1
|
Grossen AA, Evans AR, Ernst GL, Behnen CC, Zhao X, Bauer AM. The current landscape of machine learning-based radiomics in arteriovenous malformations: a systematic review and radiomics quality score assessment. Front Neurol 2024; 15:1398876. [PMID: 38915798 PMCID: PMC11194423 DOI: 10.3389/fneur.2024.1398876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Accepted: 05/21/2024] [Indexed: 06/26/2024] Open
Abstract
Background Arteriovenous malformations (AVMs) are rare vascular anomalies involving a disorganization of arteries and veins with no intervening capillaries. In the past 10 years, radiomics and machine learning (ML) models became increasingly popular for analyzing diagnostic medical images. The goal of this review was to provide a comprehensive summary of current radiomic models being employed for the diagnostic, therapeutic, prognostic, and predictive outcomes in AVM management. Methods A systematic literature review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, in which the PubMed and Embase databases were searched using the following terms: (cerebral OR brain OR intracranial OR central nervous system OR spine OR spinal) AND (AVM OR arteriovenous malformation OR arteriovenous malformations) AND (radiomics OR radiogenomics OR machine learning OR artificial intelligence OR deep learning OR computer-aided detection OR computer-aided prediction OR computer-aided treatment decision). A radiomics quality score (RQS) was calculated for all included studies. Results Thirteen studies were included, which were all retrospective in nature. Three studies (23%) dealt with AVM diagnosis and grading, 1 study (8%) gauged treatment response, 8 (62%) predicted outcomes, and the last one (8%) addressed prognosis. No radiomics model had undergone external validation. The mean RQS was 15.92 (range: 10-18). Conclusion We demonstrated that radiomics is currently being studied in different facets of AVM management. While not ready for clinical use, radiomics is a rapidly emerging field expected to play a significant future role in medical imaging. More prospective studies are warranted to determine the role of radiomics in the diagnosis, prediction of comorbidities, and treatment selection in AVM management.
Collapse
Affiliation(s)
- Audrey A. Grossen
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Alexander R. Evans
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Griffin L. Ernst
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Connor C. Behnen
- Data Science and Analytics, University of Oklahoma, Norman, OK, United States
| | - Xiaochun Zhao
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Andrew M. Bauer
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| |
Collapse
|
2
|
Wang H, Jia Q, Wang Y, Xue W, Jiang Q, Ning F, Wang J, Zhu Z, Tian L. Stacking learning based on micro-CT radiomics for outcome prediction in the early-stage of silica-induced pulmonary fibrosis model. Heliyon 2024; 10:e30651. [PMID: 38765063 PMCID: PMC11098827 DOI: 10.1016/j.heliyon.2024.e30651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 02/28/2024] [Accepted: 05/01/2024] [Indexed: 05/21/2024] Open
Abstract
Silicosis is a progressive pulmonary fibrosis disease caused by long-term inhalation of silica. The early diagnosis and timely implementation of intervention measures are crucial in preventing silicosis deterioration further. However, the lack of screening and diagnostic measures for early-stage silicosis remains a significant challenge. In this study, silicosis models of varying severity were established through a single exposure to silica with different doses (2.5mg/mice or 5mg/mice) and durations (4 weeks or 12 weeks). The diagnostic performance of computed tomography (CT) quantitative analysis was assessed using lung density biomarkers and the lung density distribution histogram, with a particular focus on non-aerated lung volume. Subsequently, we developed and evaluated a stacking learning model for early diagnosis of silicosis after extracting and selecting features from CT images. The CT quantitative analysis reveals that while the lung densitometric biomarkers and lung density distribution histogram, as traditional indicators, effectively differentiate severe fibrosis models, they are unable to distinguish early-stage silicosis. Furthermore, these findings remained consistent even when employing non-aerated areas, which is a more sensitive indicator. By establishing a radiomics stacking learning model based on non-aerated areas, we can achieve remarkable diagnostic performance to distinguish early-stage silicosis, which can provide a valuable tool for clinical assistant diagnosis. This study reveals the potential of using non-aerated lung areas as a region of interest in stacking learning for early diagnosis of silicosis, providing new insights into early detection of this disease.
