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Article

Near-Infrared Spectroscopy Regional Oxygen Saturation Based Cerebrovascular Reactivity Assessments in Chronic Traumatic Neural Injury versus in Health: A Prospective Cohort Study

by
Alwyn Gomez
1,2,*,
Izabella Marquez
3,
Logan Froese
4,
Tobias Bergmann
3,
Amanjyot Singh Sainbhi
4,
Nuray Vakitbilir
4,
Abrar Islam
4,
Kevin Y. Stein
4,5,
Younis Ibrahim
4 and
Frederick A. Zeiler
1,4,6,7,8,9
1
Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, 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 Biosystems Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada
4
Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada
5
Undergraduate Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0W2, Canada
6
Centre on Aging, Fort Garry Campus, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
7
Division of Anaesthesia, Department of Medicine, Addenbrooke’s Hospital, University of Cambridge, Cambridge CB2 0QQ, UK
8
Department of Clinical Neurosciences, Karolinksa Institutet, 171 77 Stockholm, Sweden
9
Pan Am Clinic Foundation, Winnipeg, MB R3M 3E4, Canada
*
Author to whom correspondence should be addressed.
Bioengineering 2024, 11(4), 310; https://doi.org/10.3390/bioengineering11040310
Submission received: 21 February 2024 / Revised: 15 March 2024 / Accepted: 19 March 2024 / Published: 26 March 2024
(This article belongs to the Section Biomedical Engineering and Biomaterials)
Browse Figures
Versions Notes

Abstract

:
Near-infrared spectroscopy (NIRS) regional cerebral oxygen saturation (rSO2)-based cerebrovascular reactivity (CVR) monitoring has enabled entirely non-invasive, continuous monitoring during both acute and long-term phases of care. To date, long-term post-injury CVR has not been properly characterized after acute traumatic neural injury, also known as traumatic brain injury (TBI). This study aims to compare CVR in those recovering from moderate-to-severe TBI with a healthy control group. A total of 101 heathy subjects were recruited for this study, along with 29 TBI patients. In the healthy cohort, the arterial blood pressure variant of the cerebral oxygen index (COx_a) was not statistically different between males and females or in the dominant and non-dominant hemispheres. In the TBI cohort, COx_a was not statistically different between the first and last available follow-up or by the side of cranial surgery. Surprisingly, CVR, as measured by COx_a, was statistically better in those recovering from TBI than those in the healthy cohort. In this prospective cohort study, CVR, as measured by NIRS-based methods, was found to be more active in those recovering from TBI than in the healthy cohort. This study may indicate that in individuals that survive TBI, CVR may be enhanced as a neuroprotective measure.

1. Introduction

The management of moderate-to-severe acute biomechanical neural injury, also known as traumatic brain injury (TBI), centers around the minimization of ongoing damage through the acute phase, known as secondary injury [1,2]. A key contributor to this secondary injury is the disruption of the brain’s ability to regulate cerebral blood flow (CBF) through microvascular vasomotion in response to fluctuations in arterial blood pressure (ABP) or cerebral perfusion pressure (CPP) [3,4]. This disruption in what is known as cerebrovascular reactivity (CVR) can result in periods of relative hypoperfusion or hyperperfusion, contributing to ongoing cerebral injury [5].
Significant advancements have been made in the role of CVR monitoring in the acute phase following moderate-to-severe TBI [6,7]. This includes associations with outcomes as well as work investigating CVR-guided management [8,9,10]. This progress has been largely driven by the development of continuous indices of CVR that allow for real-time monitoring of CVR at the bedside. The most prominent of these indices is the pressure reactivity index (PRx), which evaluates the correlation of intracranial pressure (ICP) as a surrogate for cerebral blood volume (CBV), with ABP as a surrogate for driving pressure [6,7]. Since the index is generated through a continuously updating Pearson correlation between ICP and ABP, values range from −1 to +1, with lower values indicating active CVR and higher values indicating a more vasopassive state [7].
PRx is ideally suited for monitoring CVR in critically ill TBI patients where invasive ICP monitoring is already indicated. However, its reliance on this invasive surrogate of CBV restricts its utilization in the chronic recovery phase or in healthy subjects. Fortunately, entirely non-invasive means of measuring CVR continuously have been developed [11,12]. The ABP variant of the cerebral oxygen index (COx_a) leverages near-infrared spectroscopy (NIRS) regional cerebral oxygen saturation (rSO2) as a surrogate for CBV and ABP as a surrogate for driving pressure. Like PRx, it utilizes a continuously updating Pearson correlation between rSO2 and ABP. As such, it also has values that range from −1 to +1, with higher values indicating a more vasopassive state [13]. Through novel techniques that leverage commercially available non-invasive continuous ABP finger cuff technology in conjunction with clinically utilized non-invasive rSO2 monitoring systems, COx_a can be measured entirely non-invasively [11,12]. This means that by combining these technologies, COx_a is not subject to the same limitations of PRx and can be utilized to evaluate CVR in populations that would otherwise be precluded from such studies. Recent work has also found COx_a to have similar statistical properties and a linear relationship to PRx [14,15]. Additionally, as rSO2 is a regional surrogate for CBV, COx_a has the potential to have improved spatial resolution compared to PRx, which is a global measure of CVR [16].
However, one existing knowledge gap surrounding this non-invasive NIRS-based CVR assessment method is its behavior in survivors long-term post-injury, and how this compares to a healthy control cohort. This prospectively conducted cohort study aims to examine CVR in a healthy group of volunteers by leveraging the non-invasive nature of COx_a. The role of age, biological sex, and hemispheric dominance on CVR are examined. Secondly, in a cohort of surviving patients recovering from moderate-to-severe TBI, CVR measured by COx_a is examined for trends through the recovery phase and compared to baseline values established through the healthy volunteer cohort.

