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17 October 2016 Two-photon microscopy measurement of cerebral metabolic rate of oxygen using periarteriolar oxygen concentration gradients
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The cerebral metabolic rate of oxygen (CMRO2) is an essential parameter for evaluating brain function and pathophysiology. However, the currently available approaches for quantifying CMRO2 rely on complex multimodal imaging and mathematical modeling. Here, we introduce a method that allows estimation of CMRO2 based on a single measurement modality—two-photon imaging of the partial pressure of oxygen (PO2) in cortical tissue. We employed two-photon phosphorescence lifetime microscopy (2PLM) and the oxygen-sensitive nanoprobe PtP-C343 to map the tissue PO2 distribution around cortical penetrating arterioles. CMRO2 is subsequently estimated by fitting the changes of tissue PO2 around arterioles with the Krogh cylinder model of oxygen diffusion. We measured the baseline CMRO2 in anesthetized rats and modulated tissue PO2 levels by manipulating the depth of anesthesia. This method provides CMRO2 measurements localized within ∼200  μm and it may provide oxygen consumption measurements in individual cortical layers or within confined cortical regions, such as in ischemic penumbra and the foci of functional activation.



Estimation of the cerebral metabolic rate of oxygen (CMRO2) is a challenging task that in common practice requires knowledge of both blood oxygenation and flow.1 CMRO2 is estimated from multiple measurements analyzed within the context of an appropriate mathematical model of the physiology and the measured quantities. Indeed, all methods of estimating CMRO2 are essentially solving a mass balance equation, where CMRO2 is equated to the difference of oxygen flowing into a region of interest and the oxygen flowing out. Such modeling adds a layer of complexity to estimating CMRO2 and raises concerns about the accuracy of the estimates due to the assumptions and limitations of the experimental methods and models used.

Several methods exist to measure CMRO2 in humans and in small animals. The leading method for measuring CMRO2 in humans is positron emission tomography (PET) using O15-labeled oxygen and water to estimate oxygen uptake and cerebral blood flow (CBF), respectively.2,3 Another method gaining popularity in human studies is the “calibrated” blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) approach.47 This method combines BOLD fMRI with arterial spin labeling methods and includes an additional calibration step (e.g., measuring local CBF and BOLD responses to mild hypercapnia).1 Near-infrared spectroscopy measurement of cerebral blood oxygenation is used in combination with blood flow measurements to assess CMRO2 in both adults and neonates.8,9 Finally, magnetic resonance spectroscopy (MRS) based on P31 and C31 can be used in humans to assess metabolic parameters tightly coupled with CMRO2, such as the tricarboxylic acid cycle rate and cerebral metabolic rate of adenosine triphosphate (CMRATP), respectively.10,11 In animals, CMRO2 is also often estimated using a combination of measurements of blood oxygenation and flow. PET and fMRI techniques were appropriately modified to allow high spatial resolution measurements of CMRO2 (e.g., 1.2  mm for microPET12 and voxel size of several mm3 for MRI13,14). In addition, MRS can be used to assess CMRO2 directly based on O17 with a few millimeters spatial resolution.15,16 Optical imaging methods offer numerous choices to measure CMRO2 in animals by combining blood oxygenation and flow measurements. Blood oxygenation can be assessed by spectroscopic optical imaging of hemoglobin saturation by using intrinsic signals,1720 visible optical coherence tomography (OCT),21,22 photoacoustic imaging (PAI),23,24 or phosphorescence lifetime imaging.2528 CBF can be obtained by laser Doppler or speckle contrast imaging,19,29 OCT,30,31 or PAI.23,24 Due to the complex cortical microvascular morphology (i.e., no single vascular input and output in the cortex), in cases where CBF and oxygenation were measured in individual vessels, both parameters must be acquired over a large field of view (1  mm or larger) in order to estimate CMRO2. By assuming the cortical thickness and that no vessels assessed on the cortical surface supply subcortical regions, the estimated CMRO2 represents an average over the entire cortical depth and field of view.

