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Method Article

Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies

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DOI:

10.3791/61608

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November 19th, 2020

 ,  ,  ,  ,  ,  ,  ,  ,  , 
1Institute of Physics, University of Campinas, 2Brazilian Institute of Neuroscience and Neurotechnology, 3Clinical Hospital, University of Campinas, 4Department of Emergency Medicine, Albert Einstein College of Medicine, 5School of Medical Sciences, University of Campinas

In This Article

Erratum Notice

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Summary

Presented here is a protocol for non-invasively monitoring cerebral hemodynamics of neurocritical patients in real-time and at the bedside using diffuse optics. Specifically, the proposed protocol uses a hybrid diffuse optical systems to detect and display real-time information on cerebral oxygenation, cerebral blood flow and cerebral metabolism.

Abstract

Neurophysiological monitoring is an important goal in the treatment of neurocritical patients, as it may prevent secondary damage and directly impact morbidity and mortality rates. However, there is currently a lack of suitable non-invasive, real-time technologies for continuous monitoring of cerebral physiology at the bedside. Diffuse optical techniques have been proposed as a potential tool for bedside measurements of cerebral blood flow and cerebral oxygenation in case of neurocritical patients. Diffuse optical spectroscopies have been previously explored to monitor patients in several clinical scenarios ranging from neonatal monitoring to cerebrovascular interventions in adults. However, the feasibility of the technique to aid clinicians by providing real-time information at the bedside remains largely unaddressed. Here, we report the translation of a diffuse optical system for continuous real-time monitoring of cerebral blood flow, cerebral oxygenation, and cerebral oxygen metabolism during intensive care. The real-time feature of the instrument could enable treatment strategies based on patient-specific cerebral physiology rather than relying on surrogate metrics, such as arterial blood pressure. By providing real-time information on the cerebral circulation at different time scales with relatively cheap and portable instrumentation, this approach may be especially useful in low-budget hospitals, in remote areas and for monitoring in open fields (e.g., defense and sports).

Introduction

Most of the complications that lead to poor outcomes for critically ill neurologic patients are related to secondary injuries caused by cerebral hemodynamic impairments. Therefore, monitoring cerebral physiology of these patients may directly impact morbidity and mortality rates1,2,3,4,5,6,7. Currently, however, there is no established clinical tool for the continuous real-time noninvasive monitoring of cerebral physiology in neurocritical patients at the bedside. Among the potential candidates, diffuse optical techniques have recently been proposed as a promising tool to fill in this gap8,9,10,11. By measuring the slow changes (i.e., on the order of tens to hundreds of ms) of the diffusively scattered near-infrared light (~650-900 nm) from the scalp, diffuse optical spectroscopy (DOS) can measure concentrations of the main chromophores in the brain, such as cerebral oxy- (HbO) and deoxy-hemoglobin (HbR)12,13. Additionally, it is possible to measure cerebral blood flow (CBF) with diffuse correlation spectroscopy (DCS)10,14,15,16,17 by quantifying the rapid fluctuations in light intensity (i.e., from a few µs to a few ms). When combined, DOS and DCS can also provide an estimate of the cerebral metabolic rate of oxygen (CMRO2)18,19,20.

The combination of DOS and DCS has been explored to monitor patients in several pre-clinical and clinical scenarios. For example, diffuse optics has been shown to provide relevant clinical information for critically-ill neonates21,22,23,24, including during cardiac surgeries to treat heart defects23,25,26,27,28. In addition, several authors have explored the use of diffuse optics to assess cerebral hemodynamics during different cerebrovascular interventions, such as carotid endarterectomy29,30,31, thrombolytic treatments for stroke32, head-of-bed manipulations33,34,35, cardiopulmonary resuscitation36, and others37,38,39. When continuous blood pressure monitoring is also available, diffuse optics can be used to monitor cerebral autoregulation, both in healthy and in critically ill subjects11,40,41,42, as well to assess the critical closing pressure of the cerebral circulation43. Several authors have validated CBF measurements with DCS against different gold standard CBF measures18, while CMRO2 measured with diffuse optics has been shown to be a useful parameter for neurocritical monitoring8,18,23,24,28,43,44,45. In addition, previous studies have validated the optically-derived cerebral hemodynamic parameters for long-term monitoring of neurocritical patients8,9,10,11, including for the prediction of hypoxic46,47,48 and ischemic events8.

The reliability of the diffuse optical techniques to provide valuable real-time information during longitudinal measurements as well as during clinical interventions remains largely unaddressed. The use of a standalone DOS system was previously compared to invasive brain tissue oxygen tension monitors, and DOS was deemed to not have a sufficient sensibility to replace the invasive monitors. However, apart from using relatively small populations, the direct comparison of the invasive and non-invasive monitors may be misguided as each technique probe different volumes containing different parts of the cerebral vasculature. Even though these studies ultimately concluded that diffuse optics is not a replacement for the invasive monitors, in both studies DOS achieved a moderate-to-good accuracy, which may be sufficient for cases and/or places wherein invasive monitors are not available.

