Non-Invasive Estimation of Intracranial Pressure-Derived Cerebrovascular Reactivity Using Near-Infrared Spectroscopy Sensor Technology in Acute Neural Injury: A Time-Series Analysis
The contemporary monitoring of cerebrovascular reactivity (CVR) relies on invasive intracranial pressure (ICP) monitoring which limits its application. Interest is shifting towards near-infrared spectroscopic regional cerebral oxygen saturation (rSO )-based indices of CVR which are less invasive and...
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Published in: | Sensors (Basel, Switzerland) Vol. 24; no. 2; p. 499 |
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Abstract | The contemporary monitoring of cerebrovascular reactivity (CVR) relies on invasive intracranial pressure (ICP) monitoring which limits its application. Interest is shifting towards near-infrared spectroscopic regional cerebral oxygen saturation (rSO
)-based indices of CVR which are less invasive and have improved spatial resolution. This study aims to examine and model the relationship between ICP and rSO
-based indices of CVR. Through a retrospective cohort study of prospectively collected physiologic data in moderate to severe traumatic brain injury (TBI) patients, linear mixed effects modeling techniques, augmented with time-series analysis, were utilized to evaluate the ability of rSO
-based indices of CVR to model ICP-based indices. It was found that rSO
-based indices of CVR had a statistically significant linear relationship with ICP-based indices, even when the hierarchical and autocorrelative nature of the data was accounted for. This strengthens the body of literature indicating the validity of rSO
-based indices of CVR and potential greatly expands the scope of CVR monitoring. |
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AbstractList | The contemporary monitoring of cerebrovascular reactivity (CVR) relies on invasive intracranial pressure (ICP) monitoring which limits its application. Interest is shifting towards near-infrared spectroscopic regional cerebral oxygen saturation (rSO[sub.2])-based indices of CVR which are less invasive and have improved spatial resolution. This study aims to examine and model the relationship between ICP and rSO[sub.2]-based indices of CVR. Through a retrospective cohort study of prospectively collected physiologic data in moderate to severe traumatic brain injury (TBI) patients, linear mixed effects modeling techniques, augmented with time-series analysis, were utilized to evaluate the ability of rSO[sub.2]-based indices of CVR to model ICP-based indices. It was found that rSO[sub.2]-based indices of CVR had a statistically significant linear relationship with ICP-based indices, even when the hierarchical and autocorrelative nature of the data was accounted for. This strengthens the body of literature indicating the validity of rSO[sub.2]-based indices of CVR and potential greatly expands the scope of CVR monitoring. The contemporary monitoring of cerebrovascular reactivity (CVR) relies on invasive intracranial pressure (ICP) monitoring which limits its application. Interest is shifting towards near-infrared spectroscopic regional cerebral oxygen saturation (rSO2)-based indices of CVR which are less invasive and have improved spatial resolution. This study aims to examine and model the relationship between ICP and rSO2-based indices of CVR. Through a retrospective cohort study of prospectively collected physiologic data in moderate to severe traumatic brain injury (TBI) patients, linear mixed effects modeling techniques, augmented with time-series analysis, were utilized to evaluate the ability of rSO2-based indices of CVR to model ICP-based indices. It was found that rSO2-based indices of CVR had a statistically significant linear relationship with ICP-based indices, even when the hierarchical and autocorrelative nature of the data was accounted for. This strengthens the body of literature indicating the validity of rSO2-based indices of CVR and potential greatly expands the scope of CVR monitoring.The contemporary monitoring of cerebrovascular reactivity (CVR) relies on invasive intracranial pressure (ICP) monitoring which limits its application. Interest is shifting towards near-infrared spectroscopic regional cerebral oxygen saturation (rSO2)-based indices of CVR which are less invasive and have improved spatial resolution. This study