Here, we present a high-spatial-resolution and more direct method for estimating CMRO2 that relies on a single experimentally obtained parameter—the partial pressure of oxygen (PO2) in tissue in the immediate vicinity (<200  μm) of penetrating cortical arterioles. Earlier attempts to measure CMRO2 by directly fitting the solution of Poisson’s equation to PO2 around vessels were limited by the inability to measure tissue PO2 at depth with adequate sensitivity and resolution.32 This limitation was recently overcome by the development of 2PLM of PO2 that allows measurements of both intravascular and interstitial (tissue) cortical PO2 in vivo with high spatial and temporal resolution.3342 Here, we estimated CMRO2 by applying the Krogh cylinder model43 to periarteriolar tissue around penetrating arterioles and fitting the experimentally determined distributions of tissue PO2 to the Krogh–Erlang solution. Our method provides CMRO2 measurements localized within 200  μm, which is defined by the tissue area where PO2 distributions are measured, and it can be easily combined with other optical microscopy tools for preclinical studies of cerebral function and metabolism.




Animal Preparation

Sprague Dawley rats (250 to 320 g) were anesthetized with isoflurane (1.5% to 2% in a mixture of O2 and air), temperature controlled, tracheotomized, and catheters were inserted in the femoral artery and vein for administering the anesthesia and dyes, and for measuring blood gases, pH, and blood pressure. We created a cranial window in the center of the parietal bone with the dura removed. Before sealing the window, we pressure-injected 0.1  μL of PtP-C343 (1.4×104  M) 300  μm below the surface of the brain using a glass micropipette. The imaging was performed a few hundred microns from the injection site. Slow diffusion of the probe in the bulk-loaded brain tissue allows imaging of PO2 for several hours following the injection. During the measurements, we ventilated rats with a mixture of air and oxygen adjusting the fraction of the inspired oxygen (FiO2=21% to 24%) to maintain systemic arterial PO2 at 95 to 110 mmHg. Isoflurane was discontinued and anesthesia maintained with a 50  mg/kg intravenous bolus of alpha-chloralose followed by continuous intravenous infusion at 40  mg/(kgh). The systemic arterial blood PCO2 was 35 to 44 mmHg and pH was 7.35 to 7.42. All experimental procedures were approved by the Massachusetts General Hospital Sub-Committee on Research Animal Care.


Experimental Protocol

Two-photon in vivo brain imaging was performed by using our previously described custom-built microscope, controlled by the custom-designed software.34,44 The optical beam was scanned in the XY plane by galvanometer scanners and focused on the sample by an objective (Olympus 20X XLumPlanFL; NA=0.95). A motorized stage controlled the focal position along the vertical axis (Z), and an electro-optic modulator served to gate the output of the high-repetition rate pulsed laser (Mai Tai, Spectra Physics).

We excited PtP-C343 phosphorescence by 10-μs-long trains of femtosecond pulses at 840 nm, followed by a 290-μs-long phosphorescence collection period. The emission was detected by two of the four photomultiplier tubes (PMTs) in our detector array. The phosphorescence output was detected by a photon-counting PMT module (H10770PA-50, Hamamatsu). In a typical experiment, we performed phosphorescence detection in two steps. First, we raster scanned the excitation beam over the field of view, rendering two-dimensional survey maps of the integrated emission intensity. After mapping the distribution of intensity, we averaged 500 to 2000 phosphorescence decays in selected point locations in the tissue for accurate PO2 determination. This acquisition time corresponded to a temporal resolution of 0.16 to 0.76 s per single-point PO2 measurement. PO2 data were typically collected in a grid pattern spanning 300×300  μm2 and consisting of 500 points, which, together with the survey mapping and selection of the grid points, took 2 to 5 min to collect. Finally, we converted phosphorescence lifetimes into PO2 values by using Stern–Volmer calibration plots.33

Structural images of the cortical vasculature were obtained by imaging the blood plasma labeled with fluorescein isothiocyanate (FITC)-dextran. We collected images of the vasculature at the PO2 imaging planes immediately before or after PO2 imaging. These images were coregistered with the PO2 data and used to define blood vessel boundaries. We also collected a three-dimensional vascular angiogram at the end of each experiment.


