Luís Oliveira a, Armindo Lage b, Manuel Pais Clemente c, and Valery V. Tuchin d,e,f SARATOV FALL MEETING 2011SEPTEMBER 27-30, 2011; SARATOV, RUSSIA a Physics Department, ISEP – Instituto Superior de Engenharia do Porto, Rua Dr. António Bernardino de Almeida, Nº 431, Porto, Portugal c Department of Electrical and Computer Engineering, Porto University – School of Engineering, Rua Dr. Roberto Frias, 4200 – 465 Porto, Portugal *b CETO – Centro de Ciências e Tecnologias Ópticas, Rua Caldas Xavier, Nº 38 – 6º E, 4150 Porto, Portugal d Institute of Optics and Biophotonics, Saratov State University, 83 Astrakhanskaya str., Saratov , Russia e Institute of Precise Mechanics and Control RAS, 24 Rabochaya str., Saratov , Russia f Optoelectronics and Measurement Techniques Laboratory, P.O. Box 4500, University of Oulu, FI-90014, Oulu, Finland

2 Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM Objectives and motivation: To improve the application of Optical technologies in clinical practice we first need to study and understand the natural difficulties that are imposed to light propagation inside biological tissue, so we can take corrective measures. Natural properties of biological tissues impose that light is absorbed and strongly scattered inside (1). Comparing between the magnitudes of the absorption and scattering coefficients we observe that scattering is the major obstacle to efficient light propagation in biological tissues. Why is scattering so strong in bio-tissue ? 1. Biological tissues contain elements that scatter light: muscle fibers, vesicles, cells, organelles and others ( Not possible to control! ). 2. The heterogeneous internal composition of tissues originates a refractive index distribution that presents a step form (tissue step refractive index profile) ( Can be controlled to enhance light propagation inside the tissue! ). Research concerning the tissue immersion method for optical clearing has proven to be very effective (2), (3).

3 Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 To explain the optical clearing effects observed experimentally, it is necessary to know the internal composition and the refractive index profile of the natural tissue (2). At optical clearing, the internal composition of tissues changes, and the variations in the absorption (μ a ) and scattering (μ s ) coefficients of the tissue cause the RI profile to become time-dependent. Two major mechanisms occur during optical clearing treatment: tissue dehydration and RI matching, but the occurrence sequence of these mechanisms is of great interest (2), (3). We were interested to study skeletal muscle. Internal composition and RI profile description was needed before Optical clearing studies.

4 2. Methodology: Fig. 1: Muscle cross-section from the abdominal wall of the Wister Han rat  Tissue selection: abdominal wall muscle from rat: Fibrous tissue with strong scattering properties Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 Tissue preparation to be measured in a dehydration process: 1. Animal sacrifice; 2. Muscle dissection from the abdominal wall; 3. Muscle samples slicing from muscle block with 0.4 mm thickness (adequate thickness for RI measurement with red contrast illumination).

5 RI and mass measurements: Dehydration with hairdryer and measurements were repeated until 10 pairs of RI and mass are obtained for consecutive dehydration states. Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM Natural state measurements: a. RI measurement with Abbe refractometer with red laser contrast illumination; b. Mass measurement with precision weighting scale; 2. Tissue dehydration with hairdryer; 3. First dehydrated state measurements.

6 3. Experimental results: The refractive index and mass measurements obtained from the natural sample and during dehydration are represented in table 1: Table 1: Mass and refractive index values measured from the tissue during dehydration Dehydration state Refractive index Mass (g) Natural Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 The refractive index rises for lower tissue mass (dehydrated tissue) Figure 2: Refractive index – mass dependence of the muscle sample during dehydration With the measurements presented in table 1 we can make a representation of the dependency between tissue’s RI and its mass:

7 4. Calculations: Gladstone and Dale law: (1) (2) Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 The RI of a biological tissue is a weighted combination of the refractive indices of the tissue components, as stated by the Gladstone and Dale law (2) : The volume fractions of tissue components, when summed together, must equal the total volume of the tissue sample (2) : Muscle composition:  A collection of muscle fiber cords distributed through the interstitial fluid (IF).  The IF is located in-between the fiber cords and also inside them. It contains a small percentage of salts and minerals, but it contains mainly water. Figure 3: Cross-section of rat skeletal- muscle: the pink areas are the fiber cords and the grey area is the IF.

