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Lim J, Aguirre AO, Rattani A, Baig AA, Monteiro A, Kuo CC, Siddiqi M, Im J, Housley SB, McPheeters MJ, Ciecierska SSK, Jaikumar V, Vakharia K, Davies JM, Snyder KV, Levy EI, Siddiqui AH. Thrombectomy outcomes for acute ischemic stroke in lower-middle income countries: A systematic review and analysis. World Neurosurg X 2024; 23:100317. [PMID: 38511159 PMCID: PMC10950731 DOI: 10.1016/j.wnsx.2024.100317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 02/21/2024] [Indexed: 03/22/2024] Open
Affiliation(s)
- Jaims Lim
- Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
- Department of Neurosurgery, Gates Vascular Institute at Kaleida Health, Buffalo, NY, USA
| | - Alexander O. Aguirre
- Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
| | - Abbas Rattani
- Department of Radiation Oncology, Tufts University Medical Center, Boston, MA, USA
| | - Ammad A. Baig
- Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
- Department of Neurosurgery, Gates Vascular Institute at Kaleida Health, Buffalo, NY, USA
| | - Andre Monteiro
- Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
- Department of Neurosurgery, Gates Vascular Institute at Kaleida Health, Buffalo, NY, USA
| | - Cathleen C. Kuo
- Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
| | - Manhal Siddiqi
- Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
| | - Justin Im
- Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
| | - Steven B. Housley
- Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
- Department of Neurosurgery, Gates Vascular Institute at Kaleida Health, Buffalo, NY, USA
| | - Matthew J. McPheeters
- Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
- Department of Neurosurgery, Gates Vascular Institute at Kaleida Health, Buffalo, NY, USA
| | | | - Vinay Jaikumar
- Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
- Department of Neurosurgery, Gates Vascular Institute at Kaleida Health, Buffalo, NY, USA
| | - Kunal Vakharia
- Department of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL, USA
| | - Jason M. Davies
- Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
- Department of Neurosurgery, Gates Vascular Institute at Kaleida Health, Buffalo, NY, USA
- Department of Bioinformatics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, USA
- Jacobs Institute, Buffalo, NY, USA
| | - Kenneth V. Snyder
- Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
- Department of Neurosurgery, Gates Vascular Institute at Kaleida Health, Buffalo, NY, USA
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, USA
- Jacobs Institute, Buffalo, NY, USA
| | - Elad I. Levy
- Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
- Department of Neurosurgery, Gates Vascular Institute at Kaleida Health, Buffalo, NY, USA
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, USA
- Jacobs Institute, Buffalo, NY, USA
- Department of Radiology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
| | - Adnan H. Siddiqui
- Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
- Department of Neurosurgery, Gates Vascular Institute at Kaleida Health, Buffalo, NY, USA
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, USA
- Jacobs Institute, Buffalo, NY, USA
- Department of Radiology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
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Santo BA, Ciecierska SSK, Mousavi Janbeh Sarayi SM, Jenkins TD, Baig AA, Monteiro A, Koenigsknecht C, Pionessa D, Gutierrez L, King RM, Gounis M, Siddiqui AH, Tutino VM. Tectonic infarct analysis: A computational tool for automated whole-brain infarct analysis from TTC-stained tissue. Heliyon 2023; 9:e14837. [PMID: 37025889 PMCID: PMC10070917 DOI: 10.1016/j.heliyon.2023.e14837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 03/06/2023] [Accepted: 03/20/2023] [Indexed: 03/29/2023] Open
Abstract
Background Infarct volume measured from 2,3,5-triphenyltetrazolium chloride (TTC)-stained brain slices is critical to in vivo stroke models. In this study, we developed an interactive, tunable, software that automatically computes whole-brain infarct metrics from serial TTC-stained brain sections. Methods Three rat ischemic stroke cohorts were used in this study (Total n = 91 rats; Cohort 1 n = 21, Cohort 2 n = 40, Cohort 3 n = 30). For each, brains were serially-sliced, stained with TTC and scanned on both anterior and posterior sides. Ground truth annotation and infarct morphometric analysis (e.g., brain-Vbrain, infarct-Vinfarct, and non-infarct-Vnon-infarct volumes) were completed by domain experts. We used Cohort 1 for brain and infarct segmentation model development (n = 3 training cases with 36 slices [18 anterior and posterior faces], n = 18 testing cases with 218 slices [109 anterior and posterior faces]), as well as infarct morphometrics automation. The infarct quantification pipeline and pre-trained model were packaged as a standalone software and applied to Cohort 2, an internal validation dataset. Finally, software and model trainability were tested as a use-case with Cohort 3, a dataset from a separate institute. Results Both high segmentation and statistically significant quantification performance (correlation between manual and software) were observed across all datasets. Segmentation performance: Cohort 1 brain accuracy = 0.95/f1-score = 0.90, infarct accuracy = 0.96/f1-score = 0.89; Cohort 2 brain accuracy = 0.97/f1-score = 0.90, infarct accuracy = 0.97/f1-score = 0.80; Cohort 3 brain accuracy = 0.96/f1-score = 0.92, infarct accuracy = 0.95/f1-score = 0.82. Infarct quantification (cohort average): Vbrain (ρ = 0.87, p < 0.001), Vinfarct (0.92, p < 0.001), Vnon-infarct (0.80, p < 0.001), %infarct (0.87, p = 0.001), and infarct:non-infact ratio (ρ = 0.92, p < 0.001). Conclusion Tectonic Infarct Analysis software offers a robust and adaptable approach for rapid TTC-based stroke assessment.
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