Data Processing

We assumed that oxygen diffusion from a penetrating arteriole can be approximated by the Krogh cylinder model of oxygen diffusion from a vessel.43 In the Krogh cylinder model [Fig. 1(a)], a vessel with cylindrical shape and radius Rart supplies a tissue cylinder with radius Rt. We also assumed that oxygen consumption (CMRO2), tissue oxygen diffusivity (D), and solubility (α) constants are spatially homogeneous and temporally invariant. If D is isotropic and all important microvascular oxygen transport phenomena are steady state, the oxygen diffusion in a tissue satisfies Poisson’s equation:

Eq. (1)

where Δ is the Laplace operator and PO2(r) is the oxygen partial pressure at location r, respectively. By assuming that (1) axial oxygen diffusion is insignificant, (2) PO2(r)/r=0 at the tissue cylinder boundary Rt, and (3) PO2 in tissue at the arteriolar wall [PO2(Rart)] is labeled PO2,art, the solution of Eq. (1) can be expressed as a well-known Krogh–Erlang formula describing oxygen diffusion from a cylinder:43

Eq. (2)

with a difference that in Eq. (2) we consider a tissue cylinder around the penetrating cortical arteriole instead of the originally considered tissue cylinder around a capillary.

Fig. 1

The Krogh cylinder, cortical vascular morphology, and tissue PO2. (a) The Krogh cylinder model of oxygen diffusion from a vessel. An infinitely long tissue cylinder with radius Rt is supplied by an infinitely long arteriole with radius Rart. PO2 map on the right hand side is computed based on Krogh–Erlang equation [Eq. (2)]. The zero oxygen flux boundary condition (dPO2/dr=0 at r=Rt) is satisfied at the external tissue boundary. (b) Maximum intensity projection of a 500-μm-thick microvascular stack. Pial artery and adjacent diving arterioles are colored red. Yellow circles emphasize capillary-free spaces around diving arterioles. Scale bar, 100  μm. (c) Baseline tissue PO2 map (color coded), overlaid on a FITC image of the microvasculature 100  μm below the brain surface. Inset in upper left corner shows 200-μm-thick MIP of FITC-labeled microvasculature. Arterioles are colored red. White rectangle in inset outlines the position of the panel (c). Scale bar, 100  μm.


In our experiments, Rart was estimated from the vascular anatomical images obtained by two-photon microscopy of FITC-labeled blood plasma. We assumed the tissue oxygen permeability Dα to be equal to the oxygen permeability of water (α=1.39  μMmmHg1; D=4×105  cm2s1).45 Periarteriolar tissue PO2 measurements were coregistered with the vascular anatomical images. The radial distance from the center of the penetrating arteriole r was estimated for each measured tissue PO2 point. Equation (2) was fit for CMRO2, Rt, and PO2,art. Nonlinear least squares fitting was performed by the Levenberg–Marquardt algorithm. Since the Krogh cylinder model does not include tissue regions beyond radius Rt, in each iterative step of the fitting procedure, the sum of the squares of residuals was calculated only for the measured PO2 points up to a radial distance of Rt. All the data processing procedures were custom-written in MATLAB (MathWorks Inc.).