aims to examine and model the relationship between ICP and rSO2-based indices of CVR. Through a retrospective cohort study of prospectively collected physiologic data in moderate to severe traumatic brain injury (TBI) patients, linear mixed effects modeling techniques, augmented with time-series analysis, were utilized to evaluate the ability of rSO2-based indices of CVR to model ICP-based indices. It was found that rSO2-based indices of CVR had a statistically significant linear relationship with ICP-based indices, even when the hierarchical and autocorrelative nature of the data was accounted for. This strengthens the body of literature indicating the validity of rSO2-based indices of CVR and potential greatly expands the scope of CVR monitoring. The contemporary monitoring of cerebrovascular reactivity (CVR) relies on invasive intracranial pressure (ICP) monitoring which limits its application. Interest is shifting towards near-infrared spectroscopic regional cerebral oxygen saturation (rSO 2 )-based indices of CVR which are less invasive and have improved spatial resolution. This study aims to examine and model the relationship between ICP and rSO 2 -based indices of CVR. Through a retrospective cohort study of prospectively collected physiologic data in moderate to severe traumatic brain injury (TBI) patients, linear mixed effects modeling techniques, augmented with time-series analysis, were utilized to evaluate the ability of rSO 2 -based indices of CVR to model ICP-based indices. It was found that rSO 2 -based indices of CVR had a statistically significant linear relationship with ICP-based indices, even when the hierarchical and autocorrelative nature of the data was accounted for. This strengthens the body of literature indicating the validity of rSO 2 -based indices of CVR and potential greatly expands the scope of CVR monitoring. The contemporary monitoring of cerebrovascular reactivity (CVR) relies on invasive intracranial pressure (ICP) monitoring which limits its application. Interest is shifting towards near-infrared spectroscopic regional cerebral oxygen saturation (rSO2)-based indices of CVR which are less invasive and have improved spatial resolution. This study aims to examine and model the relationship between ICP and rSO2-based indices of CVR. Through a retrospective cohort study of prospectively collected physiologic data in moderate to severe traumatic brain injury (TBI) patients, linear mixed effects modeling techniques, augmented with time-series analysis, were utilized to evaluate the ability of rSO2-based indices of CVR to model ICP-based indices. It was found that rSO2-based indices of CVR had a statistically significant linear relationship with ICP-based indices, even when the hierarchical and autocorrelative nature of the data was accounted for. This strengthens the body of literature indicating the validity of rSO2-based indices of CVR and potential greatly expands the scope of CVR monitoring. The contemporary monitoring of cerebrovascular reactivity (CVR) relies on invasive intracranial pressure (ICP) monitoring which limits its application. Interest is shifting towards near-infrared spectroscopic regional cerebral oxygen saturation (rSO )-based indices of CVR which are less invasive and have improved spatial resolution. This study aims to examine and model the relationship between ICP and rSO -based indices of CVR. Through a retrospective cohort study of prospectively collected physiologic data in moderate to severe traumatic brain injury (TBI) patients, linear mixed effects modeling techniques, augmented with time-series analysis, were utilized to evaluate the ability of rSO -based indices of CVR to model ICP-based indices. It was found that rSO -based indices of CVR had a statistically significant linear relationship with ICP-based indices, even when the hierarchical and autocorrelative nature of the data was accounted for. This strengthens the body of literature indicating the validity of rSO -based indices of CVR and potential greatly expands the scope of CVR monitoring. |
Audience | Academic |
Author | Stein, Kevin Y Zeiler, Frederick A Gomez, Alwyn Ibrahim, Younis Sainbhi, Amanjyot Singh Marquez, Izabella Bergmann, Tobias J G Islam, Abrar Froese, Logan Vakitbilir, Nuray |
