2.1.

Animal Preparation and Measurement Procedure

Animal procedures were conducted in accordance with the guidelines established by the National Institutes of Health and were approved by the Institutional Animal Care and Use Committee at the University of Pennsylvania. Eighteen anesthetized three- to five-day-old female piglets were used for the study. Each animal in group 1 $(n=10)$ received a single rotational injury, each animal in group 2 $(n=4)$ received a sham injury, and each animal in group 3 $(n=4)$ received a single rotational injury and a $5\text{-}\min$ hypertonic saline infusion at $30\min$ postinjury (see Table 1 ). Each animal was intubated and maintained on 2.0–2.5% isoflurane. Catheters were placed in the femoral arteries for blood pressure monitoring and reference microsphere blood withdrawals, in the femoral vein for saline and phenylephrine infusion, and in the left ventricle of the heart via the right carotid artery for fluorescent microsphere injections. Vital physiological parameters, including MAP (in mmHg), HR in beats per minute (BPM), arterial oxygen saturation [ $\mathrm{Sa}{\mathrm{O}}_2$ (in percent)], end-tidal $\mathrm{C}{\mathrm{O}}_2$ [ $\mathrm{Et}\mathrm{C}{\mathrm{O}}_2$ (in mmHg)], and body temperature [ $T$ (in degrees Celsius)] were manually recorded every $5\min$ for the duration of each study; continuous recordings were conducted whenever available. Supplemental oxygen and mechanical ventilator support were used as needed to maintain normoxia and normocarpnia.

Table 1

Summary of all animals used in the study. CA+ : cardiac arrest; HS* : hypertonic (3 %) saline.

The piglet scalp was shaved for the optical measurements, and baseline optical readings were obtained. The optical probe was then removed, and the piglet head was secured to a padded snout clamp mounted to the linkage assembly of a HYGE pneumatic actuator (Bendix Corp., Southfield, Michigan), which converts an impulsive linear motion to a rotational motion.² Immediately prior to injury, anesthesia was withdrawn. Brain injury was induced by a single rapid, nonimpact $90\mathrm{deg}$ rotation of the head in the horizontal plane, with a mean peak-angular velocity of $204\mathrm{rad}∕\mathrm{s}$ in group 1 and $209\mathrm{rad}∕\mathrm{s}$ in group 3. The center of rotation was the midcervical spine. After injury, the animal was taken off the snout clamp, and the optical probe was repositioned on the scalp. Reflexive withdrawal to a pinch stimulus was assessed every minute for the first $15\min$ , then every $3\min$ thereafter. When the pinch reflex was positive, indicating return of consciousness, anesthesia was resumed. Phenylephrine was administered as needed to maintain MAP above $40\mathrm{mmHg}$ and within $10\mathrm{mmHg}$ of preinjury baseline levels. Changes in cerebral blood oxygenation, hemoglobin concentration, and blood flow relative to baseline were continuously measured with the optical probe beginning within the first $2–5\min$ after injury and until $6\mathrm{h}$ postinjury. Spontaneous physiological events, such as apnea (a period when an animal suspends breathing³⁰) and cardiac arrest, and physiological perturbations, such as hypertonic saline infusion, were noted during the monitoring period and were used to investigate possible hemodynamic signatures in corresponding optical recordings. At $6\mathrm{h}$ postinjury, each piglet was sacrificed by an overdose of pentabarbital and the brain was perfusion fixed in formalin for fluorescent microsphere analysis.

2.2.

