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).
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.
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
- Connect all the fibers to the relevant lasers and detectors, and make sure they are properly attached to the optical probe (Figure 1B).
- Check that the optical probe is covered with a black cloth to avoid the lasers shining in the room.
- 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.
- 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
- Upon arrival at the ICU, turn off the DCS laser by switching the key to the ‘OFF’ position.
- Starting with the solid phantom marked ‘Calibrate’, run the calibration process on the FD-DOS software (BOXY, ISS) by following the steps below.
- On the ‘File’ menu, load the appropriate settings file for the probe being used by clicking on the ‘Load settings file’ option.
- 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.
- 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.
- 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.
- 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.
- 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
- Use sanitizing wipes to clean both the probe and patient forehead.
- Place the double-sided tape on the probe (Figure 1B), ensuring the tape is not in direct contact with the optical fiber tips.
- Place a laser safety googles on the subject.
- 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.
- 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
- 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).
- Start the acquisition software by pressing the ‘Start’ button in the GUI and check the DOS signal in the FD-DOS software:
- Click on the ‘Optimize All Detectors’ button in the FD-DOS software to optimize the PMT bias voltage.
- 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.
- Check the DCS signal in the ‘Correlation curves’ tab of the GUI.
- Turn on the DCS detectors by turning the switches to the ‘ON’ position.
- Ensure that each DCS detector is measuring an adequate light intensity. As a rule of thumb, more than 10 kHz is required.
- 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.
- Check the autocorrelation curves to ensure a good skin coupling (see the Representative Results and Figure 2) and reposition the optical probe if necessary.
- 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.
- 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.
- Start the data acquisition by pressing the ‘Start’ button in the GUI.
- 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
- 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.).
- 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
- Stop the data collection by pressing the ‘Stop’ button in the GUI.
- Stop the FD-DOS software by pressing the stop data acquisition and recording button represented as two red squares in the FD-DOS software.
- 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.
- Turn off the PMTs of the FD-DOS module by clicking the ‘All Detectors OFF’ button.
- Remove the probe from the patient's head and remove the double-sided tape from the probe. Then, clean the probe with sanitizing wipes.
- 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.
- Clean the system and its accessories with sanitizing wipes.
- Wheel the cart back to the storage room.
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-correlation curve; in this example it is not possible to distinguish the curves for the different source-detector separations. Figure 2C shows another example of a bad auto-correlation curve, in which the tail of the curve did not match the model used. The issue in both curves (Figure 2B,C) are related either to a bad coupling of the probe onto the skin or to light leakage from the source directly into the shorter source-detector separations.
As an example of the importance of displaying the neurophysiology at different time windows to correctly interpret changes seen in real-time before relating changes to clinical behavior, Figure 3 shows the time-series of a monitoring session from a sedated stroke patient, as seen on the GUI by the critical care personnel. During part of the monitoring session, the clinicians were suctioning the patient’s bronchial and oral secretions (represented by the shaded area in Figure 3). The patient motion induced by the intervention clearly disturbs the optical signal, which leads to the unphysiological spikes in the optical parameters; therefore, it is hard to attribute any physiological meaning to these changes. Soon after the intervention, the hemodynamic parameters returned to approximately the same values before the intervention, as expected for a stable patient. This example illustrates the stability of the real-time system in the neuro-ICU, as well as the importance of analyzing a patient's hemodynamics at different temporal windows.
In order to illustrate the feasibility of the hybrid diffuse optical device to provide meaningful information in the neuro-ICU, we present the case of a 50-year-old woman with a history of diabetes, hypertension, and congestive heart failure, who was admitted with left sided hemiparesis and was found to have an ischemic stroke due to occlusion of the right MCA (NIH stroke scale = 11). Figure 4 shows the average optical-derived parameters and the CT scan at the thirteenth day after hospitalization, while the patient was intubated and sedated. During this monitoring session, CBF and CMRO2 in the ipsilesional forehead were considerably lower than their contralesional parameters in the symmetric region. This result is consistent with a perfusion deficit and subsequent tissue necrosis caused by a large vessel ischemia. Notably, although CBF was lower in the ipsilesional hemisphere, a high OEF was found in both hemispheres. This may be consistent with the idea of misery perfusion, a state in which there is high oxygen consumption (high OEF) despite low (but non-zero) CBF as the tissue attempts to promote recovery8,51,52. Currently, misery perfusion is hard to diagnose in the neuro-ICU. Although a larger study with acute ischemic stroke patients is needed to assess the sensitivity of diffuse optical spectroscopies to detect misery perfusion, this example demonstrates the potential of the diffuse optical system to assess clinically important information in real-time.
