Preamble
General recommendations
Left ventricular chamber assessment
Visual analysis
Quantitative analysis
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Single long-axis equation: LV volume = 0.85 × (LV-area)2/ LV-length. This is typically performed using a 4-chamber view with calculations of LV volume obtained on both end-diastolic and end-systolic phases. LV area is the planimetered area of the LV cavity from an endocardial contour with the base drawn as a straight line through the medial and lateral aspects of the mitral annulus. LV length is the linear dimension from the midpoint of the mitral annular line to the apical tip of the endocardial contour.
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Biplane equation: LV volume = 0.85 × (LV-area1 x LV-area2) / LV length. Here, both 4-chamber (LV-area1) and 2-chamber [or vertical] (LV-area2) long-axis views are used to calculate both end-diastolic and end-systolic volumes, similar to the single long-axis equation.
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Multi-plane long axis: A series of long-axis views rotating around the central longitudinal axis of the LV is used to calculate volumes. Six views provide results that do not differ from short-axis stacks [14].
Right ventricular (RV) chamber assessment
Visual analysis
Quantitative analysis
Post-processing of myocardial perfusion imaging
Visual analysis
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Are most prominent when contrast arrives in the LV blood pool.
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Lead to a reduction in signal compared with baseline myocardial signal whereas a true perfusion defect does not show a decrease in signal compared with baseline. These subtle differences can be hard to appreciate visually. It can therefore be helpful to draw a region of interest (ROI) around the suspected artifact and display its SI-time profile.
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Persist only transiently before the peak myocardial contrast enhancement.
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Appear predominantly in the phase-encoding direction.
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Are approximately one pixel wide.Dark banding present at stress and at rest with no corresponding scar on LGE images is also indicative of an artifact [22]. Note however that differences in heart rate and baseline contrast can change the appearance and presence of dark banding between stress and rest perfusion images. Thus, absence of dark banding at rest with typical dark banding at stress should not on its own be considered diagnostic for an inducible perfusion defect.
Quantitative analysis
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Select an image from the dynamic series with good contrast between all cardiac compartments (some post-processing tools generate an average image of the series).
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Outline LV endocardial and epicardial contours on this image (manual or automated) (Fig. 3c).
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Propagate contours to all other dynamic images.
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Correct contour position for in-plane motion (some analysis packages register images prior to contours being outlined).
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Depending on the type of analysis to be performed, place a separate ROI in the LV blood pool. Preferably, the basal slice is used. Exclude papillary muscles and flow artifacts from the ROI.
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Select a reference point in the LV myocardium for segmentation (usually one of the RV insertion points) [5].
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Segment LV myocardium according to AHA classification [5]
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Generate SI / time profiles for myocardial segments +/− LV blood pool.
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Consider generating division into endocardial and epicardial layers and repeat analysis [20].
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SI may vary according to distance from coil. This can be partially corrected by using a pre-contrast proton density image or other coil sensitivity correction tools.
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No absolute measurement of myocardial blood flow given.
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It is a prerequisite for reliable quantification that data acquisition used an appropriate pulse sequence and contrast regime.
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Motion correction to correct for respiratory motion is preferable.
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Manual analysis methods require contour placement as described above for semi-quantitative analysis. Dynamic SI data are then typically exported to off-line workstations for further processing.
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Fully automated methods are becoming available, which generate pixel-wise maps of myocardial perfusion without user input.
Post-processing of late gadolinium enhancement (LGE) of the left ventricle
Visual assessment
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Noise is still detectable (nulled myocardium should not be a single image intensity).
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LGE regions are not saturated (LGE regions should not be a single image intensity).
Quantitative analysis
Research tools / quantitative analysis
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Outline endocardial and epicardial borders.
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Manual planimetry of LGE regions in each slice.
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Summation of LGE areas.
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Multiplication of total LGE area with slice thickness plus interslice gap as well as specific gravity of myocardium provides the approximate LGE mass, which can be used to calculate the ratio of LGE to total myocardial mass.
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Considered subjective.
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Adjustment for regions with intermediate signal intensities (grey zones) caused by partial volume can improve reproducibility of measurements [54].