2. Materials and Methods

2.1. Study Population and Data Collection

This prospective study consisted of two distinct cohorts. The first group consisted of adult (18 years or older) volunteers with no known neurological or cardiovascular conditions. These participants underwent physiological data recording during a single 30-min session in the resting awake state without any provocative testing. Data were collected between June 2020 and May 2023. Additionally, demographic information, such as age, biological sex, and handedness, were collected.
The second group consisted of adult patients that sustained moderate-to-severe TBI, based on an admission Glasgow Coma Scale (GCS) of 12 or less, for which they were admitted to the intensive care unit (ICU) at the Health Sciences Centre, Winnipeg, Manitoba, Canada between February 2020 and December 2022. Surviving patients underwent 30-min physiological data recording during standard outpatient follow-up at 3-, 6-, and 12-months post-injury. Data were collected between June 2020 and June 2023. Additionally, baseline demographic data and injury data were also collected [11].
Physiological data collection was identical between groups. ABP was collected continuously and non-invasively through a Finapres Nova finger cuff (Palatijn, Enschede, The Netherlands). Right and left frontal rSO2 was also collected continuously with the Covidien INVOS 7100 (Covidien-Medtronic, Minneapolis, MN, USA). The INVOS device emits wavelengths of light at 730 and 810 nm with two light detectors spaced 3 and 4 cm away from the emitter [17]. This arrangement allows the detector at 3 cm to provide an estimate of light absorbed by superficial tissues, while the detector at 4 cm provides an estimate of light absorption at a minimum tissue depth of approximately 1.3 cm [18]. The setup can be seen in Figure 1. ABP signals were digitized via an analog/digital converter (DT9803/DT9804/DT9826; Data Translation, Marlborough, MA, USA) with 100 Hz sampling while rSO2 was collected via digital data transfer at 1 Hz through serial output on the device. ICM+ software (Version 8.5, Cambridge Enterprise Ltd., Cambridge, UK) was utilized to record and time-lock physiological data streams. Artifacts were cleared manually utilizing ICM+ software by a trained research assistant. These artifacts were primarily due to loss of signal from NIRS sensor displacement or from disrupted ABP collection indicated by loss of ABP waveform.

2.2. Ethical Consideration

Full approval was received by the University of Manitoba Biomedical Research Ethics Board (B2020:019and B2018:103) and the Health Science Centre Research Impact Committee. For participants in both cohorts, full informed consent was obtained prior to study participation. Participants were able to withdraw from the study at any time.

2.3. Data Processing

Utilizing ICM+ software (Version 8.5), ABP and rSO2 signals were processed utilizing a 10-s non-overlapping moving average filter to remove high frequency signals not associated with vasomotion [19,20]. Next, COx_a was derived using a standard procedure of calculating a Pearson correlation between ABP and rSO2 over a 300-s window and updating the window every minute to obtain a minute-by-minute COx_a for both the right and left frontal channels [13]. This is a standard procedure for the derivation of continuous indices of CVR and is done to limit the influence of very low fluctuations in ABP and CBV that are unrelated to cerebrovascular vasomotion [6,19,20]. Minute-by-minute physiological data streams were then exported for each recording as comma separated value (.csv) files for further analysis.

2.4. Statistical Analysis

Utilizing R statistical software (Version 4.3.0, R Foundation for Statistical Computing, Vienna, Austria) and the tidyverse package, mean values for both right and left COx_a were determined for each recording. Within the healthy volunteer group, non-parametric statistical tests (Mann–Whitney U test and Wilcoxon Signed-Rank test, as appropriate) were conducted, along with standard linear regression to examine the role of hemispheric dominance, biologic sex, and age in CVR. For the chronic TBI cohort, non-parametric statistical tests were conducted to compare the first and last available COx_a measurements. Additionally, the side of cranial surgery, if performed in the acute phase, was utilized as a surrogate for the side of worse injury. As such, COx_a on the side of cranial surgery was compared to the non-surgical side for first and last available measurements. Similarly, COx_a values in the chronic TBI group were tested for statistical difference (Mann–Whitney U test) with the healthy volunteer group. For all testing, alpha was set to 0.05 and not corrected for multiple comparisons due to the exploratory nature of the analysis.

3. Results

3.1. Subject Demographics

In total, 101 healthy volunteers were recruited with one 30-min recording for each subject. There were 29 chronic TBI patients for which at least one follow-up recording was available at 3-, 6-, or 12-months and a total of 65 30-min recordings were performed during follow-up. A simple processed minute-by-minute data recording can be seen in Figure 2. The full demographic data for the healthy volunteers and chronic TBI patients can be found in Table 1 and Table 2, respectively. Notably, the cohort of healthy volunteers was statistically younger than the cohort of chronic TBI patients (26 (IQR: 22 to 31) vs. 40 (IQR: 25 to 50), p < 0.001 Mann–Whitney U test).

3.2. Healthy Volunteers

Given that COx_a is a theoretical measure of regional CVR, an exploration of hemispheric difference was first examined. COx_a values in the dominant hemisphere were compared to that of the non-dominant hemisphere in each subject utilizing a paired sample Wilcoxon test. Handedness was used as a surrogate for hemispheric dominance for language. In the healthy cohort, nine subjects reported left handedness (right hemispheric dominance) and 92 subjects reported right handedness (left hemispheric dominance). No statistically significant difference in COx_a values was found between the dominant and non-dominant hemispheres (0.14 (IQR: 0.02 to 0.21) vs. 0.11 (IQR: 0.03 to 0.21), respectively, p = 0.500 Wilcoxon Signed-Rank test). Figure 3 shows the distribution of average COx_a values by cerebral hemisphere for the group of healthy volunteers. Given this result, left and right COx_a values were averaged for each subject for the remaining analyses.
Similarly, there was no statistically significant difference between CVR in males and females as measured by COx_a (0.10 (IQR: 0.03 to 0.20) vs. 0.12 (IQR: 0.04 to 0.20), respectively, p = 0.564 Mann–Whitney U test). Figure 4 shows the distribution of averaged COx_a values by biologic sex for the group of healthy volunteers. Additionally, age was not a significant univariate linear regressor for COx_a values in the cohort.