Lastly, we present the longitudinal results obtained from a 62-year-old female who was admitted to the neuro-ICU due to a severe right middle cerebral artery (MCA) aneurysmal subarachnoid hemorrhage, with Grade V on the Hunt & Hess scale (i.e., predicting a poor outcome and a low likelihood of survival)53 and Grade III on the Fisher Scale (i.e., low to high risk of vasospasm)54. This patient was monitored throughout the hospitalization, and all the cerebral hemodynamic parameters were consistent with the clinical evolution of the patient’s condition. We refer the interested reader to a recently published case-report that contains the complete description of this case9. To illustrate the feasibility of performing measurements on different days, Figure 5 shows an offline analysis of data collected with the system at several sessions during hospitalization of the case described above and presented in details in ref.9. Here, the laterality index (LI) was computed for each physiological parameter as:
where X represents the variable measured (i.e., CBF, OEF, CMRO2), and the subscript denotes the brain hemisphere. With the LI it is possible to directly compare the differences across each hemisphere over the entire hospitalization. The laterality index has been shown to be very useful for different clinical scenarios52,55,56,57, and it can be readily assessed with the protocol presented here by sequentially measuring symmetrical regions in both hemispheres. The mean arterial pressure (MAP) was collected with an independent instrument available in the neuro-ICU, and it is also shown in Figure 5 for reference.
Careful analysis of Figure 5 reveals two significant periods of hemispheric impairment. The first period occurred between the first and the third days after hospitalization, in which all the neurophysiological parameters in the ipsilesional ROI increased more than in the symmetrical contralesional ROI. This increase in LI on the third day after hospitalization could be an indicative of a possible homeostatic attempt to restore the metabolic balance of the affected tissue. During the second period, starting after the third day of hospitalization, the LI continuously decreased, which was consistent with the worsening condition of the patient. In this case, the patient died after 9 days of hospitalization.
Figure 1: The optical environment developed to monitor patients inside an intensive care unit. (A) The hybrid diffuse optical system combines a frequency-domain diffuse optical spectroscopy (DOS) module and a diffuse correlation spectroscopy (DCS) module. (B) The customizable probe proposed in this study has as a default 4 source-detector separations (0.7, 1.5, 2.5 and 3.0 cm) for DCS and 4 source-detector separations for DOS (1.5, 2.0, 2.5 and 3.0 cm). For simplicity, the examples presented here only used the 2.5 cm source-detector separation for DCS. (C) The real-time graphical user interface (GUI) controls the diffuse optical system, and displays the measured cerebral blood flow (CBF), the oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO2) in real-time, both within a 5 min time window (left panels), and within a 2 h time window (right panels). On the bottom of the GUI, the researcher can press buttons to start and stop the data collection, to acquire a baseline period for comparison and to mark any relevant intervention(s). Please click here to view a larger version of this figure.
Figure 2: Representative autocorrelation curves for the DCS module. (A) An example of a good autocorrelation, which was approximately 1.5 at the zero delay-time extrapolation and decayed to 1 at longer delay times. As expected, the autocorrelation curves decayed faster for the longer source-detector separations. (B) An example of a bad auto-correlation curve, where it is not possible to distinguish the curves for the different source-detector separations. (C) Another example of a bad auto-correlation curve, in which the tail of the curve did not match the model used. The issues in (B) and (C) are related to either bad coupling of the probe onto the skin or to light leakage from the source directly into the shorter source-detector separations. The researcher can look at the curves on the ‘Correlation Curves’ Tab on the GUI. Please click here to view a larger version of this figure.