DRS

DRS was employed to measure cerebral blood oxygenation and hemoglobin concentrations of tissues located several centimeters into the brain through intact scalp and skull. A semi-infinite differential path-length factor method based on a modified Beer–Lambert law ^{23, 31} was employed to analyze the changes in light absorption $\left({\mu }_{\mathrm{a}}\right)$ at each wavelength (685, 785, and $830\mathrm{nm}$ ). Changes in oxy-hemoglobin concentration $\left(\Delta \mathrm{Hb}{\mathrm{O}}_2\right)$ and deoxy-hemoglobin concentration $\left(\Delta \mathrm{Hb}\right)$ were extracted from the wavelength-dependent $\Delta {\mu }_{\mathrm{a}}$ . The combination of these data yielded changes in total hemoglobin concentration $(\mathrm{THC}=\Delta \mathrm{Hb}{\mathrm{O}}_2+\Delta \mathrm{Hb}+{\mathrm{THC}}_0)$ and blood oxygen saturation $(\mathrm{St}{\mathrm{O}}_2=[(\Delta \mathrm{Hb}{\mathrm{O}}_2+{\mathrm{THC}}_0\cdot \mathrm{St}{\mathrm{O}}_{20})∕\mathrm{THC}]\times 100\%)$ , wherein the baseline THC $\left({\mathrm{THC}}_0\right)$ and blood oxygenation $\left(\mathrm{St}{\mathrm{O}}_{20}\right)$ in the healthy piglet brain were assumed to be $42\mu \mathrm{M}$ and 60%, respectively. ^{23, 32} The reduced light scattering coefficient $\left({\mu }_{\mathrm{s}}^{\prime }\right)$ of the piglet brain was assumed to be $10{\mathrm{cm}}^{-1}$ , ^{24, 32} for analysis of the hemoglobin concentrations. Note, a prefix “r” is used throughout the paper to indicate the relative change of a parameter compared to its baseline level (e.g., $\mathrm{rTHC}=\mathrm{THC}∕{\mathrm{THC}}_0$ ).

2.3.

DCS

Diffuse light also carries dynamic information about moving scatterers below the tissue surface [i.e., red blood cells (RBCs)]. In this case, a continuous wave, long-coherence-length laser is used as the light source $\left(785\mathrm{nm}\right)$ . The speckle intensity temporal fluctuations, due to movements of the scatterers, is detected using a single-mode (or few-mode) optical fiber coupled to a high-sensitivity photon-counting detector. The decay rate of the temporal autocorrelation function of the detected intensity reveals tissue blood flow information (e.g., faster decay indicates higher blood flow.^{7, 8, 9, 10, 11, 26, 33, 34, 35} A correlation diffusion equation²⁷ is used to model the propagation of the autocorrelation function in turbid media. The decay rate of the intensity autocorrelation function depends on tissue optical properties ( ${\mu }_a$ and ${\mu }_{\mathrm{s}}^{\prime }$ ), and a flow-index $\left(\alpha D_{\mathrm{b}}\right)$ , where $\alpha$ is a unitless factor representing the fraction of scatterers that are moving (e.g., RBCs) and $D_{\mathrm{b}}$ is an effective Brownian motion coefficient of the scatterers. We have observed in tissue studies that changes in $\alpha D_b$ correlate well with other flow measurement modalities such as laser Doppler,^{7, 36} color-weighted power Doppler ultrasound,³³ Xenon CT,³⁷ and arterial-spin-labeling magnetic resonance imaging (ASL-MRI).^{38, 39} Therefore, we report $\mathrm{rCBF}=\alpha D_{\mathrm{b}}∕{\left(\alpha D_{\mathrm{b}}\right)}_0$ to indicate the CBF values in the piglet brain relative to the baseline (preinjury) measurements. The absorption coefficient $\left({\mu }_{\mathrm{a}}\right)$ of the piglet brain at $785\mathrm{nm}$ was obtained from the DRS analysis and was used in a semi-infinite model²⁶ to fit to the DCS auto-correlation curves and thus to minimize the influence of THC changes on rCBF measurements. Noise in the DCS correlation curve was estimated based on the model described previously and was employed herein to improve curve fitting.⁹

2.4.

