Acute myocardial infarction: susceptibility-weighted cardiac MRI for the detection of reperfusion haemorrhage at 1.5 T.

AIM: To assess whether susceptibility-weighted imaging (SWI) provides better image contrast for the detection of haemorrhagic ischaemia-reperfusion injury in the heart. MATERIALS AND METHODS: Thirty patients (all men; mean age 53 years) underwent cardiac magnetic resonance imaging (MRI) within 7 days of primary percutaneous intervention for acute ST elevation myocardial infarction (STEMI). Multiple gradient-echo T2* sequences with magnitude and phase reconstructions were acquired. A high-pass filtered phase map was used to create a mask for the SWI reconstructions. The difference in image contrast was assessed in those patients with microvascular obstruction. A mixed effects regression model was used to test the effect of echo time and reconstruction method on phase and contrast-to-noise ratio (CNR). Medians and interquartile ranges (IQR) are reported. RESULTS: T2* in haemorrhagic infarcts was shorter than in non-haemorrhagic infarcts (33.5 ms [24.9-43] versus 49.9 ms [44.6-67.6]; p=0.0007). The effect of echo time on phase was significant (p<0.0001), as was the effect of haemorrhage on phase (p=0.0016). SWI reconstruction had a significant effect on the CNR at all echo times (echoes 1-5, p<0.0001; echo 6, p=0.01; echo 7, p=0.02). The median echo number at which haemorrhage was first visible was less for SWI compared to source images (echo 2 versus echo 5, p=0.0002). CONCLUSION: Cardiac SWI improves the contrast between myocardial haemorrhage and the surrounding tissue following STEMI and has potential as a new tool for identifying patients with ischaemia-reperfusion injury.

A robust single-shot partial sampling scheme.

A method of reducing the amount of data required to reconstruct an image is described. In this scheme, fully sampled low spatial frequency data are acquired up to a given cutoff frequency and above this point, only alternate lines are sampled. Two images are produced, one of low definition and one of high definition but aliased. The proposed algorithm unwraps the aliased data, which are then used to enhance the low pass image, yielding a best estimate of the true image. The reduced sampling technique is shown to afford biological images that are almost indistinguishable from those obtained from a complete data set.