Desktop version

Home arrow Health

  • Increase font
  • Decrease font

<<   CONTENTS   >>

Application of Biospeckle Laser Method for Drug Testing on Parasites


1 International School of Photonics, Cochin University of Science and Technology, Kochi - 682 022, Kerala, India,

E-mails: mohamedzaheerl; This email address is being protected from spam bots, you need Javascript enabled to view it (M. Z. Ansari)

  • 2Optics Laboratory, The Abdus Salam International Center for Theoretical Physics (ICTPStrada Costiera 11, Trieste - 34151, Italy, E-mail: This email address is being protected from spam bots, you need Javascript enabled to view it
  • 3Faculty of Pharmacy and Bioanalysis, University of the Andes,

Merida - 5101, Venezuela


We report on the application of the biospeckle laser method (BLM) to test drug effects on Trypanosoma cruzi (T. cruzi) parasites. The method, enabled to assess the activity of parasites under different drug concentrations, thus demonstrating the effectiveness of the proposed methodology. The spatial- temporal correlation and speckle grain size were measured in order to assess the immediate action of the drug on parasites. The achieved results allowed the validation of the methodology as a fast and non-invasive for testing the effectiveness of Epirubicin on T cruzi parasites. The proposed methodology was also validated by other well-known digital processing approaches.


American Trypanosomiasis (Chagas disease) in humans is caused by the protozoan parasite I cruzi and very frequently affects the population of the region. The available drugs for the treatment of the infection by T. cruzi are Nifurtimox and Benznidazol [1]. However, long follow-up is necessary, accompanied by side effects and low effectiveness. In this regard, the BLM have been used for testing the activity of different biological media including microorganisms [2-6]. The BLM is based on laser dynamic speckle interferometry [2]. It is well known that when a laser is reflected from a rough surface, a speckle pattern will be created at a given detection plane. If the surface is moving and when is being illuminated with coherent light, the speckle pattern of the scattered light also varies in time. Therefore, characterization of the speckle dynamics can provide information about the surface activity.

To analyze the evolution of dynamic speckle patterns, the autocorrelation of the irradiance as a function of time has been employed [4]. Other approaches include the generation of the time history speckle pattern (THSP) and its characterization using different descriptors [2], the generalized difference method [5], a modified version of the time correlation [6], the characterization of the time evolution of the texture of the speckle pattern [7], the speckle pattern contrast imaging [8], empirical mode decomposition [9], the Fujii difference method [10], and the temporal difference method [11, 12].

Additionally, other optical methods have been used for testing biological motility including a laser-diffraction capillary assay developed by Schmidt et al. [13]. Recently, Tan et al. have demonstrated the use of optical coherence tomography to evaluate the dynamic cell behavior [14]. However, those techniques require expensive equipment and also well-trained personnel. The BLM is a fast testing method and easy to implement and the assays based on its principles require minimal resources.

Drug susceptibility testing is a necessary step prior to the treatment of clinical infections. However, in case of severe parasitic infections fast and reliable results are necessary in a short period of time to determine the appropriate drug that must be used. Anthracyclines have been used in the design of anti-protozoal drugs, especially against trypanosomes [16, 17] and have been tested using traditional methods requiring long test periods. New approaches are needed in order to reduce the required time and the sample volume consumption.

The aim of this work is to use the BLM for drug susceptibility test of Epirubicin [17] on I cruzi parasites. For this purpose, the biospeckle experiment was designed considering two well-known targets of the drug: an interaction on the cell surface which is an almost instantaneous effect and an interaction with DNA which depends on internalization and transport of the drug to reach the target in the cell nucleus [18, 19].

