Part of this work was supported by a Grant-in-Aid for Scientific Research (C) from the Japanese Society for the Promotion of Science (25350520, 22500401, 15K06105) and the US-ARMY ITC-PAC Research and Development Project (FA5209-15-P-0175).

Animal care, preparation, and experimental protocols were approved by the Animal Research Committee of Tokyo University of Agriculture and Technology. For this methodology, the rat is housed in a controlled environment (24 &#176;C, 12 h light/dark cycle), with food and water available ad libitum.
1. Construction of a Conventional Multispectral Diffuse Reflectance Imaging System
<ol>
	<li>Mount nine narrowband optical interference filters with center wavelengths of 500, 520, 540, 560, 570, 580, 600, 730, and 760 nm to the filter holes of the motorized filter wheel.</li>
	<li>Construct a multispectral imaging system using a broadband white light source, a motorized filter wheel with the above set of narrowband interference filters, a light guide, a collecting lens, a video zoom lens, and a monochromatic CCD camera. The layout of optical components, shown in Figure 2, can be referred to for this construction procedure. 
	NOTE: The angle of illumination is approximately 45&#176; with respect to the sample surface.</li>
	<li>Turn on the halogen lamp light source to illuminate the surface of the sample via an interference filter, the light guide, and the collecting lens.</li>
	<li>Open the operating software of the CCD camera.</li>
</ol>
2. Animal Preparation
NOTE:&#160;In this protocol, the rat was not used for the future experiments and it was sacrificed immediately after the measurements of multispectral images.&#160;
<ol>
	<li>Connect the inlet port of an induction chamber to the outlet port of an anesthesia machine with a tube. Connect the outlet port of the induction chamber to the inlet port of the anesthesia machine with a second tube.</li>
	<li>Place the rat into the induction chamber and induce anesthesia with 5.0% isoflurane. Maintain anesthesia at a depth such that the rat does not respond to toe pinches. Lower to 2.0% isoflurane using a rotary knob on the anesthesia machine.</li>
	<li>Fix the rat head in a stereotaxic frame. Attach a mouthpiece for anesthesia to the stereotaxic frame.</li>
	<li>Connect the inlet port of the mouthpiece to the outlet port of the anesthesia machine with a tube. Connect the outlet port of the mouthpiece to the inlet port of the anesthesia machine with a tube.</li>
	<li>Shave the head region beyond the prospective incision site using hair clippers until the skin surface appears.</li>
	<li>Make a longitudinal incision approximately 20 mm long along the midline of the head using a surgical scalpel (Figure 1(a)) and expose the subcutaneous connective tissues (Figure 1(b)).</li>
	<li>Remove the subcutaneous connective tissues using a sharp curette or a pincer and pull it to both sides of the head to expose the skull bone (Figure 1(c)).</li>
	<li>Dig an ellipsoidal ditch on the skull bone inside the cranial sutures (coronal suture, sagittal suture, and lambdoid suture) using a high-speed drill (Figure 1(d)).</li>
	<li>Slowly and homogenously excavate the skull bone inside the ditch using the high-speed drill.</li>
	<li>Press lightly on the surface of the thinned skull with the tip of the pincer to estimate the bone thickness and strength after a cerebral blood vessel appears. If the thinned skull region depresses easily, terminate the reduction of the skull bone with the high-speed drill.</li>
	<li>Cut the ellipsoidal border line of the thinned skull piecemeal using the tip of the pincer or small surgical scissors.</li>
	<li>Remove the thinned skull from the brain surface slowly and gently using the pincer.</li>
	<li>Gently bathe the cranial window with physiological saline and cover it with a transparent glass plate approximately 0.1 mm thick.</li>
</ol>
3. Regulating the Fraction of Inspired Oxygen
NOTE: The respiratory condition can be changed by regulating the fraction of inspired oxygen (FiO2).
<ol>
	<li>Using a tube, connect the first port of a Y-shaped tube connector (connector 1) to the first port of another Y-shaped tube connector (connector 2).</li>
	<li>Connect the inlet port of the mouthpiece to the second port of tube connector 1.</li>
	<li>Using a tube, connect the third port of tube connector 1 to an oxygen concentration monitor device.</li>
	<li>With a tube, connect the second port of tube connector 2 to the outlet port of an anesthesia machine.</li>
	<li>Using a tube, connect the third port of tube connector 2 to the outlet port of a gas mixture device.</li>
	<li>Connect one inlet port of the gas mixture device to a high-pressure 95% O2 - 5% CO2 gas cylinder using a tube.</li>
	<li>Connect the other inlet port of the gas mixture device to a high-pressure 95% N2 - 5% CO2 gas cylinder using a tube.</li>
	<li>Change the gas flow rates of O2 and N2 using the rotary knobs on the gas mixture device.</li>
	<li>Check and regulate the FiO2 using the oxygen concentration monitor device.</li>
</ol>
4. Acquisition of the Multispectral Diffuse Reflectance Images
<ol>
	<li>Acquisition of reference images 
	NOTE: The optical components used in this experiment, such as the light source, optical fiber, and detectors have their own spectral characteristics. Therefore, the intensity of light passed through these components should be recorded as a reference image. The reference image is an image taken with a standard white diffuser illuminated with the light from the light source.
	<ol>
		<li>Put the standard white diffuser on the stage horizontally.</li>
		<li>Focus the camera lens on the surface of the white diffuser by rotating the zoom ring on the barrel.</li>
