The development of new express methods for the analysis of the efficacy of anti-cancer therapy on the cellular level is highly desirable for the analysis of chemotherapeutic agent performance. In this paper we suggest the use of parameters of cell morphology determined by holographic microscopy and tomography for the effective label free quantitative analysis of cell viability under antitumor chemotherapy and thus of cytostatic agent efficacy. As shown, measured phase shifts and cell morphology change dramatically as a result of chemotherapy and depend strongly on the cell type and agent applied. Experimentally, a comparative analysis of the antitumor efficacy of the two cytostatics, cisplatin and dioxadet, that are commonly used for chemotherapy of disseminated ovarian carcinoma has been performed. The experiments were carried out on the Wistar rat model. An essential difference in the morphology of cells, both normal (erythrocytes) and cancerous, present in ascitic fluid taken from the non-treated group of rats and the groups treated with either dioxadet or cisplatin, has been observed. The results obtained can be interpreted as an indication of the antitumor performance of both cytostatics at the cellular level and as a demonstration of the higher efficacy of therapy with dioxadet as compared to that with cisplatin. Differences in cell morphology are suggested to be applied as quantitative markers of cell viability and cytostatic agent efficacy. The conclusions made are supported by a comparison with the results of recent experiments based on survival rates of laboratory animals treated with these agents..
© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Ovarian cancer is one of most frequent cancers, ranking fifth in cancer deaths among women. More than 225,000 of new cases of ovarian cancer and over 140,000 lethal outcomes of this disease are registered annually all over the world . The most common type of ovarian cancer, comprising more than 95% of cases, is ovarian carcinoma . The standard treatment for disseminated ovarian carcinoma is a surgery followed by systemic chemotherapy . An outcome of this treatment protocol is not enough satisfactory, that facilitates the search for new treatment agents and modalities.
Testing of chemical agents efficacy is performed on various rodent models  with induced cancer of a particular type. The agent efficacy is analyzed, among other methods, at the cellular level by observation of changes in cells morphology in cytological specimens taken from treated animals. The observations, usually made with optical microscopes on specimens stained with specific chemicals or in phase-contrast microscopes, allow to visually determine and evaluate changes in cellular morphology. These measurements provide data on a nuclear area, membrane area, nucleus to cytoplasm ratio, optical density of a nucleus that is associated with DNA content, see e.g. [5,6]. However these data give a limited and in many cases mostly qualitative information on cells condition. The recently developed 3D imaging techniques implementing optical computed tomography allow for investigating nuclear morphology and texture in 3D with sub-micron spatial resolution . However this technology still operates with distributions of absorption coefficient and requires specific sample preparation using dyes and fixation agents.
More thorough quantitative analysis can be performed using methods of quantitative phase imaging (QPI), see e.g. [8–15]. These methods operate with refractive index variations and allow for obtaining quantitative data on a number of cellular parameters, namely cell shape, thickness, volume, dry mass, projected area, membrane surface area, 2D distribution of average refractive index  and 3D distribution of intracellular refractive index . The important advantage of these techniques is operation with original samples with no need for any additional chemicals. Monitoring of live cells in dynamics is also possible. Note that staining obviously alters data on intracellular refractive index . A number of advanced 2D and 3D QPI techniques were presented recently including novel lens-free 2D  and 3D  imaging platforms along with advanced reconstruction algorithms for scanning illumination holographic tomography .