AuthorAffiliation | 5 Undergraduate Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0W2, Canada 7 Division of Anaesthesia, Department of Medicine, Addenbrooke’s Hospital, University of Cambridge, Cambridge CB2 0QQ, UK 6 Centre on Aging, University of Manitoba, Winnipeg, MB R3E 0W2, Canada 2 Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0W2, Canada 3 Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada; log.froese@gmail.com (L.F.); amanjyot.s.sainbhi@gmail.com (A.S.S.); vakitbir@myumanitoba.ca (N.V.); islama9@myumanitoba.ca (A.I.); steink34@myumanitoba.ca (K.Y.S.); younis.ibrahim@umanitoba.ca (Y.I.) 4 Department of Biosystems Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada; bergmant@myumanitoba.ca (T.J.G.B.); marquezi@myumanitoba.ca (I.M.) 8 Department of Clinical Neurosciences, Karolinksa |
AuthorAffiliation_xml | – name: 4 Department of Biosystems Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada; bergmant@myumanitoba.ca (T.J.G.B.); marquezi@myumanitoba.ca (I.M.) – name: 5 Undergraduate Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0W2, Canada – name: 6 Centre on Aging, University of Manitoba, Winnipeg, MB R3E 0W2, Canada – name: 3 Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada; log.froese@gmail.com (L.F.); amanjyot.s.sainbhi@gmail.com (A.S.S.); vakitbir@myumanitoba.ca (N.V.); islama9@myumanitoba.ca (A.I.); steink34@myumanitoba.ca (K.Y.S.); younis.ibrahim@umanitoba.ca (Y.I.) – name: 7 Division of Anaesthesia, Department of Medicine, Addenbrooke’s Hospital, University of Cambridge, Cambridge CB2 0QQ, UK – name: 8 Department of Clinical Neurosciences, Karolinksa Institutet, 171 77 Stockholm, Sweden – name: 1 Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0W2, Canada; frederick.zeiler@umanitoba.ca – name: 2 Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0W2, Canada |
Author_xml | – sequence: 1 givenname: Alwyn orcidid: 0000-0002-3737-2065 surname: Gomez fullname: Gomez, Alwyn organization: Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0W2, Canada – sequence: 2 givenname: Logan orcidid: 0000-0002-6076-0189 surname: Froese fullname: Froese, Logan organization: Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada – sequence: 3 givenname: Tobias J G surname: Bergmann fullname: Bergmann, Tobias J G organization: Department of Biosystems Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada – sequence: 4 givenname: Amanjyot Singh orcidid: 0000-0003-3231-5683 surname: Sainbhi fullname: Sainbhi, Amanjyot Singh organization: Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada – sequence: 5 givenname: Nuray orcidid: 0000-0003-2764-145X surname: Vakitbilir fullname: Vakitbilir, Nuray organization: Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada – sequence: 6 givenname: Abrar surname: Islam fullname: Islam, Abrar organization: Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada – sequence: 7 givenname: Kevin Y surname: Stein fullname: Stein, Kevin Y organization: Undergraduate Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0W2, Canada – sequence: 8 givenname: Izabella surname: Marquez fullname: Marquez, Izabella organization: Department of Biosystems Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada – sequence: 9 givenname: Younis surname: Ibrahim fullname: Ibrahim, Younis organization: Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada – sequence: 10 givenname: Frederick A orcidid: 0000-0003-1737-0510 surname: Zeiler fullname: Zeiler, Frederick A organization: Department of Clinical Neurosciences, Karolinksa Institutet, 171 77 Stockholm, Sweden |
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Keywords | near-infrared spectroscopy intracranial pressure monitoring neurotrauma cerebrovascular reactivity monitoring |
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SubjectTerms | Blood Brain Brain research Catheters cerebrovascular reactivity monitoring Health sciences Hematoma Humans Infrared spectroscopy Injuries Intensive care Intracranial Pressure intracranial pressure monitoring Linear algebra Medicin och hälsovetenskap near-infrared spectroscopy neurotrauma Patients Research Design Retrospective Studies Sensors Software upgrading Spectroscopy, Near-Infrared Technology Tomography Traumatic brain injury |
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Title | Non-Invasive Estimation of Intracranial Pressure-Derived Cerebrovascular Reactivity Using Near-Infrared Spectroscopy Sensor Technology in Acute Neural Injury: A Time-Series Analysis |
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