Relative to other approaches, the key advantage of diffuse optics is its ability to simultaneously measure blood flow and tissue blood oxygenation non-invasively (and continuously) at the bedside using portable instrumentation. Compared to Transcranial Doppler ultrasound (TCD), DCS has an additional advantage: it measures perfusion at the tissue level, whereas TCD measures cerebral blood flow velocity in large arteries at the base of the brain. This distinction may be particularly important when evaluating steno-occlusive diseases in which both proximal large artery flow and leptomeningeal collaterals contribute to perfusion. Optical techniques also have advantages when compared to other traditional imaging modalities, such as Positron-Emission Tomography (PET) and Magnetic Resonance Imaging (MRI). In addition to simultaneously providing direct measures of both CBF and HbO/HbR concentrations, which is not possible with MRI or PET alone, optical monitoring also provides significantly better temporal resolution, allowing, for example, the assessment of dynamic cerebral autoregulation40,41,42 and the assessment dynamically evolving hemodynamical changes. Moreover, diffuse optical instrumentation is inexpensive and portable in comparison to PET and MRI, which is a critical advantage given the high burden of vascular disease in lower- and middle-income countries.

The protocol proposed here is an environment for real-time bedside neuromonitoring of patients at the intensive care unit (ICU). The protocol uses a hybrid optical device together with a clinical-friendly graphical user interface (GUI) and customized optical sensors to probe the patients (Figure 1). The hybrid system employed for showcasing this protocol combines two diffuse optical spectroscopies from independent modules: a commercial frequency-domain (FD-) DOS module and a homemade DCS module (Figure 1A). The FD-DOS module49,50 consists of 4 photomultiplier tubes (PMTs) and 32 laser diodes emitting at four different wavelengths (690, 704, 750 and 850 nm). The DCS module consists of a long-coherence laser emitting at 785 nm, 16 single-photon counters as detectors and a correlator board. The sampling frequency for the FD-DOS module is 10 Hz, and the maximum sampling frequency for the DCS module is 3 Hz. To integrate the FD-DOS and DCS modules, a microcontroller was programmed inside our control software to automatically switch between each module. The microcontroller is responsible for turning the FD-DOS and DCS lasers on and off, as well as the FD-DOS detectors to allow interleaved measurements of each module. In total, the proposed system can collect one combined FD-DOS and DCS sample every 0.5 to 5s, depending on the signal-to-noise ratio (SNR) requirements (longer collection times leads to better SNR). To couple the light to the forehead, we developed a 3D-printed optical probe that can be customized for each patient (Figure 1B), with source-detector separations varying between 0.8 and 4.0 cm. The standard source-detector separations used in the examples presented here are 2.5 cm for DCS and 1.5, 2.0, 2.5 and 3.0 cm for FD-DOS.

The main feature of the protocol presented in this study is the development of a real-time interface that can both control the hardware with a friendly GUI and display the main cerebral physiology parameters in real-time under different temporal windows (Figure 1C). The real-time analysis pipeline developed within the proposed GUI is fast and takes less than 50 ms to compute the optical parameters (see the Supplementary Material for more details). The GUI was inspired by current clinical instruments already available at the neuro-ICU, and it was adapted through extensive feedback by clinical users during the translation of the system to the neuro-ICU. Consequently, the real-time GUI can facilitate the adoption of the optical system by regular hospital staff, such as neurointensivists and nurses. The wide adoption of diffuse optics as a clinical research tool has the potential to enhance its ability to monitor physiologically meaningful data and can ultimately demonstrate that diffuse optics is a good option for non-invasively monitoring neurocritical patients in real-time.

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Protocol

The protocol was approved by the local committee of the University of Campinas (protocol number 56602516.2.0000.5404). Written informed consent was obtained from the patient or a legal representative prior to the measurements. We monitored patients that were admitted to the Clinics Hospital at the University of Campinas with a diagnosis of either ischemic stroke or a subarachnoid hemorrhage affecting the anterior circulation. Patients with ischemic strokes affecting the posterior circulation, patients with decompressive craniectomies due to elevated intracranial pressure and patients with other neurodegenerative diseases (dementia, Parkinson's or any other disease that can be associated with cortical atrophy) were excluded from the study protocol.