Collapse
Affiliation(s)
- Hongwei Wang
- Department of Occupational and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, China
| | - Qiyue Jia
- Department of Occupational and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, China
| | - Yan Wang
- Department of Occupational and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, China
| | - Wenming Xue
- Department of Occupational and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, China
| | - Qiyue Jiang
- Department of Occupational and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, China
| | - Fuao Ning
- Department of Occupational and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, China
| | - Jiaxin Wang
- Department of Occupational and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, China
| | - Zhonghui Zhu
- Department of Occupational and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, China
| | - Lin Tian
- Department of Occupational and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, China
| |
Collapse
|
3
|
De Simone M, Fontanella MM, Choucha A, Schaller K, Machi P, Lanzino G, Bijlenga P, Kurz FT, Lövblad KO, De Maria L. Current and Future Applications of Arterial Spin Labeling MRI in Cerebral Arteriovenous Malformations. Biomedicines 2024; 12:753. [PMID: 38672109 PMCID: PMC11048131 DOI: 10.3390/biomedicines12040753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 03/22/2024] [Accepted: 03/26/2024] [Indexed: 04/28/2024] Open
Abstract
Arterial spin labeling (ASL) has emerged as a promising noninvasive tool for the evaluation of both pediatric and adult arteriovenous malformations (AVMs). This paper reviews the advantages and challenges associated with the use of ASL in AVM assessment. An assessment of the diagnostic workup of AVMs and their variants in both adult and pediatric populations is proposed. Evaluation after treatments, whether endovascular or microsurgical, was similarly examined. ASL, with its endogenous tracer and favorable safety profile, offers functional assessment and arterial feeder identification. ASL has demonstrated strong performance in identifying feeder arteries and detecting arteriovenous shunting, although some studies report inferior performance compared with digital subtraction angiography (DSA) in delineating venous drainage. Challenges include uncertainties in sensitivity for specific AVM features. Detecting AVMs in challenging locations, such as the apical cranial convexity, is further complicated, demanding careful consideration due to the risk of underestimating total blood flow. Navigating these challenges, ASL provides a noninvasive avenue with undeniable merits, but a balanced approach considering its limitations is crucial. Larger-scale prospective studies are needed to comprehensively evaluate the diagnostic performance of ASL in AVM assessment.
Collapse
Affiliation(s)
- Matteo De Simone
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, Via S. Allende, 84081 Baronissi, Italy
| | - Marco Maria Fontanella
- Division of Neurosurgery, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Piazza Spedali Civili 1, 25123 Brescia, Italy; (M.M.F.); (L.D.M.)
| | - Anis Choucha
- Department of Neurosurgery, Aix Marseille University, APHM, UH Timone, 13005 Marseille, France;
- Laboratory of Biomechanics and Application, UMRT24, Gustave Eiffel University, Aix Marseille University, 13005 Marseille, France
| | - Karl Schaller
- Division of Neurosurgery, Diagnostic Department of Clinical Neurosciences, Geneva University Hospitals (HUG), Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; (K.S.); (P.B.)
| | - Paolo Machi
- Division of Interventional Neuroradiology, Department of Radiology and Medical Informatic, Geneva University Hospitals (HUG), Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; (P.M.); (F.T.K.); (K.-O.L.)
| | - Giuseppe Lanzino
- Department of Neurosurgery and Interventional Neuroradiology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905, USA;
| | - Philippe Bijlenga
- Division of Neurosurgery, Diagnostic Department of Clinical Neurosciences, Geneva University Hospitals (HUG), Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; (K.S.); (P.B.)
| | - Felix T. Kurz
- Division of Interventional Neuroradiology, Department of Radiology and Medical Informatic, Geneva University Hospitals (HUG), Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; (P.M.); (F.T.K.); (K.-O.L.)
| | - Karl-Olof Lövblad
- Division of Interventional Neuroradiology, Department of Radiology and Medical Informatic, Geneva University Hospitals (HUG), Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; (P.M.); (F.T.K.); (K.-O.L.)
| | - Lucio De Maria
- Division of Neurosurgery, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Piazza Spedali Civili 1, 25123 Brescia, Italy; (M.M.F.); (L.D.M.)
- Division of Neurosurgery, Diagnostic Department of Clinical Neurosciences, Geneva University Hospitals (HUG), Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; (K.S.); (P.B.)