Hybrid Instrumentation and Optical Probe

A hybrid instrument combining both the DRS and DCS techniques was used for piglet measurements.^{40, 41} Three intensity modulated $\left(70\mathrm{MHz}\right)$ diode lasers (685, 785, and $830\mathrm{nm}$ ) and a $785\text{-}\mathrm{nm}$ -long coherence-length laser (Crystalaser, reno, Nevada) were coupled to a $4\times 1$ optical switch (Dicon, Richmond, California), which enabled time sharing of the DRS and DCS measurements. The output of the source wavelength switch was fed into a second $1\times 4$ optical switch, which scanned over the four source positions on the optical probe (see Fig. 1 ). Four $1\text{-}\mathrm{mm}$ optical fibers were used for DRS detection, and four single-mode optical fibers were used for DCS detection. The fibers were arranged into two columns, probing the left and right hemispheres of the piglet brain, respectively. The source-detector separation ranged from $5\mathrm{mm}\text{to}2\mathrm{cm}$ , and the measurement at each position took $\sim 4\mathrm{s}$ , corresponding to a data acquisition rate of $\sim 4\text{frames}∕\min$ with each frame covering all four source positions. This rate is sufficient for capturing dynamic physiological changes on the scale of several minutes (see Section 3.5). Whenever available (see Table 1), analog outputs from a blood pressure monitor (Grass Technologies, West Warwick, Rhode Island) and a pulse oxymeter (Nellcor Puritan Bennett Inc., Boulder, Colorado) were continuously recorded concurrent with the DRS and DCS measurements. The system was fully automated, and marks were made and saved for the coregistration of various events.

Fig. 1

Arrangement of the optical probe. Four multimode source fibers (★), four $1\text{-}\mathrm{mm}$ DRS fibers (◆), and four single-mode DCS fibers (◼) were used for simultaneous DRS and DCS measurements. The fibers were arranged into two columns, oriented anteriorly posteriorly along most of the length of the left and right cerebral hemispheres on top of the piglet head. The source-detector separations ranged from $5\mathrm{mm}\text{to}2\mathrm{cm}$ .

A custom opaque black hood was used to secure the optical probe onto the piglet head. A marker pen was used to outline the probe position so that the probe was placed at the same location on the piglet scalp before and after injury. In order to assess the influence of probe placement repeatability on the accuracy of the diffuse optical measurements, the optical probe was removed from the piglet head after the first baseline measurement and replaced about $1\min$ later for a second baseline measurement. These double-baseline measurements were conducted before injury in six animals.

2.5.

Fluorescent Microsphere Measurements of Cerebral Blood Flow

In this study, FMs^{14, 15} were used to measure CBF for comparison to the optical method. Prior to injury, catheters were surgically placed in the femoral artery for FM reference blood withdrawals, and catheters were surgically plugged in the left ventricle of the heart via the right carotid artery for FM injections. At each time point, $1–2\times {10}^6$ $15\text{-}\mu \mathrm{m}$ -diam fluorescently labeled microspheres (Molecular Probes, Invitrogen, Carlsbad, California) were injected into the left ventricle with $10\mathrm{mL}$ of heparinized saline for $30\mathrm{s}$ . A reference blood sample was withdrawn at $0.97\mathrm{mL}∕\min$ from the femoral artery beginning $5–10\mathrm{s}$ before injection and continuing until $90\mathrm{s}$ after injection completion. Fluorescent microspheres having different excitation/emission spectra were injected during baseline optical measurements and at discrete time points postinjury ( $30\min$ , $1\mathrm{h}$ , and $6\mathrm{h}$ ).

Fixed brains were cut into $3\text{-}\mathrm{mm}$ -thick coronal sections. Sections were embedded in 2% agarose gel and cut by vibratome (Leica VT1000S, Leica Microsystems GmbH, Wetzlar, Germany) into $100–200\text{-}\mu \mathrm{m}$ -thick slices, which were then mounted onto microscope slides with gel mount (Biomeda, Foster City, California). Reference blood samples were filtered four times using $10\text{-}\mu \mathrm{m}$ -pore polycarbonate membranes (Osmonics, Minnetonka, Minnesota) to retrieve reference FMs, and filters were mounted on large microscope slides. All slides were imaged on a fluorescent slide reader (Alpha Innotech, San Leandro, California) using multiple excitation-emission wavelength pairs to isolate each FM color. FMs of each color were counted in tissue sections and filters using an automated particle counting program to determine CBF in the upper cerebrum to a tissue depth of $\sim 1.8\mathrm{cm}$ , corresponding to the top of the lateral ventricles, at different time points before and after injury. CBF relative to preinjury (rCBF) was calculated from $\mathrm{rCBF}=(ms\times r{s}_0)∕(m{s}_0\times rs)$ , where $ms$ is the number of tissue microspheres, $rs$ is the number of reference blood microspheres, $m{s}_0$ is the number of tissue microspheres at preinjury baseline, and $r{s}_0$ is the number of reference blood microspheres at preinjury baseline. The FM measurements were then compared to rCBF as determined optically using DCS at corresponding time points.