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Manual outlining of endocardial and epicardial borders for the myocardial ROI.
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Manual selection of a normal “remote” (dark) region ROI within the myocardium to define the reference SI (mean and standard deviation, SD). This subjective approach can affect measurements.
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It is susceptible to spatial variations in surface coil sensitivity.
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Selection of a threshold between normal myocardium and LGE. The relative SNR of scar tissue versus normal myocardium can vary dependent on contrast agent type, dose and time after injection, field strength, type of sequence and other variables including the underlying injury itself. As such, there is no cutoff value which works for all situations and usually manual tracing is performed as the standard of truth. But (semi-) automated thresholding may improve reproducibility after adequate standardization. As a starting point for semiautomatic thresholding we recommend 5-SD for infarction. There is currently not enough evidence to provide a cut-off for non-ischemic LGE.
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The presence of LGE within the myocardium is then determined automatically.
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Requires manual corrections to include no-reflow zones and to exclude artifacts and LV blood pool (errors in the endocardial contour).
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Manual outlining of endocardial and epicardial borders for the myocardial ROI.
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Uses the full width of the myocardial ROI SI histogram at half the maximal signal within the scar as the threshold between normal myocardium and LGE.
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Visual determination whether LGE is present or not, and, if LGE is present, manual selection of a ROI that includes the region of “maximum” signal. This subjective selection can affect measurements.
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Is also susceptible to spatial variations in surface coil sensitivity, albeit perhaps less so than the n-SD technique [51].
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Considered more reproducible than the n-SD technique [53].
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Since the technique assumes a bright LGE core, it may be less accurate than the n-SD technique if LGE is patchy or grey [56].
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Requires manual corrections to include no-reflow zones and to exclude artifacts and LV blood pool (errors in the endocardial contour).
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As the research application(s) are evolving and consensus evidence is being accumulated, the writing group chooses to refrain from making a dedicated statement at this time regarding the optimal method for quantitative assessment of dark-blood/grey blood LGE images.
Post-processing of T1 mapping
Background
Visual analysis
Quantitative analysis
Post-processing of T2-weighted imaging
Visual analysis
Semi-quantitative analysis
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Outline LV endocardial and epicardial contours.
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For the T2 SI ratio, draw the contour for a ROI in a large area of the skeletal muscle closest to the heart and to the center of the reception field of the coil (for short axis views preferably in the M. serratus anterior [66].
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Draw the contour for a ROI in the affected area and divide the SI by that of the skeletal muscle.
Post-processing of T2 mapping
Background
Visual analysis
Quantitative analysis
Post-processing of T2* imaging
Visual analysis
Quantitative analysis
Flow image interpretation and post-processing
Background
Visual analysis
Quantitative analysis
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Net volume [ml| = antegrade volume - retrograde volume
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Regurgitant fraction [%] = (retrograde volume / antegrade volume) * 100.
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Cardiac output (liters/min = (net volume [ml] x heart rate [beats/minute])/1000) and cardiac index (cardiac output/body surface area) when integrating heart rate and body surface area (BSA)
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Regional flow to both lungs by measuring cardiac output in each branch pulmonary artery (e.g., percentage of flow to the right lung = (right pulmonary artery flow / right pulmonary artery flow + left pulmonary artery flow) Å~ 100).
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Regurgitant volumes of the atrioventricular valves may be obtained by either of 2 methods: A) direct measurement of diastolic flow across the valve and subtraction of systolic forward flow across the associated semilunar valve or B) measurement of ventricular stroke volume using cine CMR and subtraction of forward flow across the associated semilunar valve.
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Quantitative aortic regurgitant volume may be inaccurate in the presence of a large, dilated aorta. An alternative is to subtract net pulmonary artery flow or the sum of caval return from the forward flow across the aortic valve in the absence of significant aortic to pulmonary collateral flow (noting that this will be a slight overestimate as bronchial flow is ~ 5% if total aortic output) [79].
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Estimation of cardiac shunts is feasible by calculating Qp/Qs based on the stroke volume obtained by flow measurements in the pulmonary artery and at the aortic sinutubular junction. Shunts can also be quantified by direct measurement of the flow through the shunt.