Abstract Body (Do not enter title and authors here): Background- The identification of chronic myocardial infarction (MI) typically relies on contrast-enhanced MRI, late-gadolinium enhancement (LGE) MRI. Native (contrast-free) T1 mapping at 3T has been shown to identify chronic MI but visualization of it is more difficult compared to LGE MRI. Data-driven utilization of distinctive native T1-weighted MRI signal intensity patterns in infarcted and remote myocardium may be a superior alternative to standard native-T1 mapping. We hypothesized that native T1-weighted signal intensity patterns can be used to generate images of chronic MI with similar contrast-to-noise ratio (CNR) to LGE MRI. We tested this hypothesis using a data-driven approach applied to native T1-weighted signal patterns of chronic MI and compared the resulting CNR to the CNRs of LGE and native T1 maps at 3T.

Methods- The study included a dataset of spatially aligned short-axis, native-T1-weighted and LGE images of hearts from canine (n=24) with surgically implemented chronic MI. Unsupervised clustering techniques (self-organizing maps and t-distributed stochastic neighbor embedding) were used to analyze the T1-weighted images to arrive at native T1-weighted pixel intensity patterns. Data-driven native mapping (DNM) utilizing deep neural networks were used to map these patterns to corresponding pixels in LGE images. This allowed for creation of visually enhanced maps with improved chronic MI contrast. Pearson correlation analysis compared DNM with standard T1 maps.

Results- Native T1-weighted images showed distinct pixel intensity patterns between infarcted and remote myocardium. CNR from DNM (mean ± SD, 15.01±2.88) was significantly higher than native T1 maps (5.64±1.58, p<0.001) but not different from LGE images (15.51±2.43, p=0.40). Infarcted areas in LGE images correlated more strongly with DNM (R²=0.85) than with native T1 maps (R²=0.71, p<0.001).

Conclusion- Native T1-weighted pixels contain information that can be extracted using the DNM approach to enhance image contrast between infarcted and remote myocardium. The proposed approach allows for robust visualization of chronic infarct territories without contrast agents, offering a viable contrast-agent-free alternative to LGE MRI. Patient studies are needed for clinical translation.