2.6.

Data Analysis

$\text{Mean}\pm \text{standard}$ deviation of cerebral hemodynamic parameters (Hb, $\mathrm{Hb}{\mathrm{O}}_2$ , THC, $\mathrm{St}{\mathrm{O}}_2$ , and rCBF) from large source-detector separations (1, 1.5, and $2\mathrm{cm}$ ) were reported for each individual animal. The total thickness of the scalp and skull layers of the piglet brain was $<4\mathrm{mm}$ , and therefore, they should have a relatively small (compared to humans) influence on the accuracy of cerebral hemodynamic changes, especially relative changes, measured at large source-detector separations.^{23, 25, 32} Linear regression was used to demonstrate correlation and agreement between the FM and DCS measurements of rCBF. CBF measured with FMs in the upper cerebrum were normalized to the preinjury value from the same animal to obtain ${\mathrm{rCBF}}_{\mathrm{FM}}$ at various time points postinjury. rCBF measured using DCS $\left({\mathrm{rCBF}}_{\mathrm{DCS}}\right)$ was averaged over $2\min$ at the corresponding FM time points. Measurements from the left and right hemispheres were averaged to improve the signal-to-noise ratio. The results from each experimental group were reported as $\text{mean}\pm \text{standard}$ error. A one-way repeated measures analysis of variance (ANOVA) was employed to statistically interpret the group results. When significant differences were found, a Student t-test was used to determine the time point when significant changes occurred. Significance was adjusted for multiple comparisons using Bonferroni correction and $p⩽0.01$ .

3.1.

Repeatability of Probe Placement

From the six animals with double-baseline measurements, good agreement was observed between the first and second baseline measurements ( $\mathrm{rCBF}=101\pm 7\%$ , $p=0.88$ ; $\mathrm{rTHC}=108\pm 12\%$ , $p=0.54$ ; and $\mathrm{rSt}{\mathrm{O}}_2=107\pm 7\%$ , $p=0.45$ ), indicating that removal and replacement of the probe had a relatively small influence on the measured optical cerebral hemodynamic values.

3.2.

Comparison of ${\mathrm{rCBF}}_{\mathrm{DCS}}$ to ${\mathrm{rCBF}}_{\mathrm{FM}}$

Figure 2 compares rCBF obtained by DCS to rCBF by FMs in eight animals from the three groups. Regression analysis revealed a linear relationship between ${\mathrm{rCBF}}_{\mathrm{DCS}}$ and ${\mathrm{rCBF}}_{\mathrm{FM}}$ , with a correlation coefficient of $R=0.89$ $(p<0.00001)$ . The slope of the regression was calculated to be 1.03 (95% confidence interval, CI: 0.74–1.32), which is not significantly different from identity $(p=0.80)$ . The intercept was 25.2%, with a 95% CI ranging from 12.4 to 38.0%.

Fig. 2

Correlation between rCBF measured by DCS and fluorescent microspheres. A linear relationship between the two techniques ( $R=0.89$ , $p<0.00001$ ) was observed. The slope (1.03) is not significantly different from that of identity $(p=0.80)$ . The intercept is 25.2%, with a 95% confidence interval from 12.4 to 38.0%.

3.3.