		<li>Adjust the integration time of the camera by selecting the appropriate value from the drop-down list of integration times in the operating software of the camera so that the greatest amount of light produces a signal that is approximately 75% of the maximum counts. While watching the histogram of pixel values, adjust the integration time until the signal intensity level is approximately 75% of the maximum counts.</li>
		<li>Select the &#34;save&#34; command from the file menu to save an image to a file.</li>
		<li>Change the filter location by rotating the filter wheel.</li>
		<li>Save an image at the other wavelengths according to the process described above. The file name should identify the sample and the wavelength used (e.g., W500, W520, W540 &#8230; W760).</li>
	</ol>
	</li>
	<li>Acquisition of sample images 
	Note: Images of diffusely-reflected light intensity of exposed rat brain at nine wavelengths are captured and saved on the hard drive of a personal computer using the same acquisition conditions.
	<ol>
		<li>Gently place the rat on the stage and slowly adjust the stage level so that the camera can focus on the surface of the rat brain.</li>
		<li>Select the &#34;save&#34; command from the file menu to save an image to a file.</li>
		<li>Change the filter location by rotating the filter wheel.</li>
		<li>Save an image at the other wavelengths according to the process described above. The file name should identify the sample and the wavelength (e.g., R500, R520, R540 &#8230; R760).</li>
	</ol>
	</li>
	<li>Acquisition of dark images 
	NOTE: The CCD camera can generate a light intensity in response to an electrical signal. However, there is some minor output due to noise in the electric circuits and detectors, even if light does not enter to the detector; this is called dark current noise. To accurately measure the spectral intensity of light, the dark current component should be recorded as a dark image and then subtracted from the measured signal. The dark image is an image taken with the light path blocked.
	<ol>
		<li>Turn off the halogen lamp light source.</li>
		<li>Block the light path to the CCD camera system using a shielding plate.</li>
		<li>Select the &#34;save&#34; command from the file menu to save an image to a file. The file name should identify the sample (e.g., Dark).</li>
	</ol>
	</li>
</ol>
5. Visualizing the Hemoglobin Content and the Light Scattering Parameter
NOTE: A set of multispectral diffuse reflectance images is saved to the hard drive of a personal computer and analyzed offline. A multiple regression analysis aided by a Monte Carlo simulation19 of the multispectral diffuse reflectance images at nine wavelengths (500, 520, 540, 560, 570, 580, 600, 730, and 760 nm) is then performed to visualize the two-dimensional maps of oxygenated hemoglobin concentration, deoxygenated hemoglobin concentration, total hemoglobin concentration, regional cerebral oxygen saturation, and scattering power. The detailed algorithm has been published in the literatures17,18.
<ol>
	<li>Subtract the dark image from both the reference image and the sample image at each wavelength.</li>
	<li>Normalize the sample image by the reference image at each wavelength &#955;. Treat the normalized image as the diffuse reflectance image R.</li>
	<li>Calculate the absorbance (or optical density) image A by taking the logarithm of the reciprocal of the diffuse reflectance image R at each wavelength &#955;: 
	<img alt="Equation 1" src="/files/ftp_upload/55399/55399eq1.jpg" />&#160;&#160;&#160;&#160; (1)</li>
	<li>Generate a three-dimensional matrix by stacking the absorbance images in the order of their wavelengths, where the x-y plane shows the structural information obtained for the brain surface and the z-axis shows the spectral information.</li>
	<li>Perform a multiple regression analysis for the absorbance spectrum A(&#955;) at each x-y coordinate.</li>
	<li>Use the absorbance spectrum A(&#955;) as the dependent variable and the molar extinction coefficient spectra of oxygenated hemoglobin &#949;HbO (&#955;) and deoxygenated hemoglobin &#949;HbR (&#955;) as the independent variables for step 5.5 (published values for &#949;HbO (&#955;) and &#949;HbR (&#955;) are provided in Table 1).</li>
	<li>Check the two-dimensional maps (images) of the three multiple regression coefficients aHbO, aHbR, and a0.</li>
	<li>Generate a three-dimensional matrix by stacking the images of the multiple regression coefficients in the order aHbO, aHbR, and a0, where the x-y plane shows the structural information obtained for the brain surface and the z-axis shows the multiple regression coefficients.</li>
	<li>Calculate the oxygenated hemoglobin concentration CHbO, the deoxygenated hemoglobin concentration CHbR, and the scattering power b from the set of multiple regression coefficients aHbO, aHbR, and a0 at each x-y coordinate using the following empirical formulae (he values of &#946;HbO,i, &#946;HbR,i, and &#946;0,i (i = 0,1,2,3) are provided in Table 2): 
	<img alt="Equation 2" src="/files/ftp_upload/55399/55399eq2.jpg" />&#160;&#160;&#160;&#160; (2) 
	<img alt="Equation 3" src="/files/ftp_upload/55399/55399eq3.jpg" /> &#160;&#160;&#160; (3) 
	<img alt="Equation 4" src="/files/ftp_upload/55399/55399eq4.jpg" /> &#160;&#160;&#160; (4)</li>
	<li>Check the two-dimensional maps (images) of the oxygenated hemoglobin concentration CHbO, the deoxygenated hemoglobin concentration CHbR, and the scattering power b.</li>
	<li>Calculate a two-dimensional map of the total hemoglobin concentration CHbT by summing CHbO and CHbR at each x-y coordinate.</li>
	<li>Calculate a two-dimensional map of the regional cerebral oxygen saturation rSO2 by dividing the oxygenated hemoglobin concentration CHbO by the total hemoglobin concentration CHbT at each x-y coordinate.</li>
</ol>

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The authors have nothing to disclose.

