Society for Cardiovascular Magnetic Resonance reference values ("normal values") in cardiovascular magnetic resonance: 2025 update

Abstract

Quantitative assessment of morphological and functional cardiac parameters by cardiovascular magnetic resonance (CMR) is essential for research and routine clinical practice. Beyond established parameters of chamber size and function, tissue properties such as relaxation times play an increasing role. Normal reference ranges are required for interpretation of results obtained by quantitative CMR. Since the last publication of the "normal values review" in 2020 many new publications related to CMR reference values have been published, which were integrated in this update. The larger sample size provides greater statistical confidence in the estimates of upper and lower limits, and enables further partitioning, e.g., by age and ethnicity for several parameters. Previous topics were expanded by new sections.

Keywords: Cardiovascular magnetic resonance; Normal values; Reference range.

Graphical abstract

Fig. 1

Contouring of the left and right ventricle. Note that left ventricular papillary muscle mass has been isolated and added to left ventricular mass. Right ventricular papillary muscles and trabeculations were included in the right ventricular volume

Fig. 2

Measurements of left ventricular diameters obtained on cine balanced steady-state free precession images during diastole (A, B) and systole (C, D) on the four-chamber view (A, C) and short-axis view (B, D). The longitudinal diameter of the left ventricle was measured on the four-chamber view as the distance between the mitral valve plane and left ventricular apex (A, C). On the four-chamber view, the transverse diameter was defined as the distance between the septum and the lateral wall at the basal level. On the short-axis view, the transverse diameter was obtained at the level of the basal papillary muscles (B, D)

Fig. 3

Measurements of left atrial area (A2C, A4C, A3C), longitudinal (L2C, L4C), and anteroposterior (APD) diameters on the two-, four-, and three-chamber view according to reference

Fig. 4

Measurements of maximal left and right atrial volume using the Simpson’s method, obtained on a short-axis cine stack of balanced steady-state free precession images covering the atria, by contouring left (red) and right (blue) atrial borders at ventricular systole according to reference

Fig. 5

Measurements of maximal right atrial areas (red), transverse diameters (blue), and longitudinal diameters (yellow) obtained on right ventricular two-chamber view (A) and four-chamber view (B) balanced steady-state free precession images at ventricular systole according to reference . The longitudinal parameters (yellow) are obtained from the posterior wall of the right atrium to the center of the tricuspid plane and the transverse diameters (blue) are obtained perpendicular to the longitudinal parameter, at the mid level of the right atrium

Fig. 6

Example of measurement approaches for left ventricular trabeculation. (A) End-diastolic thickness (in mm) of trabeculation according to the methodology in : three slices representing base, mid, and apex were selected from within the entire left ventricular stack; trabeculated myocardial thickness was measured per slice; segment 17 excluded from analysis; authors do not clarify whether papillary muscles had been included or excluded from the trabecular measurement—in this reproduction we have excluded papillary muscles. (B) Maximal non-compacted (NC, red lines)/compacted (C, orange lines) wall thickness ratio according to the methodology in : papillary muscles that were clearly observed as compact tubular structures were not included in the measurements; measurements in mm are shown in white and the maximal NC/C parameter highlighted in blue. (C) Trabeculation mass according to the methodology in : the endocardial contour (red) was manually drawn; the trabecular contour (orange) was automatically segmented and papillary muscles (blue) that were included in the compact myocardial mass, were semi-automatically segmented; all slices of the left ventricular short-axis stack were analyzed. (D) Fractal dimension according to the methodology in : using a semi-automatic level-set segmentation with bias field correction; all slices of the left ventricular short-axis stack are analyzed except for the apical slice; fractal dimensions per slice reported in the top right corner

Fig. 7

Image of a 4D flow sequence illustrating the site of measurement of peak systolic velocity at the vena contracta level according to reference . 4D four-dimensional

Fig. 8

Measurements of mitral valve annulus diameter (red arrow) obtained on a four-chamber view (A), two-chamber view (B), and three-chamber view (C) and tricuspid valve annulus diameter (blue arrow) obtained on a four-chamber view (A) at diastole according to reference

Fig. 9

Sites of measurement of the thoracic aorta. AS aortic sinus, STJ sinotubular junction, AA ascending aorta, BCA proximal to the origin of the brachiocephalic artery, T1 between the origin of the brachiocephalic artery and the left common carotid artery, T2 between the origin of the left common carotid artery and the left subclavian artery, IR isthmic region, DA descending aorta, D thoracoabdominal aorta at the level of the diaphragm

Fig. 10

Cusp-commissure (red lines) and cusp-cusp (blue lines) measurements at the level of the aortic sinus according to reference

Fig. 11

Measurements of the diastolic diameters of the aortic annulus (red arrow), the aortic sinus (blue arrow), and the sinotubular junction (yellow arrow) on a left ventricular outflow tract view obtained with a balanced steady-state free precession sequence

Fig. 12

Measurement of aortic pulse wave velocity (PWV) according to reference . Through plane flow-measurements at the level of the pulmonary trunk cutting across both the ascending and the proximal descending aorta, just below the diaphragm perpendicular to the descending aorta and just above the bifurcation of the abdominal aorta (A). Corresponding velocity encoded images (B). PWV is subsequently calculated from the distance along the aortic centerline between measurement locations (Δx) and the foot-to-foot transit time from the resulting velocity waveforms (Δt) (C).