1. Preparations before moving the system to the ICU

  1. Connect all the fibers to the relevant lasers and detectors, and make sure they are properly attached to the optical probe (Figure 1B).
  2. Check that the optical probe is covered with a black cloth to avoid the lasers shining in the room.
  3. Turn the system power switch to the ‘ON’ position. After powering the system, wait 30s and then turn the DCS laser key switch to the ‘ON’ position. The FD-DOS lasers are automatically turned on when the system is powered.
  4. While the system is being prepared, obtain consent from either the participant or a legal representative. After obtaining consent, bring the cart to the patient’s room.
    NOTE: Since the hybrid system has a built-in battery that lasts up to 45 min, it does not need to be turned off during transport.

2. Calibration and gain settings of the DOS system

  1. Upon arrival at the ICU, turn off the DCS laser by switching the key to the ‘OFF’ position.
  2. Starting with the solid phantom marked ‘Calibrate’, run the calibration process on the FD-DOS software (BOXY, ISS) by following the steps below.
    1. On the ‘File’ menu, load the appropriate settings file for the probe being used by clicking on the ‘Load settings file’ option.
    2. Place the probe on the curved side of the phantom, ensuring a good contact with the surface and then optimize the PMT bias voltage by clicking on the ‘Optimize All Detectors’ button in the FD-DOS software.
    3. Run the calibration for multiple source-detector separations by clicking on the option ‘Calc. Waveform Calib. Values for Optical Props. and Multiple Distances’ from the ‘Calibrate’ menu.
    4. Open the ‘User-defined Calculations’ option from the ‘Text-Mon’ menu to check that the measured optical properties match the prespecified values (written in the solid phantom), and that the fitting R2 is close to one.
  3. Repeat the steps above (except step 2.2.3) to measure the optical properties of the phantom marked as ‘Check’ to ensure the calibration was adequate. The measured optical properties should match, within 10%, the values specified in the phantoms.
    CAUTION: Make sure to turn off PMTs (by clicking on the ‘All Detectors OFF’ button) every time the probe is moved to avoid damaging PMTs due to direct illumination from ambient light.
  4. If the calibration is not adequate, re-run the calibration process (steps 2.2 and 2.3). Ensuring a good calibration of the FD-DOS system is essential to the validity of the FD-DOS measurements.

3. Preparation of the participant at the bedside

  1. Use sanitizing wipes to clean both the probe and patient forehead.
  2. Place the double-sided tape on the probe (Figure 1B), ensuring the tape is not in direct contact with the optical fiber tips.
  3. Place a laser safety googles on the subject.
  4. Place the probes over the region-of-interest (ROI) and wrap the elastic straps around the subject’s head. Although not strictly necessary for FD-DOS and DCS, it is advisable to cover the optical probe with a black cloth or black bandage to reduce noise due to ambient light.
    NOTE: It is important to assure that the elastic strap is neither too tight nor too loose. If the strap is too tight it may cause significant discomfort to the patient, and if the strap is too loose it may lead to poor data quality as the double-sided tape is not strong enough to keep the probes in place.
  5. After the probe is properly secured to the patient's forehead, turn on the DCS laser by switching the key to the ‘ON’ position.
    CAUTION: The DCS system uses a Class 3B laser which is hazardous for eye exposure. It is very important to only turn on the lasers when the probe is properly attached to the patient’s forehead.

4. Data quality assessment

  1. Before starting to acquire data with the GUI, write the DCS source-detector separations in the ‘Settings’ tab of the GUI.
    NOTE: The DCS system does not require a calibration step, but the proper input of the source-detector separations is necessary for the real-time analysis (see Supplementary Material for details).
  2. Start the acquisition software by pressing the ‘Start’ button in the GUI and check the DOS signal in the FD-DOS software:
    1. Click on the ‘Optimize All Detectors’ button in the FD-DOS software to optimize the PMT bias voltage.
    2. Check the optical properties and the R2 of the DOS fitting in the ‘User Defined Calculation’ option from the ‘Text-Mon’ menu. The R2 coefficient should be close to unity and, as a rule of thumb, the absorption coefficient of human patients should be within 0.05 and 0.2 cm-1, while the scattering coefficient should be within 6 and 13 cm-113.
  3. Check the DCS signal in the ‘Correlation curves’ tab of the GUI.
    1. Turn on the DCS detectors by turning the switches to the ‘ON’ position.
    2. Ensure that each DCS detector is measuring an adequate light intensity. As a rule of thumb, more than 10 kHz is required.
    3. If the measured intensity is higher than 800 kHz, use a neutral density filter to reduce the photon counts to avoid damaging the detectors. This is typically a problem for shorter (< 1 cm) source-detector separations.
      NOTE: Apart from potentially damaging the DCS detectors, photon counts higher than 800 kHz may also bring errors due to non-linear effects in the detector.
    4. Check the autocorrelation curves to ensure a good skin coupling (see the Representative Results and Figure 2) and reposition the optical probe if necessary.
    5. If the repositioning of the probe was necessary in the previous step, repeat Steps 4.2 and 4.3. These steps may need to be repeated multiple times.
      NOTE: The DCS and the FD-DOS detectors must be turned off each time the probe is moved. To turn the DCS detectors off, manually move the switches to the ‘OFF’ position. The FD-DOS detector is turned off by clicking the ‘All Detectors OFF’ button in the FD-DOS software.
  4. When a good contact between the probe and the skin is achieved, stop the data collection by clicking the ‘Stop’ button in the GUI. Then, set the experiment and patient identifiers in the ‘Folder’ textbox and write the ROI name in the ‘File name’ textbox.
  5. Start the data acquisition by pressing the ‘Start’ button in the GUI.
  6. Collect data in the first ROI for as long as required by the protocol. If necessary, move the probe to the other ROIs and repeat the measurement.
    NOTE: The monitoring period may vary depending on the study goals.

