Research Papers

Quantification of Blood-Brain Barrier Solute Permeability and Brain Transport by Multiphoton Microscopy

[+] Author and Article Information
Lingyan Shi, Min Zeng

Department of Biomedical Engineering,
The City College of the City
University of New York,
160 Convent Avenue,
New York, NY 10031

Yi Sun

Department of Electrical Engineering,
The City College of the City
University of New York,
160 Convent Avenue,
New York, NY 10031

Bingmei M. Fu

Department of Biomedical Engineering,
The City College of the City
University of New York,
160 Convent Avenue,
New York, NY 10031
e-mail: fu@ccny.cuny.edu

1Corresponding author.

Contributed by the Bioengineering Division of ASME for publication in the Journal of Biomechanical Engineering. Manuscript received May 24, 2013; final manuscript received September 23, 2013; accepted manuscript posted November 5, 2013; published online February 13, 2014. Assoc. Editor: Mohammad Mofrad.

J Biomech Eng 136(3), 031005 (Feb 13, 2014) (9 pages) Paper No: BIO-13-1240; doi: 10.1115/1.4025892 History: Received May 24, 2013; Revised September 23, 2013; Accepted November 05, 2013

Development of an optimal systemic drug delivery strategy to the brain will require noninvasive or minimally invasive methods to quantify the permeability of the cerebral microvessel wall or blood-brain barrier (BBB) to various therapeutic agents and to measure their transport in the brain tissue. To address this problem, we used laser-scanning multiphoton microscopy to determine BBB permeability to solutes (P) and effective solute diffusion coefficients (Deff) in rat brain tissue 100–250 μm below the pia mater. The cerebral microcirculation was observed through a section of frontoparietal bone thinned with a microgrinder. Sodium fluorescein, fluorescein isothiocyanate (FITC)-dextrans, or Alexa Fluor 488-immunoglobulin G (IgG) in 1% bovine serum albumin (BSA) mammalian Ringer's solution was injected into the cerebral circulation via the ipsilateral carotid artery by a syringe pump at a constant rate of ∼3 ml/min. P and Deff were determined from the rate of tissue solute accumulation and the radial concentration gradient around individual microvessels in the brain tissue. The mean apparent permeability P values for sodium fluorescein (molecular weight (MW) 376 Da), dextran-4k, -20k, -40k, -70k, and IgG (MW ∼160 kDa) were 14.6, 6.2, 1.8, 1.4, 1.3, and 0.54 × 10−7 cm/s, respectively. These P values were not significantly different from those of rat pial microvessels for the same-sized solutes (Yuan et al., 2009, “Non-Invasive Measurement of Solute Permeability in Cerebral Microvessels of the Rat,” Microvasc. Res., 77(2), pp. 166–73), except for the small solute sodium fluorescein, suggesting that pial microvessels can be a good model for studying BBB transport of relatively large solutes. The mean Deff values were 33.2, 4.4, 1.3, 0.89, 0.59, and 0.47 × 10−7 cm2/s, respectively, for sodium fluorescein, dextran-4k, -20k, -40k, -70k, and IgG. The corresponding mean ratio of Deff to the free diffusion coefficient Dfree, Deff/Dfree, were 0.46, 0.19, 0.12, 0.12, 0.11, and 0.11 for these solutes. While there is a significant difference in Deff/Dfree between small (e.g., sodium fluorescein) and larger solutes, there is no significant difference in Deff/Dfree between solutes with molecular weights from 20,000 to 160,000 Da, suggesting that the relative resistance of the brain tissue to macromolecular solutes is similar over a wide size range. The quantitative transport parameters measured from this study can be used to develop better strategies for brain drug delivery.