8 (3) Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 The volume fraction of water in rat skeletal muscle is indicated in literature as (4). The RI of water in natural rat skeletal-muscle can be calculated for a specific wavelength by equation 3 (2) : Considering the Abbe refractometer that we have used to measure the RI of samples, the reference wavelength is 589 nm. This way, and using this wavelength in equation 3, we obtain the RI of water as (4) Since the density of water is 1 g/cm 3, we can consider that the density (  ) of a material is defined in g/cm 3 by equation 4: By interchanging volume and density in equation 4, we obtain an expression to determine the volume as a function of mass and density. In the case of natural rat muscle, we can also write the volume fraction of water as the ratio of water volume and sample volume: (5)

9 (6) (7) Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 Tissue water mass is the difference between natural sample mass and completely dehydrated sample mass. Using this information, considering equation 4 and using the densities of water (  w ) and dry matter (  dry ), equation 5 takes the form (5) : Since  w =1, the previous equation can be simplified: (8) Performing a similar deduction, the volume fraction of the dry matter in the natural sample can be calculated by the following equation:

10 Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 In each dehydrated state of the tissue in which we have taken experimental measurements, we need corrected versions of equations 7 and 8 to determine the volume fractions of water and dry matter. (9) This way, for each dehydrated state i of the tissue, we consider the following relations: (10) At every tissue state (natural or dehydrated) the sum of the volume fractions in equations 9 and 10 must equal 1. To calculate the volume fractions of dry matter and water for each dehydrated state with the previous equations, we have used the measurements presented in table 1. In these equations we have two unknown parameters: dry matter density and dry matter mass. We do know that these parameters do not change during dehydration. By the time we have performed this study, the dry matter density of rat muscle had not been already reported.

11 Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 On the other hand, some researchers have reported some values for no fat bovine muscle (6), (7), (8). These values were used in our calculations as the best approximation available. We can calculate the dry matter volume fraction from the water volume fraction of that has been reported. In the following calculations, we will use the available data to estimate the variation of sample water content in the dehydration process. Using the natural water volume fraction of rat muscle, along with the dry matter density of no fat bovine muscle in equation 6, we have determined the dry matter mass for rat muscle. (6) We have performed this calculation twice, considering both the dry matter density values measured by different research groups (7), (8).

12 Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 According to data from the first group of researchers, bovine muscle presents a dry matter density of  (g/cm 3 ) = 1.55 – 0.349x10 -3 T, with T representing the absolute temperature of the sample (measured in Kelvin) (7). For 27 ºC (300K) and dry matter density of g/cm 3, we obtain a dry mass of g. Another group has reported a density of g/cm 3 for the dry matter of bovine muscle at 10 ºC (283 K). This data corresponds to g of dry matter mass in our case (8). Based on the previous calculated values, we have determined the RI of dry matter for each tissue state (natural and dehydrated). For these calculations, we have used the following derivation of equation 1: (12) Table 2 contains the calculated RI values for dry matter in each dehydrated state according to data from the first research group (7) :

13 Sample state NaturalDehydrated i=1i=2i=3i=4i=5i=6i=7i=8i=9i= Table 2: Calculated values for water content and dry matter RI during dehydration based on data from the first research group Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 This way, we have calculated the mean and standard deviation of the RI for the dry matter of rat muscle, using the following two equations (9) : (13) (14) The results were:

