1. A novel method for detecting intracranial pressure changes by monitoring cerebral perfusion via electrical impedance tomography.
- Author
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Zhu MX, Li JY, Cai ZX, Wang Y, Wang WC, Guo YT, Gao GB, Guo QD, Shi XT, and Li WC
- Subjects
- Animals, Swine, Disease Models, Animal, Neurophysiological Monitoring methods, Brain diagnostic imaging, Brain blood supply, Electric Impedance, Intracranial Hypertension diagnostic imaging, Intracranial Hypertension physiopathology, Intracranial Hypertension diagnosis, Tomography methods, Cerebrovascular Circulation physiology, Intracranial Pressure physiology
- Abstract
Background: Acute and critical neurological diseases are often accompanied with elevated intracranial pressure (ICP), leading to insufficient cerebral perfusion, which may cause severe secondary lesion. Existing ICP monitoring techniques often fail to effectively meet the demand for real-time noninvasive ICP monitoring and warning. This study aimed to explore the use of electrical impedance tomography (EIT) to provide real-time early warning of elevated ICP by observing cerebral perfusion., Methods: An intracranial hypertension model was prepared by injecting autologous un-anticoagulated blood into the brain parenchyma of twelve Landrace swine. Invasive ICP monitoring was used as a control method, and a high-precision EIT system was used to acquire and analyze the changing patterns of cerebral perfusion EIT image parameters with respect to ICP. Four EIT parameters related to cerebral perfusion were extracted from the images, and their potential application in detecting ICP elevation was analyzed., Results: When ICP increased, all EIT perfusion parameters decreased significantly (P < 0.05). When the subjects were in a state of intracranial hypertension (ICP > 22 mmHg), the correlation between EIT perfusion parameters and ICP was more significant (P < 0.01), with correlation coefficients ranging from -0.72 to -0.83. We tested the objects when they were in baseline ICP and in ICP of 15-40 mmHg. Under both circumstances, ROC curve analysis showed that the comprehensive model of perfusion parameters based on the random forest algorithm had a sensitivity and specificity of more than 90% and an area under the curve (AUC) of more than 0.9 for detecting ICP increments of both 5 and 10 mmHg., Conclusion: This study demonstrates the feasibility of using perfusion EIT to detect ICP increases in real time, which may provide a new method for real-time non-invasive monitoring of patients with increased ICP., Competing Interests: Declarations. Ethics approval and consent to participate: All experimental procedures and investigations performed during this study were ethically approved by the Animal Research Ethics Committee of the Air Force Medical University and conducted based on its guidelines on animal experiments (Ethical permission number: IACUC-20241299). Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)
- Published
- 2025
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