| |
Collapse
|
4
|
Zhang Y, Chen Y, Li R, Ma L, Han H, Li Z, Zhang H, Yuan K, Zhao Y, Jin W, Chen P, Zhou W, Ye X, Li Y, Wang S, Chen X, Zhao Y. Overloaded transnidal pressure gradient as the hemodynamic mechanism leading to arteriovenous malformation rupture: a quantitative analysis using intravascular pressure monitoring and color-coded digital subtraction angiography. J Neurointerv Surg 2024:jnis-2023-021348. [PMID: 38471763 DOI: 10.1136/jnis-2023-021348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 02/18/2024] [Indexed: 03/14/2024]
Abstract
BACKGROUND The hemodynamics of brain arteriovenous malformations (AVMs) may have implications for hemorrhage. This study aimed to explore the hemodynamics of ruptured AVMs by direct microcatheter intravascular pressure monitoring (MIPM) and indirect quantitative digital subtraction angiography (QDSA). METHODS We recruited patients with AVMs at a tertiary neurosurgery center from October 2020 to March 2023. In terms of MIPM, we preoperatively super-selected a predominant feeding artery and main draining vein through angiography to measure intravascular pressure before embolization. In processing of QDSA, we adopted previously standardized procedure for quantitative hemodynamics analysis of pre-embolization digital subtraction angiography (DSA), encompassing main feeding artery, nidus, and the main draining vein. Subsequently, we investigated the correlation between AVM rupture and intravascular pressure from MIPM, as well as hemodynamic parameters derived from QDSA. Additionally, we explored the interrelationships between hemodynamic indicators in both dimensions. RESULTS After strict screening of patients, our study included 10 AVMs (six ruptured and four unruptured). We found that higher transnidal pressure gradient (TPG) (53.00±6.36 vs 39.25±8.96 mmHg, p=0.042), higher feeding artery pressure (FAP) (72.83±5.46 vs 65.00±6.48 mmHg, p=0.031) and higher stasis index of nidus (3.54±0.73 vs 2.43±0.70, p=0.043) were significantly correlated with AVM rupture. In analysis of interrelationships between hemodynamic indicators in both dimensions, a strongly positive correlation (r=0.681, p=0.030) existed between TPG and stasis index of nidus. CONCLUSIONS TPG and FAP from MIPM platform and nidus stasis index from QDSA platform were correlated with AVM rupture, and both were positively correlated, suggesting that higher pressure load within nidus may be the central mechanism leading to AVM rupture.
Collapse
Affiliation(s)
- Yukun Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Neurosurgery, Peking University International Hospital, Beijing, China
| | - Yu Chen
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Ruinan Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Li Ma
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Heze Han
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhipeng Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Haibin Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Kexin Yuan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yang Zhao
- Department of Neurosurgery, Peking University International Hospital, Beijing, China
| | - Weitao Jin
- Department of Neurosurgery, Peking University International Hospital, Beijing, China
| | - Pingting Chen
- College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China
| | - Wanting Zhou
- Department of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Xun Ye
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Youxiang Li
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Beijing, China
| | - Shuo Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xiaolin Chen
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yuanli Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| |
Collapse
|
5
|
Shabani Z, Schuerger J, Zhu X, Tang C, Ma L, Yadav A, Liang R, Press K, Weinsheimer S, Schmidt A, Wang C, Sekhar A, Nelson J, Kim H, Su H. Increased Collagen I/Collagen III Ratio Is Associated with Hemorrhage in Brain Arteriovenous Malformations in Human and Mouse. Cells 2024; 13:92. [PMID: 38201296 PMCID: PMC10778117 DOI: 10.3390/cells13010092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 12/23/2023] [Accepted: 12/28/2023] [Indexed: 01/12/2024] Open
Abstract
Background: The increase in the collagen I (COL I)/COL III ratio enhances vessel wall stiffness and renders vessels less resistant to blood flow and pressure changes. Activated microglia enhance inflammation-induced fibrosis. Hypotheses: The COL I/COL III ratio in human and mouse brain arteriovenous malformations (bAVMs) is associated with bAVM hemorrhage, and the depletion of microglia decreases the COL I/COL III ratio and hemorrhage. Method: COL I, COL III, and hemorrhages were analyzed in 12 human bAVMs and 6 control brains, and mouse bAVMs induced in three mouse lines with activin receptor-like kinase 1 (n = 7) or endoglin (n = 7) deleted in the endothelial cells or brain focally (n = 5). The controls for the mouse study were no-gene-deleted litter mates. Mouse bAVMs were used to test the relationships between the Col I/Col III ratio and hemorrhage and whether the transient depletion of microglia reduces the Col I/Col III ratio and hemorrhage. Results: The COL I/COL III ratio was higher in the human and mouse bAVMs than in controls. The microhemorrhage in mouse bAVMs was positively correlated with the Col I/Col III ratio. Transient depletion of microglia reduced the Col I/Col III ratio and microhemorrhage. Conclusions: The COL I/COL III ratio in the bAVMs was associated with bAVM hemorrhage. The depletion of microglia reduced the bAVM Col I/Col III ratio and hemorrhage.
Collapse
Affiliation(s)
- Zahra Shabani
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Joana Schuerger
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Xiaonan Zhu
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Chaoliang Tang
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Li Ma
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Alka Yadav
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Rich Liang
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Kelly Press
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Shantel Weinsheimer
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Annika Schmidt
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Calvin Wang
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Abinav Sekhar
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Jeffrey Nelson
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Helen Kim
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| | - Hua Su
- Center for Cerebrovascular Research, University of California, San Francisco, CA 94143, USA; (Z.S.); (J.S.); (X.Z.); (C.T.); (L.M.); (A.Y.); (R.L.); (K.P.); (S.W.); (A.S.); (C.W.); (A.S.); (J.N.); (H.K.)
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA 94143, USA
| |
Collapse
|