The cortical vasculature consists of a planar mesh of pial arteries and veins at the cortical surface that dive into the cortex supplying a complex microvascular network and draining the blood back to the surface. Figure 1(b) shows a typical cortical vascular anatomical image of the rat cortex. Vascular images, such as in Fig. 1(b), reveal that periarteriolar tissue around penetrating arterioles is largely devoid of capillaries, whereas the tissue away from penetrating arterioles exhibits high capillary density. One possible explanation for this morphological feature could be that the periarteriolar region is characterized by reduced cell density, and thus, it does not need as much oxygen as other tissue regions. However, published data on the density of neurons and astrocytes in cerebral cortex demonstrate the absence of anatomical differences between periarteriolar spaces and other cortical regions.46 Therefore, a more likely explanation is that highly oxygenated blood from cortical penetrating arterioles efficiently supplies large periarteriolar tissue territories, and formation of capillaries near the arterioles is simply not required. Figure 1(c) shows an example map of cortical tissue oxygen concentration, where large PO2 gradients originating from the diving arteriole are dominating the tissue PO2 landscape. The central part of Fig. 1(c) shows a typical radially symmetrical profile of periarteriolar tissue PO2 in a plane parallel with the cortical surface (e.g., perpendicular to the propagation axis of the penetrating arteriole).

To obtain data for the CMRO2 fitting, we typically imaged tissue PO2 over a grid spanning 300×300  μm2 and selected a subset of the PO2 data within an arc around the arteriole with the most uniform and steepest PO2 descent. Figure 2 shows four individual examples, where CMRO2 was estimated based on periarteriolar tissue PO2 profiles from the upper 100 to 160  μm of cortex in four different subjects. The estimated mean CMRO2 was 1.71±0.16  μmolcm3min1, where individual measurements varied between 1.4  μmolcm3min1 and 2.1  μmolcm3min1 (Table 1), in agreement with the previously measured 2.5±1.0  μmolcm3min1 in rats under a similar anesthesia regime.47 The estimated Krogh cylinder tissue radius Rt varied between 70.4 and 106.5  μm, in agreement with the measured distances Rcap,min of the closest capillaries to the penetrating arteriole (Table 1).

Fig. 2

Baseline CMRO2 measurements. (a–d) Tissue PO2 maps (color coded) around penetrating arterioles overlaid on the corresponding FITC images of microvasculature in different animals (rats I to IV). Insets show MIPs of FITC-labeled microvasculature. Arterioles in insets are colored red. The white rectangle in each insert outlines the position of the corresponding panel with the PO2 data. Yellow lines outline regions of interest with PO2 data included in the fitting procedure. Imaging depths below brain surface are 100  μm (rat I), 150  μm (rat II), 124  μm (rat III), and 160  μm (rat IV). Scale bars, 100  μm. (e–h) Tissue PO2 from the corresponding upper panels as a function of the radial distance from the penetrating arteriole with PO2 fit indicated by solid line.


Table 1

Estimated Krogh cylinder parameters.

Rat #CMRO2 (μmol cm−3 min−1) fittedRt (μm) fittedPO2,art (mmHg) fittedRart (μm) fixedRcap,min (μm)

aStandard error.

Figure 3 illustrates the likely influence of physiological and morphological parameters, such as blood pressure, heart rate, and microvascular configuration upon cerebral PO2 and estimation of CMRO2. Two CMRO2 measurements were performed along the same penetrating arteriole in rat II (Fig. 2) at two imaging depths (150 and 130  μm below the cortical surface). The data at the two depths were collected 30 min apart. The result indicates a significant increase in the baseline tissue PO2 in the second measurement in comparison with the first measurement. This is likely due to an increase in blood flow, since no noticeable change in PO2 was previously observed in penetrating arterioles of similar caliber over the difference in depth of only 20  μm.41,42 The variation of the baseline tissue PO2 and change in microvascular configuration at different depths may influence the CMRO2 fitting procedure. However, we anticipated that CMRO2 should not exhibit significant changes within a cortical layer. In agreement with this expectation, the estimated CMRO2 at these two depths was found to be the same (1.4  μmolcm3min1; Table 2).

Fig. 3

CMRO2 estimation at different baseline tissue PO2 and two cortical depths along the same penetrating arteriole. (a, b) Tissue PO2 maps (color coded) overlaid on FITC images of microvasculature at depths of (a) 150  μm and (b) 130  μm below the brain surface. Inset in the lower left corner shows 160-μm-thick MIPs of FITC-labeled microvasculature. Arterioles are colored red. White rectangles in insets outline the position of the panels (a) and (b). Regions of interest with PO2 data included in the fitting procedure are the same as in rat II (Fig. 2). Scale bars, 100  μm. (c) Tissue PO2 dependence on the radial distance from the arteriole with PO2 fits indicated by solid lines.