Digital holographic microscopy and tomography is a rapidly developing group of QPI techniques widely applied in various areas of biomedical research. In particular, several research groups dealt with in-vitro monitoring of individual live cells and their response to external stimuli, including, for instance, chemotherapy of B-cell lymphoma , B16F10 electroporation  or photodynamic treatment of HeLa cells [23,24]. Several works were devoted to investigations of multicellular organisms, e.g. studies of Zebrafish blood flow or larvae circulation [25,26] and microorganism identification . These techniques have been already applied for investigation of cellular response to light exposure  or chemical substances [29, 30]. QPI-assisted morphological analysis was also used for identification of morphological deviations in red blood cells resulted from iron-refractory iron deficiency anaemia . Unlike methods of fluorescence microscopy and dye-assisted far-field microscopy that are commonly used in cellular research, digital holographic microscopy and tomography do not require any specific preparation of samples. And likewise other QPI techniques they allow for cells investigation in terms of refractive index variations, which provide quantitative information on spatial distributions of cellular parameters. It is worth emphasizing that holographic tomography allows for determination of these distributions in 3D.
In this paper digital holographic microscopy and tomography were used for determination of a number of morphological parameters of cells (average phase shift, volume, membrane area) that were shown to change dramatically in the course of chemotherapy depending on the cell type and agent applied. The changes in phase shift and cells morphology were considered as quantitative markers of cells viability and efficacy of cytostatic agents (cell-growth inhibiting drugs) and were used for comparative analysis of the efficacy of ovarian carcinoma treatment in Wistar rats by the two commonly used cytostatics, Cisplatin (CPC) and Dioxadet (DOD) (see , where these agents performance was evaluated in terms of median survival of treated laboratory animals). The main advantage of our approach as compared to other methods of analysis (e.g. [5, 6]) is that it allows for label-free determination of quantitative parameters characterizing cellular morphology and correlating with cell conditions. It is demonstrated that holographic analysis of ovarian carcinoma cells taken from rats subjected to chemotherapy can be used for assessment of the treatment efficacy. The conclusions made were shown to be in agreement with recent results on the analysis of these cytostatics efficacy evaluated by experimentally determined survival rates of rats exposed to chemotherapy with these agents .
2. Experimental approach
2.1. Rat model, chemotherapeutic agents applied and specimen preparation
The study was carried out on 34 female Wistar rats weighing 220–270 g. The rats were purchased from Rappolovo animal nursery (Leningrad Region, Russia) and housed 5–7 days in polypropylene cages under standard 24-h light-dark regimen (12L:12D) at 22 ± 2°C with relative humidity of 50–60%. The rats received standard laboratory crop from Laboratorkorm Ltd. (Moscow, Russia) and tap water ad libitum. The rat ovarian cancer strain was obtained from N.N. Blokhin National Medical Research Center of Oncology (Moscow, Russia). Dioxadet was from Chemconsult (Saint Petersburg, Russia) and Cisplatin was purchased from Pharmachemie (Haarlem, Netherlands). Maintenance and care of all animals were carried out according to the ethical principles established by the European convention for the protection of vertebrate animals, used for experimental and other scientific purposes (accepted in Strasbourg 18.03.1986 and confirmed in Strasbourg 15.06.2006), and approved by Local ethical committee of the N.N. Petrov National Medical Research Center of Oncology.
On the 7th day after intraperitoneal transplantation of ovarian cancer to 4 rats, ascitic fluid was collected from one rat and transplanted to 30 rats. Ascites from a rat with ovarian cancer was diluted with saline (1:4), and injected intraperitoneally to the rats at a number of 1×107 cells per rat. The tumor progressed quickly, causing ascites (about 90% of rats had hemorrhagic ascites), peritoneal carcinomatosis, and death of the animal without treatment in 7–14 days after ovarian cancer inoculation. The day of tumor transplantation was taken for day 0. After ovarian cancer transplantation, the rats were divided at random into 3 groups, 10 per group. Two days (48 h) after ovarian cancer transplantation, the animals were narcotized with ether and received a single intraperitoneal injection of 2 ml saline (control) or antitumor drugs in previously determined maximal tolerated doses (experimental groups): 1.5 mg/kg Dioxadet in saline (Dioxadet group), 4 mg/kg Cisplatin (Cisplatin group) as the initial solution, respectively. The ascitic fluid was taken from all of three experimental animal groups on the 9-th day after inoculation of tumor cells. The diagnosis of ovarian cancer was confirmed by cytological examination of ascitic smear stained with haematoxylin and eosin according to a standard protocol. Microscopic analysis of samples was carried out in visible spectral range using an Eclipse-Ni-U microscope (Nikon) equipped with a DS-Fi2 camera (Nikon). Images were recorded by a video system and displayed on a computer screen with NIS- Elements Basic Research (Nikon) software. This methodology has been thoroughly described in our previous report .