Average Injury Effects

Although each animal received individual care and had a distinct temporal hemodynamic response to the TBI, similar trends can be observed across animals within each of the groups. Changes in physiological parameters are summarized in Table 2 . Compared to preinjury values, only MAP in group 1 was found significantly lower at $3\mathrm{h}$ $(p=0.005)$ and $6\mathrm{h}$ $(p=0.002)$ and the $3\text{-}\mathrm{h}$ postinjury pH value in the venous blood gas (group 1) was significantly higher $(p=0.007)$ .

Table 2

Summary of physiological parameters in animal groups 1 and 2 ( mean±standard error). VBG: venous blood gas; ABG: arterial blood gas. The asterisk in each row indicates significant difference from the corresponding pre-injury value (p⩽0.01) .

Figure 3 demonstrates the average injury effects on cerebral hemodynamics measured optically from the 10 injured piglets in group 1. The traumatic brain injury was found to have a significant impact on cerebral hemoglobin concentrations (ANOVA, $p=0.001$ for rHb, $p=0.01$ for $\mathrm{rHb}{\mathrm{O}}_2$ , and $p=0.005$ for rTHC) and rCBF $(p=3\times {10}^{-7})$ . Compared to preinjury levels, rHb, $\mathrm{rHb}{\mathrm{O}}_2$ , and rTHC increased $67\pm 13\%$ $(p=0.0006)$ , $24\pm 13\%$ $(p=0.1)$ , and $41\pm 11\%$ $(p=0.005)$ , respectively, immediately after injury and continued increasing over the next $6\mathrm{h}$ [see Fig. 3a, 3b, 3c]. These changes are likely related to the accumulation of subdural and subarachnoid blood due to the rotational injury. $\mathrm{St}{\mathrm{O}}_2$ dropped significantly immediately postinjury ( $52\pm 3\%$ , $p=0.02$ ), maintained this reduction at $30\min$ postinjury ( $54\pm 2\%$ , $p=0.009$ ), but gradually normalized to preinjury levels [see Fig. 3d]. rCBF decreased significantly to $50\pm 6\%$ of preinjury level $(p=0.00003)$ immediately after injury and continued at that level over the $6\mathrm{h}$ [Fig. 3e]. By comparison, no significant changes in rHb (ANOVA, $p=0.32$ ), $\mathrm{rHb}{\mathrm{O}}_2$ $(p=0.68)$ , rTHC $(p=0.18)$ , $\mathrm{St}{\mathrm{O}}_2$ $(p=0.92)$ , or rCBF $(p=0.87)$ were observed over the $6\mathrm{h}$ in the control group $(n=4)$ .

Fig. 3

Average injury effects on Hb, $\mathrm{Hb}{\mathrm{O}}_2$ , THC, $\mathrm{St}{\mathrm{O}}_2$ , and rCBF for animals in group 1 ( $n=10$ , error bars represent standard error). Traumatic brain injury produced significant increases in cerebral hemoglobin concentrations and decreases in oxygen saturation. Compared to preinjury levels, rHb, $\mathrm{rHb}{\mathrm{O}}_2$ , and rTHC increased significantly within the first $10\min$ after injury and continued to increase over the next $6\mathrm{h}$ . $\mathrm{St}{\mathrm{O}}_2$ dropped significantly by $30\min$ postinjury, but gradually returned to preinjury levels. rCBF decreased significantly within the first $10\min$ after injury and continued at that level over the $6\mathrm{h}$ . The asterisk in each plot indicates a significant difference from the corresponding pre-injury value $(p⩽0.01)$ .

3.4.