The most critical step in this protocol is the removal of the thinned skull region to make the cranial window; this should be performed carefully to avoid unexpected bleeding. This step is important for obtaining high-quality multispectral diffuse reflectance images with high accuracy. The use of a stereomicroscope is recommended for the surgical procedure if possible. Small pieces of gelatin sponge are useful for hemostasis.
The optical system described in this article passes a monochromatic light through an interference filter located in front of the light source. This can be modified by placing the filter wheel in front of the video camera lens or CCD camera. In this case, however, the focal plane can be variable if interference filters with different thicknesses are used, and this will cause a deterioration of the image quality. It is necessary to remove the glass plate from the cranial window if a recording electrode is inserted into the cortical tissue for electrophysiology measurements, such as measurements of the electrical local field potential. In this case, the imaging system can detect undesirable specular reflection from the cortical surface. This problem can be avoided by using a set of polarization plates with a crossed Nicols alignment.
The conventional multispectral imaging apparatus demonstrated in this article is somewhat time-consuming to use, since the filter positions in the wheel are changed mechanically. This means that the imaging system captures each diffuse reflectance image sequentially at a different wavelength-point. Because of this limitation, this system is inadequate to capture fast IOSs, such as changes in the reflectance spectrum due to neuronal activities20. Although oxygenated hemoglobin and deoxygenated hemoglobin are the main chromophores in the living brain tissue, the other chromophores, such as cytochrome c oxidase, flavin adenine dinucleotide and nicotinamide adenine dinucleotide, also contribute to the absorption coefficient in the visible wavelength region. Therefore, the estimated values of CHbO, CHbR, CHbT, rSO2, and b can be affected by the minor chromophores. Moreover, this approach integrates all information along the depth direction because it relies on diffuse reflection. Therefore, the imaging system does not perform depth-resolved measurements.
It is advantageous that the algorithm used for the present system can also be applied to multispectral diffuse reflectance images captured by other rapid spectral imaging techniques, such as an acousto-optical tunable filter21, a multi-aperture lenslet array with interference filters22, and the spectral reconstruction images from an RGB image17,23. Using the proposed algorithm and rapid spectral techniques together is a promising approach for evaluating fast IOS imaging, as well as for use in clinical situations.
Most multispectral brain imaging techniques to date have mainly focused on cortical hemodynamics and tissue metabolism, such as cerebral blood volume, regional cerebral oxygen saturation, and cerebral metabolic rate of oxygen10,11,12,13,14. Several existing approaches evaluate the scattering amplitude under the assumption that the scattering power is constant15,16. However, morphological alterations of tissues due to pathophysiological changes and a reduction of viability in living cortical tissue can affect the size of biological scatterers4,5,6,7,8,9. Therefore, it is important to estimate the scattering parameter of b quantitatively to evaluate the tissue morphologies of the brain. The significance of the present technique with respect to existing methods is its ability to simultaneously measure the spatiotemporal changes in cerebral hemodynamics and cortical tissue morphology.
In terms of future applications, this algorithm can be used for monitoring brain function, vitals, and viability in the cortical tissue of various brain disorder animal models, such as traumatic brain injury, epileptic seizure, stroke, and ischemia.

Multispectral diffuse reflectance imaging is the most common technique for obtaining a spatial map of intrinsic optical signals (IOSs) in cortical tissue. IOSs observed in the in vivo brain are mainly attributed to three phenomena: variations in light absorption and scattering properties due to cortical hemodynamics, variation in absorption depending on the reduction or oxidization of cytochromes in mitochondria, and variations in light scattering properties induced by morphological alterations1.
Light in the visible (VIS) to near-infrared (NIR) spectral range is effectively absorbed and scattered by biological tissue. The diffuse reflectance spectrum of the in vivo brain is characterized by absorption and scattering spectra. The reduced scattering coefficients &#956;s&#39; of brain tissue in the VIS-to-NIR wavelength range result in a monotonous scattering spectrum exhibiting smaller magnitudes at longer wavelengths. The reduced scattering coefficient spectrum &#956;s&#39;(&#955;) can be approximated to be in the form of the power law function2,3 as &#956;s&#39;(&#955;) = a &#215; &#955;-b. The scattering power b is related to the size of biological scatterers in living tissue2,3. Morphological alterations of the tissue and reduction of the viability of living cortical tissue can affect the size of the biological scatterers4,5,6,7,8,9.
An optical system for multispectral diffuse reflectance imaging can be easily constructed from an incandescent light source, simple optical components, and a monochromatic charged-coupled device (CCD). Therefore, various algorithms and optical systems for multispectral diffuse reflectance imaging have been used to evaluate cortical hemodynamics and/or tissue morphology10,11,12,13,14,15,16,17,18.
The method described in this article is used to visualize both the hemodynamics and light scattering properties of rat cerebral tissue in vivo using a conventional multispectral diffuse reflectance imaging system. The advantages of this method over alternative techniques are the ability to evaluate spatiotemporal changes in both cerebral hemodynamics and cortical tissue morphology, as well as its applicability to various brain dysfunction animal models. Therefore, the method will be appropriate for investigations of traumatic brain injury, epileptic seizure, stroke, and ischemia.