2.2. Experimental methodology
Ascitic smears taken from rats of the three groups (non-treated and treated with CPC or DOD) were applied onto microscope slides and dried in the air atmosphere. Then the specimens were investigated by means of digital holographic microscopy and tomography, and sets of optical and morphological characteristics of cells were acquired.
A home-made laboratory digital holographic microscope was constructed in the configuration of off-axis Mach-Zehnder schematic (see Fig. 1) providing spatial resolution of about 0.8 µm. Several dozens of digital holograms were taken for each specimen in the course of its XY-scanning using a motorized translation stage (Standa). Holograms were recorded by the sensor matrix of a global-shutter-equipped CCD camera Videoscan-205 (Videoscan). Sets of digital holograms covering entire specimen areas were recorded with scanning pitch defined by the field of view used in each experiment.
Numerical processing of holograms comprised several steps, namely, reconstruction by means of the least square minimization algorithm [34,35], phase unwrapping  and cells segmentation. The phase image quality was improved by coherent noise reduction procedure based on the recording of a series of holograms with small lateral shifts of the specimen within the field of view and coherent noise elimination . As a result spatial distributions of integral phase shift induced by the specimens were obtained.
Basically the phase shift δϕ introduced by an object to the transmitted wave front in a certain object point is characterized by the refractive index n and object thickness l: δϕ ∼∫ ndl. In our case the 2D distribution of integral phase shift of the object wave front passed through the specimen was formed by the distributions of cell thickness, thickness of a nonuniform thin layer of dehydrated residual of ascitic fluid, and integral refractive index. To remove a smooth curvature of background phase induced by the ascitic fluid layer a morphological top-hat filtering  was applied in addition to the reconstruction procedure described above. To eliminate errors produced by this layer the phase shift was recorded for each specimen in the areas containing no cells. Based on these data the ascitic fluid phase distribution was modeled and then subtracted from the distributions obtained in cell-containing areas. The retrieved spatial distributions of phase shift introduced by individual cells were further processed aimed to obtain morphological and optical parameters of cells.
3D distributions of cellular parameters were obtained using a holographic tomographic microscope 3D Explorer (Nanolive). 3D resolution was achieved by recording of a set of holograms at different angles provided by the object beam rotation in 360 degrees around the optical axis. Data obtained by means of holographic tomography allowed for calculation of cell volume, projected area and membrane surface area. Note that a limitation of the methodology concerns the specimen preparation procedure. Specimens with a single layer of cells are most suitable for analysis in the holographic microscope, with a view to obtain high-quality phase images of the cells and reliably measured data on cellular morphology.
3. Experimental results and discussion
Representative images of cells in the specimens of ascitic fluid taken from the control non-treated rats and those treated with CPC and DOD, are shown in Figs. 2 and 3. Figure 2 presents data obtained in the holographic microscope and Fig. 3 demonstrates those from the tomographic microscope. Two major types of cells were identified in the specimens taken from the non-treated animals: ovarian carcinoma cells and erythrocytes. Erythrocytes (indicated by white arrows in Figs. 2 and 3) have typical shape of biconcave disks and are 2–4 times smaller than ovarian carcinoma cells. Carcinoma cells are round-shaped with a prominent internal structure. In the specimens taken from rats subjected to chemotherapy cells of the third type were observed. These are fragmented “giant” cells, similar in morphology to those dead through mitotic catastrophe [39,40] (see Figs. 2(b),(c) and 3(b), (c), (e), (f)). They cover significantly larger area and are thinner than regular ovarian carcinoma cells. The number of “giant” cells in specimens taken from CPC- and DOD-treated rats was approximately the same.