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de Lange, E. C., de Boer, B. A., and Breimer, D. D., 1999, “Microdialysis for Pharmacokinetic Analysis of Drug Transport to the Brain,” Adv. Drug Delivery Rev., 36(2–3), pp. 211–227. [CrossRef]
Wang, R., Ashwal, S., Tone, B., Tian, H. R., Badaut, J., Rasmussen, A., and Obenaus, A., 2007, “Albumin Reduces Blood-Brain Barrier Permeability but Does Not Alter Infarct Size in a Rat Model of Neonatal Stroke,” Pediatr. Res., 62(3), pp. 261–266. [CrossRef] [PubMed]
Cornford, E. M., Young, D., Paxton, J. W., and Sofia, R. D., 1992, “Blood-Brain Barrier Penetration of Felbamate,” Epilepsia, 33(5), pp. 944–954. [CrossRef] [PubMed]
van Uitert, R. L., Sage, J. I., Levy, D. E., and Duffy, T. E., 1981, “Comparison of Radio-Labeled Butanol and Iodoantipyrine as Cerebral Blood Flow Markers,” Brain Res., 222(2), pp. 365–372. [CrossRef] [PubMed]
Zlokovic, B. V., Begley, D. J., Djuricic, B. M., and Mitrovic, D. M., 1986, “Measurement of Solute Transport Across the Blood-Brain Barrier in the Perfused Guinea Pig Brain: Method and Application to N-Methyl-Alpha-Aminoisobutyric Acid,” J. Neurochem., 46(5), pp. 1444–1451. [CrossRef] [PubMed]
Crone, C., 1963, “Permeability of Capillaries in Various Organs as Determined by Use of Indicator Diffusion Method,” Acta Physiol. Scand., 58(4), pp. 292–305. [CrossRef] [PubMed]
Easton, A. S., and Fraser, P. A., 1994, “Variable Restriction of Albumin Diffusion Across Inflamed Cerebral Microvessels of the Anaesthetized Rat,” J. Physiol., 475(1), pp. 147–157. [PubMed]
Elsinga, P. H., Hendrikse, N. H., Bart, J., Vaalburg, W., and van Waarde, A., 2004, “PET Studies on P-Glycoprotein Function in the Blood-Brain Barrier: How It Affects Uptake and Binding of Drugs Within the CNS,” Curr. Pharm. Des., 10(13), pp. 1493–1503. [CrossRef] [PubMed]
Gaber, M. W., Yuan, H., Killmar, J. T., Naimark, M. D., Kiani, M. F., and Merchant, T. E., 2004, “An Intravital Microscopy Study of Radiation-Induced Changes in Permeability and Leukocyte-Endothelial Cell Interactions in the Microvessels of the Rat Pia Mater and Cremaster Muscle,” Brain Res. Brain Res. Protoc., 13(1), pp. 1–10. [CrossRef] [PubMed]
Yuan, H., Gaber, M. W., McColgan, T., Naimark, M. D., Kiani, M. F., and Merchant, T. E., 2003, “Radiation-Induced Permeability and Leukocyte Adhesion in the Rat Blood-Brain Barrier: Modulation With Anti-ICAM-1 Antibodies,” Brain Res., 969(1–2), pp. 59–69. [CrossRef] [PubMed]
Berk, D. A., Yuan, F., Leunig, M., and Jain, R. K., 1997, “Direct in vivo Measurement of Targeted Binding in a Human Tumor Xenograft,” Proc. Natl. Acad. Sci. USA, 94(5), pp. 1785–1790. [CrossRef]
Chary, S. R., and Jain, R. K., 1989, “Direct Measurement of Interstitial Convection and Diffusion of Albumin in Normal and Neoplastic Tissues by Fluorescence Photobleaching,” Proc. Natl. Acad. Sci. USA, 86(14), pp. 5385–5389. [CrossRef]
Flessner, M. F., Lofthouse, J., and Zakaria, el-R., 1997, “In Vivo Diffusion of Immunoglobulin G in Muscle: Effects of Binding, Solute Exclusion, and Lymphatic Removal,” Am. J. Physiol., 273(6 Pt 2), pp. H2783–H2793. [PubMed]
