Abstract Body (Do not enter title and authors here): Introduction Late gadolinium enhancement (LGE) is the gold standard for myocardial viability imaging, recommended by all major cardiology societies. In this study, we aimed to develop a time-efficient viability imaging technique utilizing a dynamic contrast enhancement(dDCE) model to shorten the LGE wait time, provide quantitative measures of the contrast washout procedure, and potentially enable a fast and quantitative mean for scar imaging.
Methods A canine study(n=10) was conducted on reperfused myocardial infarction(MI). A dDCE model using dynamic post-contrast T1 maps was adopted to depict the contrast washout process. dDCE maps were reconstructed using the whole dataset(dDCE_30min) and a 5-minute subset of the T1 maps(dDCE_5min). To test the dDCE models for shortening the LGE wait time, LGE_dDCE images were synthesized using the dDCE_5min maps and compared to the clinical LGE images. Remote and MI dDCE parameters on dDCE_30min and dDCE_5min maps were compared to test the model's ability to extract physiological features.
Results dDCE_30min and dDCE_5min map showed a good visuospatial difference between remote and MI(Fig. 1A) and no quantitative difference (Fig.1B). v_e and PS showed a significant elevation in MI than in remote (61.12±13.65% vs 13.43±5.00%, P=0.018; 44.62±21.40mL/g/min vs 0.42±0.55mL/g/min, P=0.018, respectively). v_p and F_p were significantly decreased in MI than in remote (4.17±2.06% vs 10.85±3.77%, P=0.02; 1.11±0.32mL/g/min vs 1.51±0.42mL/g/min, P=0.04, respectively). Representative LGE and LGE_dDCE images showed high agreement in the presence of MI (Fig. 2A). Bland-Altman analysis showed good agreement between LGE and LGE_dDCE images for the measurement of infarct area (bias, -1.74 ± 6.60 %, Fig. 2B) and transmuraltiy (bias, 1.86 ± 2.73 %, Fig. 2C). The simple liner regression showed strong correlations between LGE and LGE_dDCE images for the infarct area (R², 0.95; slope, 0.93, P<0.01; Fig. 2D) and transmurality (R², 0.97; slope, 0.93, P<0.01; Fig. 2E). ROC analysis showed that the AUC was 0.97 (95% CI: 0.94 to 1.00) (Fig. 2F). Increased lesion-blood pool contrast by 10 folds on dDCE images improved subendocardial MI detection (Fig.3).
Conclusions The developed dDCE model provides comparable viability assessment ability to the standard LGE images without the prolonged wait time and reflects MI pathophysiological changes. It shows the potential for a rapid and quantitative myocardial viability imaging protocol using cardiac magnetic resonance.