Average phase shifts introduced by the cells of each type were calculated from the reconstructed phase images. The data averaged over 40–80 cells from each group are summarized in Table 1 and plotted in Fig. 4(a), (c), (e). Histograms demonstrating average phase shift distributions over a number of cells are shown in Fig. 4(b,d,f). As can be seen in Fig. 4(b), in the control group of non-treated rats the phase shifts introduced to the object beam wave front by erythrocytes and ovarian carcinoma cells demonstrate relatively wide distributions with maxima at about 3.4 and 3.6 rad, respectively. As can be seen in Figs. 4(d) and 4(f), after chemotherapy with either CPC or DOD the phase shift distributions modified and shifted toward lower values. These phase shift changes were due to changes in cells morphology caused by the treatment. Also, Figs. 4(d) and 4(f) demonstrate phase shift distributions introduced by the “giant” cells that do not exist in Fig. 4(b). The phase shift values related to these cells in Figs. 4(d) and 4(f) have negative values because the phase shift in cells was determined with respect to that in ascitic fluid, which had higher refractive index than the “giant” cells.
A quantitative analysis related to cytostatic efficacy can be done using the determined average phase shift values that are given in Table 1 and shown in Figs. 4 (a), (c) and (e). For erythrocytes, the average phase shift decreased from 3.43 rad in the non-treated group to 1.71 rad and to 1.31 rad in groups treated with CPC and DOD, respectively. For ovarian carcinoma cells, the average phase shift decreased from 2.94 rad to 1.88 rad and to 1.32 rad, respectively. Statistical significance of the phase shift differences is designated in Figs. 4(a), (c) and (e)) by the error bars and by asterisks indicating the significance levels of p<0.05 and p<0.01. As can be seen in Table 1 and Fig. 4, chemotherapeutic treatment with either CPC or DOD resulted in the significant decrease of average phase shifts in all cells observed, while this decrease was systematically lower in the case of DOD. Since the phase shift value is closely related with the cellular morphology and cell refractive index, it can be associated with cell viability and used as a quantitative characteristic of the chemotherapy efficacy. This suggestion is supported by recent results showing that the significant decrease of the phase shift in living cells is related to cell death through necrosis pathway [23,24]. Therefore, statistically significant difference between the phase shifts shown in Figs. 4(c)-(f) can be associated with different efficacy of CPC and DOD as chemotherapeutic agents.
Note that the statistical difference between the data obtained in each of the three cell groups was confirmed using the standard nonparametric Mann-Whitney test under an assumption that each cell group in each specimen belongs to the same population (null hypothesis). The test was performed on erythrocytes and ovarian carcinoma cells, the specimens were compared pair-wise. The differences obtained were found to be significant at the significance level of p<0.01 or in some cases p<0.05 (indicated in Fig. 4).
The 3D distributions of intracellular refractive index obtained with tomographic microscope provided data on other parameters, characterizing cellular morphology, namely cell volume, projected area and membrane surface area. The experimental data determined in each type of cells were averaged over 40 cells in each specimen. The mean values of cell volume, projected area, and membrane surface area determined in ovarian carcinoma cells are presented in Table 2 and plotted in Fig. 5. These data provide important additional information on cells viability and behavior and can unlikely be obtained by conventional microscopy. The results obtained were tested pair-wise by means of Mann-Whitney test at the level of significance p<0.01.
