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@article{173237,
        author = {Abubakar Shehu Barde and Muhammad Zeeshan and Aalia Abdullah and Ayush kumar and Ashafa Isa},
        title = {Role of MRI in Ischemic Stroke Diagnosis: A SYSTEMATIC REVIEW},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {9},
        pages = {2175-2181},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=173237},
        abstract = {Stroke has been identified among the world's leading causes of morbidity and mortality accounting for 10% of total death, mostly ischemic in nature, which is caused by arterial blockage resulting in brain tissue death because of oxygen and nutrients taken away. Magnetic resonance imaging (MRI) has become a vital tool for stroke diagnosis, especially in identifying acute Ischaemic Stroke (AIS), early diagnosis is essential for the best possible post-stroke care. CT is widely used as the first imaging modality for stroke assessment. However, stroke has a golden hours or treatment window period of which the brain tissue can be salvaged, so an imaging modality that will give detailed happening of the process by identifying the infarct core and penumbra is required for a treatment plan. A literature search has been conducted using various databases and articles published between 2010 and 2024 discussing the role of MRI in the diagnosis and treatment of ischemic stroke, the function of MRI in ischaemic stroke detection, its benefits over alternative imaging modalities, and its usage in treatment planning using advanced MRI technology, such as Diffusion-Weighted Imaging (DWI), Perfusion-Weighted Imaging (PWI), DWI-PWI mismatch, Magnetic Resonance Angiography (MRA), and the incorporation of machine learning techniques, are been reviewed. While MRI offers superior diagnostic precision, challenges such as accessibility, cost, and longer scan times remain barriers to its widespread adoption, nonetheless, MRI's ability to delineate infarct core and penumbra, combined with emerging machine learning applications, makes it an indispensable tool for improving patient outcomes in stroke care.},
        keywords = {Magnetic resonance imaging, Ischaemic stroke, Perfusion-weighted imaging, Diffusion-weighted imaging, Magnetic resonance angiography.},
        month = {February},
        }