<table><tbody><tr><td>150-W halogen-lamp light source</td><td>Hayashi Watch Works Co., Ltd, Tokyo, Japan</td><td>LA-150SAE</td><td></td></tr><tr><td>Light guide</td><td>Hayashi Watch Works Co., Ltd, Tokyo, Japan</td><td>LGC1-5L1000</td><td></td></tr><tr><td>Collecting lens</td><td>Hayashi Watch Works Co., Ltd, Tokyo, Japan</td><td>SH-F16</td><td></td></tr><tr><td>Interference filters l@ 500 nm</td><td>Edmund Optics Japan Ltd, Tokyo, Japan</td><td>#65088</td><td></td></tr><tr><td>Interference filters l@ 520 nm</td><td>Edmund Optics Japan Ltd, Tokyo, Japan</td><td>#65093</td><td></td></tr><tr><td>Interference filters l@ 540 nm</td><td>Edmund Optics Japan Ltd, Tokyo, Japan</td><td>#65096</td><td></td></tr><tr><td>Interference filters l@ 560 nm</td><td>Edmund Optics Japan Ltd, Tokyo, Japan</td><td>#67766</td><td></td></tr><tr><td>Interference filters l@ 570 nm</td><td>Edmund Optics Japan Ltd, Tokyo, Japan</td><td>#67767</td><td></td></tr><tr><td>Interference filters l@ 580 nm</td><td>Edmund Optics Japan Ltd, Tokyo, Japan</td><td>#65646</td><td></td></tr><tr><td>Interference filters l@ 600 nm</td><td>Edmund Optics Japan Ltd, Tokyo, Japan</td><td>#65102</td><td></td></tr><tr><td>Interference filters l@ 730 nm</td><td>Edmund Optics Japan Ltd, Tokyo, Japan</td><td>#65115</td><td></td></tr><tr><td>Interference filters l@ 760 nm</td><td>Edmund Optics Japan Ltd, Tokyo, Japan</td><td>#67777</td><td></td></tr><tr><td>Motorized filter wheel&amp;nbsp;</td><td>Andover Corporation, NH, USA</td><td>FW-MOT-12.5</td><td></td></tr><tr><td>8-bit monochromatic CCD camera</td><td>THE IMAGINGSOURCE, Germany</td><td>DMK21BU618.H</td><td></td></tr><tr><td>Video zoom lens</td><td>Edmund Optics Japan Ltd, Tokyo, Japan</td><td>VZM&lt;sup&gt;TM&lt;/sup&gt;300i</td><td></td></tr><tr><td>Spectralon white standard with 99% diffuse reflectance</td><td>Labsphere Incorporated, North Sutton, NH, USA</td><td>SRS-99-020</td><td></td></tr></tbody></table>

simultaneous evaluation of cerebral hemodynamics and light scattering properties of the in vivo rat brain using multispectral diffuse reflectance imaging

The simultaneous evaluation of cerebral hemodynamics and the light scattering properties of in vivo rat brain tissue is demonstrated using a conventional multispectral diffuse reflectance imaging system. This system is constructed from a broadband white light source, a motorized filter wheel with a set of narrowband interference filters, a light guide, a collecting lens, a video zoom lens, and a monochromatic charged-coupled device (CCD) camera. An ellipsoidal cranial window is made in the skull bone of a rat under isoflurane anesthesia to capture in vivo multispectral diffuse reflectance images of the cortical surface. Regulation of the fraction of inspired oxygen using a gas mixture device enables the induction of different respiratory states such as normoxia, hyperoxia, and anoxia. A Monte Carlo simulation-based multiple regression analysis for the measured multispectral diffuse reflectance images at nine wavelengths (500, 520, 540, 560, 570, 580, 600, 730, and 760 nm) is then performed to visualize the two-dimensional maps of hemodynamics and the light scattering properties of the in vivo rat brain.