Fig. 13

Measurement of the dimensions of the pulmonary arteries on balanced steady-state free precession images from reference . Oblique sagittal image of the main pulmonary artery (A). The pale band in (A) shows the acquisition plane of the cross-sectional image of the main pulmonary artery in (B). Right and left pulmonary arteries on the scout image (C) with band indicating the location of cine acquisitions transecting the right (D) and left (E) pulmonary artery

Fig. 14

Measurement of the diameters of the pulmonary arteries according to reference . Diameters were measured perpendicular to the vessel on maximum-intensity projection images. The diameters of the main pulmonary artery were obtained on an axial (A) and sagittal oblique (B) view and the diameters of the proximal and distal right and left pulmonary artery were obtained on axial (A) and right and left anterior oblique (paracoronal) views (C and D), respectively

Fig. 15

Example of measuring myocardial T1-relaxation time with a region of interest (ROI) in a MOLLI 5s(3s)3s native T1 map (A), a post-GBCA (gadolinium-based contrast agent) (B) T1 map and an extracellular volume map (C). According to the SCMR guidelines for post-processing in cardiovascular magnetic resonance, for global assessment of T1-relaxation time, the ROI was drawn in the septum of a mid-cavity short-axis map, avoiding inclusion of adjacent tissue . A blood ROI was also drawn in the native T1 map and copied onto the post-GBCA map. MOLLI modified look-locker inversion-recovery, SCMR Society for Cardiovascular Magnetic Resonance

Fig. 16

Illustration of strain computation using the Harmonic Phase (HARP) tool on tagged MRI images (A-D) and from feature tracking on cine MRI images (E-H). In HARP, first a semi-automated frequency analysis of the tagged MRI image (A) is performed to identify the harmonic peaks in each of the tag directions (B), filters are then applied to isolate the peaks and obtain the corresponding phase maps from which Eulerian strain maps (C) can be computed. Subplot (D) shows the strain curve at the mid-ventricular level for an asymptomatic volunteer obtained based on tracking of the user-defined mesh (A). In feature tracking of cine MRI images, endo- and epicardial contours are drawn at end-diastole (E) or end-systole (G). A characteristic pixel pattern in the order of a few millimeters squared is identified as a template. The software then tries to discern a similar pattern in the subsequent frame from which displacement of the pixels is computed (F). This is repeated through the entire cycle to obtain displacement from which strain is computed. Subplot (H) shows the strain curve at the mid-ventricular level computed from feature tracking. The tagged and cine MRI images and the strain curves were from the same participant. MRI magnetic resonance imaging

Fig. 17

(A) The quantification of myocardial perfusion proceeds from the segmentation of images acquired during the first pass of contrast through the heart to delineate myocardial segments and a region in the center of the LV blood pool for the arterial input. This example shows one short-axis image for a mid-slice level in the left ventricle. (B) For each myocardial segment, one obtains a signal-intensity versus time curve. A useful semi-quantitative parameter for the assessment of the perfusion in a myocardial segment is the upslope, which is estimated from a fit to approximately 3-5 points during the initial myocardial contrast enhancement. (C) An analogous upslope parameter can be extracted from the first pass peak of the arterial input function. A perfusion index can be calculated from the ratio of the two upslopes as shown in the formula below panel (A), and accounts for some changes in the arterial input between rest and stress. (D) Absolute estimates of myocardial blood flow in mL/min/g can be obtained from the myocardial contrast enhancement curves and the arterial input function by fitting to a kinetic model for contrast enhancement, or, as done for this example, to estimate the myocardial impulse response by constrained deconvolution. Constraints are that the impulse response should be a monotonically decaying function of time, and requiring a relatively smooth, “regularized” impulse response. Myocardial blood flow (MBF) is estimated from the peak amplitude of the impulse response. (E) The ratio of myocardial blood flows during stress, divided by MBF at rest, provides the most accurate estimate of the coronary flow reserve. In comparison, other ratios of perfusion indices (e.g., upslope index) for stress and rest systematically underestimate the flow reserve but may still prove useful for the detection of disease, assuming that one has established the normal range of the index. LV left ventricular

Fig. 18

Position of the ¹H-MRS voxel within the interventricular septum for determination of myocardial triglyceride ratio. From Reference . MRS magnetic resonance spectroscopy