, Zavodni A, et al. T1 mapping of the myocardium: intra-individual assessment of post-contrast T1 time evolution and extracellular volume fraction at 3T for Gd-DTPA and Gd-BOPTA. J Cardiovasc Magn Reson 2012;14:26.
  39. Dabir D, Child N, Kalra A, et al. Reference values for healthy human myocardium using a T1 mapping methodology: results from the International T1 Multicenter cardiovascular magnetic resonance study. J Cardiovasc Magn Reson 2014;16:69.
  40. Fontana M, White SK, Banypersad SM, et al. Comparison of T1 mapping techniques for ECV quantification. Histological validation and reproducibility of ShMOLLI versus multibreath-hold T1 quantification equilibrium contrast CMR. J Cardiovasc Magn Reson 2012;14:88.
  41. Sibley CT, Noureldin RA, Gai N, et al. T1 Mapping in cardiomyopathy at cardiac MR: comparison with endomyocardial biopsy. Radiology 2012;265:724-32.
  42. Iles LM, Ellims AH, Llewellyn H, et al. Histological validation of cardiac magnetic resonance analysis of regional and diffuse interstitial myocardial fibrosis. Eur Heart J Cardiovasc Imaging 2014.
  43. Iles L, Pfluger H, Phrommintikul A, et al. Evaluation of diffuse myocardial fibrosis in heart failure with cardiac magnetic resonance contrast-enhanced T1 mapping. J Am Coll Cardiol 2008;52:1574-80.
  44. Weber KT, Brilla CG. Pathological hypertrophy and cardiac interstitium. Fibrosis and renin-angiotensin-aldosterone system. Circulation 1991;83:1849-65.
  45. Swynghedauw B. Molecular mechanisms of myocardial remodeling. Physiol Rev 1999;79:215-62.
  46. Mann DL, Barger PM, Burkhoff D. Myocardial recovery and the failing heart: myth, magic, or molecular target? J Am Coll Cardiol 2012;60:2465-72.
  47. Wynn TA, Ramalingam TR. Mechanisms of fibrosis: therapeutic translation for fibrotic disease. Nat Med 2012;18:1028-40.
  48. Kong P, Christia P, Frangogiannis NG. The pathogenesis of cardiac fibrosis. Cell Mol Life Sci 2014;71:549-74.
  49. Wong TC, Piehler K, Meier CG, et al. Association between extracellular matrix expansion quantified by cardiovascular magnetic resonance and short-term mortality. Circulation 2012;126:1206-16.
  50. Wong TC, Piehler K, Kang IA, et al. Myocardial extracellular volume fraction quantified By cardiovascular magnetic resonance is increased in diabetes and associated with mortality and incident heart failure admission. Eur Heart J 2014;35:657-64.
  51. Tamarappoo BK, John BT, Reinier K, et al. Vulnerable myocardial interstitium in patients with isolated left ventricular hypertrophy and sudden cardiac death: a postmortem histological dvaluation J Am Heart Assoc 2012;1:e001511.
  52. Zannad F, Alla F, Dousset B, Perez A, Pitt B. Limitation of excessive extracellular matrix turnover may contribute to survival benefit of spironolactone therapy in patients with congestive heart failure: insights from the randomized aldactone evaluation study (RALES). Rales Investigators. Circulation 2000;102:2700-6.
  53. Schwartzkopff B, Brehm M, Mundhenke M, Strauer BE. Repair of coronary arterioles after treatment with perindopril in hypertensive heart disease. Hypertension 2000;36:220-5.
  54. Brilla CG, Funck RC, Rupp H. Lisinopril-mediated regression of myocardial fibrosis in patients with hypertensive heart disease. Circulation 2000;102:1388-93.
  55. Diez J, Querejeta R, Lopez B, Gonzalez A, Larman M, Martinez Ubago JL. Losartan-dependent regression of myocardial fibrosis is associated with reduction of left ventricular chamber stiffness in hypertensive patients. Circulation 2002;105:2512-7.
  56. Izawa H, Murohara T, Nagata K et al. Mineralocorticoid receptor antagonism ameliorates left ventricular diastolic dysfunction and myocardial fibrosis in mildly symptomatic patients with idiopathic dilated cardiomyopathy: a pilot study. Circulation 2005;112:2940-5.
  57. Schelbert EB, Piehler KM, Zareba KM, et al. Extracellular matric expansion in non-infarcted myocardium is associated with subsequent death, hospitalization for heart failure, or both across the ejection fraction spectrum (Abstract). J Am Coll Cardiol 2014;63:A1007.
  58. Wong TC, Piehler KM, Kellman P, Schelbert EB. Extracellular matrix expansion is more strongly associated with cardiovascular outcomes than left ventricular mass. J Am Coll Cardiol 2014;63:A986.
  59. Mongeon FP, Jerosch-Herold M, Coelho-Filho OR, Blankstein R, Falk RH, Kwong RY. Quantification of extracellular matrix expansion by CMR in infiltrative heart disease. JACC Cardiovasc Imag 2012;5:897-907.
  60. Robbers LF, Baars EN, Brouwer WP et al. T1 mapping shows increased extracellular matrix size in the myocardium due to amyloid depositions. Circ Cardiovasc Imaging 2012;5:423-6.
  61. Banypersad SM, Sado DM, Flett AS et al. Quantification of Myocardial Extracellular Volume Fraction in Systemic AL Amyloidosis: An Equilibrium Contrast Cardiovascular Magnetic Resonance Study. Circ Cardiovasc Imag 2012;6:34-9.
  62. Barison A, Aquaro GD, Pugliese NR, et al. Measurement of myocardial amyloid deposition in systemic amyloidosis: insights from cardiovascular magnetic resonance imaging. J Intern Med 2014.
  63. Puntmann VO, Voigt T, Chen Z, et al. Native T1 mapping in differentiation of normal myocardium from diffuse disease in hypertrophic and dilated cardiomyopathy. JACC Cardiovasc Imag 2013;6:475-84.
  64. Flett AS, Sado DM, Quarta G, et al. Diffuse myocardial fibrosis in severe aortic stenosis: an equilibrium contrast cardiovascular magnetic resonance study. Eur Heart J Cardiovasc Imag 2012;13:819-26.
  65. Su MY, Lin LY, Tseng YH, et al. CMR-Verified Diffuse Myocardial Fibrosis Is Associated With Diastolic Dysfunction in HFpEF. JACC Cardiovasc Imag 2014;7:991-7.
  66. Mascherbauer J, Marzluf BA, Tufaro C, et al. Cardiac magnetic resonance postcontrast T1 time is associated with outcome in patients with heart failure and preserved ejection fraction. Circ Cardiovasc Imag 2013;6:1056-65.
  67. van Heerebeek L, Borbely A, Niessen HW, et al. Myocardial structure and function differ in systolic and diastolic heart failure. Circulation 2006;113:1966-73.

Clinical Topics: Heart Failure and Cardiomyopathies, Valvular Heart Disease, Vascular Medicine, Lipid Metabolism, Acute Heart Failure, Heart Failure and Cardiac Biomarkers

Keywords: Amyloidogenic Proteins, Amyloidosis, Anemia, Aortic Valve Stenosis, Biological Markers, 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

< Back to Listings