We mainly proposed the dynamic speckle activity segmentation by spatial-temporal speckle correlation technique as an alternative and fast algorithm for detection of different degrees of motility of I cruzi parasites during the incubation period. This approach enabled to obtain presumptive results of tiypanocide action of the pharmaceutical product in a very short period of time. Additionally, it is very well-known that the average speckle size increases linearly with the distance from the scattering surface to the observation plane and decreases as the illuminated area increases [19]. Therefore, the computation of the second-order statistics of the speckle dynamics, namely the speckle grain size measurement provided information about the surface roughness and diffusion area [20]. Finally, speckle grain size evolution was used to characterize the physical processes occurring during immediate action of the drug on the parasites. Additionally, the methodology was validated by other digital speckle methods and good agreement was achieved comparing all the obtained results.



Spatial-temporal correlation evaluation of speckle signals gives information related with the speckle dynamics [21, 22]. The algorithm uses a con-elation analysis of the temporal sequence of speckle patterns. For the computation, each speckle pattern in the sequence is divided into equal fragment matrices, and thereby calculating the correlation of each fragment pair of two patterns taken. Thus, the activity of the given fragment is characterized in tenns of square matrix of correlation coefficients [21].

Each m, ti"h correlation coefficient is given by:

where, i,j are the pixel number of the m, «nh fragments of the speckle pattern; i = 1..., I; j = 1..., J; m = 1..., M; ti = 1..., N; S is the i,jnh pixel intensity; к is the frame sequence (к = 0, 1.); tQis the time of the initial frame; x is the temporal distance between two adjacent frames. The measured coefficients represent the normalized intensities of correlation peaks located in the center of each fragment, and temporal evolution of each m, n'th peak intensity corresponds to a biospeckle activity of the fragment.

Speckle homogeneity test was carried out to ensure that the biospeckle properties of each sub-image are homogeneous. In this case, the intensity is calculated as a mean of all intensities of all peaks and the correlation coefficient can be expressed as [22, 23]:

where, im= 1, ...,2/, MI and jn = 1, J, 2J, NJ.


A normalized auto-covariance function of the speckle intensity pattern I(x, y) obtained in the observation plane (x, у) of the camera was measured to evaluate the speckle grain size. This function corresponds to the normalized autocorrelation function of the intensity. Its width provides a reasonable measurement of the average width of the speckle grain [20]. The autocorrelation function C can be calculated by:

where, FT is the Fourier Transform and () is a spatial average. The horizontal dimension of the speckle grain denoted by dx is the full width at half maximum (FWHM) of the horizontal profile of c(x,y).


The speckle data was also evaluated using absolute values of difference (AVD). In each well containing the assay, the region of interest (ROI) was selected. Each ROI was analyzed by means of the AVD calculation, through the creation of a THSP and then a co-occurrence matrix (COM). The AVD processing can be expressed as [24, 25]:

where, COM is the co-occurrence matrix related to the THSP and i and j represent the dimension of the COM matrix, respectively [2].

The qualitative biospeckle index adopted was the GD that can be expressed as [24, 25]:

The GD outcomes were used to compare between the motility index of the assay before and after the incubation of the drug. The level of activity can be represented in colors, with blue for low activity and red for high activity.



In the experiment, fiver infusion tiyptose (LIT) was used as a medium for the growth of Epiniastigote forms of I cruzi at 28°C. The reaction mixture (100 pi) containing in a well was prepared by adding 5 pi of either a solution of Epiru- bicin (2 mg/ml in saline) or saline to 95 pi of LIT culture medium containing

  • 2.4 x io3 parasites. A 100 pg.mT1 concentration of Epirubicin was used in the assay well. The assay was carried out at room temperature (20-25°C).

The scheme of the experimental setup is shown in Figure 9.1. As a coherent light source, we used a 1-mW He-Ne laser operating at 632.8 nm emission which was expanded by a 1 О-cm focal lens to create a 10-mm spot on the well plate with parasites. A high-resolution CCD camera (Thorlabs USB.2, 30 fps, 6.45-pm square pixels with a resolution of 1280 x Ю24 Pixels) recorded videos with duration of 1 minute. The parameters of the CCD camera are: optical system of focal lengths range 3.5-75 mm with maximum aperture of up to f/0.95, as well as 18-108 mm f/2.5 zoom lens was used with the CCD camera. Successive speckles were collected with a frame rate of 30 frames per second.

