Robotically assisted transcranial Doppler with artificial intelligence for assessment of cerebral vasospasm after subarachnoid hemorrhage
| Title: | Robotically assisted transcranial Doppler with artificial intelligence for assessment of cerebral vasospasm after subarachnoid hemorrhage |
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| Authors: | Shooka Esmaeeli, Courtney M. Hrdlicka, Andres Brenes Bastos, Jeffrey Wang, Santiago Gomez-Paz, Khalid A. Hanafy, Vasileios-Arsenios Lioutas, Christopher S. Ogilvy, Ajith J. Thomas, Shahzad Shaefi, Corey R. Fehnel, Ala Nozari |
| Source: | Journal of Neurocritical Care, Vol 13, Iss 1, Pp 32-40 (2020) |
| Publisher Information: | The Korean Neurocritical Care Society, 2020. |
| Publication Year: | 2020 |
| Collection: | LCC:Neurology. Diseases of the nervous system |
| Subject Terms: | vasospasm, intracranial, subarachnoid hemorrhage, middle cerebral artery, ultrasonography, doppler, transcranial, anterior cerebral artery, artificial intelligence, Neurology. Diseases of the nervous system, RC346-429 |
| More Details: | Background Transcranial Doppler (TCD) ultrasound is an essential tool for the detection of cerebral vasospasm after subarachnoid hemorrhage (SAH) but is limited by the availability of skilled operators. We examined the clinical feasibility and concordance of a robotically assisted TCD system with artificial intelligence with routine handheld TCD after SAH. Methods We evaluated TCD velocities in the anterior cerebral artery (ACA) and middle cerebral artery (MCA) of two patients with high-grade SAH and angiographic evidence of vasospasm. A single channel TCD device with a handheld diagnostic probe as well as a robotically assisted TCD device was used, the relationship of the two tests was evaluated using the bootstrap method of resampling for the concordance correlation coefficient (CCC) paired with a Pearson’s correlation analysis, followed by a Bland-Altman plot. Results Patient 1 developed angiographic and TCD evidence of vasospasm in the proximal right MCA, but except for periods of disorientation remained neurologically intact. Angiographic, TCD and clinical evidence of ACA spasm occurred 6 days after ictus in patient 2. Robotically measured mean flow velocities were comparable to manual TCDs in the MCAs (CCC=0.83; 95% confidence interval [CI], 0.42 to 0.96; P=0.001) but not in the ACAs (CCC=0.26; 95% CI, –0.01 to 0.71; P=0.26). Conclusion Robotically assisted TCD system with artificial intelligence provides an alternative to manual TCD for assessment of MCA velocities in patients with SAH, expanding the availability of TCD to settings in which specialized clinicians are not available. Further studies for validation of this technology are warranted. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English Korean |
| ISSN: | 2005-0348 2508-1349 |
| Relation: | http://www.e-jnc.org/upload/pdf/jnc-200002.pdf; https://doaj.org/toc/2005-0348; https://doaj.org/toc/2508-1349 |
| DOI: | 10.18700/jnc.200002 |
| Access URL: | https://doaj.org/article/b76efd36de014a0698abcc902692f2af |
| Accession Number: | edsdoj.b76efd36de014a0698abcc902692f2af |
| Database: | Directory of Open Access Journals |
| ISSN: | 20050348 25081349 |
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| DOI: | 10.18700/jnc.200002 |
| Published in: | Journal of Neurocritical Care |
| Language: | English Korean |