5. Considerations for the experimenter during the measurement

  1. After starting the measurement, write in the ‘Experiment Info’ tab of the GUI the relevant patient information (e.g., type and location of the injury, drugs being administered, age, sex, etc.).
  2. Ensure that any relevant event that occurred during the monitoring period is marked by clicking the ‘Mark’ button on the GUI. After each mark, make sure to write the event description in the ‘Experiment Info’ tab of the GUI.

6. Stop data collection

  1. Stop the data collection by pressing the ‘Stop’ button in the GUI.
  2. Stop the FD-DOS software by pressing the stop data acquisition and recording button represented as two red squares in the FD-DOS software.
  3. Turn off the DCS detectors by flipping the switches to the ‘OFF’ position and turn off the DCS laser by turning the key to the ‘OFF’ position.
  4. Turn off the PMTs of the FD-DOS module by clicking the ‘All Detectors OFF’ button.
  5. Remove the probe from the patient's head and remove the double-sided tape from the probe. Then, clean the probe with sanitizing wipes.
  6. Repeat the measurement of the optical properties of each solid phantom as soon as possible to ensure the calibration remained adequate throughout the monitoring session (see step 4.2.2).
    NOTE: Ideally, the calibration step should be done right after removing the optical probes from the patient's head (step 6.6). However, due to timing issues, in the examples presented in the next section this was done in the storage facility.
  7. Clean the system and its accessories with sanitizing wipes.
  8. Wheel the cart back to the storage room.

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Results

Ideally, the normalized autocorrelation curves obtained with the DCS module should be approximately 1.5 at the zero delay-time extrapolation (when using single-mode fibers14), and the curves should decay to 1 at longer delay times. The curve should be smooth, and it should have a faster decay for the longer source-detector separations. An example of a good autocorrelation is shown in Figure 2A. Figure 2B shows an example of a bad auto-cor...

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Discussion

This paper presented a hybrid optical system that can provide real-time information about cerebral blood flow, cerebral oxygenation, and cerebral oxygen metabolism of neurocritical patients at the beside. The use of diffuse optical techniques had been previously addressed as a potential marker for non-invasive, bedside monitoring in clinical scenarios. A previous study focused on the clinical aspects and the feasibility of optical monitoring during hospitalization in the neuro-ICU through a case report9...

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Disclosures

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: RC Mesquita has one pending patent application and two other patents relevant to this work (United States patents 10,342,488 and 10,064,554). No author currently receives royalties or payments from these patents.

   

Acknowledgements

We acknowledge the support by the São Paulo Research Foundation (FAPESP) through Proc. 2012/02500-8 (RM), 2014/25486-6 (RF) and 2013/07559-3. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
3D PrinterSethi3DS23D-printer used to print the customizable probes
Arduino UNOArduinoUNO REV3Microcontroller responsible to interleave the DCS and FD-DOS measurements
DCS CorrelatorCorrelator.comFlex11-16chComponent of the DCS module
DCS Dectectors IO BoardsExcelitas TechnologySPCM-AQ4C-IOComponent of the DCS module
DCS DetectorsExcelitas TechnologySPCM-AQ4CComponent of the DCS module
DCS LaserCrystaLaserDL785-120-SOComponent of the DCS module
DCS Power supplyArtesynUMP10T-S2A-S2A-S2A-S2A-IES-00-AComponent of the DCS module (power supply for the DCS detecto; 2, 5 and 30V)
FD-DOS fibersISSImagent suppliesThe fibers used for FD-DOS detection and illumination are provived by ISS
Flexible 3D printer materialSethi3DNinjaFlexMaterial used to print the flexible customizable probes
ImagentISSImagentFD-DOS module
Laser safety googlesThorlabsLG9
Multi-mode fiberThorlabsFT400EMTMulti-mode fiber used for DCS illumination
Neutral density filter 1.0 ODEdmund Optics53-705Neutral density filter for the short source detector separations
Single-mode optical fiberThorlabs780HPSingle-mode optical fiber used for the DCS detectors
System batterySMSNET4System battery used for transportation