3.3. Chronic Traumatic Brain Injury Patients

Age was not found to be a significant univariate linear regressor for COx_a in either the first or last available follow-up in the chronic TBI cohort. Interestingly, COx_a was statistically lower in both the first available (−0.02 (IQR: −0.04 to 0.11), p = 0.005 Mann–Whitney U test) and the last available (0.02 (IQR: −0.05 to 0.16), p = 0.021 Mann–Whitney U test) follow up measurement in the chronic TBI group compared to the cohort of healthy volunteers (0.12 (IQR: 0.03 to 0.20)). While there was no statistical difference between COx_a at the first available measurement and the last available measurement, there was a trend for COx_a to be higher during the last available follow up (−0.02 (IQR: −0.04 to 0.11) vs. 0.02 (IQR: −0.05 to 0.16), respectively, p = 0.537 Wilcoxon Signed-Rank test). Figure 5 shows the distribution of COx_a values for these groups in a violin plot. In those that underwent cranial surgery, COx_a was not found to be significantly different between the side of surgery and the non-surgical side at either the first available measurement (−0.01 (IQR: −0.08 to 0.03) vs. 0.06 (IQR: −0.06 to 0.16), p = 0.497, Wilcoxon Signed-Rank test) or the last available measurement (0.05 (IQR: 0.00 to 0.16) vs. 0.03 (IQR: −0.06 to 0.16), p = 0.376, Wilcoxon Signed-Rank test).

4. Discussion

In this prospective cohort study, the non-invasive nature of COx_a was leveraged for the first time to examine the CVR in both a healthy group of volunteers as well as in a group of patients recovering from moderate-to-severe TBI. This was made possible by the novel, entirely non-invasive method of measuring COx_a. This study presents several interesting findings relating to both healthy subjects and chronic TBI patients.
First, by leveraging the improved spatial resolution of NIRS, hemispheric differences in CVR were able to be explored in a healthy population. There were no statistically significant differences in COx_a between the dominant and non-dominant frontal lobes examined through the NIRS sensors. While prior studies leveraging various modalities have identified hemispheric differences in the pathologic state, there is little evidence for differences in the healthy state [21,22]. It should be noted that no provocative testing was performed to augment potential cerebral activity in the presumed dominant hemisphere for speech. In a healthy resting state, hemispheric differences in CVR are likely minimal.
When assessing differences in CVR based on the biologic sex of the healthy volunteers, no significant difference was found. While the TBI cohort was not perfectly balanced between male and female participants in terms of numbers, both groups were well represented in this cohort. This is a departure from what has been observed in early studies examining sex differences in CVR in the acute TBI setting, where females were found to have worse CVR [23,24,25]. More recent studies in the acute TBI population, like this one, have failed to identify any difference in CVR between males and females [26,27]. It should be noted that those prior studies were limited by cohorts that were predominantly male. This was similar to the currently presented chronic TBI cohort, where the vast majority of patients were male, limiting the value of examining sex differences in this cohort. In a healthy state, CVR does not significantly differ between males and females.
Age was not found to be a significant regressor for COx_a in the healthy volunteers; however, the age distribution of this group was quite narrow with a distribution centered around a young age. Similarly, age was not a significant regressor for COx_a at either the first or last available visit of the chronic TBI cohort. It should be noted that, in both cohorts, the age distribution was very narrow and centered around a younger age. This may explain, in part, why these findings are in contrast to prior studies examining the effect of age on CVR in acute TBI, where CVR was found to be worse with age [8,23,28,29,30,31,32]. In the literature on healthy subjects, a recent study showed no age-related difference when CVR was evaluated with transcranial Doppler (TCD) [33]. Thus, it remains unclear if differences in CVR with age is a phenomenon isolated to the acute injury phase or if the age distribution of the present cohorts have limited detection of this effect over a wide age range.
Utilizing the side of cranial surgery as a surrogate for the side of worse cerebral injury, there was no statistical difference between COx_a on the surgical side versus the non-surgical side at either the first or last available measurement. The side of surgical intervention was felt to be the most objective indicator of the side of worse injury, however, given that less than half of the cohort underwent cranial surgery, these findings may be the results of an underpowered subgroup analysis.
Perhaps the most interesting finding of this study is that CVR, as measured by COx_a, was found to be more active at both the first and last available follow-ups in the chronic TBI cohort than in the healthy volunteer cohort. Additionally, CVR appeared to trend towards normalization between the first and last follow-up of the chronic TBI patients. This could indicate that in those that survive moderate-to-severe TBI, CVR is hyperactive in the recovery phase. This could be due to either a survival bias, in which those that survive this type of injury have more active CVR at baseline, or it could be a true adaptive mechanism of neuronal protection in the recovery phase of injury. The trend towards normalization seen in this cohort could also indicate that this is a mechanism that dissipates with time. In a recent study examining CVR leveraging TCD and provocative testing (sit-stand maneuvers), differences between a healthy group and a chronic TBI group were minimal. However, time since injury in that study was much longer, with a median time of 18 months since injury, which may support the notion of normalization over time [34].
An alternative hypothesis is that a reduced COx_a in the chronic TBI cohort may represent an inability of NIRS-based rSO2 to act as a surrogate for CBV. This might be due to artifacts from the prior craniotomy, cranioplasty, or from cerebral atrophy and gliosis following injury. In both instances, the rSO2 signal might not truly be that of viable cerebral tissue. This could result in an rSO2 signal with little variability that is completely decoupled from ABP changes and would manifest as a COx_a value close to zero. As the COx_a values in the healthy volunteers are above zero, this artifactual decoupling of rSO2 signals would give the appearance of a more active CVR state. It is also worth noting that while statistically significant, the difference between the two cohorts is not very large and the physiological relevance of this difference is unclear.