Table 2

Estimated Krogh cylinder parameters at different depths and baseline tissue PO2.

Depth (μm)CMRO2 (μmol cm−3 min−1) fittedRt (μm) fittedPO2,art (mmHg) fittedRart (μm) fixed

aStandard error.

To experimentally manipulate CMRO2, we modulated the level of anesthesia in rat IV (Fig. 2) by applying isoflurane (2%) on top of the ongoing alpha-chloralose anesthesia. Adding isoflurane resulted in a decrease in both blood pressure and heart rate (from 100 to 76 mmHg and from 8 to 6.5 Hz, respectively) and an increase in tissue PO2. The increase in PO2 is expected if neuronal activity and the associated CMRO2 decrease under deeper anesthesia. Isoflurane is also a vasodilator that increases blood perfusion, which further reduces oxygen extraction fraction and increases tissue PO2.48 Figure 4 shows the comparison of CMRO2 estimated at the same imaging location (160  μm deep) between the two anesthesia regimes. As expected, deeper anesthesia caused an increase in the baseline tissue PO2 [Fig. 4(c)]. The PO2 dependence on the radial distance from the arteriole was markedly less steep with the addition of isoflurane [Fig. 4(c)]. The measured CMRO2 decreased from 1.56±0.36  μmolcm3min1 (alpha-chloralose only) to 1.38±0.35  μmolcm3min1 (combined alpha-chloralose and isoflurane) (Table 3). The difference was not significant mostly due to the uncertainty in fitting the tissue radius Rt. However, when Rt was treated as a fixed parameter in the CMRO2 estimation, which is likely to be appropriate here, considering that we are comparing CMRO2 measurements at the same location, the CMRO2 error decreased to 0.07  μmolcm3min1 (Table 3).

Fig. 4

CMRO2 estimation at two anesthesia depths. (a, b) Tissue PO2 maps (color coded) at two different anesthesia levels, overlaid on FITC image of microvasculature 160  μm below brain surface. (a) Alpha-chloralose anesthesia; (b) combined alpha-chloralose and isoflurane anesthesia. Inset in lower right corner shows 312-μm-thick MIP of FITC-labeled microvasculature. Arterioles are colored red. White rectangle in inset outlines the positions of the panels (a) and (b). Regions of interest with PO2 data included in the fitting procedure are the same as in rat IV (Fig. 2). Scale bars, 100  μm. (c) Tissue PO2 dependence on the radial distance from the arteriole with PO2 fits indicated by solid lines.


Table 3

Estimated Krogh cylinder parameters at different anesthesia depths.

AnesthesiaCMRO2 (μmol cm−3 min−1) fittedRt (μm)PO2,art (mmHg) fittedRart (μm) fixed
Alpha-chloralose1.56±0.36a106.5±8.9 Fitted63.1±2.89.1
Alpha-chloralose + isoflurane1.38±0.35106.6±9.1 Fitted66.0±2.910.0
Alpha-chloralose1.56±0.07106.5 Fixed63.0±2.09.1
Alpha-chloralose + isoflurane1.35±0.07106.5 Fixed64.9±2.010.0

aStandard error.