References

  1. Papanikolaou, J., et al. Cardiac and central vascular functional alterations in the acute phase of aneurysmal subarachnoid hemorrhage. Critical Care Medicine. 40 (1), 223-232 (2012).
  2. Sarrafzadeh, A. S., Vajkoczy, P., Bijlenga, P., Schaller, K. Monitoring in neurointensive care - The challenge to detect delayed cerebral ischemia in high grade aneurysmal SAH. Frontiers in Neurology. 5 (134), (2014).
  3. Messerer, M., Daniel, R. T., Oddo, M. Neuromonitoring after major neurosurgical procedures. Minerva Anestesiologica. 78 (7), 810-822 (2012).
  4. Le Roux, P., et al. Consensus summary statement of the International Multidisciplinary Consensus Conference on Multimodality Monitoring in Neurocritical Care: A statement for healthcare professionals from the Neurocritical Care Society and the European Society of Intensive Care Medicine. Intensive Care Medicine. 40 (9), 1189-1209 (2014).
  5. Roh, D., Park, S. Brain Multimodality Monitoring: Updated Perspectives. Current Neurology and Neuroscience Reports. 16 (6), 1-10 (2016).
  6. Oddo, M., Villa, F., Citerio, G. Brain multimodality monitoring: An update. Current Opinion in Critical Care. 18 (2), 111-118 (2012).
  7. Sandsmark, D. K., Kumar, M. A., Park, S., Levine, J. M. Multimodal Monitoring in Subarachnoid Hemorrhage. Stroke. 43 (5), 1440-1445 (2012).
  8. Baker, W. B., et al. Continuous non-invasive optical monitoring of cerebral blood flow and oxidative metabolism after acute brain injury. Journal of Cerebral Blood Flow and Metabolism. 39 (8), 1469-1485 (2019).
  9. Menezes Forti, R., et al. Real-time non-invasive assessment of cerebral hemodynamics with diffuse optical spectroscopies in a neuro intensive care unit: an observational study. Frontiers in Medicine. 7 (147), (2020).
  10. Kim, M. N., et al. Noninvasive measurement of cerebral blood flow and blood oxygenation using near-infrared and diffuse correlation spectroscopies in critically brain-injured adults. Neurocritical Care. 12 (2), 173-180 (2010).
  11. Selb, J., et al. Prolonged monitoring of cerebral blood flow and autoregulation with diffuse correlation spectroscopy in neurocritical care patients. Neurophotonics. 5 (04), 1(2018).
  12. Durduran, T., Choe, R., Baker, W. B., Yodh, A. G. Diffuse optics for tissue monitoring and tomography. Reports on Progress in Physics. 73 (7), 76701(2010).
  13. Jacques, S. L. Optical properties of biological tissues: a review. Physics in Medicine and Biology. 58 (11), 37-61 (2013).
  14. Durduran, T., Yodh, A. G. Diffuse correlation spectroscopy for non-invasive, micro-vascular cerebral blood flow measurement. NeuroImage. 85, 5163(2014).
  15. Durduran, T., et al. Diffuse optical measurement of blood flow, blood oxygenation, and metabolism in a human brain during sensorimotor cortex activation. Optics Letters. 29 (15), 1766(2004).
  16. Selb, J., et al. Sensitivity of near-infrared spectroscopy and diffuse correlation spectroscopy to brain hemodynamics: simulations and experimental findings during hypercapnia. Neurophotonics. 1 (1), 15005(2014).
  17. Shang, Y., Li, T., Yu, G. Clinical applications of near-infrared diffuse correlation spectroscopy and tomography for tissue blood flow monitoring and imaging. Physiological Measurement. 38 (4), 1-26 (2017).
  18. Mesquita, R. C., et al. Direct measurement of tissue blood flow and metabolism with diffuse optics. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 369 (1955), 4390-4406 (2011).
  19. Culver, J. P., et al. Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia. Journal of Cerebral Blood Flow and Metabolism. 23 (8), 911-924 (2003).
  20. Valabrègue, R., Aubert, A., Burger, J., Bittoun, J., Costalat, R. Relation between Cerebral Blood Flow and Metabolism Explained by a Model of Oxygen Exchange. Journal of Cerebral Blood Flow and Metabolism. 23 (5), 536-545 (2003).
  21. Farzam, P., et al. Shedding light on the neonatal brain: probing cerebral hemodynamics by diffuse optical spectroscopic methods. Scientific Reports. 7 (1), 15786(2017).
  22. Wong, F. Cerebral blood flow measurements in the neonatal brain. Prenatal and Postnatal Determinants of Development. 109, 69-87 (2016).
  23. Busch, D. R., et al. Noninvasive optical measurement of microvascular cerebral hemodynamics and autoregulation in the neonatal ECMO patient. Pediatric Research. , 1-9 (2020).
  24. Dehaes, M., et al. Cerebral oxygen metabolism in neonatal hypoxic ischemic encephalopathy during and after therapeutic hypothermia. Journal of Cerebral Blood Flow and Metabolism. 34 (1), 87-94 (2014).
  25. Ferradal, S. L., et al. Non-invasive assessment of cerebral blood flow and oxygen metabolism in neonates during hypothermic cardiopulmonary bypass: Feasibility and clinical implications. Scientific Reports. 7 (1), 44117(2017).
  26. Busch, D. R., et al. Continuous cerebral hemodynamic measurement during deep hypothermic circulatory arrest. Biomedical Optics Express. 7 (9), 3461(2016).
  27. Wang, D., et al. Fast blood flow monitoring in deep tissues with real-time software correlators. Biomedical Optics Express. 7 (3), 776(2016).