As can be seen from the data in Table 2 and Fig. 5(a), (c), (e) all the three parameters demonstrate remarkable decrease in specimens from treated rats as compared to those from untreated ones. However cells obtained from the DOD-treated rats demonstrate significantly larger decrease of the parameters than those from the CPC-treated ones. Histograms representing statistical distributions of these parameters over a number of cells, shown in Fig. 5(b), (d), (f), demonstrate that after chemotherapy with either CPC or DOD all the distributions modified and shifted toward lower values. And again chemotherapy with DOD caused more profound changes than that with CPC. These results are in a good agreement with those obtained by holographic microscopy and shown in Fig. 4 and Table 1.
Cellular mechanisms responsible for the detected decrease of morphological parameters of cells as a result of chemotherapy are not quite clear as yet and require additional studies. However the tendencies observed are definitely associated with the applied chemotherapeutic treatment and can be indicative of its efficacy.
The conclusions on the cytostatics efficiency made above were compared with the results obtained by the traditional biomedical test. The antitumor efficiency of both cytostatics was previously tested on the same rat model after a single intraperitoneal injection [32,33] and after hyperthermic intraperitoneal chemoperfusion (HIPEC) during surgery . The drug efficiency was evaluated by the increase in median survival of animals. The Bayesian statistical analysis of several experiments carried on monitoring of rats lifespan after a single intraperitoneal injection of either CPC or DOD showed that DOD increased median survival by 13 days (85%) while CPC increased that by only 10 days (66%) . Note that surgery + HIPEC caused a different survival pattern: the median survival of rats from the control group which received only surgery was 9 days, while HIPEC provided prolongation up to 25.5 days with CPC and to 49 days with DOD . Therefore, in both variants of intraperitoneal chemotherapy, namely the single intraperitoneal injection or HIPEC, DOD provided a more pronounced antitumor effect than CPC. These data are in a good agreement with the morphological changes in tumor cells after exposure to DOD and CPC presented in this paper. Mention that the antitumor efficiency of both cytostatics is usually explained by their direct destructive effect towards the cellular DNA by alkylation, irrespective of the cell cycle. Alkylation was shown to cause formation of intra- and inter-spiral sutures. Accumulation of these sutures leads to tumor cells death.
The results reported in this paper demonstrate also that both DOD and CPC affect not only tumor cells but erythrocytes as well. The observed ’giant’ cells may be indicative of tumor cell destruction during mitosis.
We have demonstrated the essential difference in morphology of both normal (erythrocytes) and cancerous (ovarian carcinoma) cells in the ascitic fluid taken from the non-treated group of rats and the groups treated with DOD and CPC. The decrease of average phase shift was clearly observed in both normal and cancerous cells taken from the rats treated by each of the chemotherapeutic agents as compared to those from the untreated ones. Specific ’giant’ fragmented cells were discovered in specimens taken from both DOD- and CPC-treated rats. These cells can be considered as dead through mitotic catastrophe and can be indicative of agent performance.
Strong arguments toward the existence of correspondence between average phase shift determined by digital holography and cell condition has already been demonstrated in our recent studies where correlations between cell death pathways and the phase shift changes have been observed [23, 24, 42]. Therefore, the average phase shift can be considered as an indicator of cell death pathway. In particular the phase shift decrease is associated with cell death through necrosis, which is predominant at high-dose chemotherapeutic treatments. The observed noticeable difference in volume of cells taken from rats treated with different agents can be considered as an indirect marker of cells viability and agent efficiency. The statistically significant difference of average phase shifts in cells of the specimens from CPC- and DOD-treated rats demonstrate an advantage of chemotherapy with Dioxadet in comparison to that with Cisplatin. The analysis of 3D distributions of intracellular refractive index also demonstrates statistically significant difference between major morphological parameters of the cells in specimens taken from CPC- and DOD-treated rats and non-treated ones. These results can also be interpreted as demonstration of higher efficiency of therapy with Dioxadet as compared to that with Cisplatin. The conclusions made are in a perfect agreement with the results of earlier independent studies demonstrating higher survival rates of rats treated with Dioxadet as compared to Cisplatin. The results obtained and suggested methodology can find applications in personalized medicine for evaluation of drug efficacy. The analysis of cell morphology by means of digital holography and tomography can be used as a method for quantitative evaluation of drug efficacy at the cellular level.