Figure 3: Cerebral physiology of a monitoring session from a sedated stroke patient, as would be seen on the GUI by the critical care personnel. The GUI displays the cerebral blood flow (CBF, in red), the oxygen extraction fraction (OEF, in blue) and the cerebral metabolic rate of oxygen (CMRO2, in green) in real-time for both (A) short (i.e., 5 min) and (B) long (i.e., 2 h) time windows as well as an (C) average value over the last 5 min. During part of this monitoring session, clinicians were suctioning the patient’s bronchial and oral secretions (represented by the shaded area in B). Please click here to view a larger version of this figure.
Figure 4: Neurophysiological information of a patient diagnosed with severe ischemic stroke in the right middle-cerebral artery on the thirteenth day after hospitalization. (A) Cerebral blood flow (CBF), oxygen extraction fraction (OEF), cerebral metabolic rate of oxygen (CMRO2) and total hemoglobin concentration (HbT) measured with the diffuse optical system in the contralesional and the ipsilesional hemispheres. (B) Computed tomography (CT) scan from the single-day measurement of the patient. The red areas in the CT images represent the presumed optical sensitivity region and the purple ellipse shows the approximate injury location. Please click here to view a larger version of this figure.
Figure 5: Temporal evolution of the laterality index for the optically derived physiological parameters in a 62-year old female patient following a high-grade aneurysmal subarachnoid hemorrhage (aSAH). The changes in the ipsilesional region of interest (ROI) compared to the changes in the contralesional ROI are shown in the left axis for cerebral blood flow (CBF, red circles), oxygen extraction fraction (OEF, blue diamond) and cerebral metabolic rate of oxygen (CMRO2, green triangles). The evolution of the mean arterial pressure (MAP, gray squares) was collected independently, and is shown in the right-axis for comparison. The error bars of each point represent the standard deviation of each parameter across the monitoring session. For some days, the standard deviation was too small to be shown. Please click here to view a larger version of this figure.
Supplementary Materials. Please click here to download this file.
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. The focus of this work is to detail relevant and innovative aspects related to real-time monitoring with diffuse optics. Specifically, this paper proposed a real-time GUI that provides clear and useful information for clinicians. The GUI allows for easy comparison of different time periods, which is important for interpreting clinically relevant data. The implementation of the GUI presented here can be easily translated for DCS system based on a software-correlator with the caveat that the real-time display frequency must be limited to ~20 Hz. Real-time averaging of the autocorrelation curves can be used to down sample faster acquisition rates. In the future, real-time information provided by the proposed protocol may be used to guide therapy, potentially improving the clinical outcome of neurocritical patients.
This work also proposes the use of a customizable optical probe that can address different settings and therefore suit different purposes and needs for clinicians. The proper selection of the source-detector separation is a critical step for maximizing the cerebral sensitivity of diffuse optics. In most cases, an optimal probe for DCS measurements in adults should have at least a short (< 1 cm) and a long (> 2.5 cm) source-detector separation. The long source-detector separation was shown to provide the best compromise between signal-to-noise ratio (SNR) and cerebral sensitivity12,14,16, while the short separation is mostly sensitive to the extra-cerebral tissues and is useful to differentiate the extra-cerebral changes from cerebral changes12,16. For FD-DOS, a simple probe that provides a reasonable compromise between SNR and cerebral sensitivity in adults contains 4 source-detector separations (1.5, 2.0, 2.5 and 3.0 cm)58. The most critical step for a FD-DOS measurement is the calibration procedure that is necessary to compare the AC and phase changes from different fibers (Section 2 of the protocol). A poor calibration of a FD-DOS system can lead to large errors in the retrieved values of the optical properties of the tissue, which will affect the accuracy of both the cerebral oxygenation and cerebral blood flow values. Of importance, the protocol proposed in this study focus in an optical probe for FD-DOS that contains a single PMT and multiple light sources. The calibration procedure described here needs to be modified for experiments utilizing multiple detectors. For studies using multiple detectors, the bias voltage of the PMT should not be changed during the calibration procedure, and thus a careful selection of the optical properties of the calibration phantoms is necessary.