Representative spectral images of diffuse reflectance acquired from in vivo rat brains are shown in Figure 3. The images at 500, 520, 540, 560, 570, and 580 nm clearly visualize a dense network of blood vessels in the cerebral cortex. The deterioration of contrast between blood vessels and the surrounding tissue observed in the images at 600, 730, and 760 nm reflects the lower absorption of light by hemoglobin at longer and NIR wavelengths.
Figure 4 shows representative estimated images of an exposed rat brain for oxygenated hemoglobin concentration, deoxygenated hemoglobin concentration, total hemoglobin concentration, regional cerebral oxygen saturation, and scattering power. As expected from the diffuse reflectance images at shorter wavelengths in Figure 3, the total hemoglobin concentration in the blood vessel region is higher than that in the surrounding tissue region. On the other hand, the oxygenated hemoglobin concentrations in arterioles are higher than those in venules due to the hemoglobin in arterial blood being much more oxygenated than in venous blood. Therefore, the distribution of arterioles and venules can be clearly distinguished in the estimated image of regional oxygen saturation.
Representative estimated images of an exposed rat brain during changes in FiO2 for diffuse reflectance at 500 nm r(500), concentration of oxygenated hemoglobin CHbO, concentration of deoxygenated hemoglobin CHbR, concentration of total hemoglobin CHbT, regional cerebral oxygen saturation rSO2, and scattering power b are shown in Figure 5. The value of rSO2 increased under hyperoxic conditions and decreased remarkably after the induction of anoxic conditions. The value of b was slightly increased during the period from the onset of anoxia until respiratory arrest, whereas it continuously decreased during the period from 5 min to 30 min after the onset of anoxia. These changes in the value of b were indicative of morphological changes, such as the swelling and shrinkage of cellular and subcellular structures, induced by the loss of tissue viability in brain.
<img alt="Figure 1" src="/files/ftp_upload/55399/55399fig1.jpg" /> 
Figure 1: Steps in the Surgical Exposure of the Rat Cerebral Cortex. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55399/55399fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/55399/55399fig2.jpg" /> 
Figure 2: Schematic Diagram of the Experimental Apparatus for Administering Anesthesia and Changing the Fraction of Inspired Oxygen. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55399/55399fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/55399/55399fig3.jpg" /> 
Figure 3: Representative Multispectral Diffuse Reflectance Images at 500, 520, 540, 560, 570, 580, 600, 730, and 760 nm, Obtained from an In Vivo Rat Brain. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55399/55399fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/55399/55399fig4.jpg" /> 
Figure 4: Representative Estimated Images of an Exposed Rat Brain. (a) Concentration of oxygenated hemoglobin CHbO, (b) concentration of deoxygenated hemoglobin CHbR, (c) concentration of total hemoglobin CHbT, (d) regional cerebral oxygen saturation rSO2, and (e) scattering power b. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55399/55399fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/55399/55399fig5.jpg" /> 
Figure 5: Representative Results of an Exposed Rat Brain During Changes in FiO2. Images of in vivo rat cortical tissue during changes in FiO2 for diffuse reflectance at 500 nm r(500), concentration of oxygenated hemoglobin CHbO, concentration of deoxygenated hemoglobin CHbR, concentration of total hemoglobin CHbT, regional cerebral oxygen saturation rSO2, and scattering power b. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55399/55399fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Wavelength&#160;&#955; nm</td>
			<td>&#949;HbO (&#955;)</td>
			<td>&#949;HbR (&#955;)</td>
		</tr>
		<tr>
			<td>500</td>
			<td>113.03712</td>
			<td>112.6548</td>
		</tr>
		<tr>
			<td>520</td>
			<td>130.69296</td>
			<td>170.58384</td>
		</tr>
		<tr>
			<td>540</td>
			<td>287.4744</td>
			<td>251.5968</td>
		</tr>
		<tr>
			<td>560</td>
			<td>176.11128</td>
			<td>290.4552</td>
		</tr>
		<tr>
			<td>570</td>
			<td>240.2784</td>
			<td>243.3888</td>
		</tr>
		<tr>
			<td>580</td>
			<td>270.5616</td>
			<td>199.908</td>
		</tr>
		<tr>
			<td>600</td>
			<td>17.28</td>
			<td>79.25688</td>
		</tr>
		<tr>
			<td>730</td>
			<td>2.106</td>
			<td>5.95188</td>
		</tr>
		<tr>
			<td>760</td>
			<td>3.1644</td>
			<td>8.36201</td>
		</tr>
	</tbody>
</table>
Table 1: The Values of &#949;HbO and &#949;HbO used for the Multiple Regression Analysis. The molar extinction coefficients of oxygenated hemoglobin &#949;HbO and deoxygenated hemoglobin &#949;HbR at each wavelength &#955;.
<table fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>i</td>
			<td>&#946;HbO,i</td>
			<td>&#946;HbR,i</td>
			<td>&#946;b,i</td>
		</tr>
		<tr>
			<td>0</td>
			<td>-8.3302</td>
			<td>-5.85271</td>
			<td>-0.76587</td>
		</tr>
		<tr>
			<td>1</td>
			<td>4405.877</td>
			<td>-143.23</td>
			<td>53.34134</td>
		</tr>
		<tr>
			<td>2</td>
			<td>2740.622</td>
			<td>3798.067</td>
			<td>124.4656</td>
		</tr>
		<tr>
			<td>3</td>
			<td>-4.40454</td>
			<td>-2.81699</td>
			<td>-1.36919</td>
		</tr>
	</tbody>
</table>
Table 2: The Values of &#946;HbO,i, &#946;HbR,i, and &#946;0,i (i = 0,1,2,3) used in the Empirical Formulae for CHbO, CHbR, and b. Note that the units of CHbO and CHbR derived from these empirical formulae are the volume concentration, in which the hemoglobin concentration of whole blood with a hematocrit reading of 44% is taken to be the 100% volume concentration of hemoglobin. The empirical formulae for hemoglobin concentrations can be derived from the diffuse reflectance spectra calculated by the Monte Carlo simulation of light transport19. The detailed process for the derivation of the empirical formulae has been described in the literature17,18.

Watch this Scientific Journal Video about Simultaneous Evaluation of Cerebral Hemodynamics and Light Scattering Properties of the In Vivo Rat Brain Using Multispectral Diffuse Reflectance Imaging at J

Simultaneous Evaluation of Cerebral Hemodynamics and Light Scattering Properties of the In Vivo Rat Brain Using Multispectral Diffuse Reflectance Imaging

The simultaneous evaluation of cerebral hemodynamics and the light scattering properties of in vivo rat brain tissue is demonstrated using a conventional multispectral diffuse reflectance imaging system.