Fox, J. R., and Wayland, H., 1979, “Interstitial Diffusion of Macromolecules in the Rat Mesentery,” Microvasc. Res., 18(2), pp. 255–276. [CrossRef] [PubMed]
Granger, H. J., and Taylor, A. E., 1975, “Permeability of Connective Tissue Linings Isolated From Implanted Capsules: Implications for Interstitial Pressure Measurements,” Circ. Res., 36(1), pp. 222–228. [CrossRef] [PubMed]
Jain, R. K., Stock, R. J., Chary, S. R., and Rueter, M., 1990, “Convection and Diffusion Measurements Using Fluorescence Recovery After Photobleaching and Video Image Analysis: in Vitro Calibration and Assessment,” Microvasc. Res., 39(1), pp. 77–93. [CrossRef] [PubMed]
Nicholson, C., 2001, “Diffusion and Related Transport Mechanisms in Brain Tissue,” Rep. Prog. Phys., 64(7), pp. 815–884. [CrossRef]
Nicholson, C., and Tao, L., 1993, “Hindered Diffusion of High Molecular Weight Compounds in Brain Extracellular Microenvironment Measured With Integrative Optical Imaging,” Biophys. J., 65(6), pp. 2277–2290. [CrossRef] [PubMed]
Tao, L., and Nicholson, C., 1996, “Diffusion of Albumins in Rat Cortical Slices and Relevance to Volume Transmission,” Neuroscience, 75(3), pp. 839–847. [CrossRef] [PubMed]
Stroh, M., Zipfel, W. R., Williams, R. M., Webb, W. W., and Saltzman, W. M., 2003, “Diffusion of Nerve Growth Factor in Rat Striatum as Determined by Multiphoton Microscopy,” Biophys. J., 85(1), pp. 581–588. [CrossRef] [PubMed]
Binder, D. K., Papadopoulos, M. C., Haggie, P. M., and Verkman, A. S., 2004, “In Vivo Measurement of Brain Extracellular Space Diffusion by Cortical Surface Photobleaching,” J. Neurosci., 24(37), pp. 8049–8056. [CrossRef] [PubMed]
Thorne, R. G., and Nicholson, C., 2006, “In Vivo Diffusion Analysis With Quantum Dots and Dextrans Predicts the Width of Brain Extracellular Space,” Proc. Natl. Acad. Sci. USA, 103(14), pp. 5567–5572. [CrossRef]
Thorne, R. G., Lakkaraju, A., Rodriguez-Boulan, E., and Nicholson, C., 2008, “In Vivo Diffusion of Lactoferrin in Brain Extracellular Space Is Regulated by Interactions With Heparan Sulfate,” Proc. Natl. Acad. Sci. USA, 105(24), pp. 8416–8421. [CrossRef]
Adamson, R. H., Lenz, J. F., and Curry, F. E., 1994, “Quantitative Laser Scanning Confocal Microscopy on Single Capillaries: Permeability Measurement,” Microcirculation, 1(4), pp. 251–265. [CrossRef] [PubMed]
Fu, B. M., Curry, F. E., and Weinbaum, S., 1995, “A Diffusion Wake Model for Tracer Ultrastructure-Permeability Studies in Microvessels,” Am. J. Physiol., 269(6 Pt 2), pp. H2124–H2140. [PubMed]
Fu, B. M., Adamson, R. H., and Curry, F. R., 2005, “Determination of Microvessel Permeability and Tissue Diffusion Coefficient of Solutes by Laser Scanning Confocal Microscopy,” ASME J. Biomech. Eng., 127(2), pp. 270–278. [CrossRef]
Yuan, W., Lv, Y., Zeng, M., and Fu, B. M., 2009, “Non-invasive Measurement of Solute Permeability in Cerebral Microvessels of the Rat,” Microvasc. Res., 77(2), pp. 166–173. [CrossRef] [PubMed]
