Abstract
Stroke is a leading cause of morbidity and mortality worldwide, necessitating rapid and accurate diagnostic techniques to guide effective treatment strategies. Computed Tomography Perfusion (CTP) imaging has emerged as a crucial tool in stroke management, providing detailed insights into cerebral blood flow, volume, and perfusion dynamics. Unlike conventional non-contrast CT, CTP enables clinicians to differentiate salvageable brain tissue from irreversible infarction, aiding in treatment decisions such as thrombolysis and mechanical thrombectomy. This paper explores the role of CTP in predicting stroke outcomes, discussing its technical principles, clinical applications, benefits, and limitations. Additionally, recent advancements in artificial intelligence and machine learning in CTP analysis are examined. The findings highlight the growing significance of CTP imaging in optimizing stroke management and improving patient prognosis.
Citations
IRE Journals:
Ryan Ragbir
"Role of CT Perfusion Imaging in Predicting Stroke Outcomes" Iconic Research And Engineering Journals Volume 8 Issue 9 2025 Page 729-731
IEEE:
Ryan Ragbir
"Role of CT Perfusion Imaging in Predicting Stroke Outcomes" Iconic Research And Engineering Journals, 8(9)
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IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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