Our study demonstrates that we can estimate CMRO2 using the Krogh cylinder model based on a single measurement modality—periarteriolar tissue PO2 measurement by two-photon microscopy in a single plane perpendicular to the vessel axis. With this method, no measurements of blood flow are required for the CMRO2 estimation. Using this method, we obtained a mean baseline CMRO2 of 1.71±0.16  μmolcm3min1, within the error bounds of previously reported CMRO2 under similar anesthesia in rats measured by MRI (2.5±1.0  μmolcm3min1).47

Several properties of the cortical vascular and cellular architecture make this simple model based on the Krogh cylinder applicable. First, the large tissue PO2 gradients around cortical penetrating arterioles (Figs. 1 and 2) are readily detectable with two-photon microscopy of PO2. Second, all oxygen consumed by the tissue adjacent to the penetrating arteriole is supplied by the arteriole. This is evident from (1) the large tissue PO2 gradients surrounding penetrating arterioles34,36,41,4951 (Fig. 2) and (2) the absence of other oxygen sources (i.e., capillaries) in a 50 to 100-μm radius around penetrating arterioles in rats [Fig. 1(b)] and also in mice.52 The oxygen delivery from penetrating arterioles is also consistent with observations of intravascular radial PO2 profiles in penetrating arterioles demonstrating a PO2 decrease from the vessel center to the arteriolar wall.41 Third, while at the cellular scale CMRO2 is likely heterogeneous, CMRO2 based on an approximate 200×200  μm2 area around a penetrating arteriole likely represents an accurate average CMRO2 estimate for a particular cortical depth. This is implied from the uniform distribution of neural and glial cells within a cortical column (300  μm in diameter in the rat primary somatosensory cortex),46 although this result does not necessarily guarantee that the density of synapses, which are the major contributors to the cortical oxygen consumption,53 is uniform as well. This also suggests that the spatial localization of our CMRO2 measurement is 200  μm. We also note that the depth resolution of PO2 imaging in our experiments is 5  μm.34 Fourth, the diameters of penetrating arterioles (15 to 20  μm) and their blood flow are sufficiently large so that the axial change in intravascular PO2 is small and thus, the influence of axial PO2 gradients is negligible.45,54 This is a requirement for the Krogh cylinder model, where a single cylindrical oxygen source supplies a homogeneous tissue cylinder.43

Here, we address several important aspects of our measurements, including differences from other reported measurements and potential sources of errors: (1) most of our measurements were obtained in the upper cortical layer (layer I, i.e., the top 150  μm in the rat), which has a lower density of both neuronal cell bodies and synapses than most deeper cortical layers.55,56 Deeper cortical layers may exhibit higher CMRO2.47 (2) The fit of Eq. (2) estimates CMRO2/(Dα). Therefore, the accuracy of our CMRO2 estimate depends on the accuracy of the assumed values for the tissue permeability to oxygen (e.g., Dα). Unfortunately, the literature does not provide clear guidance on the accurate values to use for D and α in the rat brain cortex. Measurements of D have been typically preformed in muscle. In the hamster retractor muscle, Bentley et al.57 measured D=2.41×105  cm2s1. The oxygen diffusion constant in water (D=4×105  cm2s1) that we applied in our calculations likely leads to an overestimation of CMRO2, although oxygen diffusion in the brain cortex is probably faster than in the muscle due to a higher water content in the brain cortex.58,59 On the other hand, the oxygen solubility in water (α=1.3  μMmmHg1) that we applied in our calculations is lower than the reported solubility in the frog sartorius muscle (α=1.6  μMmmHg1),60 and the solubility of oxygen in brain cortex may be even higher due to a higher lipid content. (3) The mean relative error of the CMRO2 estimates was 18%, with the relative error of individual measurements varying between 12% and 23% (Table 1). The largest contributor to the error of the CMRO2 fit is the uncertainty in the Rt estimation. If we assume that oxygen flux through the arteriolar wall is JO2, CMRO2 can be expressed by considering a simple mass balance of oxygen delivered to and consumed in the tissue cylinder as CMRO2=2RartJO2/(Rt2Rart2). If JO2 is constant, the relative error of CMRO2 is related to the relative error of Rt as ΔCMRO2/CMRO22ΔRt/Rt. Increasing the number of collected tissue PO2 points may be one possible approach to reduce this uncertainty. When performing the CMRO2 measurement on rat II (Fig. 2), we increased the number of acquired PO2 points by 2×, which resulted in a significantly reduced relative error of both Rt (4.5%) and CMRO2 (11.6%). This approach, however, leads to doubling the data acquisition time. Our current acquisition of PO2 points on a grid pattern leads to a nonuniform distribution of PO2 points as a function of the radial distance from the arteriole. It is possible that other PO2 acquisition patterns, such as a radial grid, may improve the CMRO2 fitting error without the need to increase the number of PO2 measurement points. Future work will also investigate the effect of periarteriolar microvascular configurations in realistic vascular anatomical networks (VANs) on the periarteriolar tissue PO2 distribution and CMRO2 estimation. The combined experimental and numerical modeling approach61 may be utilized to further investigate the effect of nearby capillary and arteriolar vascular segments on the axial symmetry and radial extent of the periarteriolar tissue PO2 profiles, including potential changes of the tissue territories supplied by these vessels at different CMRO2 and CBF levels.41 The influence of the deviations of the PO2 measurement plane from a plane perpendicular to the arteriole on estimating CMRO2 may also require further attention. Finally, the CMRO2 fitting error is significantly lower if we fix Rt in the fitting procedure (Fig. 4). We believe that this approach may be appropriate when comparing CMRO2 changes at the same location.