4.1. Study Limitations

There are a number of limitations that must be considered when interpreting the findings of this study. First is that in both groups the age distribution was somewhat limited, with few subjects being included with advanced age. This limits the ability of these cohorts to identify age-related variation in CVR. Similarly, the small number of female subjects in the chronic TBI cohort, while consistent with the epidemiology of the condition, limits evaluation of biologic sex differences in this pathologic state. Subject age was also significantly different between the chronic TBI cohort and the healthy volunteer cohort which may have impacted CVR in an unpredictable way.
While 29 subjects were included in the chronic TBI cohort, there were a significant number of missed follow-up sessions, with only 65 recordings available out of a potential 87. This limited the ability to fully examine the trajectory of COx_a over the course of recovery, with all three recordings available for less than half of the cohort. Additionally, those that did participate generally had quite good functional outcomes as measured by extended Glasgow outcome scale (GOSE). This means that the chronic TBI cohort was nearly fully recovered from their TBI. This type of sampling bias may have increased physiologic similarity between the healthy volunteer and chronic TBI cohorts. Further, the limited number of subjects in this study, while able to provide statistically significant findings, limits the ability to determine the clinical significance of such findings.
Additionally, the low temporal resolution of the NIRS device used in this study precluded the use of more sophisticated wavelet coherence techniques for evaluating CVR continuoulsy. These methods, however, are still in their early development and their advantages over time-domain–based indices of CVR are not fully understood [29,35]. Further, the limited evaluation of only the frontal lobes in the chronic TBI cohort would not fully evaluate CVR in the region of injury in those with cerebral insult in alternative locations. It should be noted, however, that popular contemporary measures of CVR, such as PRx, are also global measures of CVR with no better spatial resolution than COx_a [36].
Finally, rSO2 can be affected by a number of factors, beyond pressure-modulated arteriolar dilation and constriction, data for which were not collected during this study. This includes any factor that changes the regional concentrations of oxygenated hemoglobin (OxHgB) and total hemoglobin (HgB) values, such as systemic HgB levels and systemic oxygen saturation (SpO2). Metabolic factors, such as end-tidal carbon dioxide (ETCO2) and neuronal activity, and therefore the effects of neurovascular coupling, were not strictly controlled or measured. Additionally, as rSO2 is prone to interference, it is notable that no provocative testing, such as hyper- and hypoventilation, was performed to ensure that rSO2 signals were reflective of cerebral microvasculature, as assumed by COx_a.

4.2. Future Work

The findings of this study will need further validation and exploration. Future studies examining CVR utilizing COx_a would benefit from larger multicenter cohorts, with more age profiles and an even split in biological sex. This would better identify age and biological sex contributions to CVR in healthy volunteers and chronic TBI patients. The inclusion of provocative testing, such as cognitive testing and language testing may also elucidate hemispheric differences in CVR. Additionally, ETCO2 and SpO2 monitoring coupled with respiratory rate modulation would also help to ensure that rSO2 signals were reflective of cerebral microvasculature.
Additionally, utilizing NIRS devices with improved temporal resolution and more comprehensive cortical mapping, a fuller evaluation of CVR may be possible in both cohorts. This could be accomplished through leveraging wavelet coherence-based methodologies in combination with a complete spatial assessment of the brain [37].
Finally, while the evolution of COx_a was evaluated here in a chronic TBI population, it would be of interest to examine the outcome associations of COx_a in the chronic phase. Additionally, the relationship between CVR in the acute versus chronic phases should also be explored.

5. Conclusions

This prospective study leveraged novel techniques of non-invasively measuring CVR to evaluate various metrics in both healthy volunteers and chronic TBI patients. Within the cohort of healthy volunteers, CVR, as measured by COx_a, did not differ by biologic sex or the hemisphere of language dominance. There was no clear relationship between age and COx_a either; however, the demographics of the cohort were skewed to a younger population. Compared to the healthy volunteers, chronic TBI patients had more active CVR at follow-up with a trend towards normalization of CVR at last available follow-up, as determined by COx_a. Future studies will need to validate these findings in a larger, more distributed cohort.

Author Contributions

Conceptualization, A.G. and F.A.Z.; data curation, A.G., L.F. and F.A.Z.; formal analysis, A.G. and I.M.; funding acquisition, F.A.Z.; methodology, A.G. and I.M.; supervision, F.A.Z.; visualization, A.G.; writing—original draft, A.G.; writing—review & editing, A.G., I.M., L.F., T.B., A.S.S., N.V., A.I., K.Y.S., Y.I. and F.A.Z. All authors have read and agreed to the published version of the manuscript.

Funding

Research reported in this publication was supported by the National Institute of Neurological Disorders and Stroke (NINDS) of the National Institutes of Health (NIH) under Award Number R03NS114335. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This work was also directly supported by the University of Manitoba Endowed Manitoba Public Insurance (MPI) Chair in Neuroscience, the Natural Sciences and Engineering Research Council of Canada (NSERC) (DGECR-2022-00260, RGPIN-2022-03621, ALLRP-578524-22 and ALLRP-576386-22, ALLRP 586244-23).

Institutional Review Board Statement

Full approval was received by the University of Manitoba Biomedical Research Ethics Board (B2020:019and B2018:103) and the Health Science Centre Research Impact Committee.

Informed Consent Statement

For participants in both cohorts, full informed consent was obtained prior to study participation. Participants were able to withdraw from the study at any time.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Acknowledgments

FAZ is supported through the University of Manitoba Endowed Manitoba Public Insurance (MPI) Chair in Neuroscience/TBI Research Endowment, NSERC, Canadian Institutes of Health Research (CIHR), the MPI Neuroscience Research Operating Fund, the Health Sciences Centre Foundation Winnipeg, the Canada Foundation for Innovation (CFI) (Project #: 38583), Research Manitoba (Grant #: 3906 and 5429) and the University of Manitoba VPRI Research Investment Fund (RIF). AG is supported through a CIHR Fellowship (Grant #: 472286). LF is supported through a Research Manitoba PhD Fellowship, the Brain Canada Thomkins Travel Scholarship, NSERC and the Graduate Enhancement of Tri-Council Stipends (GETS)—University of Manitoba. KYS is supported through the University of Manitoba R.G. and E.M. Graduate Fellowship (Doctoral) in Biomedical Engineering, and the University of Manitoba MD/PhD program, and NSERC CGS-D (CGS D-579021-2023).