Schematic of the experimental setup used for the assessment of parasite motility

FIGURE 9.1 Schematic of the experimental setup used for the assessment of parasite motility.


In this section, the trypanocidal effect of the drug on I cruzi parasites was characterized using the second order statistics parameter. When the parasites are illuminated with a laser, a speckle pattern is obtained and a sequence of images is registered. Through the evaluation of the dynamic speckles using the methods discussed in Section 2.2, it becomes easier to identify different degrees of motility of the parasites during the Epirubicin effect.


After the action of the drug on the parasites, the time-varying correlation of speckle images was performed. The temporal analysis leads to evaluation of the effect of Epirubicin drug on 7 cruzi parasites. The temporal correlation coefficient evolution C(t) for parasites undergoing different incubation periods of the drug is shown in Figure 9.2. Decorrelation is reduced with the increase of incubation period of the drug on the parasites. C(t) curves provide information about the motility index associated with the parasites before the treatment with Epirubicin as well as quantifies the motility in tenns of the immediate drug action (t = 1 min) and after 15 minutes of incubation with the drug. Note that, before treatment parasites show a greater degree of motility but the correlation C{t) decreases fastly with time. The activity of the parasites just during the incubation in the first minute and after 15 minutes of incubation decreases which leads to a slower decrease of the

Evolution of the correlation coefficient versus correlation time (in frames) for parasites during different incubation times

FIGURE 9.2 Evolution of the correlation coefficient versus correlation time (in frames) for parasites during different incubation times.

correlation coefficient and the reduced decorrelation. Thus due to the drug action, parasites are less active and reduce their movements which can be described as iimnediate effect of the drug on the parasites.


When considering second-order statistics of speckle images, the size of the speckle grain can provide information about surface roughness and diffusion surface as dx and dy are inversely proportional to the diameter of the diffusing area [20]. Thus, photons which are backscattered by the small surface as a result of the reduced activity of the parasites due to the action of the drug lead to larger speckle sizes. The evolution of the speckle grain size of dx is shown in Figure 9.3. Similar curves were obtained with a speckle grain size of dy (not shown here). Parasites show a relatively smaller speckle size before treatment with the drug. Before to be treated

Variation of horizontal speckle grain sizes dx as a function of time (frames) during different incubation periods

FIGURE 9.3 Variation of horizontal speckle grain sizes dx as a function of time (frames) during different incubation periods.

with the drug parasites show a higher degree of mobility, therefore the incident photons are backscattered by larger diffusion spots and thus produce a smaller speckle size [20]. This interpretation was previously observed by the spatial-temporal aspects of speckle patterns (Figure 9.2). Due to the drug incubation process, surface dimensions are continuously decreasing, leading to reduced surface scattering area. This, in turn generated a relatively larger speckle size (red line of Figure 9.3). The effect of the drug can be correlated with the increase of speckle grain size. As can be seen, Epirubicin has an instantaneous effect on the speckle dynamics as would be expected from an interaction of the drug on the cell surface, without entering the cell [18]. However, after 15 minutes of drug action the value of speckle grain size is shorter than in case of the results at the first minute, indicating that besides the effect of the Epirubicin, there was an additional effect may be related with the evaporation of the medium what introduces an erroneous interpretation. Therefore, care must be taken when designing the experiment in order to avoid the evaporation of the liquid. Anyway, still there is an appreciable difference when compared to the speckle grain size of the parasites without drug.


Figure 9.4(a) shows the quantitative evaluation of parasites motility under the action of Epirubicin drug (100 pg/ml). The parasites activity before and after the drug incubation has been measured using the COM matrices. The COM matrix presents the number of occurrences of a particular intensity level followed by its effect in the characteristic dynamic image, called the THSP. The activity of the sample can be quantified as a measure of the spread values around the main diagonal. For the sample showing high activity, the corresponding COM matric resembles a cloud-like shape and the values lie far away from the principal diagonal. The values that represent the activity lie rather on or near the diagonal if the sample presents low activity.

