Background: Mechanical revascularization has become an essential treatment for acute ischemic stroke patients. Post-treatment imaging frequently displays hyperdense regions, prompting concerns regarding possible cerebral hemorrhage. Dual-energy computed tomography (DECT), as an advanced imaging modality, offers the potential to discern between hemorrhage and harmless contrast leakage. Aim: This study aims to assess the diagnostic precision of DECT in distinguishing cerebral hemorrhage from contrast extravasation post-mechanical revascularization in acute ischemic stroke cases. Methods: A comprehensive search was performed for PubMed, EMBASE, and the Cochrane Library until January 2023. We focused on studies that focused on the diagnostic efficacy of DECT for this specific application. R software (version 4.0.3) coupled with mada package facilitated the analyses pooling metrics such as sensitivity, specificity, false-positive rate estimates, diagnostic odds ratio, and positive and negative Likelihood Ratios. These metrics were reported with a 95% Confidence Interval (CI). Results: Our analysis included 5 studies involving 241 patients. DECT demonstrated a pooled sensitivity of 94.5% (95% CI: 25.9% to 99.9%, I 2 =0%) and a specificity of 99% (95% CI: 77.3% to 100%, I 2 =0%). The false-positive rate was minimal at 1% (95% CI: 0% to 22.7%). The positive likelihood ratio was calculated as 98.94 (95% CI: 3.34 to 2929.22), while the negative likelihood ratio was 0.05 (95% CI: 0.001 to 2.21). The diagnostic odds ratio was substantial at 1795.17 (95% CI: 10.04 to 321055.24), signifying a robust performance of DECT in making the differentiation. Conclusion: While DECT manifests impressive accuracy in differentiating cerebral hemorrhage from contrast extravasation after mechanical revascularization in acute ischemic stroke cases, the wide confidence intervals signify a degree of uncertainty in these estimates. Nevertheless, given its high diagnostic metrics, DECT can substantially influence post-intervention evaluations, paving the way for more informed clinical decisions and potentially reducing patient adverse outcomes. However, further studies with larger sample sizes might help refine these diagnostic estimates.