  28. Ko, T. S., et al. Non-invasive optical neuromonitoring of the temperature-dependence of cerebral oxygen metabolism during deep hypothermic cardiopulmonary bypass in neonatal swine. Journal of Cerebral Blood Flow & Metabolism. 40 (1), 187-203 (2018).
  29. Pennekamp, C. W. A. A., et al. Near-infrared spectroscopy can predict the onset of cerebral hyperperfusion syndrome after carotid endarterectomy. Cerebrovascular Diseases. 34 (4), 314-321 (2012).
  30. Pennekamp, C. W. A. A., Bots, M. L., Kappelle, L. J., Moll, F. L., de Borst, G. J. The Value of Near-Infrared Spectroscopy Measured Cerebral Oximetry During Carotid Endarterectomy in Perioperative Stroke Prevention. A Review. European Journal of Vascular and Endovascular Surgery. 38 (5), 539-545 (2009).
  31. Shang, Y., et al. Cerebral monitoring during carotid endarterectomy using near-infrared diffuse optical spectroscopies and electroencephalogram. Physics in Medicine and Biology. 56 (10), 3015-3032 (2011).
  32. Delgado-Mederos, R., et al. Transcranial diffuse optical assessment of the microvascular reperfusion after thrombolysis for acute ischemic stroke. Biomedical Optics Express. 9 (3), 1262(2018).
  33. Favilla, C. G., et al. Optical Bedside Monitoring of Cerebral Blood Flow in Acute Ischemic Stroke Patients During Head-of-Bed Manipulation. Stroke. 45 (5), 1269-1274 (2014).
  34. Gregori-Pla, C., et al. Early microvascular cerebral blood flow response to head-of-bed elevation is related to outcome in acute ischemic stroke. Journal of Neurology. 266 (4), 990-997 (2019).
  35. Kim, M. N., et al. Continuous optical monitoring of cerebral hemodynamics during head-of-bed manipulation in brain-injured adults. Neurocritical Care. 20 (3), 443-453 (2014).
  36. Ko, T., et al. Prediction of Return of Spontaneous Circulation During Cardiopulmonary Resuscitation using Frequency-Domain Diffuse Optical Spectroscopy in a Pediatric Swine Model of Asphyxial Cardiac Arrest. Biophotonics Congress: Biomedical Optics Congress 2018 (Microscopy/Translational/Brain/OTS). , (2018).
  37. Favilla, C. G., et al. Non-invasive respiratory impedance enhances cerebral perfusion in healthy adults. Frontiers in Neurology. 8, (2017).
  38. Favilla, C. G., et al. Perfusion Enhancement with Respiratory Impedance After Stroke (PERI-Stroke). Neurotherapeutics. 16 (4), 1296-1303 (2019).
  39. Ritzenthaler, T., et al. Cerebral near-infrared spectroscopy a potential approach for thrombectomy monitoring. Stroke. 48 (12), 3390-3392 (2017).
  40. Fantini, S., Sassaroli, A., Tgavalekos, K. T., Kornbluth, J. Cerebral blood flow and autoregulation: current measurement techniques and prospects for noninvasive optical methods. Neurophotonics. 3 (3), 31411(2016).
  41. Parthasarathy, A. B., et al. Dynamic autoregulation of cerebral blood flow measured non-invasively with fast diffuse correlation spectroscopy. Journal of Cerebral Blood Flow and Metabolism. 38 (2), 230-240 (2018).
  42. Kainerstorfer, J. M., Sassaroli, A., Tgavalekos, K. T., Fantini, S. Cerebral autoregulation in the microvasculature measured with near-infrared spectroscopy. Journal of Cerebral Blood Flow and Metabolism. 35 (6), 959-966 (2015).
  43. Baker, W. B., et al. Noninvasive optical monitoring of critical closing pressure and arteriole compliance in human subjects. Journal of Cerebral Blood Flow and Metabolism. 37 (8), 2691-2705 (2017).
  44. Lin, P. Y., et al. Non-invasive optical measurement of cerebral metabolism and hemodynamics in infants. Journal of Visualized Experiments. (73), e4379(2013).
  45. Wintermark, P., Hansen, A., Warfield, S. K., Dukhovny, D., Soul, J. S. Near-infrared spectroscopy versus magnetic resonance imaging to study brain perfusion in newborns with hypoxic-ischemic encephalopathy treated with hypothermia. NeuroImage. 85, 287-293 (2014).
  46. Busch, D. R., et al. Detection of brain hypoxia based on noninvasive optical monitoring of cerebral blood flow with diffuse correlation spectroscopy. Neurocritical Care. 30 (1), 72-80 (2019).
  47. Davies, D. J., et al. Cerebral oxygenation in traumatic brain injury: Can a non-invasive frequency domain near-infrared spectroscopy device detect changes in brain tissue oxygen tension as well as the established invasive monitor. Journal of Neurotrauma. 36 (7), 1175-1183 (2019).
  48. Leal-Noval, S. R., et al. Invasive and noninvasive assessment of cerebral oxygenation in patients with severe traumatic brain injury. Intensive Care Medicine. 36 (8), 1309-1317 (2010).
  49. Fantini, S., Franceschini, M. A., Fishkin, J. B., Barbieri, B., Gratton, E. Quantitative determination of the absorption spectra of chromophores in strongly scattering media: a light-emitting-diode based technique. Applied Optics. 33 (22), 5204(1994).
  50. Fantini, S., et al. Frequency-domain multichannel optical detector for noninvasive tissue spectroscopy and oximetry. Optical Engineering. 34 (1), 32(1995).
  51. Carpenter, D. A., Grubb, R. L., Tempel, L. W., Powers, W. J. Cerebral oxygen metabolism after aneurysmal subarachnoid hemorrhage. Journal of Cerebral Blood Flow and Metabolism. 11 (5), 837-844 (1991).