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Chesnut, R.; Aguilera, S.; Buki, A.; Bulger, E.; Citerio, G.; Cooper, D.J.; Arrastia, R.D.; Diringer, M.; Figaji, A.; Gao, G.; et al. A Management Algorithm for Adult Patients with Both Brain Oxygen and Intracranial Pressure Monitoring: The Seattle International Severe Traumatic Brain Injury Consensus Conference (SIBICC). Intensive Care Med. 2020, 46, 919–929. [Google Scholar] [CrossRef] [PubMed]
  2. Carney, N.; Totten, A.M.; O’Reilly, C.; Ullman, J.S.; Hawryluk, G.W.J.; Bell, M.J.; Bratton, S.L.; Chesnut, R.; Harris, O.A.; Kissoon, N.; et al. Guidelines for the Management of Severe Traumatic Brain Injury, Fourth Edition. Neurosurgery 2017, 80, 6–15. [Google Scholar] [CrossRef] [PubMed]
  3. Rangel-Castilla, L.; Gasco, J.; Nauta, H.J.W.; Okonkwo, D.O.; Robertson, C.S. Cerebral Pressure Autoregulation in Traumatic Brain Injury. Neurosurg. Focus. 2008, 25, E7. [Google Scholar] [CrossRef]
  4. Sorrentino, E.; Diedler, J.; Kasprowicz, M.; Budohoski, K.P.; Haubrich, C.; Smielewski, P.; Outtrim, J.G.; Manktelow, A.; Hutchinson, P.J.; Pickard, J.D.; et al. Critical Thresholds for Cerebrovascular Reactivity after Traumatic Brain Injury. Neurocrit. Care 2012, 16, 258–266. [Google Scholar] [CrossRef] [PubMed]
  5. Armstead, W.M. Cerebral Blood Flow Autoregulation and Dysautoregulation. Anesthesiol. Clin. 2016, 34, 465–477. [Google Scholar] [CrossRef]
  6. Czosnyka, M.; Smielewski, P.; Piechnik, S.; Steiner, L.A.; Pickard, J.D. Cerebral Autoregulation Following Head Injury. J. Neurosurg. 2001, 95, 756–763. [Google Scholar] [CrossRef] [PubMed]
  7. Budohoski, K.P.; Czosnyka, M.; de Riva, N.; Smielewski, P.; Pickard, J.D.; Menon, D.K.; Kirkpatrick, P.J.; Lavinio, A. The Relationship Between Cerebral Blood Flow Autoregulation and Cerebrovascular Pressure Reactivity after Traumatic Brain Injury. Neurosurgery 2012, 71, 652–661. [Google Scholar] [CrossRef]
  8. Steiner, L.A.; Czosnyka, M.; Piechnik, S.K.; Smielewski, P.; Chatfield, D.; Menon, D.K.; Pickard, J.D. Continuous Monitoring of Cerebrovascular Pressure Reactivity Allows Determination of Optimal Cerebral Perfusion Pressure in Patients with Traumatic Brain Injury. Crit. Care Med. 2002, 30, 733–738. [Google Scholar] [CrossRef] [PubMed]
  9. Petkus, V.; Preiksaitis, A.; Chaleckas, E.; Chomskis, R.; Zubaviciute, E.; Vosylius, S.; Rocka, S.; Rastenyte, D.; Aries, M.J.; Ragauskas, A.; et al. Optimal Cerebral Perfusion Pressure: Targeted Treatment for Severe Traumatic Brain Injury. J. Neurotrauma 2020, 37, 389–396. [Google Scholar] [CrossRef] [PubMed]
  10. Tas, J.; Beqiri, E.; van Kaam, R.C.; Czosnyka, M.; Donnelly, J.; Haeren, R.H.; van der Horst, I.C.C.; Hutchinson, P.J.; van Kuijk, S.M.J.; Liberti, A.L.; et al. Targeting Autoregulation-Guided Cerebral Perfusion Pressure after Traumatic Brain Injury (COGiTATE): A Feasibility Randomized Controlled Clinical Trial. J. Neurotrauma 2021, 38, 2790–2800. [Google Scholar] [CrossRef]
  11. Gomez, A.; Dian, J.; Froese, L.; Zeiler, F.A. Near-Infrared Cerebrovascular Reactivity for Monitoring Cerebral Autoregulation and Predicting Outcomes in Moderate to Severe Traumatic Brain Injury: Proposal for a Pilot Observational Study. JMIR Res. Protoc. 2020, 9, e18740. [Google Scholar] [CrossRef]
  12. Gomez, A.; Dian, J.; Zeiler, F.A. Continuous and Entirely Non-Invasive Method for Cerebrovascular Reactivity Assessment: Technique and Implications. J. Clin. Monit. Comput. 2020, 35, 307–315. [Google Scholar] [CrossRef] [PubMed]
  13. Brady, K.M.; Lee, J.K.; Kibler, K.K.; Smielewski, P.; Czosnyka, M.; Easley, R.B.; Koehler, R.C.; Shaffner, D.H. Continuous Time-Domain Analysis of Cerebrovascular Autoregulation Using near-Infrared Spectroscopy. Stroke 2007, 38, 2818–2825. [Google Scholar] [CrossRef] [PubMed]
  14. Gomez, A.; Froese, L.; Bergmann, T.J.G.; Sainbhi, A.S.; Vakitbilir, N.; Islam, A.; Stein, K.Y.; Marquez, I.; Ibrahim, Y.; Zeiler, F.A. Non-Invasive Estimation of Intracranial Pressure-Derived Cerebrovascular Reactivity Using Near-Infrared Spectroscopy Sensor Technology in Acute Neural Injury: A Time-Series Analysis. Sensors 2024, 24, 499. [Google Scholar] [CrossRef] [PubMed]
  15. Gomez, A.; Sainbhi, A.S.; Stein, K.Y.; Vakitbilir, N.; Froese, L.; Zeiler, F.A. Statistical Properties of Cerebral near Infrared and Intracranial Pressure-Based Cerebrovascular Reactivity Metrics in Moderate and Severe Neural Injury: A Machine Learning and Time-Series Analysis. Intensiv. Care Med. Exp. 2023, 11, 57. [Google Scholar] [CrossRef] [PubMed]
  16. Davies, D.J.; Su, Z.; Clancy, M.T.; Lucas, S.J.E.; Dehghani, H.; Logan, A.; Belli, A. Near-Infrared Spectroscopy in the Monitoring of Adult Traumatic Brain Injury: A Review. J. Neurotrauma 2015, 32, 933–941. [Google Scholar] [CrossRef] [PubMed]
  17. Moerman, A.; Vandenplas, G.; Bové, T.; Wouters, P.F.; De Hert, S.G. Relation between Mixed Venous Oxygen Saturation and Cerebral Oxygen Saturation Measured by Absolute and Relative Near-Infrared Spectroscopy during off-Pump Coronary Artery Bypass Grafting. Br. J. Anaesth. 2013, 110, 258–265. [Google Scholar] [CrossRef] [PubMed]
  18. Hogue, C.W.; Levine, A.; Hudson, A.; Lewis, C. Clinical Applications of Near-Infrared Spectroscopy Monitoring in Cardiovascular Surgery. Anesthesiology 2021, 134, 784–791. [Google Scholar] [CrossRef]
  19. Howells, T.; Johnson, U.; McKelvey, T.; Enblad, P. An Optimal Frequency Range for Assessing the Pressure Reactivity Index in Patients with Traumatic Brain Injury. J. Clin. Monit. Comput. 2015, 29, 97–105. [Google Scholar] [CrossRef] [PubMed]