Fu, B. M., and Shen, S., 2004, “Acute VEGF Effect on Solute Permeability of Mammalian Microvessels in vivo,” Microvasc. Res., 68(1), pp. 51–62. [CrossRef] [PubMed]
Fu, B. M., Adamson, R. H., and Curry, F. E., 1998, “Test of a Two-Pathway Model for Small-Solute Exchange Across the Capillary Wall,” Am. J. Physiol., 274(6 Pt 2), pp. H2062–H2073. [PubMed]
Easton, A. S., Sarker, M. H., and Fraser, P. A., 1997, “Two Components of Blood-Brain Barrier Disruption in the Rat,” J. Physiol., 503(Pt 3), pp. 613–623. [CrossRef] [PubMed]
Evans, A. J., James, J. J., Cornford, E. J., Chan, S. Y., Burrell, H. C., Pinder, S. E., Gutteridge, E., Robertson, J. F., Hornbuckle, J., and Cheung, K. L., 2004, “Brain Metastases From Breast Cancer: Identification of a High-Risk Group,” Clin. Oncol. (R. Coll. Radiol.), 16(5), pp. 345–349. [CrossRef] [PubMed]
Friedman, J. H., Koller, W. C., Lannon, M. C., Busenbark, K., Swanson-Hyland, E., and Smith, D., 1997, “Benztropine Versus Clozapine for the Treatment of Tremor in Parkinson's Disease,” Neurology, 48(4), pp. 1077–1081. [CrossRef] [PubMed]
Jansen, E. N., 1994, “Clozapine in the Treatment of Tremor in Parkinson's Disease,” Acta Neurol. Scand., 89(4), pp. 262–265. [CrossRef] [PubMed]
Lieberman, J. A., and Stroup, T. S., 2011, “The NIMH-CATIE Schizophrenia Study: What Did We Learn?,” Am. J. Psychiatry, 168(8), pp. 770–775. [CrossRef] [PubMed]
Jones, P. B., Barnes, T. R., Davies, L., Dunn, G., Lloyd, H., Hayhurst, K. P., Murray, R. M., Markwick, A., and Lewis, S. W., 2006, “Randomized Controlled Trial of the Effect on Quality of Life of Second- vs First-Generation Antipsychotic Drugs in Schizophrenia: Cost Utility of the Latest Antipsychotic Drugs in Schizophrenia Study (CUtLASS 1),” Arch. Gen. Psychiatry, 63(10), pp. 1079–1087. [CrossRef] [PubMed]
Brown, R. C., Egleton, R. D., and Davis, T. P., 2004, “Mannitol Opening of the Blood-Brain Barrier: Regional Variation in the Permeability of Sucrose, but Not 86Rb+ or Albumin,” Brain Res., 1014(1–2), pp. 221–227. [CrossRef] [PubMed]
Garcia-Villalon, A. L., Roda, J. M., Alvarez, F., Gomez, B., and Dieguez, G., 1992, “Carotid Blood Flow in Anesthetized Rats: Effects of Carotid Ligation and Anastomosis,” Microsurgery, 13(5), pp. 258–261. [CrossRef] [PubMed]
Pardridge, W. M., 1998, “CNS Drug Design Based on Principles of Blood-Brain Barrier Transport,” J. Neurochem., 70(5), pp. 1781–1792. [CrossRef] [PubMed]
Curry, F. E., and Frokjaer-Jensen, J., 1984, “Water Flow Across the Walls of Single Muscle Capillaries in the Frog, Rana Pipiens,” J. Physiol., 350, pp. 293–307. [PubMed]
Fu, B. M., and Shen, S., 2003, “Structural Mechanisms of Acute VEGF Effect on Microvessel Permeability,” Am. J. Physiol. Heart Circ. Physiol., 284(6), pp. H2124–H2135. [CrossRef] [PubMed]
Kendall, S., and Michel, C. C., 1995, “The Measurement of Permeability in Single Rat Venules Using the Red Cell Microperfusion Technique,” Exp. Physiol., 80(3), pp. 359–372. [PubMed]
Fraser, P. A., Dallas, A. D., and Davies, S., 1990, “Measurement of Filtration Coefficient in Single Cerebral Microvessels of the Frog,” J. Physiol., 423, pp. 343–361. [PubMed]