Robust Long-Term Monitoring

All 14 injured piglets survived $6\mathrm{h}$ ( $n=10$ for group 1 and $n=4$ for group 3). Figure 4 shows the results of the $6\mathrm{h}$ monitoring period from a representative animal. Cerebral hemodynamic parameters measured with DRS and DCS, specifically THC, $\mathrm{St}{\mathrm{O}}_2$ , and rCBF, are shown in the top three panels. Vital physiological parameters, including MAP, $\mathrm{Sa}{\mathrm{O}}_2$ , and HR, are displayed in the bottom three panels. In this animal, THC increased to $84\mu \mathrm{M}$ immediately after the injury, continued to gradually increase to $110\mu \mathrm{M}$ during the first $2\mathrm{h}$ , and then stayed at that level until $6\mathrm{h}$ postinjury. Blood oxygen saturation in the brain tissue $\left(\mathrm{St}{\mathrm{O}}_2\right)$ and systemically $\left(\mathrm{Sa}{\mathrm{O}}_2\right)$ were relatively stable throughout the $6\text{-}\mathrm{h}$ monitoring period. However, immediately after the injury, rCBF, MAP, and HR were elevated ( $\mathrm{rCBF}=140\%$ , $\mathrm{MAP}=94\mathrm{mmHg}$ , $\mathrm{HR}=245\mathrm{BPM}$ ), and then they decreased dramatically within the first $10\min$ .

Fig. 4

Robust long-term monitoring from a representative animal. Cerebral hemodynamics (THC, $\mathrm{St}{\mathrm{O}}_2$ , and rCBF) measured with DRS and DCS are plotted in the top three panels, while vital physiological parameters (MAP, $\mathrm{Sa}{\mathrm{O}}_2$ , and HR) are displayed in the bottom three panels. Good correlation between changes in MAP and changes in rCBF were observed. Solid vertical bars mark various physiological events: $M_1$ , begin phenylephrine dose titration; $M_2$ , begin continuous phenylephrine infusion at $1\mathrm{\mu g}∕\mathrm{kg}∕\min$ ; and $M_3$ , $M_4$ , and $M_5$ , administer boluses of hypertonic (3%) saline. Error bars in the top three panels represent standard deviation of cerebral hemodynamic parameters from large source-detector separations (1, 1.5, and $2\mathrm{cm}$ ).

At $\sim 15\min$ postinjury, phenylephrine infusion was begun via the femoral vein. Between marks M1 and M2, the phenylephrine dose was titrated until MAP was within $10\mathrm{mmHg}$ of preinjury MAP. The resultant increases in MAP and rCBF can be observed in Fig. 4. The animal was maintained on the final phenylephrine dose $(1\mu \mathrm{g}∕\mathrm{kg}∕\min )$ until the end of the study. Between 4 and $5.5\mathrm{h}$ , three boli of hypertonic (3%) saline were injected into the animal (M3, M4, and M5). Good correlation between changes in MAP and rCBF were observed. Changes in HR were not found to correlate with rCBF changes over the $6\mathrm{h}$ . Similar and consistent profiles were observed from other animals in groups 1 and 3. Cerebral hemodynamics measured with diffuse optics were found to be robust and consistent with vital physiological recordings over the entire monitoring period.

3.5.

Sensitivity to Transient Physiological Events

In addition to providing robust long-term monitoring capability, the diffuse optical techniques were sufficiently sensitive to capture the dynamics of transient physiological events, such as apnea, cardiac arrest, and hypertonic saline infusion. Examples in this section illustrate the temporal profiles of the measured cerebral hemodynamic changes during these events.

3.5.1.

Apnea

Six episodes of spontaneous apnea from five animals in group 1, two episodes from one animal in group 2, and two episodes from two animals in group 3 were observed and recorded. Figure 5 shows an example of an apnea event whose dynamics were captured optically. In this case, apnea caused a significant drop in systemic blood oxygen saturation (67%). MAP rose by $26\mathrm{mmHg}$ , increasing blood flow to the brain by 36% relative to the preinjury value. $\mathrm{St}{\mathrm{O}}_2$ decreased, but only by $\sim 2\%$ , most likely because the increased rCBF provided a sufficient increase in ${\mathrm{O}}_2$ delivery. Upon mechanical ventilation of the animal (the vertical marks in Fig. 5), all physiological parameters were successfully returned to their preapnea states. Because the duration of and response to apnea are different from animal to animal, the magnitudes of the changes in cerebral hemodynamics varied. However, the same trends (decreased $\mathrm{St}{\mathrm{O}}_2$ , increased MAP, and rCBF) were observed consistently in all apnea events and were abolished by mechanical ventilation.