  20. Fraser, C.D.; Brady, K.M.; Rhee, C.J.; Easley, R.B.; Kibler, K.; Smielewski, P.; Czosnyka, M.; Kaczka, D.W.; Andropoulos, D.B.; Rusin, C. The Frequency Response of Cerebral Autoregulation. J. Appl. Physiol. 2013, 115, 52–56. [Google Scholar] [CrossRef]
  21. Lang, E.W.; Yip, K.; Griffith, J.; Lagopoulos, J.; Mudaliar, Y.; Dorsch, N.W. Hemispheric Asymmetry and Temporal Profiles of Cerebral Pressure Autoregulation in Head Injury. J. Clin. Neurosci. 2003, 10, 670–673. [Google Scholar] [CrossRef]
  22. Vavilala, M.S.; Tontisirin, N.; Udomphorn, Y.; Armstead, W.; Zimmerman, J.J.; Chesnut, R.; Lam, A.M. Hemispheric Differences in Cerebral Autoregulation in Children with Moderate and Severe Traumatic Brain Injury. Neurocrit. Care 2008, 9, 45–54. [Google Scholar] [CrossRef] [PubMed]
  23. Czosnyka, M.; Hutchinson, P.J.; Balestreri, M.; Hiler, M.; Smielewski, P.; Pickard, J.D. Monitoring and Interpretation of Intracranial Pressure after Head Injury. Acta Neurochir. Suppl. 2006, 96, 114–118. [Google Scholar] [CrossRef] [PubMed]
  24. Czosnyka, M.; Radolovich, D.; Balestreri, M.; Lavinio, A.; Hutchinson, P.; Timofeev, I.; Smielewski, P.; Pickard, J.D. Gender-Related Differences in Intracranial Hypertension and Outcome after Traumatic Brain Injury. Acta Neurochir. Suppl. 2008, 102, 25–28. [Google Scholar] [CrossRef]
  25. Zeiler, F.A.; Donnelly, J.; Nourallah, B.; Thelin, E.P.; Calviello, L.; Smielewski, P.; Czosnyka, M.; Ercole, A.; Menon, D.K. Intracranial and Extracranial Injury Burden as Drivers of Impaired Cerebrovascular Reactivity in Traumatic Brain Injury. J. Neurotrauma 2018, 35, 1569–1577. [Google Scholar] [CrossRef]
  26. Batson, C.; Froese, L.; Gomez, A.; Sainbhi, A.S.; Stein, K.Y.; Alizadeh, A.; Zeiler, F.A. Impact of Age and Biological Sex on Cerebrovascular Reactivity in Adult Moderate/Severe Traumatic Brain Injury: An Exploratory Analysis. Neurotrauma Rep. 2021, 2, 488–501. [Google Scholar] [CrossRef] [PubMed]
  27. Batson, C.; Froese, L.; Sekhon, M.; Griesdale, D.; Gomez, A.; Thelin, E.P.; Raj, R.; Aries, M.; Gallagher, C.; Bernard, F.; et al. Impact of Chronological Age and Biological Sex on Cerebrovascular Reactivity in Moderate/Severe Traumatic Brain Injury: A CAnadian High-Resolution Traumatic Brain Injury (CAHR-TBI) Study. J. Neurotrauma 2022, 40, 1098–1111. [Google Scholar] [CrossRef] [PubMed]
  28. Czosnyka, M.; Balestreri, M.; Steiner, L.; Smielewski, P.; Hutchinson, P.J.; Matta, B.; Pickard, J.D. Age, Intracranial Pressure, Autoregulation, and Outcome after Brain Trauma. J. Neurosurg. 2005, 102, 450–454. [Google Scholar] [CrossRef] [PubMed]
  29. Liu, X.; Donnelly, J.; Czosnyka, M.; Aries, M.J.H.; Brady, K.; Cardim, D.; Robba, C.; Cabeleira, M.; Kim, D.-J.; Haubrich, C.; et al. Cerebrovascular Pressure Reactivity Monitoring Using Wavelet Analysis in Traumatic Brain Injury Patients: A Retrospective Study. PLoS Med. 2017, 14, e1002348. [Google Scholar] [CrossRef] [PubMed]
  30. Aries, M.J.H.; Czosnyka, M.; Budohoski, K.P.; Kolias, A.G.; Radolovich, D.K.; Lavinio, A.; Pickard, J.D.; Smielewski, P. Continuous Monitoring of Cerebrovascular Reactivity Using Pulse Waveform of Intracranial Pressure. Neurocrit. Care 2012, 17, 67–76. [Google Scholar] [CrossRef]
  31. Hiler, M.; Czosnyka, M.; Hutchinson, P.; Balestreri, M.; Smielewski, P.; Matta, B.; Pickard, J.D. Predictive Value of Initial Computerized Tomography Scan, Intracranial Pressure, and State of Autoregulation in Patients with Traumatic Brain Injury. J. Neurosurg. 2006, 104, 731–737. [Google Scholar] [CrossRef]
  32. Radolovich, D.K.; Aries, M.J.H.; Castellani, G.; Corona, A.; Lavinio, A.; Smielewski, P.; Pickard, J.D.; Czosnyka, M. Pulsatile Intracranial Pressure and Cerebral Autoregulation after Traumatic Brain Injury. Neurocrit. Care 2011, 15, 379–386. [Google Scholar] [CrossRef] [PubMed]
  33. Yam, A.T.; Lang, E.W.; Lagopoulos, J.; Yip, K.; Griffith, J.; Mudaliar, Y.; Dorsch, N.W.C. Cerebral Autoregulation and Ageing. J. Clin. Neurosci. 2005, 12, 643–646. [Google Scholar] [CrossRef]
  34. Ding, K.; Tarumi, T.; Tomoto, T.; Mccolloster, M.; Le, T.; Dieppa, M.; Diaz-Arrastia, R.; Bell, K.; Madden, C.; Cullum, C.M.; et al. Impaired Cerebral Blood Flow Regulation in Chronic Traumatic Brain Injury. Brain Res. 2020, 1743, 146924. [Google Scholar] [CrossRef] [PubMed]
  35. Addison, P.S. A Review of Wavelet Transform Time-Frequency Methods for NIRS-Based Analysis of Cerebral Autoregulation. IEEE Rev. Biomed. Eng. 2015, 8, 78–85. [Google Scholar] [CrossRef]
  36. Czosnyka, M.; Smielewski, P.; Kirkpatrick, P.; Piechnik, S.; Laing, R.; Pickard, J.D. Continuous Monitoring of Cerebrovascular Pressure-Reactivity in Head Injury. Acta Neurochir. Suppl. 1998, 71, 74–77. [Google Scholar] [CrossRef]
  37. Sainbhi, A.S.; Froese, L.; Gomez, A.; Marquez, I.; Amenta, F.; Batson, C.; Stein, K.Y.; Zeiler, F.A. High Spatial and Temporal Resolution Cerebrovascular Reactivity for Humans and Large Mammals: A Technological Description of Integrated fNIRS and niABP Mapping System. Front. Physiol. 2023, 14, 1124268. [Google Scholar] [CrossRef]
Bioengineering 11 00310 g001
Figure 1. A demonstration of the setup of an entirely non-invasive collection of the arterial blood pressure (ABP)-based cerebral oxygen index (COx_a). Bilateral frontal lobe regional cerebral oxygen saturation (rSO2) was collected with sensor pads placed on the forehead (Covidien INVOS 7100, Covidien-Medtronic, Minneapolis, MN, USA) while arterial blood pressure was measured non-invasively thought a finger cuff (Finapres Nova, Palatijn, Enschede, The Netherlands).