  52. Johansen-Berg, H., et al. The role of ipsilateral premotor cortex in hand movement after stroke. Proceedings of the National Academy of Sciences, U.S.A. 99 (22), 14518-14523 (2002).
  53. Hunt, W. E., Hess, R. M. Surgical risk as related to time of intervention in the repair of intracranial aneurysms. Journal of Neurosurgery. 28 (1), 14-20 (1968).
  54. Fisher, C. M., Kistler, J. P., Davis, J. M. Relation of Cerebral Vasospasm to Subarachnoid Hemorrhage Visualized by Computerized Tomographic Scanning. Neurosurgery. 6 (1), 1-9 (1980).
  55. Carey, J. R., et al. Analysis of fMRI and finger tracking training in subjects with chronic stroke. Brain. 125 (4), 773-788 (2002).
  56. Lindenberg, R., Renga, V., Zhu, L. L., Nair, D., Schlaug, G. Bihemispheric brain stimulation facilitates motor recovery in chronic stroke patients. Neurology. 75 (24), 2176-2184 (2010).
  57. Schaechter, J. D., et al. Motor recovery and cortical reorganization after constraint-induced movement therapy in stroke patients: A preliminary study. Neurorehabilitation and Neural Repair. 16 (4), 326-338 (2002).
  58. Dehaes, M., et al. Assessment of the frequency-domain multi-distance method to evaluate the brain optical properties: Monte Carlo simulations from neonate to adult. Biomedical Optics Express. 2 (3), 552(2011).
  59. Fantini, S., Sassaroli, A. Frequency-domain techniques for cerebral and functional near-infrared spectroscopy. Front Neurosci. 14, 1-18 (2020).
  60. Blaney, G., Sassaroli, A., Pham, T., Fernandez, C., Fantini, S. Phase dual-slopes in frequency-domain near-infrared spectroscopy for enhanced sensitivity to brain tissue: First applications to human subjects. Journal of Biophotonics. 13 (1), 201960018(2020).
  61. Abdalsalam, O., O'Sullivan, T. D., Howard, S., Zhang, Y. Self-calibrated frequency domain diffuse optical spectroscopy with a phased source array. Optical Tomography and Spectroscopy of Tissue XIII Conference. 1087403, 2(2019).
  62. Applegate, M. B., Istfan, R. E., Spink, S., Tank, A., Roblyer, D. Recent advances in high speed diffuse optical imaging in biomedicine Recent advances in high speed diffuse optical imaging in biomedicine. APL Photonics. 5, 040802(2020).
  63. Torricelli, A., et al. Time domain functional NIRS imaging for human brain mapping. NeuroImage. 85, 28-50 (2014).
  64. Pifferi, A., et al. New frontiers in time-domain diffuse optics , a review. Journal of Biomedical Optics. 21 (9), 091310(2016).
  65. Gagnon, L., Desjardins, M., Jehanne-Lacasse, J., Bherer, L., Lesage, F. Investigation of diffuse correlation spectroscopy in multi-layered media including the human head. Optics Express. 16 (20), 15514(2008).
  66. Verdecchia, K., et al. Assessment of a multi-layered diffuse correlation spectroscopy method for monitoring cerebral blood flow in adults. Biomedical Optics Express. 7 (9), 3659(2016).
  67. Liemert, A., Kienle, A. Light diffusion in a turbid cylinder II Layered case. Optics Express. 18 (9), 9266(2010).
  68. Hallacoglu, B., Sassaroli, A., Fantini, S. Optical characterization of two-layered turbid media for non-invasive, absolute oximetry in cerebral and extracerebral tissue. PLoS One. 8 (5), 64095(2013).
  69. Alexandrakis, G., Busch, D. R., Faris, G. W., Patterson, M. S. Determination of the optical properties of two-layer turbid media by use of a frequency-domain hybrid Monte Carlo diffusion model. Applied Optics. 40 (22), 3810(2001).
  70. Martelli, F., Sassaroli, A., Del Bianco, S., Yamada, Y., Zaccanti, G. Solution of the time-dependent diffusion equation for layered diffusive media by the eigenfunction method. Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics. 67 (5), 14(2003).
  71. Mesquita, R. C., et al. Influence of probe pressure on the diffuse correlation spectroscopy blood flow signal: extra-cerebral contributions. Biomedical Optics Express. 4 (7), 978(2013).
  72. Wang, D., et al. Influence of probe pressure on the pulsatile diffuse correlation spectroscopy blood flow signal on the forearm and forehead regions. Neurophotonics. 6 (03), 1(2019).
  73. Baker, W. B., et al. Pressure modulation algorithm to separate cerebral hemodynamic signals from extracerebral artifacts. Neurophotonics. 2 (3), 35004(2015).
  74. He, L., et al. Noninvasive continuous optical monitoring of absolute cerebral blood flow in critically ill adults. Neurophotonics. 5 (04), 1(2018).
  75. Milej, D., et al. Quantification of cerebral blood flow in adults by contrast-enhanced near-infrared spectroscopy: Validation against MRI. Journal of Cerebral Blood Flow & Metabolism. , (2019).
  76. Diop, M., Verdecchia, K., Lee, T. Y., St Lawrence, K. Calibration of diffuse correlation spectroscopy with a time-resolved near-infrared technique to yield absolute cerebral blood flow measurements. Biomedical Optics Express. 2 (7), 2068(2011).
  77. Khalid, M., et al. Development of a stand-alone DCS system for monitoring absolute cerebral blood flow. Biomedical Optics Express. 10 (9), 4607(2019).
  78. Kohl-Bareis, M., et al. Noninvasive monitoring of cerebral blood flow by a dye bolus method: Separation of brain from skin and skull signals. Journal of Biomedical Optics. 7 (3), 464(2002).

