1.

Introduction

Stroke occurs when arteries supplying blood to the brain burst (hemorrhagic stroke) or are obstructed¹ (ischemic stroke). About 90% of all strokes are ischemic, occurring from occlusion of one of the main arteries supplying the brain. Under these conditions brain cells undergo a series of pathophysiologic changes, but ultimately die from lack of oxygen supply.² Cerebral ischemia results in changes in regional concentrations of oxyhemoglobin, deoxyhemoglobin, and water.³ Because these molecules absorb specific wavelengths of light, ischemia alters the optical properties of brain tissue. Since the most commonly involved artery in ischemic strokes is the middle cerebral artery (MCA) we chose to focus our experiments on MCA occlusion^{4, 5} (MCAo).

Several groups have studied brain response during cerebral ischemia using optical imaging methods. Common to them is the observation of changes in cerebral hemodynamic parameters after ischemia. Wolf used near infrared spectroscopy (NIRS) to show a decrease in oxyhemoglobin and an increase in deoxyhemoglobin during focal cerebral ischemia in rats.⁶ Culver demonstrated⁷ in an intact skull rat model that tissue hemoglobin saturation values drop by $11\pm 4\%$ from baseline during MCAo. Similar results have been reported in mouse⁸ and piglet models⁹ as well as in humans¹⁰ during neurosurgery. In the latest study, patients with ischemic events experience decreases in oxyhemoglobin, total hemoglobin, and brain tissue oxygen saturation levels of 42, 18, and 25%, respectively, from baseline, whereas an increase of 20% from baseline in deoxyhemoglobin was observed.

Although the preceding examples clearly demonstrate physiological changes following MCA occlusion, significant challenges remain to provide quantitative spatiotemporal maps of cortical absorption and scattering. This would enable us to more accurately assess hemodynamic and metabolic changes from different regions of the brain and ultimately gain a more complete understanding of stroke physiology. Consequently, in this paper we introduce a noncontact and scan-free approach based on spatial light modulation to detect and map tissue chromophore changes in the brain during cerebral ischemia.

In this method, periodic near-IR (NIR) illumination patterns with different spatial frequencies are projected on the rat cortex during ischemic stroke. A CCD camera captures the diffusely reflected light and Monte Carlo solutions are used as model functions in an inversion algorithm for determining optical properties. Measurements of the changes in absorption in the NIR spectral region and the knowledge of the molar extinction coefficients of individual chromophores, enables us to quantify changes in oxyhemoglobin $\left(\mathrm{ct}{\mathrm{O}}_2\mathrm{Hb}\right)$ , deoxyhemoglobin (ctHHb) total hemoglobin concentration $(\mathrm{ctTHb}=\mathrm{ct}{\mathrm{O}}_2\mathrm{Hb}+\mathrm{ctHHb})$ , and oxygen saturation $[\mathrm{st}{\mathrm{O}}_2=100\times (\mathrm{ct}{\mathrm{O}}_2\mathrm{Hb}∕\mathrm{ctTHb})]$ . Observations from this study indicate that in addition to significant changes in $\mathrm{ct}{\mathrm{O}}_2\mathrm{Hb}$ , ctTHb, and $\mathrm{st}{\mathrm{O}}_2$ during cerebral ischemia, as described in other studies,^{7, 8, 9, 10} spatial frequency modulation analysis reveals alterations in cortical scattering that are consistent with ischemically induced processes such as cellular swelling and tissue edema.

2.

Materials and Methods

2.2.

Instrument

A schematic of the experimental arrangement of the spatial light illumination is illustrated in Fig. 1 . Periodic illumination patterns of various spatial frequencies with a $120\text{-}\mathrm{deg}$ phase-shifting step between three adjacent patterns were projected onto the brain from a commercial digital light projector (BENQ, PB8260) controlled by a computer. The light intensity distribution of this pattern has the form of an amplitude-modulated sinusoidal wave. These patterns were created on a personal computer using PowerPoint software and projected sequentially using Microsoft Office’s ActiveX controls via an external LabView program (Ver. 7). The patterns were converted from white light projection to NIR using a filter wheel (Spectral Product, AB302) placed immediately at the output of the projector. We used five narrow NIR bandpass filters between 680 and $980\mathrm{nm}$ (Andover Corp.) placed on a five-position wheel.

Fig. 1

Schematic diagram of the optical arrangement used for brain imaging. Components are FW, filter wheel; L, lens; and M, mirror.