Figure 1. A demonstration of the setup of an entirely non-invasive collection of the arterial blood pressure (ABP)-based cerebral oxygen index (COx_a). Bilateral frontal lobe regional cerebral oxygen saturation (rSO2) was collected with sensor pads placed on the forehead (Covidien INVOS 7100, Covidien-Medtronic, Minneapolis, MN, USA) while arterial blood pressure was measured non-invasively thought a finger cuff (Finapres Nova, Palatijn, Enschede, The Netherlands).
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Figure 2. A 30-min sample of arterial blood pressure (ABP) sampled at 100 Hz and left and right frontal regional cerebral oxygen saturation (L rSO2 and R rSO2) sampled at 1 Hz. The bottom two series show the left and right ABP-derived cerebral oxygen index (L COx_a and R COx_a) updated on a minute-by-minute basis.
Figure 2. A 30-min sample of arterial blood pressure (ABP) sampled at 100 Hz and left and right frontal regional cerebral oxygen saturation (L rSO2 and R rSO2) sampled at 1 Hz. The bottom two series show the left and right ABP-derived cerebral oxygen index (L COx_a and R COx_a) updated on a minute-by-minute basis.
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Figure 3. A density plot of the distribution of average arterial blood pressure (ABP)-derived cerebral oxygen index (COx_a) by cerebral hemisphere in the healthy volunteer cohort. Note the significant degree of overlap between groups, consistent with the lack of statistically significant differences between COx_a in dominant (rose) and non-dominant (blue) hemispheres.
Figure 3. A density plot of the distribution of average arterial blood pressure (ABP)-derived cerebral oxygen index (COx_a) by cerebral hemisphere in the healthy volunteer cohort. Note the significant degree of overlap between groups, consistent with the lack of statistically significant differences between COx_a in dominant (rose) and non-dominant (blue) hemispheres.
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Figure 4. A density plot of the distribution of average arterial blood pressure (ABP)-derived cerebral oxygen index (COx_a) by biologic sex in the healthy volunteer cohort. Note the significant degree of overlap between groups, consistent with the lack of statistically significant differences between COx_a in females (rose) and males (blue).
Figure 4. A density plot of the distribution of average arterial blood pressure (ABP)-derived cerebral oxygen index (COx_a) by biologic sex in the healthy volunteer cohort. Note the significant degree of overlap between groups, consistent with the lack of statistically significant differences between COx_a in females (rose) and males (blue).
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Figure 5. A violin plot of the distribution of average arterial blood pressure (ABP)-derived cerebral oxygen index (COx_a) by cohort. Note the significantly higher values of the healthy volunteer group (blue) compared to the first available (rose) or last available (green) measurement in the chronic traumatic brain injury (TBI) cohort; however, a high degree of overlap is still present.
Figure 5. A violin plot of the distribution of average arterial blood pressure (ABP)-derived cerebral oxygen index (COx_a) by cohort. Note the significantly higher values of the healthy volunteer group (blue) compared to the first available (rose) or last available (green) measurement in the chronic traumatic brain injury (TBI) cohort; however, a high degree of overlap is still present.
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Table 1. Demographic Data of the Healthy Volunteers.
Table 1. Demographic Data of the Healthy Volunteers.
Demographic ParameterMedian or Number of Patients
N = 101
Age (IQR)26 (22 to 31)
Biologic SexMale subjects (%)41 (40.6)
Female subjects (%)60 (59.4)
HandednessRight (%)92 (91.8)
Left (%)9 (8.9)
Subject Average COx_a (IQR)0.12 (0.03 to 0.20)
Subject Average ABP (IQR)101.5 (83.8 to 105.5) mmHg
Subject Average rSO2 (IQR)Right72.6 (66.2 to 79.1)%
Left73.7 (69.6 to 79.0)%
ABP = arterial blood pressure; COx_a = cerebral oxygen index based on arterial blood pressure; IQR = interquartile range; rSO2 = regional cerebral oxygen saturation.
Table 2. Demographic Data of the Chronic Traumatic Brain Injury Patients.
Table 2. Demographic Data of the Chronic Traumatic Brain Injury Patients.
Demographic ParameterMedian or Number of Patients
N = 29
Age (IQR)40 (25 to 50)
Biologic SexMale subjects (%)24 (82.8)
Female subjects (%)5 (17.2)
Admission GCS (IQR)7 (4 to 8)
Admission PupilsBilaterally reactive (%)22 (81.5)
Unilaterally reactive (%)5 (17.2)
Bilaterally unreactive (%)1 (3.4)
Cranial Surgery SideRight7
Left6
None16
Marshall CT ClassificationI (%)0 (0)
II (%)1 (3.4)
III (%)11 (37.9)
IV (%)6 (20.7)
V (%)11 (37.9)
VI (%)0 (0)
Follow-up GOSE3-Month6 (5 to6)
6-Month7 (5 to7)
12-Month1 (5)
Recording Sessions3-Month23
6-Month24
12-Month18
Subject Average COx_a (IQR)3-Month−0.02 (−0.04 to 0.06)
6-Month0.05 (−0.06 to 0.17)
12-Month0.02 (−0.04 to 0.11)
Subject Average ABP (IQR)93.5 (83.8 to105.5) mmHg
Subject Average rSO2 (IQR)Right69.0 (64.6 to73.9)%
Left70.1 (65.5 to 73.7)%
ABP = arterial blood pressure; COx_a = cerebral oxygen index based on arterial blood pressure; CT = computed tomography; GCS = Glasgow coma scale; GOSE = extended Glasgow outcome scale; IQR = interquartile range; rSO2 = regional cerebral oxygen saturation.
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MDPI and ACS Style

