T2-prepared SSFP had higher diagnostic accuracy than T2-prepared dark-blood TSE with respect to determining the coronary artery distribution and determining whether a patient had an acute or chronic MI. In this study, relying on dark-blood TSE images yielded correct diagnoses in 82% of patients with acute MI and only 44% for chronic MI, while the T2-prepared SSFP images had 100% diagnostic accuracy. With dark-blood TSE, most of the incorrect cases could be attributed to signal loss caused by through-plane cardiac motion. The higher percentage of false-positive TSE images for the chronic MI cases was partially due to a larger number of patients with arrhythmia or large RR variation. In this study the reference standard for determing the correct assessment of edema in acute MI was based on correlation with delayed enhancement, which was compatible with the clinical presentation, including coronary angiography.
The expected difference in T2-weighted signal intensity (exp(-TE/T2)) between acute MI and normal myocardium is estimated to be on the order of 25-50% for T2 in range 45-50 ms for normal myocardium and 60-65 ms for acute MI. Therefore, signal uniformity is of paramount importance for detection of relatively small changes in T2 expected for edema. Signal uniformity is critical for determination of the size of elevated T2 region. In this regard, correction of surface-coil intensity variation is very important. Signal loss due to through-plane cardiac motion in dark-blood prepared TSE imaging reduces the reliability of this method, and while this may be mitigated to some extent by adjusting the timing of readout, it is difficult to achieve the desired level of reliability, particularly in a clinical setting with higher heart rates and significant R-R variability.
The T2-prepared SSFP approach was sensitive to small changes in T2 and had uniform signal intensity. SSFP off-resonance banding artifacts were not found to be a problem, although good shimming is desirable. Fat saturation was not used in the current study and on some occasions fat-water cancellation (particularly epicardial fat) led to dark voxels in the border between fat and myocardium due to a partial-volume effect. This could be avoided by slight center frequency adjustment (typically 50 Hz) without degrading the water signal. Importantly, unlike the signal loss in dark-blood TSE, the fat-water cancellation was easily distinguishable and could be read through, not leading to a false result. The further reduction of TR or the introduction of fat saturation would improve this situation.
The SNR of dark-blood TSE was significantly higher than the T2
-prepared SSFP due to a number of factors, such as the readout flip angle, bandwidth, and parallel imaging loss. However, our analysis indicates that signal uniformity limits accurate detection and diagnosis of acute MI— not necessarily the SNR. Given the fact that TSE has higher SNR, it would be expected that the CNR between edema and remote regions would be correspondingly higher since the TE used to set the T2
-weighted contrast was approximately the same. However, the CNR for the T2
-prepared SSFP was approximately the same as the TSE, implying that either the T2
-weighted contrast for the TSE was reduced or the cardiac motion-related signal losses contributed to a loss of contrast. The T2
-weighted contrast mechanism for TSE relies on adjusting the TE, which is determined by the phase-encode order, whereas the T2
-prepared SSFP sequence determines the TE in the T2
-preparation and uses a linear phase-encode order. The TSE method used a product sequence with TSE parameters selected approximately the same as in prior literature (1
). It is also noted that the SNR and CNR measurements in this paper were calculated by convention using the noise SD, which differs from the previous reported (1
) definition using mean noise. While the mean and SD are related for a given noise distribution, the SD is a more meaningful statistic for predicting detectability and is preferable to the mean, which depends on the number of receive coil elements.
Stagnant blood along the endocardial surface is another source of artifact in dark-blood TSE imaging (). While arguably the blood rims might be discriminated from myocardium using other images to define the endocardial border, this requires perfect breath-hold registration and adds complexity. These artifacts can further confound assessment of the size of edema regions. Although none of the false-positive cases in this study were attributed to this artifact, such artifacts may reduce the confidence particularly for apical slices. The bright signals also create a dilemma in image display since it is difficult to set a grayscale that properly covers normal myocardium, the slightly brighter acute MI, and the much brighter blood near the endocardium.
Example illustrating bright-blood artifact for dark-blood TSE image (left) resulting from stagnant blood within trabeculae along endocardial wall. The corresponding T2-prepared SSFP image (right) has no blood artifact.
Increasing the imaging slice thickness (e.g., to 15 mm (1
)) and commensurately increasing the dark-blood preparation slice thickness will reduce the effects of cardiac motion-related signal loss for dark-blood prepared TSE. The 6-mm slice thickness used in this comparison may have somewhat reduced the diagnostic accuracy of the dark-blood TSE. However, increasing the slice thickness also increases the stagnant-blood artifact (4
). Since the T2
-prepared SSFP method does not have either of these artifacts, which are caused by the dark-blood preparation, the T2
-prepared SSFP is a more robust method. The sensitivity for detection of edema with increased slice thickness will not be significantly reduced in cases with large size regions of edema. However, thicker slices will have reduced sensitivity for detecting focal areas of edema that may result in cases such as acute myocarditis or sarcoidosis (4
). In cases with a large region of edema, an increased slice thickness would improve the SNR for both dark-blood TSE and T2
-prepared SSFP methods.