The diffusely reflected light, which contains information about the brain tissue optical properties, was recorded by a $16\text{-}\mathrm{bit}$ CCD camera (Cascade, 512F) mounted normal to the brain surface. The optical axis of the camera lens was perpendicular to the center of the imaging region. The camera is equipped with an imaging objective (Nikon $f∕1.8$ lens, Japan) lens combined with an extender and is capable of imaging up to $30\text{frames}∕\mathrm{s}$ at full $512\times 512$ resolution. The distance between the CCD lens and the brain was about $100\mathrm{mm}$ . A $6\times 6\text{-}\mathrm{mm}$ area was imaged onto the CCD with resolution of $0.012\mathrm{mm}∕\text{pixel}$ for both the $x$ and $y$ axes. As a part of the calibration procedure, a lab jack was used to bring the rat’s head to focus within the CCD view.

To compensate for the wavelength-dependent illumination and detection throughput, image exposure times were chosen at each wavelength, prior to each experiment as a part of system calibration, to fill the dynamic range of the camera, ranging from $10\mathrm{ms}$ ( $\mathrm{QE}\sim 50\%$ at $680\mathrm{nm}$ ) to $1\mathrm{s}$ ( $\mathrm{QE}\sim 10\%$ at $980\mathrm{nm}$ ). The mirror appearing in the setup was aligned at a small angle of incidence, $\sim 15\mathrm{deg}$ to the vertical axis, to obtain projection illumination at a small angle, and therefore avoid the detection of specular reflected light. Polarized filters (Meadowlark Optics, VLM-200-IR-R) in both the illumination and detector paths were aligned with the polarization planes orthogonal to each other for additional specular elimination. The entire system is controlled by a personal computer through a LabView platform.

As already mentioned, the principle component of our working system is a commercial digital light projector that is used to produce the patterned illumination. However, to fit the projector to our demands such as illumination stability, high intensity, and scalability to a small region of interest, the following modification steps were required. The white light source (Mercury lamp, OSRAM, $300\mathrm{W}$ ) and the power supply of the projector were replaced with a $300\text{-}\mathrm{W}$ quartz-tungsten-halogen (QTH) (EIKO, EXR, 82v) bulb and with a corresponding power supply. We decide to use this bulb since it gives a smooth broadband spectral profile along the NIR region and stable intensity over time (light output variation less then 0.6%). As shown in Sec. 3, these fluctuations are negligible compared to the signals arriving from the brain during acute ischemic injury.

To boost intensity from the QTH bulb and to use the entire spectral band, the color wheel inside the projector was carefully removed, enabling the projector to work as usual. To prevent warming of the projector, a hybrid hot mirror (Reynard Corp., C-R00670-00) was introduced between the QTH bulb and the optics inside the projector. Both the bulb and the hybrid mirror were maintained inside the projector through careful mechanical design and holders. To collimate the patterns on the surface of brain, to obtain a small $(\sim 10\times 10\text{-}\mathrm{mm})$ and adjustable field of view, and to compensate for aberrations derived from using white source, a new lens system was design based on a set of achromatic lenses (LA-series, ThorLabs), replacing the original lens system of the projector.

2.4.

Imaging and Data Processing

Imaging was performed through the surgically created imaging window on anesthetized rats held in a stereotactic frame. The reflected image of the region of interest (ROI) of the cortex was acquired on a CCD camera while projecting spatially modulated NIR light onto the region of interest. Image sets of each of the five wavelengths were acquired over a $6\times 6\text{-}{\mathrm{mm}}^2$ brain surface, with six spatial frequencies ranging from 0 to $\sim 0.26{\mathrm{mm}}^{-1}$ . Images at each frequency were obtained as shown in Eq. 1. The resulting 90 images (6 spatial frequencies, 3 phase shifts for each frequency, 5 wavelengths) provide a quantitative frequency response (or modulation transfer function, MTF) of the diffuse reflectance of the brain [see Fig. 2c ].

Fig. 2

(a) Top view of the rat skull. The rectangle shows the cranial window above the region of the left parietal somatosensory barrel cortex used for imaging. (b) Enlarged photograph of the rat cortex ROI. The scale bar corresponds to $1\mathrm{mm}$ . (c) Averaged diffuse reflectance versus spatial frequency at $680\mathrm{nm}$ . The line represents the fitting of the theory to the experimental measurement (circle). Error bars show the spatial standard deviation of the diffuse reflectance ROI pixel value.

Diffuse reflectance images were obtained from the ROI selected by the investigators, and processed by fitting frequency-dependent data to a Monte Carlo model. To separate light absorption from light scattering and subsequently generate chromophore maps faster, we used only two spatial frequencies (from the six frequencies): $0{\mathrm{mm}}^{-1}$ (dc frequency) and $0.16{\mathrm{mm}}^{-1}$ (ac frequency) in our experiments. As a result, multispectral maps were generated approximately every $\sim 1.5\min$ to study the changes in cortical perfusion with time following experimental manipulation.