Kimura, M., Dietrich, H. H., Huxley, V. H., Reichner, D. R., and Dacey, R. G., Jr., 1993, “Measurement of Hydraulic Conductivity in Isolated Arterioles of Rat Brain Cortex,” Am. J. Physiol., 264(6 Pt 2), pp. H1788–H1797. [PubMed]
Roberts, T. J., Chapman, A. C., and Cipolla, M. J., 2009, “PPAR-Gamma Agonist Rosiglitazone Reverses Increased Cerebral Venous Hydraulic Conductivity During Hypertension,” Am. J. Physiol. Heart Circ. Physiol., 297(4), pp. H1347–H1353. [CrossRef] [PubMed]
Chen, B., and Fu, B. M. M., 2009, “A Time-Dependent Electrodiffusion-Convection Model for Charged Macromolecule Transport Across the Microvessel Wall and in the Interstitial Space,” Cell. Mol. Bioeng., 2(4), pp. 514–532. [CrossRef]
Fu, B., Curry, F. R., Adamson, R. H., and Weinbaum, S., 1997, “A Model for Interpreting the Tracer Labeling of Interendothelial Clefts,” Ann. Biomed. Eng., 25(2), pp. 375–397. [CrossRef] [PubMed]
Tao, L., 1999, “Effects of Osmotic Stress on Dextran Diffusion in Rat Neocortex Studied With Integrative Optical Imaging,” J. Neurophysiol., 81(5), pp. 2501–2507. [PubMed]
Thorne, R. G., Hrabetova, S., and Nicholson, C., 2004, “Diffusion of Epidermal Growth Factor in Rat Brain Extracellular Space Measured by Integrative Optical Imaging,” J. Neurophysiol., 92(6), pp. 3471–3481. [CrossRef] [PubMed]
Tsai, P. S., Friedman, B., Ifarraguerri, A. I., Thompson, B. D., Lev-Ram, V., Schaffer, C. B., Xiong, Q., Tsien, R. Y., Squier, J. A., and Kleinfeld, D., 2003, “All-Optical Histology Using Ultrashort Laser Pulses,” Neuron, 39(1), pp. 27–41. [CrossRef] [PubMed]
Chen, B., Pogue, B. W., Luna, J. M., Hardman, R. L., Hoopes, P. J., and Hasan, T., 2006, “Tumor Vascular Permeabilization by Vascular-Targeting Photosensitization: Effects, Mechanism, and Therapeutic Implications,” Clin. Cancer Res., 12(3 Pt 1), pp. 917–923. [CrossRef] [PubMed]
Rueckel, M., Mack-Bucher, J. A., and Denk, W., 2006, “Adaptive Wavefront Correction in Two-Photon Microscopy Using Coherence-Gated Wavefront Sensing,” Proc. Natl. Acad. Sci. USA, 103(46), pp. 17137–17142. [CrossRef]
Chaigneau, E., Wright, A. J., Poland, S. P., Girkin, J. M., and Silver, R. A., 2011, “Impact of Wavefront Distortion and Scattering on 2-Photon Microscopy in Mammalian Brain Tissue,” Opt. Exp., 19(23), pp. 22755–22774. [CrossRef]
Sun, Y., 2000, “Hopfield Neural Network Based Algorithms for Image Restoration and Reconstruction - Part I: Algorithms and Simulations,” IEEE Trans. Signal Process., 48(7), pp. 2105–2118. [CrossRef]
Sun, Y., 2009, “A Family of Likelihood Ascent Search Multiuser Detectors: Approaching Optimum Performance via Random Multicodes With Linear Complexity,” IEEE Trans. Commun., 57(8), pp. 2215–2220. [CrossRef]
Rusek, F., Persson, D., Lau, B. K., Larsson, E. G., Marzetta, T. L., Edfors, O., and Tufvesson, F., 2013, “Scaling Up MIMO,” IEEE Signal Process. Mag., 30(1), pp. 40–60. [CrossRef]
Sun, Y., 2000, “Hopfield Neural Network Based Algorithms for Image Restoration and Reconstruction - Part II: Performance Analysis,” IEEE Trans. Signal Process., 48(7), pp. 2119–2131. [CrossRef]