The parasites not treated with the drug show a higher degree of motility which can easily be followed using the COM matrix as shown in Figure 9.4(a). After the drug action, the activity of parasites decreases as a result of the instantaneous interaction of the drug on the cell surface [26, 27]. Similarly and confirming our hypothesis, after fifteen minutes, one can observe a slight decrease in the activity of the assay, attributed to the evaporation of the saline solution as in case of Figure 9.3 and previous reports [28, 29].

Quantitative evaluation of parasites motility under the action of Epirubicin drug

FIGURE 9.4 Quantitative evaluation of parasites motility under the action of Epirubicin drug (100 pg/ml). (a) COM matrices displaying different degrees of activity characterized by the number of occurrences of intensity values on the THSP images (respectively at 1 min (without drug control), 1 min of Epirubicin action, and 15 min of Epirubicin action); (b) corresponding AVD values, showing its characteristics variation with frequency; (c) Normalized AVD values quantifying the motility as a function of incubation time (minutes). Error bar corresponds to the standard error (SE). The letters denote significant differences (p<0.05) between the mean values of AVD using a statistical Tukey’s test.

Figure 9.4(b) shows the corresponding AVD values, showing its characteristics variation with frequency. As shown in Refs. [30, 31], higher frequency contributes more to the AVD values and thereby quantifying the activity/motility of the assay.

Figure 9.4(c) presents the normalized AVD values as the motility measure of the parasites as a function of incubation time (minutes). As can be seen, there is an instantaneous and drastic change (decrease) in the parasites activity under the action of Epirubicin during the first minute of incubation. The assay shows a further decrease in its activity during 15 minutes of incubation. All the values are statistically significant (p<0.05) using a statistical Tukey’s test.

Next, for a qualitative evaluation of the assay, an algorithm, the generalized differences (GD) as the spatial activity index was used and the results are presented in Figure 9.5.

Figure 9.5 shows the spatial activity distribution of the assay before and after the incubation with Epirubicin (100 pg/ml). One can easily differentiate between the motility of the parasites; the parasites without drug show a greater degree of motility in comparison to that treated with the drug (Figure 9.5a). The GD values for the parasites incubated with the drug have been decreased (Figure 9.5b and c) and that is due to the instantaneous action of the Epirubicin.

Motility index, the GD of the parasites incubated with Epirubicin drug

FIGURE 9.5 Motility index, the GD of the parasites incubated with Epirubicin drug (100 pg/ml). (a) t = 1 min (without drug), (b) t = 1 min (with Epirubicin) and (c) t = 15 min (with Epirubicin). The activity of the parasites incubated with the drug has been discriminated with that of treated without Epirubicin. The color bar represents the activity level with blue (low activity) to red (high activity).

Collectively, the results suggest that all analyzed digital methods were able in minor or major degree to detect and distinguish the instantaneous biological action of the drug on parasites. In general, it was possible to obtain a linear tendency which shows that the measured parameter of the biospeckle pattern of the parasites decreases as the time increases. The four evaluation methods used: Spatial-temporal correlation technique, speckle grain size, AVD, and GD susceptibility tests, show similar results, being able to distinguish among different situations with parasites and drug or without drug.


A biospeckle methodology was designed for the evaluation of drug susceptibility on I cruzi parasites. Digital image processing was performed by four different methods that achieved the same results. The effective action of Epirubicin on I cruzi parasites was clearly demonstrated in all cases. The results evidenced a very fast action of the drug that may be related to its instantaneous effect on the membrane of the parasites. All the methods used here reproduced the results with quite good correlation, thus demonstrating its applicability. The validated methodology open new research directions and it starts a possible way to perform a fast method to evaluate drug susceptibility on a biological system including bacteria, viruses, and microorganisms.