Imaging was started before induction of ischemia to establish baseline chromophore concentrations and repeated during and after experimental intervention. Throughout the entire study, baseline images were obtained between 15 and $25\min$ before induction of experimental injury to establish baseline chromophore concentrations. Thus, each rat served as its own control, decreasing the number of animals required for the study. Postinjury imaging was started approximately $15\min$ after MCA occlusion and continued for $1\mathrm{h}$ . The image analysis was performed off-line on a PC computer with custom software developed in MATLAB (version 7.04, The MathWorks, Inc). All images before analysis were digitally filtered by a 2-D Gaussian low-pass filter with size of $9\times 9$ with standard deviation (FWHM) of $\sigma =1.5$ using the fspecial function in MATLAB and a $3\times 3$ binning operation was performed.

3.

Results and Discussion

During experiments, the region of the left parietal somatosensory barrel cortex centered at the whisker $C2$ functional representation location was monitored pre- and post-MCA occlusion. A rat brain illustration together with the cranial window for optical imaging and the approximate position of the left MCAo are presented in Fig. 2a. The enlarged region photograph of the cranial window is shown in Fig. 2b. The size of this ROI is about $4\left(\mathrm{V}\right)\times 4.9\left(\mathrm{H}\right){\mathrm{mm}}^2$ . The relationship between the measured diffuse reflectance from brain tissue and the spatial modulation frequency is shown in Fig. 2c for $680\text{-}\mathrm{nm}$ light. As demonstrated by this plot, the brain tissue acts like a low-pass spatial filter, attenuating the reflectance more strongly as the spatial frequency increases. The data was fit to the MC model using a nonlinear least-squares optimization routine. As can be seen, the numerical calculations are in quantitative agreement with experimental data with low fitting error. These errors are believed to be mainly due to the phantom calibration process and the assumption of homogeneity in the computational model.

Once the information of Fig. 2c is obtained, optical coefficients are retrieved by using an MC model, as discussed previously in Sec. 2.5. As mentioned in the introduction, mapping the absorption coefficient at each wavelength with the knowledge of the wavelength-dependent molar extinction $\left(\epsilon \right)$ values of the chromophores^{15, 16, 17} enables us to calculate tissue chromophore concentration $\left(C\right)$ separately at each pixel using the following equation¹⁸

An example of the changes in the $\mathrm{ct}{\mathrm{O}}_2\mathrm{Hb}$ , ctHHb, and $\mathrm{st}{\mathrm{O}}_2$ maps before and after the occlusion is shown in Fig. 3a . The grayscale to the right of each map represents the absolute chromophore value of each pixel in the map. To better visualize changes, mean color scales were set at 50% for all of the preocclusion data. No a priori knowledge about tissue chromophore content has been assumed (other then standard nonnegative constrains). Averaging over each of these maps we found a $22\pm 10.2\%$ increase in deoxyhemoglobin concentration and a $43\pm 6.6\%$ and $32\pm 4.1\%$ decrease in oxyhemoglobin and oxygen saturation, respectively, from baseline values following MCA occlusion. These changes reflect the pathophysiologic state of the brain and the ability of spatially modulated light to quantify changes in chromophore concentrations with time.

Fig. 3

Results from a representative rat (out of seven). (a) Oxy-, deoxyhemoglobin (μM) and oxygen saturation (%) maps pre-and post-MCAo. In all panels, higher concentration values correspond to brighter pixels. Scale values are represented by the scale bar to the right of each panel. Field of view $\sim 6\times 6\mathrm{mm}$ . (b) Time course of quantitative values of cerebral hemodynamics from the barrel cortex before and after MCA occlusion obtained from the area in Fig. 2b. The error bars give the standard error $(\pm \mathrm{SE})$ of all pixels in ROI.

A representative time course of the absolute changes in chromophore concentration within the entire cortex of Fig. 2b pre-MCAo (baseline) and post-MCAo are presented in Fig. 3b. A decrease in the ctTHb from baseline in the amount of $19\pm 7.3\%$ is observed. In the intact brain, ctTHb tracks blood flow as long as the hematocrit is constant, but in thrombosed vessels, this relationship may change. For example, if blood flow decreases or stops but the vessels do not collapse, ctTHB can remain high in the occluded region.^{7, 14} However, our signals are derived primarily from superficial microvasculature a few millimeters in depth beneath the skull. Because these vessels are significantly downstream from the MCA occlusion site, we expect that the observed reduction in ctTHB is a consequence of stroke-induced termination of flow.