Gomez, A.; Marquez, I.; Froese, L.; Bergmann, T.; Sainbhi, A.S.; Vakitbilir, N.; Islam, A.; Stein, K.Y.; Ibrahim, Y.; Zeiler, F.A. Near-Infrared Spectroscopy Regional Oxygen Saturation Based Cerebrovascular Reactivity Assessments in Chronic Traumatic Neural Injury versus in Health: A Prospective Cohort Study. Bioengineering 2024, 11, 310. https://doi.org/10.3390/bioengineering11040310

AMA Style

Gomez A, Marquez I, Froese L, Bergmann T, Sainbhi AS, Vakitbilir N, Islam A, Stein KY, Ibrahim Y, Zeiler FA. Near-Infrared Spectroscopy Regional Oxygen Saturation Based Cerebrovascular Reactivity Assessments in Chronic Traumatic Neural Injury versus in Health: A Prospective Cohort Study. Bioengineering. 2024; 11(4):310. https://doi.org/10.3390/bioengineering11040310

Chicago/Turabian Style

Gomez, Alwyn, Izabella Marquez, Logan Froese, Tobias Bergmann, Amanjyot Singh Sainbhi, Nuray Vakitbilir, Abrar Islam, Kevin Y. Stein, Younis Ibrahim, and Frederick A. Zeiler. 2024. "Near-Infrared Spectroscopy Regional Oxygen Saturation Based Cerebrovascular Reactivity Assessments in Chronic Traumatic Neural Injury versus in Health: A Prospective Cohort Study" Bioengineering 11, no. 4: 310. https://doi.org/10.3390/bioengineering11040310

APA Style

Gomez, A., Marquez, I., Froese, L., Bergmann, T., Sainbhi, A. S., Vakitbilir, N., Islam, A., Stein, K. Y., Ibrahim, Y., & Zeiler, F. A. (2024). Near-Infrared Spectroscopy Regional Oxygen Saturation Based Cerebrovascular Reactivity Assessments in Chronic Traumatic Neural Injury versus in Health: A Prospective Cohort Study. Bioengineering, 11(4), 310. https://doi.org/10.3390/bioengineering11040310

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