Russian Science Foundation (RSF) (# 14-13-00266).
The authors declare that there are no conflicts of interest related to this article
1. A. Jemal, F. Bray, M. Center, J. Ferlay, E. Ward, and D. Forman, “Global cancer statistics,” CA: Cancer J. Clin. 61, 69–90 (2011).
2. B. Stewart and C. Wild, World Cancer Report 2014 (World Health Organization, 2014).
3. Z. Kemp and J. Ledermann, “Update on first-line treatment of advanced ovarian carcinoma,” Int. J. Womens Heal. 5, 45–51 (2013).
4. V. N. Anisimov, M. A. Zabezhinski, I. G. Popovich, G. B. Pliss, V. G. Bespalov, V. A. Alexandrov, A. N. Stukov, I. V. Anikin, I. N. Alimova, P. A. Egormin, A. V. Panchenko, T. S. Piskunova, A. V. Semenchenko, M. L. Tyndyk, and M. N. Yurova, “Rodent models for the preclinical evaluation of drugs suitable for pharmacological intervention in aging,” Expert. Opin. Drug Discov. 7, 85–95 (2012). [CrossRef] [PubMed]
5. J. Lobo, E. Y.-S. See, M. Biggs, and A. Pandit, “An insight into morphometric descriptors of cell shape that pertain to regenerative medicine,” J. Tissue Eng. Regen. Medicine 10, 539–553 (2016). [CrossRef]
6. A. A. Gamal el Din, M. A. Badawi, S. E. Abdel Aal, N. A. Ibrahim, F. A. Morsy, and N. M. Shaffie, “DNA cytometry and nuclear morphometry in ovarian benign, borderline and malignant tumors,” Open Access Maced. J. Med. Sci. 3, 537–544 (2015). [CrossRef]
7. V. Nandakumar, L. Kelbauskas, K. F. Hernandez, K. M. Lintecum, P. Senechal, K. J. Bussey, P. C. W. Davies, R. H. Johnson, and D. R. Meldrum, “Isotropic 3d nuclear morphometry of normal, fibrocystic and malignant breast epithelial cells reveals new structural alterations,” Plos ONE 7, e29230 (2012). [CrossRef] [PubMed]
8. M. Mir, B. Bhaduri, R. Wang, R. Zhu, and G. Popescu, “Quantitative phase imaging,” Prog. Opt. 57, 133–217 (2012). [CrossRef]
9. G. Popescu, “Quantitative phase imaging of nanoscale cell structure and dynamics,” Methods Cell Biol. 90, 87–115 (2008). [CrossRef]
10. K. Lee, K. Kim, J. Jung, J. Heo, S. Cho, S. Lee, G. Chang, Y. Jo, H. Park, and Y. Park, “Quantitative phase imaging techniques for the study of cell pathophysiology: from principles to applications,” Sensors 13, 4170–4191 (2013). [CrossRef] [PubMed]
11. P. Marquet, C. Depeursinge, and P. J. Magistretti, “Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders,” Neurophotonics 1, 020901 (2014). [CrossRef]
12. S. Ban, E. Min, S. Baek, H. M. Kwon, G. Popescu, and W. Jung, “Optical properties of acute kidney injury measured by quantitative phase imaging,” Biomed. Opt. Express 9, 921–932 (2018). [CrossRef] [PubMed]
13. P. Girshovitz and N. T. Shaked, “Generalized cell morphological parameters based on interferometric phase microscopy and their application to cell life cycle characterization,” Biomed. Opt. Express 3, 1757–1773 (2012). [CrossRef] [PubMed]
14. R. Cao, W. Xiao, X. Wu, L. Sun, and F. Pan, “Quantitative observations on cytoskeleton changes of osteocytes at different cell parts using digital holographic microscopy,” Biomed. Opt. Express 9, 72–85 (2018). [CrossRef] [PubMed]