  • absolute values of difference
  • biospeckle
  • liver infusion tryptose
  • speckle correlation
  • speckle grain size
  • standard error


  • 1. Rivera, G., Garcia, B., Pichardo, O., Torres, B. N., & Monge, A., (2009). New therapeutic target for drug design against Trypanosoma cruzi', advances and perspectives. Cun: Med. Chew.,16(25), 3286.-3293.
  • 2. Arizaga, R., Trivi, M., & Rabal, H., (1999). Speckle time evolution characterization by the co-occurrence matrix analysis. Optics and Laser Technology, 31(2), 163-169.
  • 3. Waterman-Storer, С. M., Desai, A., Bulinski, J. C., & Sahnon, E. D., (1998). Fluorescent speckle microscopy, a method to visualize the dynamics of protein assemblies in living cells. Current Biology-, 5(22), 1227-1230, SI.
  • 4. Aizu, Y. A., & Asakura, T., (1991). Bio-speckle phenomena and their application to the evaluation of blood flow. Optics and Laser Technology, 23(4), 205-219.
  • 5. Arizaga, R. A., Cap, N. L., Rabal, H. J., & Trivi, M., (2002). Display of local activity using dynamical speckle patterns. Optical Engineering, 41(2), 287-295.
  • 6. Pomarico, J. A., & DiRocco, H. O., (2004). Compact device for assessment of microorganism motility. Review of Scientific Instruments, 75( 11), 4727-4731.
  • 7. Limia, M. F., Nunez, A. M., Rabal, H., & Trivi, M., (2002). Wavelet transform analysis of dynamic speckle patterns texture. Applied optics, 41(32), 6745-6750.
  • 8. Briers, J. D., & Webster, S., (1996). Quasi-real time digital version of flow monitoring using laser speckle contrast analysis (LASCA). J. Biomed Opt., 2,174-179.
  • 9. Federico, A., & ICaufmann, G. H., (2006). Evaluation of dynamic speckle activity using the empirical mode decomposition method. Optics Communications, 267(2), 287-294.
  • 10. Ansari, M. Z., & Nirala, A. K., (2015). Biospeckle assessment of torn plant leaf tissue and automated computation of leaf vein density (LVD). The European Physical Journal Applied Physics, 70(2), 21201.
  • 11. Marti-Lopez, L., Cabrera, H., Martinez-Celorio, R. A., & Gonzalez-Peiia, R., (2010). Temporal difference method for processing dynamic speckle patterns. Optics Communications, 283(24), 4972-4977.
  • 12. Minz, P. D., & Nirala, A. K., (2014). Intensity based algorithms for biospeckle analysis. Optik-International Journal for Light and Electron Optics, 725(14), 3633-3636.
  • 13. Schmidt, S., Widman, M. T., & Worden, R. M., (1997). A laser-diffraction capillary assay to measure random motility in bacteria. Biotechnology’ Techniques, 11(6), 423-426.
  • 14. Tan, W., Oldenburg, A. L., Norman, J. J., Desai, T. A., & Boppart, S. A., (2006). Optical coherence tomography of cell dynamics in three-dimensional tissue models. Optics Express, 74(16), 7159-7171.
  • 15. Zuma, A. A., Cavalcanti, D. P., Maia, M. C., De Souza, W., & Motta, M. С. M., (2011). Effect of topoisomerase inhibitors and DNA-binding drugs on the cell proliferation and ultra structure of Tiypanosoma cruzi. International Journal of Antimicrobial Agents, 37(5), 449-456.
  • 16. Jobe, M., Anwuzia-Iwegbu, C., Banful, A., Bosier, E., Iqbal, M., Jones, K., & Ward, E., (2012). Differential in vitro activity of the DNA topoisomerase inhibitor idarubicin against Tiypanosoma rangeli and Tiypanosoma cruzi. Memorias do Institute Oswaldo Cruz, 107(1), 946-950.
  • 17. Triton, T. R., & Yee, G., (1982). The anticancer agent adriamycin can be actively cytotoxic without entering cells. Science, 217(4556), 248-250.