Simultaneous Evaluation of Cerebral Hemodynamics and Light Scattering Properties of the In Vivo Rat Brain Using Multispectral Diffuse Reflectance Imaging

The simultaneous evaluation of cerebral hemodynamics and the light scattering properties of in vivo rat brain tissue is demonstrated using a conventional ...

simultaneous-evaluation-cerebral-hemodynamics-light-scattering

Nanyang Technological University

Research

JoVE Journal

Neuroscience

7.6K Views.  Tokyo University of Agriculture & Technology.  De gelijktijdige evaluatie van cerebrale hemodynamica en de lichtverstrooiende eigenschappen van in vivo rattenhersenweefsel wordt aangetoond met conventionele multispectrale diffuse reflectie-afbeeldingssysteem. 

Video: Simultaneous Evaluation of Cerebral Hemodynamics and Light Scattering Properties of the In Vivo Rat Brain Using Multispectral Diffuse Reflectance Imaging

How to Build a Laser Speckle Contrast Imaging (LSCI) System to Monitor Blood Flow

Laser Speckle Contrast Imaging (LSCI) is a simple yet powerful technique that is used for full-field imaging of blood flow. The technique analyzes fluctuations in a dynamic speckle pattern to detect the movement of particles similar to how laser Doppler analyzes frequency shifts to determine particle speed. Because it can be used to monitor the movement of red blood cells, LSCI has become a popular tool for measuring blood flow in tissues such as the retina, skin, and brain. It has become especially useful in neuroscience where blood flow changes during physiological events like functional activation, stroke, and spreading depolarization can be quantified. LSCI is also attractive because it provides excellent spatial and temporal resolution while using inexpensive instrumentation that can easily be combined with other imaging modalities. Here we show how to build a LSCI setup and demonstrate its ability to monitor blood flow changes in the brain during an animal experiment.

How to Build a Laser Speckle Contrast Imaging LSCI System to Monitor Blood Flow

This video demonstrates how to build a Laser Speckle Contrast Imaging (LSCI) system that can easily be used to monitor blood flow.

Laser Speckle Contrast Imaging (LSCI) is a simple yet powerful technique that is used for full-field imaging of blood flow.  The technique analyzes ...

Non-invasive Optical Measurement of Cerebral Metabolism and Hemodynamics in Infants

Perinatal brain injury remains a significant cause of infant mortality and morbidity, but there is not yet an effective bedside tool that can accurately screen for brain injury, monitor injury evolution, or assess response to therapy. The energy used by neurons is derived largely from tissue oxidative metabolism, and neural hyperactivity and cell death are reflected by corresponding changes in cerebral oxygen metabolism (CMRO2). Thus, measures of CMRO2 are reflective of neuronal viability and provide critical diagnostic information, making CMRO2 an ideal target for bedside measurement of brain health.
Brain-imaging techniques such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT) yield measures of cerebral glucose and oxygen metabolism, but these techniques require the administration of radionucleotides, so they are used in only the most acute cases.
Continuous-wave near-infrared spectroscopy (CWNIRS) provides non-invasive and non-ionizing radiation measures of hemoglobin oxygen saturation (SO2) as a surrogate for cerebral oxygen consumption. However, SO2 is less than ideal as a surrogate for cerebral oxygen metabolism as it is influenced by both oxygen delivery and consumption. Furthermore, measurements of SO2 are not sensitive enough to detect brain injury hours after the insult 1,2, because oxygen consumption and delivery reach equilibrium after acute transients 3. We investigated the possibility of using more sophisticated NIRS optical methods to quantify cerebral oxygen metabolism at the bedside in healthy and brain-injured newborns. More specifically, we combined the frequency-domain NIRS (FDNIRS) measure of SO2 with the diffuse correlation spectroscopy (DCS) measure of blood flow index (CBFi) to yield an index of CMRO2 (CMRO2i) 4,5.
With the combined FDNIRS/DCS system we are able to quantify cerebral metabolism and hemodynamics. This represents an improvement over CWNIRS for detecting brain health, brain development, and response to therapy in neonates. Moreover, this method adheres to all neonatal intensive care unit (NICU) policies on infection control and institutional policies on laser safety. Future work will seek to integrate the two instruments to reduce acquisition time at the bedside and to implement real-time feedback on data quality to reduce the rate of data rejection.

We combined frequency-domain near-infrared spectroscopy measures of cerebral hemoglobin oxygenation with diffuse correlation spectroscopy measures of cerebral blood flow index to estimate an index of oxygen metabolism. We tested the utility of this measure as a bedside screening tool to evaluate the health and development of the newborn brain.

Perinatal brain injury remains a significant cause of infant mortality  and morbidity, but there is not yet an effective bedside tool that can  accurately ...

Medicine

Simultaneous PET/MRI Imaging During Mouse Cerebral Hypoxia-ischemia

Dynamic changes in tissue water diffusion and glucose metabolism occur during and after hypoxia in cerebral hypoxia-ischemia reflecting a bioenergetics disturbance in affected cells. Diffusion weighted magnetic resonance imaging (MRI) identifies regions that are damaged, potentially irreversibly, by hypoxia-ischemia. Alterations in glucose utilization in the affected tissue may be detectable by positron emission tomography (PET) imaging of 2-deoxy-2-(18F)fluoro-&#7429;-glucose ([18F]FDG) uptake. Due to the rapid and variable nature of injury in this animal model, acquisition of both modes of data must be performed simultaneously in order to meaningfully correlate PET and MRI data. In addition, inter-animal variability in the hypoxic-ischemic injury due to vascular differences limits the ability to analyze multi-modal data and observe changes to a group-wise approach if data is not acquired simultaneously in individual subjects. The method presented here allows one to acquire both diffusion-weighted MRI and [18F]FDG uptake data in the same animal before, during, and after the hypoxic challenge in order to interrogate immediate physiological changes.

