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The ratio of the maximum density values: a new method for predicting hemorrhagic transformation in acute ischemic stroke patients undergoing mechanical thrombectomy.
- Source :
- Frontiers in Neurology; 2024, p1-6, 6p
- Publication Year :
- 2024
-
Abstract
- Background: It is challenging yet critical to differentiate between hemorrhagic transformation (HT) and contrast extravasation on non-contrast-enhanced computed tomography (NCCT) scans following mechanical thrombectomy (MT) in patients with acute ischemic stroke. We propose a new method called the ratio of maximum density values (RMDV) to minimize the confusion of contrast extravasation and to evaluate the diagnostic significance of RMDV in predicting HT on immediate post-interventional NCCT scans. Methods: We conducted a retrospective analysis of the prospective patients' database who received MT for acute ischemic stroke caused by occlusion of the intracranial large artery and showed postinterventional cerebral hyperdensities (PCHDs) on NCCT scans immediately after MT. Based on the subsequent NCCT scans, we divided patients with PCHDs into the HT and the non-HT groups. The clinical characters and radiological details were collected and compared to the two groups. We assessed the ability of RMDV >1 to predict HT by analyzing the receiver operating characteristic curve. Results: One hundred and three patients showed PCHDs; 58 (56.31%) were classified as HT, while 45 (43.69%) were classified as non-HT. The only notable distinction between the two groups was the proportion of RMDV >1 in the HT group. The correlation between HT and RMDV >1 with an area under the curve of 0.826 (95% confidence interval, 0.739 to 0.894). The sensitivity, specificity, positive, and negative predictive values of RMDV >1 on NCCT for predicting HT were 89.66, 75.56, 82.54, and 85.00%, respectively. Conclusion: The utilization of RMDV >1 on immediate NCCT scans after MT can predict early HT with good sensitivity and specificity. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 16642295
- Database :
- Complementary Index
- Journal :
- Frontiers in Neurology
- Publication Type :
- Academic Journal
- Accession number :
- 176710938
- Full Text :
- https://doi.org/10.3389/fneur.2024.1357689