Fig. 5

Cerebral hemodynamic changes during an episode of apnea in a representative animal. Apnea caused a significant drop in $\mathrm{Sa}{\mathrm{O}}_2$ . As a result, MAP increased significantly and raised rCBF to produce only a slight decrease in $\mathrm{St}{\mathrm{O}}_2$ . Following initiation of mechanical ventilation (solid vertical line), all physiological parameters returned to their preapnea states. Error bars in $\mathrm{St}{\mathrm{O}}_2$ and rCBF represent standard deviation from large source-detector separations (1, 1.5, and $2\mathrm{cm}$ ).

3.5.2.

Apnea followed by cardiac arrest

Two apnea events were followed by cardiac arrest in one piglet in group 3, and cerebral hemodynamic changes during these episodes were recorded optically. As shown in Fig. 6a, hemodynamics during the first period of apnea followed the same trends described above ( $\mathrm{St}{\mathrm{O}}_2$ decreased from 57 to 48%, MAP increased from $43\text{to}66\mathrm{mmHg}$ , and rCBF increased from 28 to 46% of preinjury levels). Cardiac arrest occurred about $3\min$ after the onset of apnea (the vertical marks in Fig. 6), producing a significant decrease in MAP to $13\mathrm{mmHg}$ . As a result, rCBF decreased dramatically to 13% and $\mathrm{St}{\mathrm{O}}_2$ decreased further down to 37%, indicating a significant decrease in oxygen delivery to the brain. About $4\min$ later, mechanical ventilation successfully resuscitated the animal from cardiac arrest. Initial increases in MAP were seen, which then gradually normalized to preapnea levels as rCBF and $\mathrm{St}{\mathrm{O}}_2$ returned to preapnea values. Diffuse optical techniques captured similar dynamic changes following a second apnea event in the same animal two hours later [Fig. 6b].

Fig. 6

Cerebral hemodynamic changes in a single animal during two episodes of apnea followed by cardiac arrest. (A) The onset of apnea produced the same $\mathrm{St}{\mathrm{O}}_2$ , rCBF, and MAP trends observed in Fig. 5. Cardiac arrest (solid vertical line) caused a significant decrease in MAP and rCBF, resulting in a further significant decrease in $\mathrm{St}{\mathrm{O}}_2$ . After ventilatory resuscitation, $\mathrm{St}{\mathrm{O}}_2$ , rCBF, and MAP gradually returned to preapnea levels. (B) The same “biphasic” dynamic change was observed during apnea in the same animal $2\mathrm{h}$ later. Error bars in $\mathrm{St}{\mathrm{O}}_2$ and rCBF represent standard deviation from large source-detector separations (1, 1.5, and $2\mathrm{cm}$ ).

3.5.3.

Hypertonic saline infusion

Hypertonic (3%) saline is widely employed in the clinical setting to increase cerebral blood flow by decreasing intracranial pressure and increasing systemic blood pressure.⁴² The effect is thought to work by extracting water from the tissue compartments, particularly swollen brain tissue, into the circulatory system.⁴² Four piglets in group 3 $(n=4)$ were infused with hypertonic saline over a $5\text{-}\min$ period starting $30\min$ postinjury. Temporal changes in rCBF and MAP from one representive example is displayed in Fig. 7 . The infusion effectively elevated rCBF by 24% of preinjury levels and MAP by $12\mathrm{mmHg}$ . These rCBF and MAP changes were well correlated $(R=0.95)$ with each other. Similar trends were observed in the other animals receiving hypertonic saline.

Fig. 7

Cerebral hemodynamic changes during hypertonic (3%) saline infusion. The infusion effectively elevated rCBF and MAP. The solid vertical lines indicate the start and end of the infusion. Error bars in rCBF represent standard deviation from large source-detector separations (1, 1.5, and $2\mathrm{cm}$ ).