Fluctuations in chromophore concentrations pre- and post-MCAo can also be seen in Fig. 3b. Mean values do not exceed more then $\pm 3\mu \mathrm{M}$ for hemoglobin and $\pm 3\%$ for $\mathrm{st}{\mathrm{O}}_2$ . As previously stated in Sec. 2.4, measurement of brain optical properties and generation of an image (a unit measurement) required $1.5\min$ . Thus, each unit measurement is an average of the dynamic optical properties over $1.5\min$ . The nature of these fluctuations may change after the stroke and thus account for additional measurement errors. With further advances in technology and faster image acquisition, this potential source of error is likely to be reduced.

While light absorption is related to the concentrations of individual chromophores, light scattering is related to tissue structural properties such as density, size, and distribution of scattering. Tissue scattering properties are believed to depend on intracellular (nuclei, mitochondria) and extracellular (protein) structures.¹⁹ Therefore, examination of the scattering behavior can provide fundamental insight into microstructural physiology. Extracting the mean particle size and number density of scattering particles from the reduced scattering coefficient spectrum in breast tissue was discussed recently by Wang ²⁰ In the following, we report our observation on the behavior of scattering properties during brain ischemia. Several studies have shown that the wavelength dependence of scattering in tissue in the NIR follows a power-law dependence of the form^{21, 22}

Changes in the reduced scattering coefficient, scattering amplitude, and scattering power over time for the entire ROI (single animal) shown in Fig. 2b are plotted in Fig. 4a, 4b, 4c, respectively. The mean scattering values pre-MCA occlusion are $\sim 4\%$ higher than postocclusion. The decrease in the scattering power with ischemia can be explained by an increase in the average size of the scatterers. This could be the result of cell swelling in response to acute injury.²⁴ Changes in scattering amplitude $\left(A\right)$ are influenced by (1) number of particles, (2) the ratio of the refractive index outside (extracellular) to inside (intracellular) the scattering particle, and (3) particle distribution. Since 1 and 3 are assumed not to change in the first hour of ischemic injury, the measured drop in scattering amplitude most likely reflects a homogenization of refractive index due to injury-induced alterations in cell and organelle permeability. This reduction in spatial variation of refractive index causes more light to passes through the cortex, and less light to be scattered. Hence, by measuring scattering amplitude and power one can get an impression of the degree of cellular injury in terms of cell swelling (edema) and membrane damage. A summary of scattering changes for all animals is presented in Table 1 .

Fig. 4

Time course of the quantitative values of scattering properties ( ${\mu }_s^{\prime }$ , sp, and $A$ ) before and after MCA occlusion obtained from the entire ROI of Fig. 2b.

Table 1

Statistics comparing brain properties pre-MCAo and 45min post-MCAo over the entire cortex for seven rats.

Regional changes in cortical properties can also observed by converting absorption and scattering maps into histogram distributions before and after the MCAo, as shown in Fig. 5 and 6 , respectively. Figure 5 illustrates that when a wide ROI is selected, overlap between histograms diminishes contrast between pre- and post-MCAo optical properties. This is a result of partial-volume effects (in all three spatial dimensions) of sampling heterogeneous tissue. When a more homogeneous ROI is selected (Fig. 6), pre- and post-MCAo histograms are clearly separated. This is an expected result as we sample a more homogenous region of the cortex. Note that mean values of each property in Fig. 5 are almost identical to those in Fig. 6. However, values for the variance are reduced, for example, by 67, 63, 25, and 38% for absorption, scattering, scatter amplitude, and scatter power, respectively, in the homogenous region (Fig. 6).

Fig. 5

(a) and (b) Absorption and (c) and (d) scattering property histograms before (solid lines) and after (dashed lines) MCAo for the entire cortex.

Fig. 6

(a) and (b) Absorption and (c) and (d) scattering property histograms before (solid lines) and after (dashed lines) MCAo for the parenchyma. The small box denotes the ROI used for analysis.