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Erratum


Formal Correction: Erratum: Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies
Posted by JoVE Editors on 12/07/2022. Citeable Link.

An erratum was issued for: Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies. The Authors section was updated from:

Rodrigo Menezes Forti1,2
Marilise Katsurayama2,3
Lenise Valler2,3
Andrés Quiroga1,2
Luiz Simioni1
Julien Menko4
Antonio L. E. Falcão3
Li Min Li2,5
Rickson C. Mesquita1,2
1Institute of Physics, University of Campinas
2Brazilian Institute of Neuroscience and Neurotechnology
3Clinical Hospital, University of Campinas
4Department of Emergency Medicine, Albert Einstein College of Medicine
5School of Medical Sciences, University of Campinas

to:

Rodrigo Menezes Forti1,2
Marilise Katsurayama2,3
Giovani Grisotti Martins1
Lenise Valler2,3
Andrés Quiroga1,2
Luiz Simioni1
Julien Menko4
Antonio L. E. Falcão3
Li Min Li2,5
Rickson C. Mesquita1,2
1Institute of Physics, University of Campinas
2Brazilian Institute of Neuroscience and Neurotechnology
3Clinical Hospital, University of Campinas
4Department of Emergency Medicine, Albert Einstein College of Medicine
5School of Medical Sciences, University of Campinas

Tags

Cerebral Blood FlowCerebral OxygenationDiffuse Correlation SpectroscopyOptical Probe CalibrationPatient-Specific PhysiologyBedside MonitoringCerebral Oxygen Metabolism
Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies
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