In addition to the cerebral oxygenation measurements, the DOS module also improves the calculation of CBF, as the DCS model also depends on the optical properties of the tissue. This study employed a commercial FD-DOS system with a single modulation frequency to recover the optical properties and the cerebral oxygenation. However, there are other alternatives that could provide more accurate information, such as time domain DOS or multi-frequency FD-DOS systems59,60,61,62,63,64. These systems may reduce the experimental complexity as they require a single source-detector separation to recover the cerebral physiology, whereas the traditional FD-DOS employed here requires multiple source-detector separations and thus multiple fibers attached to the head. Additionally, since the main interest of this protocol was the long-term trends in the cerebral physiology, this study opted to conduct interleaved DOS and DCS measurements. In the future, to avoid cross-contamination and to increase the sampling frequency, it is possible to acquire simultaneous DOS and DCS measurements by including notch filters on the DOS and DCS detectors.
One limitation of the current protocol is the restriction of the probe placement to the forehead. As of now, it is difficult to acquire DCS measurements through hair. This is not an issue for insults covering a larger portion of the brain, as is mostly often the case in the neuro-ICU. However, measurements on the forehead may not be sensitive to small MCA or PCA strokes, for example. With further improvements of the optical probes, it may be possible to measure through the hair, and by combining the system with a neuro navigation device it would be possible to make measurements over a small local ROI. By gathering detailed spatial information onto the optical information, we expect a marked improvement in the sensitivity of diffuse optics to the hemodynamic impairments due to focal cerebrovascular disorders.
Finally, it is important to mention a few limitations of the diffuse optical techniques. First, diffuse optics is inherently sensitive to the extra-cerebral tissue, and better modeling of the data may be necessary to properly account for the difference in the extra-cerebral and cerebral physiologies65,66,67,68,69,70. Additionally, the DCS measurement of CBF is sensitive to the external pressure of the optical probe against the tissue. For example, by increasing the probe pressure we reduce the blood flow in the external tissues, which will also reduce the CBF measured by DCS71,72,73. Note, however, that although the CBF is reduced due to increasing probe pressure, the heart rate pulsatility of CBF is unchanged72. Interestingly, it is possible to use these changes in CBF due to the external probe pressure to separate the extra-cerebral and cerebral physiologies73. Last, the optical derived CBF has physical units (i.e., cm2/s) rather than the more usual clinical units (i.e., ml/100g of tissue/min). Some authors have proposed the use of indocyanine-green (ICG) to recover absolute CBF from DOS and to calibrate the CBF index from DCS to absolute clinical units74,75,76,77,78. However, the accuracy of the calibration factor from ICG may not be directly translated to different situations due to abnormalities in the macro and microcirculation following brain trauma.
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.
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.
|3D Printer||Sethi3D||S2||3D-printer used to print the customizable probes|
|Arduino UNO||Arduino||UNO REV3||Microcontroller responsible to interleave the DCS and FD-DOS measurements|
|DCS Correlator||Correlator.com||Flex11-16ch||Component of the DCS module|
|DCS Dectectors IO Boards||Excelitas Technology||SPCM-AQ4C-IO||Component of the DCS module|
|DCS Detectors||Excelitas Technology||SPCM-AQ4C||Component of the DCS module|
|DCS Laser||CrystaLaser||DL785-120-SO||Component of the DCS module|
|DCS Power supply||Artesyn||UMP10T-S2A-S2A-S2A-S2A-IES-00-A||Component of the DCS module (power supply for the DCS detecto; 2, 5 and 30V)|
|FD-DOS fibers||ISS||Imagent supplies||The fibers used for FD-DOS detection and illumination are provived by ISS|
|Flexible 3D printer material||Sethi3D||NinjaFlex||Material used to print the flexible customizable probes|
|Laser safety googles||Thorlabs||LG9|
|Multi-mode fiber||Thorlabs||FT400EMT||Multi-mode fiber used for DCS illumination|
|Neutral density filter 1.0 OD||Edmund Optics||53-705||Neutral density filter for the short source detector separations|
|Single-mode optical fiber||Thorlabs||780HP||Single-mode optical fiber used for the DCS detectors|
|System battery||SMS||NET4||System battery used for transportation|
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