Table 1 summarizes the results of statistical comparisons before and $45\min$ after MCAo for $\mathrm{ct}{\mathrm{O}}_2\mathrm{Hb}$ , ctHHb, ctTHb, $\mathrm{st}{\mathrm{O}}_2$ , and the three scattering parameters for the seven rats used in this study. For each parameter, we calculated both the mean and the median for the entire cortical ROI. In all analyses, a difference of $p<0.05$ was regarded as statistically significant. The results of the analysis show that all chromophores display statistically highly significant differences between pre- and post-MCAo. The percent changes apparent from the table show a $17\pm 4.7\%$ increase in tissue concentration of deoxyhemoglobin and $45\pm 3.1$ , $23\pm 5.4$ , and $21\pm 2.2\%$ decreases in oxyhemoglobin, total hemoglobin concentration, and cerebral tissue oxygen saturation levels, respectively, following induction of cerebral ischemia. Our findings are consistent with previous observations, considering the variance in measurements, and agree well with known directions of change with cerebral ischemia. For comparison, Culver ⁷ reported chromophore baselines for $\mathrm{ct}{\mathrm{O}}_2\mathrm{Hb}$ $\left(55\text{to}85\mu \mathrm{M}\right)$ , ctHHb $\left(23\text{to}41\mu \mathrm{M}\right)$ , ctTHb $\left(81\text{to}125\mu \mathrm{M}\right)$ , and $\mathrm{st}{\mathrm{O}}_2$ (65 to 73%) in a rat model. The authors also observed a 15% maximum decrease of $\mathrm{st}{\mathrm{O}}_2$ after MCAo, while we observe a maximum decrease of 21% in $\mathrm{st}{\mathrm{O}}_2$ following MCAo. In a human subject, an increase of 20% from baseline in deoxyhemoglobin and 42, 18, and 25% decreases in oxyhemoglobin, total hemoglobin, and brain tissue oxygen saturation concentrations, respectively, were reported.¹⁰

Ischemia results in higher concentrations of ctHHb due to ongoing metabolic activity, and lower $\mathrm{ct}{\mathrm{O}}_2\mathrm{Hb}$ with reduced hemoglobin delivery. These physiological parameters can be grouped into a simple ischemic index, $I_{\mathrm{isch}}=\mathrm{ct}\mathrm{H}\mathrm{Hb}∕\mathrm{ct}{\mathrm{O}}_2\mathrm{Hb}$ . Average values of $I_{\mathrm{isch}}$ for seven rats increased more then twofold after MCAo from $0.66\pm 0.08$ to $1.52\pm 0.28$ (Table 1). To visualize ischemic spatial variations before and after MCAo, we show $I_{\mathrm{isch}}$ images for a representative rat in Fig. 7 . A cross-sectional profile from the left vein towards the right vein was applied as shown in Fig. 7a. The graphs in Fig. 7b represent the gradient profile of $I_{\mathrm{isch}}$ before and after MCAo, respectively. Overall, our results show approximately threefold increase in $I_{\mathrm{isch}}$ levels after MCAo. Prior to occlusion, we observe that $I_{\mathrm{isch}}$ varies across the cortex, with significantly higher levels in the cortical veins (0.83 to 1) compared to the central parenchymal region of mixed microvasculature (0.65 to 0.75). As expected the $I_{\mathrm{isch}}$ spatial profile after MCAo remained approximately the same, but overall levels increased ( $\sim 2.6$ to 3 in veins versus $\sim 1.7$ to 2.2 in parenchyma).

Fig. 7

Ischemic index $(I_{\mathrm{isch}}=\mathrm{ctHHB}∕\mathrm{ct}{\mathrm{O}}_2\mathrm{Hb})$ gradient profile measured before (left) and after (right) MCAo. The dotted lines represents the cross-sectional view along the two cortical veins. Field of view $\sim 6\times 6\mathrm{mm}$ .

4.

Conclusions

In this pilot study, spatially modulated optical imaging using NIR structured illumination was used to measure neural tissue optical properties and cerebral chromophore changes during acute ischemic injury in rat brains. Using this technique, we were able to separate and quantify the absorption and reduced scattering coefficients of tissue in the NIR range. Once determined, the optical properties were used to map and quantify the physiological state of brain tissue in space and time.

Our results show an increase in the tissue concentration of deoxyhemoglobin $(17\pm 4.7\%)$ and a decrease in oxyhemoglobin $(45\pm 3.1\%)$ , total hemoglobin $(23\pm 5.4\%)$ , and cerebral tissue oxygen saturation $(21\pm 2.2\%)$ following induction of cerebral ischemia. Using a simple ischemic index $(I_{\mathrm{isch}}=\mathrm{ct}\mathrm{H}\mathrm{Hb}∕\mathrm{ct}{\mathrm{O}}_2\mathrm{Hb})$ an average of more then twofold contrast is observed after MCAo. We also observed decreases in both scatter power and scatter amplitude of approximately 35% following MCA occlusion, suggesting that optical methods have sensitivity to neural tissue alterations such as cellular swelling and/or tissue edema that may occur secondary to hemodynamic changes.