Grahic Jump Location
Fig. 1

Illustration of the scanning region and the orientation of a microvessel in the brain tissue using multiphoton microscopy to determine the blood-brain barrier solute permeability and brain-tissue diffusion coefficient. x-z is the cross-sectional plane of the microvessel and y is the axial direction of the vessel. The ROI (scanning region) has a size of ∼200 μm × 8 μm × 100 μm (x, y, z).

Grahic Jump Location
Fig. 2

In vitro calibration experiments to determine the linear range of fluorescence intensity versus concentration under the same instrumental settings in the in vivo experiments. (a) Sodium fluorescein, (b) FITC-dextran-20k, and (c) IgG.

Grahic Jump Location
Fig. 3

Determination of microvessel solute permeability P using multiphoton microscopy in rat brain. (a) A cross-sectional image (x-z) showing the fluorescence dye (dex-20k) filling the microvessel lumen and spreading into the surrounding tissue. The ROI for determining P is enclosed by the dashed line. Its circumference was chosen as 10–20 μm from the vessel perimeter to avoid contamination from the adjacent vessels. (b) Total fluorescence intensity in the ROI (a) as a function of perfusion time. Fluorescence intensity in this figure is proportional to the total mass of solute accumulated in the measuring region surrounding the microvessel. The slope of regression line over the initial linear accumulation is used for the estimation of permeability P = 1/I0*(dI/dt)0* r/2. r is the radius of the vessel.

Grahic Jump Location
Fig. 4

Determination of effective solute diffusion coefficient Deff in rat brain tissue. (a) Eight straight lines were drawn from the center of the vessel lumen. The averaged fluorescence intensity along these eight directions is plotted from the vessel wall to ∼20 μm far from the wall at different times, the green lines shown in (b). Exp 25 sec, exp 50 sec, and exp 75 sec are the measured intensity profiles from the experiments at 25 s, 50 s, and 75 s, respectively. The black lines are the best-fitting model predictions when the proper Deff is chosen. The best-fitting value of Deff/Dfree is 0.145 in this run of experiments for dex-20k. Model 25 sec, model 50 sec, and model 75 sec are the predicted intensity profiles by the theoretical model at 25 s, 50 s, and 75 s, respectively.

Grahic Jump Location
Fig. 5

Apparent permeability P as a function of solute Stokes radius. P of individual microvessels (○) and mean values ± SD (▪) are plotted.

Grahic Jump Location
Fig. 6

Comparison of solute diffusive permeability Pd for rat cerebral microvessels (▪ current study) and that for rat pial microvessels (◊ [27]) and (○ [10]). Values are mean ± SD (*p = 0.016).

Grahic Jump Location
Fig. 7

Effective solute diffusion coefficient Deff plotted as a function of solute Stokes radius. Deff measured from the current in vivo study (▪) are also compared with those from previous in vivo and ex vivo studies. Values are mean ± SD.

Grahic Jump Location
Fig. 8

Comparison of the original (top left) and corrected (top right) images for the wavefront distortion and scattering and the effect of the image distortions on determining the solute brain tissue diffusion coefficient Deff (bottom). In the bottom plot, the green lines are the curves of the averaged intensity over eight directions versus time (see Fig. 4(b)) from the original images, the red lines are from the corrected images, and the black lines are the model predictions with the best-fitting Deff/Dfree. Model 25 sec, model 50 sec, and model 75 sec are the predicted intensity profiles by the theoretical model at 25 s, 50 s, and 75 s, respectively. Exp 25 sec and exp 25 sec (corrected), exp 50 sec and exp 50 sec (corrected), and exp 75 sec and exp 75 sec (corrected) are the intensity profiles determined out of the original and corrected images from the experiments at 25 s, 50 s, and 75 s, respectively.



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