The method presented here uses simultaneous positron emission tomography and magnetic resonance imaging. In the cerebral hypoxia-ischemia model, dynamic changes in diffusion and glucose metabolism occur during and after injury. The evolving and irreproducible damage in this model necessitates simultaneous acquisition if meaningful multi-modal imaging data are to be acquired.

Dynamic changes in tissue water diffusion and glucose metabolism occur during and after hypoxia in cerebral hypoxia-ischemia reflecting a bioenergetics ...

Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy

To obtain a comprehensive understanding of the human brain, utilization of cerebral blood flow (CBF) as a source of contrast is desired because it is a key hemodynamic parameter related to cerebral oxygen supply. Resting state low frequency fluctuations based on oxygenation contrast have been shown to provide correlations between functionally connected regions. The presented protocol uses optical diffuse correlation spectroscopy (DCS) to assess blood flow-based resting state functional connectivity (RSFC) in the human brain. Results of CBF-based RSFC in human frontal cortex indicate that intra-regional RSFC is significantly higher in the left and right cortices compared to inter-regional RSFC in both cortices. This protocol should be of interest to researchers who employ multi-modal imaging techniques to study human brain function, especially in the pediatric population.

This protocol demonstrates how to measure resting state functional connectivity in the human prefrontal cortex using a custom-made diffuse correlation spectroscopy instrument. The report also discuss practical aspects of the experiment as well as detailed steps for analyzing the data.

To obtain a comprehensive understanding of the human brain, utilization of cerebral blood flow (CBF) as a source of contrast is desired because it is a ...

Bioengineering

Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis

Stimulated Raman scattering (SRS) microscopy has emerged as a powerful optical imaging technique for tissue diagnosis. In recent years, two-color SRS has been shown to be able to provide hematoxylin and eosin (H&amp;E)-equivalent images that allow fast and reliable diagnosis of brain cancer. Such capability has enabled exciting intraoperative cancer diagnosis applications. Two-color SRS imaging of tissue can be done with either a picosecond or femtosecond laser source. Femtosecond lasers have the advantage of enabling flexible imaging modes, including fast hyperspectral imaging and real-time, two-color SRS imaging. A spectral-focusing approach with chirped laser pulses is typically used with femtosecond lasers to achieve high spectral resolution. 
Two-color SRS acquisition can be realized with orthogonal modulation and lock-in detection. The complexity of pulse chirping, modulation, and characterization is a bottleneck for the widespread adoption of this method. This article provides a detailed protocol to demonstrate the implementation and optimization of spectral-focusing SRS and real-time, two-color imaging of mouse brain tissue in the epi-mode. This protocol can be used for a broad range of SRS imaging applications that leverage the high speed and spectroscopic imaging capability of SRS.

Stimulated Raman scattering (SRS) microscopy is a powerful, nondestructive, and label-free imaging technique. One emerging application is stimulated Raman histology, where two-color SRS imaging at the protein and lipid Raman transitions are used to generate pseudo-hematoxylin and eosin images. Here, we demonstrate a protocol for real-time, two-color SRS imaging for tissue diagnosis.

Stimulated Raman scattering (SRS) microscopy has emerged as a powerful optical imaging technique for tissue diagnosis. In recent years, two-color SRS has ...

Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) is the most common type of acquired brain injury. Since patients with traumatic brain injury show a tremendous variability and heterogeneity (age, gender, type of trauma, other possible pathologies, etc.), animal models play a key role in unraveling factors that are limitations in clinical research. They provide a standardized and controlled setting to investigate the biological mechanisms of injury and repair following TBI. However, not all animal models mimic the diffuse and subtle nature of mTBI effectively. For example, the commonly used controlled cortical impact (CCI) and lateral fluid percussion injury (LFPI) models make use of a craniotomy to expose the brain and induce widespread focal trauma, which are not commonly seen in mTBI. Therefore, these experimental models are not valid to mimic mTBI. Thus, an appropriate model should be used to investigate mTBI. The Marmarou weight drop model for rats induces similar microstructural alterations and cognitive impairments as seen in patients who sustain mild trauma; therefore, this model was selected for this protocol. Conventional computed tomography and magnetic resonance imaging (MRI) scans commonly show no damage following a mild injury, because mTBI induces often only subtle and diffuse injuries. With diffusion weighted MRI, it is possible to investigate microstructural properties of brain tissue, which can provide more insight into the microscopic alterations following mild trauma. Therefore, the goal of this study is to obtain quantitative information of a selected region-of-interest (i.e., hippocampus) to follow up disease progression after obtaining a mild and diffuse brain injury.

The overall goal of this procedure is to obtain quantitative microstructural information of the hippocampus in a rat with mild traumatic brain injury. This is done using an advanced diffusion-weighted magnetic resonance imaging protocol and region-of-interest based analysis of parametric diffusion maps.

Mild traumatic brain injury (mTBI) is the most common type of acquired brain injury. Since patients with traumatic brain injury show a tremendous ...

