- Oral presentation
- Open Access
T2-mapping of ischaemia/reperfusion-injury in the in vivo mouse heart
© Bohl et al; licensee BioMed Central Ltd. 2010
- Published: 21 January 2010
- Left Ventricular Volume
- Left Coronary Artery
- Mouse Heart
- Healthy Mouse
- Basal Section
Oedema is a key feature of acute ischaemia/reperfusion (IR) injury. As such, it is a diagnostic - and potentially therapeutic - target, assessable using MRI. To date, its application in the mouse heart is limited due to the challenges associated with low SNR inherent in T2-weighting, miniscule anatomy, and rapid motion. Absolute quantification of transverse relaxation time (T2-mapping) circumvents SNR constraints and may be an alternative to T2-weighted imaging. We have therefore measured myocardial T2 in IR-mice and related T2-maps to the histological area-at-risk (AAR)
The left coronary artery (LCA) was occluded for 45 minutes followed by 24 hours of reperfusion. For histology, hearts were excised, cannulated, dye-perfused after LCA-reocclusion, and sliced. AAR was determined planimetrically (ratio of unstained to stained myocardium, %LV). Myocardial T2 was measured in healthy and IR mice (n = 5/9) on a 9.4 Tesla MR system using a double-gated spin-echo pulse-sequence (matrix 128 × 128; field-of - view 25.6 × 25.6 mm; 6-8 contiguous slices (1 mm); 8 echo-times (TE, 7-34 ms); repetition time = 1 respiratory cycle. Regions of interest (40-80 voxels) were placed in healthy (septal) and IR (anterior) myocardium. High-T2 myocardium was quantified using a semi-automated threshold tool (cut-off T2NORMAL + 1, 2 and 3 standard-deviations, SD), expressed as fraction of left ventricular volume (%LV) and the spatial extent compared with histology (n = 4). In order to improve congruence with histology, the 1SD datasets were manually corrected (1SD-c) by excluding high-T2 pixels located remotely to the LCA territory. Correlation (r2) between methods was determined.
The area-at-risk exhibits prolonged T2, likely reflecting myocardial oedema. T2-mapping can be used to identify and quantify the AAR non-invasively and without the SNR constraints impeding T2-weighted imaging. Semi-automated analysis requires a low T2-cut-off. However, accuracy can be improved by manual exclusion of remote pixels, which would otherwise be erroneously included in the threshold-measurements. This problem is most prominent in basal sections where bright flow and motion artifacts exist.
This article is published under license to BioMed Central Ltd.