  • 18. Chiquero, M. J., Perez-Victoria, J. M., O’Valle, F., Gonzalez-Ros, J. M., Del Moral, R. G., Ferragut, J. A., & Gamarro, F., (1998). Altered drug membrane permeability in a multidrug-resistant Leishmania tropica line. Biochemical Pharmacology’, 55(2), 131-139.
  • 19. Nassif, R., Pellen, F., Magne, C., Le Jeune, B., Le Brun, G., & Abboud, M., (2012). Scattering through fruits during ripening: Laser speckle teclmique correlated to biochemical and fluorescence measurements. Optics Express, 20(21), 23887-23897.
  • 20. Muravsky, L. I., Maksymenko, O. P., & Frankevych, L. F., (2006). Studying of botanical specimen ageing with spatial-temporal speckle correlation technique.” In: Зы Ini. Scientific Conf. Influence of Electromagnetic Field on Agricultural Environment "AGROL.4SER 2006" (pp. 83-89). Lublin, Poland, Papers and short communications.
  • 21. Ansari, M. Z., & Nirala, A. K., (2013). Biospeckle activity measurement of Indian fruits using the methods of cross-correlation and inertia moments. Optik-International Journal for Light and Electron Optics, 724(15), 2180-2186.
  • 22. Zdunek, A., Muravsky, L. I., Frankevych. L., & Konstankiewicz, K., (2007). New nondestructive method based on spatial-temporal speckle correlation technique for evaluation of apples quality during shelf-life. International Agrophysics, 27(3), 305.
  • 23. Ansari, M. Z., Ramirez-Miquet, E. E., Otero, I., Rodriguez, D., & Darias, J. G., (2016). Real tune and online dynamic speckle assessment of growing bacteria using the method of motion history image. Journal of Biomedical Optics, 21(6), 066006.
  • 24. Braga, R. A., Gonzalez-Peiia, R. J., Viana, D. C., & Rivera, F. P., (2017). Dynamic laser speckle analyzed considering in homogeneities in the biological sample. Journal of Biomedical Optics, 22(4), 045010.
  • 25. Chiquero, M. J., Perez-Victoria, J. M, O’Valle, F., Gonzalez-Ros, J. M., Del Moral, R. G., Ferragut, J. A., & Gamarro, F., (1998). Altered drug membrane permeability in a multidrug-resistant Leishmania tropica line. Biochemical Pharmacology, 55(2), 131-139.
  • 26. Triton, T. R., & Yee, G., (1982). The anticancer agent adriamycin can be actively cytotoxic without entering cells. Science, 277(4556), 248-250.
  • 27. Ansari, M. Z., Grassi, H. C., Cabrera, H., & Andrades, E. D. J., (2016). Real time monitoring of drug action on T. cruzi parasites using a biospeckle laser method. Laser Physics, 26(6), 065603.
  • 28. Ramirez-Miquet, E. E., Cabrera, H., Grassi, H. C., Andrades, E. D. J., Otero, I., Rodriguez, D., & Darias, J. G., (2017). Digital imaging information technology for biospeckle activity assessment relative to bacteria and parasites. Lasers in Medical Science, 32(6), 1375-1386.
  • 29. Ansari, M. Z., & Nirala, A. K., (2013). Assessment of bio-activity using the methods of inertia moment and absolute value of the differences. Optik, 124(6), 512-516.
  • 30. Ansari, M. Z., & Nirala, A. K., (2015). Assessment ofFevicol (adhesive) drying process through dynamic speckle techniques. AIMS Bioeng., 2(2), 49-59.
  • 31. Ansari, M. Z., Grassi, H. C., Cabrera, H., Velasquez, A., & Andrades, E. D., (2016). Online fast biospeckle monitoring of drug action in Tiypanosoma cruzi parasites by motion history image. Lasers in Medical Science, 31(1), 1447-1454.
<<   CONTENTS   >>

Related topics