14 Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 We have performed a similar calculation to estimate the RI of the dry matter of rat muscle, but now based on data from the other research group (8) : Once again, using our mass measurements during dehydration and performing a similar calculation, we have determined the volume fractions of water and the RI of the dry matter for all the dehydration states of the muscle. The results are presented in table 3: Sample state NaturalDehydrated i=1i=2i=3i=4i=5i=6i=7i=8i=9i= Table 3: Calculated values for water content and dry matter RI during dehydration based on data from the second research group. From data in table 3, we have also calculated the mean and standard deviation of dry matter refractive index, obtaining the following:

15 Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 Figure 4 contains the dependencies between water volume fraction and sample mass during the dehydration process for both cases studied: Finally, we can characterize the skeletal muscle from rat in terms of RIs and volume fractions of its components. Table 4 contains the resultant data for this characterization: Natural rat muscle Global refractive index Water content Solid part content Solid part refractive index (mean from both cases calculated above based on data from different groups) Refractive index of water (calculated by equation 3) ± ± ± Table 4: Parameters that characterize the optical constitution of natural skeletal muscle. Figure 4: Dependences between tissue water content and sample mass calculated on the basis of dry matter densities measured by different research groups (◊ - at 27 ºC and - 10ºC).

16 5. Discussion and conclusion: Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011 As we could see with this study, it was possible to obtain important data concerning the constitution of a fibrous tissue and discriminate the optical properties of its components by using a very simple experimental method. The knowledge of these parameters is of great importance for other studies, like for instance the ones of optical clearing treatments of tissues that we have performed later (3), (10). By knowing the magnitude of the step in the RI profile of the natural muscle we can understand and quantify the refractive index matching mechanism that occurs during optical clearing. The information obtained allows to redirect the research that ultimately will lead to the full application of optical clearing treatments in clinical procedures that use optical technologies. A similar study could be performed with other types of tissue to allow a similar characterization.

17 Acknowledgements: Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011  The authors would like to thank to the Institute of Histology and Embryology of Professor Abel Salazar (Porto University – Medical School) for all support given to accomplish the present work.  Valery Tuchin is thankful for support by the following grants: Photonics4life-FP7-ICT RFBR Bel_а RF Ministry of Science and Education 2.1.1/4989, /2950, and RF Governmental contracts , and FiDiPro Project (40111/11), University of Oulu, Finland

18 References: Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM V. V. Tuchin, Light-Tissue Interactions, in Biomedical Photonics Handbook – Chp. 3, Tuan Vo-Dinh Editor. CRC Press LLC, V. V. Tuchin, Optical Clearing of Tissues and Blood, SPIE Optical Engineering Press, L. M. Oliveira, A. S. Lage, M. A. Pais Clemente, and V. V. Tuchin, J. Biomed. Opt., Vol. 15, R. Reinoso, B. A. Telfer, and M. Rowland, “Tissue water content in rats measured by desiccation,” J. Pharmacol. Toxicol. Methods 38, 87– L. M. Oliveira, A. S. Lage, M. A. Pais Clemente, and V. V. Tuchin, “Optical characterization and composition of abdominal wall muscle from rat,” Opt. Lasers Eng. 476, 667– S. Ginzburg, M. A. Gromov, G. I. Krasovskaya, Handbook on thermophysical characteristics of food products. Moscow: Agropromizdat; V. P. Latyshev, M. N. Gritsyn, N. A. Tsyrulnikova, Study of thermophysical properties of food products in the temperature range 77 – 373 K. In: Proceedings of the all union research institute of refrigerating industry. Moskow: P A. E. Kostaropoulos, Die Wärme-and temperature litfähigkeit getrocketer Lebensmittel. Diss Karlsruhe. 1971, 128s. 9.J. Maroco. Análise Estatística com utilização do SPSS. Edições Sílabo, L. M. Oliveira, Study of the spectral transmission response of biological tissues under the influence of different osmotic agents, FEUP Edições, Porto – Portugal, 2007.

19 Optical Characterization of Skeletal Muscle LUÍS OLIVEIRA, ARMINDO LAGE, M. PAIS CLEMENTE and VALERY V. TUCHIN – SFM-2011