Abstract Background: Coronary artery disease (CAD) is the most common cause of death worldwide. Diagnosis of acute coro-nary syndrome (ACS) usually depends on the presenting symptoms, electrocardiographic findings, and serum level of cardiac enzymes. Cardiac magnetic resonance (CMR) can be helpful in suspected cases, with negative cardiac biomarkers and normal or indeterminate electrocardiographic findings. While late gadolinium enhancement (LGE) imaging is the current gold 'in vivo' standard to detect infarcted myocardial segments, the use of intravenous contrast can be problematic in patients with impaired renal function. Aim of Study: We aimed to explore the diagnostic accuracy of T1 and T2 mapping to detect acutely infarcted myocardial segments, using LGE images as the 'gold standard'. Patients and Methods: We retrospectivelyanalyzed CMR scans of 40 patients presenting with acute myocardial infarction acquired within 48 hours after undergoing primary percuta-neous coronary intervention. Tissue mapping values [native T1, extracellular volume (ECV), and T2] were compared between acutely infarcted and remote regions and segments, using LGE as the gold standard. ROC curve analysis was used to determine optimal cut-off values to differentiate between acutely infarcted and remote segments. Results: All tissue mapping values were significantly higher in hyperenhanced (acutely infarcted) versus remote regions/segments (p<0.001 for all). Our suggested optimal cut-off values for native T1 (1095 ms) and T2 (54 ms) to differentiate hyperenhanced segments versus remote ones showed reasonable specificities (77% and 72%) and NPVs (79% for each); however, sensitivities were generally low (55% and 63%). Applying the same cut-off values to segments with no microvascular obstruction (MVO) yielded better diagnostic accuracy compared to those with MVO. Conclusion: Native (non-contrast) tissue mapping has the potential to detect acutely infarcted myocardial segments with implications for the diagnostic pathways in patients with chronic kidney disease. However, the pseudo normalization effect of MVO lowers the diagnostic accuracy of this modality, with the need to improve currently used imaging sequences to permit their routine application in clinical practice.