Cerebrovascular Reactivity Measurement with Functional Near Infrared Spectroscopy

Cerebrovascular reactivity (CVR) is the capacity of blood vessels in the brain to alter cerebral blood flow (either with dilation or constriction) in response to chemical or physical stimuli. The amount of reactivity in the cerebral microvasculature depends on the integrity of the capacitance vasculature and is the primary function of endothelial cells. CVR is, therefore, an indicator of the microvasculature&#8217;s physiology and overall health. Imaging methods that can measure CVR are available but can be costly, and require magnetic resonance imaging centers and technical expertise. In this study, we used fNIRS technology to monitor changes of oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the cerebral microvasculature to assess the CVR of 15 healthy controls (HC) in response to a vasoactive stimulus (inhaled 5% carbon dioxide or CO2). Our results suggest that this is a promising imaging technology that offers a non-invasive, accurate, portable, and cost-effective method of mapping cortical CVR and associated microvasculature function, resulting from a traumatic brain injury or other conditions associated with cerebral microvasculopathy.

Presented here is a protocol for imaging and measurement of cerebrovascular reactivity in humans with functional Near Infrared Spectroscopy (fNIRS). fNIRS is a novel imaging modality that captures the concentration changes of hemoglobin species in the brain&#8217;s outermost cortex under specific stimuli.

Cerebrovascular reactivity (CVR) is the capacity of blood vessels in the brain to alter cerebral blood flow (either with dilation or constriction) in ...

Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury

Mild traumatic brain injuries (mTBIs) are a significant public health problem. Repeated exposure to mTBI can lead to cumulative, long-lasting functional deficits. Numerous studies by our group and others have shown that mTBI stimulates cytokine expression and activates microglia, decreases cerebral blood flow and metabolism, and impairs cerebrovascular reactivity. Moreover, several works have reported an association between derangements in these neuroinflammatory and hemodynamic markers and cognitive impairments. Herein we detail methods to characterize the neuroinflammatory and hemodynamic tissue response to mTBI in mice. Specifically, we describe how to perform a weight-drop model of mTBI, how to longitudinally measure cerebral blood flow using a non-invasive optical technique called diffuse correlation spectroscopy, and how to perform a Luminex multiplexed immunoassay on brain tissue samples to quantify cytokines and immunomodulatory phospho-proteins (e.g., within the MAPK and NF&#954;B pathways) that respond to and regulate activity of microglia and other neural immune cells. Finally, we detail how to integrate these data using a multivariate systems analysis approach to understand the relationships between all of these variables. Understanding the relationships between these physiologic and molecular variables will ultimately enable us to identify mechanisms responsible for mTBI.

This protocol presents methods to characterize the neuroinflammatory and hemodynamic response to mild traumatic brain injury and to integrate these data as part of a multivariate systems analysis using partial least squares regression.

Mild traumatic brain injuries (mTBIs) are a significant public health problem. Repeated exposure to mTBI can lead to cumulative, long-lasting functional ...

Quantification of Cerebral Perfusion using Laser Speckle Imaging and Infarct Volume using MRI in a Pre-clinical Model of Posterior Circulation Stroke

Background: Basilar artery occlusion (BAO) is a subset of posterior circulation stroke that carries a mortality as high as 90%.&#160; The current clinical standard to diagnose ischemic stroke include computerized tomography (CT), CT angiography and perfusion and magnetic resonance imaging (MRI). Large animal pre-clinical models to accurately reflect the clinical disease as well as methods to assess stroke burden and evaluate treatments are lacking.
Methods: We describe a canine model of large vessel occlusion (LVO) stroke in the posterior circulation, and developed a laser speckle imaging (LSI) protocol to monitor perfusion changes in real time.&#160; We then utilized high b-value DWI (b=1800s/mm2) MRI to increase detection sensitivity. We also evaluated the ability of magnetic resonance angiography (MRA) to assess arterial occlusion and correlate with DSA. Finally, we verified infarct size from apparent diffusion coefficient (ADC) mapping with histology.&#160;
Results:&#160; Administration of thromboembolism occluded the basilar artery as tracked by DSA (n=7).&#160; &#160;LSI correlated with DSA, demonstrating a reduction in perfusion after stroke onset that persisted throughout the experiment, allowing us to monitor perfusion in real time.&#160; DWI with an optimized b-value for dogs illustrated the stroke volume and allowed us to derive ADC and magnetic resonance angiography (MRA) images. The MRA performed at the end of the experiment correlated with DSA performed after occlusion. Finally, stroke burden on MRI correlated with histology.
Conclusions: Our studies demonstrate real time perfusion imaging using LSI of a canine thromboembolic LVO model of posterior circulation stroke, which utilizes multimodal imaging important in the diagnosis and treatment of ischemic stroke.

A canine model of LVO stroke was utilized to develop laser speckle imaging to monitor cerebral perfusion in real-time.&#160; Diffusion-weighted MRI was optimized to image infarct volume utilizing a high b-value, enabling ADC and MRA, correlated with DSA at the time of stroke.&#160; Finally, ADC reconstructions correlated with histological findings.

Background: Basilar artery occlusion (BAO) is a subset of posterior circulation stroke that carries a mortality as high as 90%.&#160; The current clinical ...

Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies

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&#160;monitoring in open fields (e.g., defense and sports).

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.

Neurophysiological monitoring is an important goal in the treatment of neurocritical patients, as it may prevent secondary damage and directly impact ...

Simultaneous Evaluation of Cerebral Hemodynamics and Light Scattering Properties of the In Vivo Rat Brain Using Multispectral Diffuse Reflectance Imaging

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