15. P. Memmolo, L. Miccio, A. Finizio, P. A. Netti, and P. Ferraro, “Holographic tracking of living cells by three-dimensional reconstructed complex wavefronts alignment,” Opt. Lett. 39, 2759–2762 (2014). [CrossRef] [PubMed]
16. S. Shin, K. Kim, T. Kim, J. Yoon, K. Hong, J. Park, and Y. Park, “Optical diffraction tomography using a digital micromirror device for stable measurements of 4d refractive index tomography of cells,” in Quantitative Phase Imaging II, vol. 9718 (International Society for Optics and Photonics, 2016), p. 971814. [CrossRef]
17. L. Cherkezyan, H. Subramanian, V. Stoyneva, J. D. Rogers, S. Yang, D. Damania, A. Taflove, and V. Backman, “Targeted alteration of real and imaginary refractive index of biological cells by histological staining,” Opt. Lett. 37, 1601–1603 (2012). [CrossRef] [PubMed]
19. F. Momey, A. Berdeu, T. Bordy, J.-M. Dinten, F. K. Marcel, N. Picollet-D’Hahan, X. Gidrol, and C. Allier, “Lensfree diffractive tomography for the imaging of 3d cell cultures,” Biomed. Opt. Express 7, 949–962 (2016). [CrossRef] [PubMed]
20. J. Kostencka, T. Kozacki, A. Kuś, B. Kemper, and M. Kujawińska, “Holographic tomography with scanning of illumination: space-domain reconstruction for spatially invariant accuracy,” Biomed. Opt. Express 7, 4086–4101 (2016). [CrossRef] [PubMed]
21. H. Choi, Z. Li, H. Sun, D. Merrill, J. Turek, M. Childress, and D. Nolte, “Biodynamic digital holography of chemoresistance in a pre-clinical trial of canine B-cell lymphoma,” Biomed. Opt. Express 9, 2214–2228 (2018). [CrossRef] [PubMed]
22. V. L. Calin, M. Mihailescu, N. Mihale, A. V. Baluta, E. Kovacs, T. Savopol, and M. G. Moisescu, “Changes in optical properties of electroporated cells as revealed by digital holographic microscopy,” Biomed. Opt. Express 8, 2222–2234 (2017). [CrossRef] [PubMed]
23. A. V. Belashov, A. A. Zhikhoreva, T. N. Belyaeva, E. S. Kornilova, N. V. Petrov, A. V. Salova, I. V. Semenova, and O. S. Vasyutinskii, “Digital holographic microscopy in label-free analysis of cultured cells’ response to photodynamic treatment,” Opt. Lett. 41, 5035–5038 (2016). [CrossRef] [PubMed]
24. A. V. Belashov, A. A. Zhikhoreva, T. N. Belyaeva, E. S. Kornilova, N. V. Petrov, A. V. Salova, I. V. Semenova, and O. S. Vasyutinskii, “Hela cells response to photodynamic treatment with Radachlorin at various irradiation parameters,” Proc. SPIE 10414, 104140U (2017). [CrossRef]
25. D. Donnarumma, A. Brodoline, D. Alexandre, and M. Gross, “Blood flow imaging in zebrafish by laser doppler digital holography,” Microsc. Res. Tech. 81, 153–161 (2018). [CrossRef]
27. B. Javidi, I. Moon, S. Yeom, and E. Carapezza, “Three-dimensional imaging and recognition of microorganism using single-exposure on-line (SEOL) digital holography,” Opt. Express 13, 4492–4506 (2005). [CrossRef] [PubMed]
28. A. Calabuig, M. Mugnano, L. Miccio, S. Grilli, and P. Ferraro, “Investigating fibroblast cells under “safe” and “injurious” blue-light exposure by holographic microscopy,” J. Biophotonics 10, 919–927 (2017). [CrossRef]