Advances in the development of contrast agents for multiphoton imaging of PO2 and multiphoton imaging instrumentation may bring significant improvements and opportunities for CMRO2 measurements based on tissue PO2 maps. Significantly brighter and red-shifted PO2-sensitive dyes62 should allow faster, more accurate, and deeper tissue PO2 imaging in the brain cortex relative to our current 300-μm imaging depth limited primarily by the contamination of the deep signals with the out-of-focus phosphorescence. Faster and more accurate acquisition of tissue PO2 may significantly reduce both acquisition time and CMRO2 measurement error. It may potentially enable the possibility to estimate CMRO2 directly based on Eq. (1) both around penetrating arterioles and in a tissue away from them, providing smooth mapping of PO2 between capillaries. Currently, the complexity of the spatial distribution of the tissue PO2 around apparently randomly oriented cortical capillaries and the relatively small variation of the tissue PO2 around them are making it challenging to estimate CMRO2 based on Eq. (1) around capillaries. Alternatively, advanced modeling of oxygen advection and diffusion in realistic VANs may be utilized to estimate CMRO2 based on tissue PO2 imaging anywhere in the cortical tissue.32 In this approach, modeling may be further constrained by adding the blood flow and intravascular oxygenation measurements.63,64



The steady-state oxygen distribution in cortical tissue satisfies Poisson’s equation, exhibiting a simple dependence on CMRO2 [Eq. (1)]. We present a method of estimating CMRO2 based on Eq. (1) that utilizes two-photon microscopy imaging of cortical tissue PO2 and exploits the specific morphology of cortical penetrating arterioles and neighboring microvessels that allows us to model the periarteriolar tissue PO2 distribution with the Krogh cylinder model. This method depends on a single imaging parameter (e.g., periarteriolar tissue PO2), making it significantly less complex and potentially more accurate than existing CMRO2 measuring methods that rely on multimodal imaging of blood oxygenation and blood flow. In addition, the measurement is spatially localized to a small tissue area (200  μm), and it can be easily combined with other optical microscopy tools for preclinical studies in animals, providing approaches to address critical questions related to cortical pathological conditions and in understanding the fMRI signal.


We gratefully acknowledge support from the National Institutes of Health (NIH) grants NS091230, NS55104, NS092986, NS057198, EB021018, EB00790, AG042026, and EB018464.



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Biographies for the authors are not available.

© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-423X/2016/$25.00 © 2016 SPIE
Sava Sakadžić, Mohammad A. Yaseen, Rajeshwer Jaswal, Emmanuel Roussakis, Anders M. Dale, Richard B. Buxton, Sergei A. Vinogradov, David A. Boas, and Anna Devor "Two-photon microscopy measurement of cerebral metabolic rate of oxygen using periarteriolar oxygen concentration gradients," Neurophotonics 3(4), 045005 (17 October 2016).
Published: 17 October 2016

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