29. M. Mugnano, P. Memmolo, L. Miccio, S. Grilli, F. Merola, A. Calabuig, A. Bramanti, E. Mazzon, and P. Ferraro, “In vitro cytotoxicity evaluation of cadmium by label-free holographic microscopy,” J. Biophotonics p. e201800099 (2018). [CrossRef] [PubMed]
30. N. Pavillon, J. Kühn, C. Moratal, P. Jourdain, C. Depeursinge, P. J. Magistretti, and P. Marquet, “Early cell death detection with digital holographic microscopy,” PloS One 7, e30912 (2012). [CrossRef] [PubMed]
31. M. Mugnano, P. Memmolo, L. Miccio, F. Merola, V. Bianco, A. Bramanti, A. Gambale, R. Russo, I. Andolfo, and A. Iolascon et al., “Label-free optical marker for rbc phenotyping of inherited anaemias,” Anal. Chem. 12, 7495–7501 (2018). [CrossRef]
32. V. G. Bespalov, E. A. Vyshinskaya, I. N. Vasil’eva, A. L. Semenov, M. A. Maidin, N. V. Barakova, and A. N. Stukov, “Comparative study of antitumor efficiency of intraperitoneal and intravenous cytostatics in experimental rats with disseminated ovarian cancer,” Bull. Exp. Biol. Medicine 162, 383–386 (2017). [CrossRef]
33. V. Bespalov, I. Alvovsky, G. Tochilnikov, A. Stukov, E. Vyshinskaya, A. Semenov, I. Vasilyeva, O. Belyaeva, G. Kireeva, K. Senchik, N. Zhilinskaya, J. Von, L. Krasilnikova, V. Alexandrov, N. Khromov-Borisov, D. Baranenko, and A. Belyaev, “Comparative efficacy evaluation of catheter intraperitoneal chemotherapy, normothermic and hyperthermic chemoperfusion in a rat model of ascitic ovarian cancer,” Int. J. Hyperth. 34, 545–550 (2018). [CrossRef]
36. R. M. Goldstein, H. A. Zebker, and C. L. Werner, “Satellite radar interferometry: Two-dimensional phase unwrapping,” Radio Sci. 23, 713–720 (1988). [CrossRef]
37. A. V. Belashov, A. A. Zhikhoreva, V. G. Bespalov, V. I. Novik, N. T. Zhilinskaya, I. V. Semenova, and O. S. Vasyutinskii, “Refractive index distributions in dehydrated cells of human oral cavity epithelium,” JOSA B 34, 2538–2543 (2017). [CrossRef]
38. E. R. Dougherty and R. A. Lotufo, Hands-on morphological image processing, vol. 59 (SPIE press, 2003). [CrossRef]
40. I. V. Sorokina, T. V. Denisenko, G. Imreh, P. A. Tyurin-Kuzmin, V. O. Kaminskyy, V. Gogvadze, and B. Zhivotovsky, “Involvement of autophagy in the outcome of mitotic catastrophe,” Sci. Reports 7, 14571 (2017). [CrossRef]
41. V. G. Bespalov, G. S. Kireeva, O. A. Belyaeva, O. E. Kalinin, K. Y. Senchik, A. N. Stukov, G. I. Gafton, K. D. Guseynov, and A. M. Belyaev, “Both heat and new chemotherapeutic drug dioxadet in hyperthermic intraperitoneal chemoperfusion improved survival in rat ovarian cancer model,” J. Surg. Oncol. 113, 438–442 (2016). [CrossRef]
42. I. V. Semenova, A. V. Belashov, T. N. Belyaeva, E. S. Kornilova, A. V. Salova, A. A. Zhikhoreva, and O. S. Vasyutinskii, “Necrosis and apoptosis pathways of cell death at photodynamic treatment in vitro as revealed by digital holographic microscopy,” Proc. SPIE 10497, 104970D (2018).