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0PILOT STUDY OF THE SMALL INTESTINAL VASCULAR SYSTEM IN THE CONTEXT OF PERITONITIS
DEVELOPMENT USING OPTICAL IMAGING
POLINA A. TIMOSHINA 1,2,3 ANDREY DANILOV4, YURY I. SURKOV u, , VALERY V. TUCHIN 1,2,3,5 ,
SERGEY KAPRALOV4
institution of Physics, Saratov State University, Astrahanskaja str., 83, Saratov, 410012, Russia,
2Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, Lenin Avenue, 36,
Tomsk, 634050, Russia 3Science Medical Center, Saratov State University, Saratov 410012, Russia 4Saratov State Medical University named after V.I. Razumovsky 5Ititute ofPrecision Mechanics and Control, FRC "Scientific Research Centre of the Russian Academy of
Sciences," Saratov 410028
INTRODUCTION
Peritonitis is an unresolved problem of abdominal surgery. Mortality in this disease ranges from 2.6% to 60% and increases up to 90% with the development of multiple organ failure [1, 2]. Vascular reactions developing in this disease are complex and multifaceted, and require further study. In this regard, this work tested the use of the speckle-contrast visualization method to analyze changes in the vascular system of the small intestine under the conditions of the development of an experimental model of peritonitis in laboratory
MATERIALS AND METHODS
The study were carried out on 8-week-old Wistar female rats (weight between 275 ± 25 g). Peritonitis with small intestinal flora was modeled according to an original technique.
Fixed and anesthetized (Zoletil+Xylanite), after processing the surgical field, the animal underwent a mini-laparotomy with a 2-3 mm incision. A loop of the small intestine was taken on holders from the wound, after which 4 perforations with a diameter of 1 mm were applied with a laser surgical unit.
The study was conducted on the 3rd day after surgery. Relaparotomy, revision of abdominal organs were performed; pronounced signs of peritonitis were observed: dilated intestinal loops, lack of peristalsis, purulent effusion in the abdominal cavity with a characteristic colibacillary odor. The dome of the cecum and part of the ileum were removed from the wound and placed on a slide table.
Laser speckle contrast imaging (LSCI) techniques are based on the registration of spatial and temporal statistics of the speckle pattern, calculation of contrast of time-averaged dynamic speckles in dependence on the camera exposure time [3-14]. The most useful modification appeared to the Spatio-Temporal Laser Speckle Contrast Imaging (stLSCI). The contrast of the speckle image is calculated as the ratio of standard deviation of the intensity fluctuations for many pixels within a chosen area at different times and the pixel mean intensity averaged for all pixels of the area [3]. The LSC was calculated using the recorded speckle field image over an area typically 5^5 or 7^7 pixels in size [3-5]:
LSCk =°Iklh ,
(1)
where k is the number of frames in a sequence of speckle-modulated images, Ik average intensity of scattered light of the analyzed frame and aIk the root-mean-square value of the fluctuation component of the pixel brightness.
To calculate image stLSCI, the set of obtained speckle images was processed using software developed in the MATLAB environment (MathWorks, USA). A spatio-temporal window was used with dimensions of 5x5 pixels in the spatial domain and 100 pixels in the temporal domain. As a result of analyzing a set of 100 consecutive raw speckle images, a single image of the stLSC distribution was obtained, in which the speckle contrast value for each pixel was color-coded. When registering speckle-modulated images, information about
the dynamics of the probed object can be obtained as a result of analyzing the dependence of the speckle contrast (the resulting speckle-modulated images of the object's surface) on the exposure time.
Fig. 1 shows a diagram of the experimental setup used to visualize microhemodynamics in the vessels of the ears of laboratory rats.
Figure 1 Scheme of the experimental setup.
This setup allows recording images of the same sample area both in coherent light (laser illumination) and incoherent illumination without mechanical readjustment for microscopic analysis. A CMOS camera (Thorlabs CS235MU Kiralux series, 1920x1200 pixels (2.3 MP) matrix, pixel size 5.86x5.86 ^m; 12 bits/pixel) is used as a detector with the exposure time T of 10-15 ms and with lens zoom 4x. The laser beam from the He-Ne laser HNL210L (Thorlabs) with a wavelength of 633 nm is directed through an optical fiber to a collimating mirror to the object under study, located on a special glass table.
OCT
A spectral tomograph GAN930V2-BU (Thorlabs, USA) operating at a central wavelength of 930 nm with an axial resolution of 5.34 ^m in air was used for OCT monitoring. The OCT system's focus was set at a depth of 800 ^m. The ear of a laboratory rat was placed on a specialized substrate under the OCT system.
RESULTS
Figure 2 presents standard speckle-contrast images, while Figure 3 displays standard OCT cross-sectional images of the small intestine walls in laboratory rats. The image on the left represents the control group, while the image on the right represents a group with an induced peritonitis model.
a) b)
Figure 2: Speckle-contrast images of the small intestinal wall of laboratory rats.
I J
a) b)
Figure 3: OCT cross-sectional images of the small intestinal wall of laboratory rats.
For the laboratory rat from the control group, it can be noted that the intestinal wall demonstrates a layered structure characteristic of healthy tissue. There are no signs of inflammatory changes or thickening. Smooth contours and uniformity of optical density in the layers indicate a normal tissue condition without pronounced morphological disorders. Optical inhomogeneities associated with blood vessels with a diameter of approximately 40-50 ^m are observed.
For the group with induced peritonitis, it can be noted that significant changes in the structure of the intestinal wall are observed, including tissue thickening and increased contrast between the layers of the small intestine. An increase in optical density is observed in certain areas, which may indicate possible infiltration by immune cells and accumulation of fluid in the intercellular spaces. The diameter and density of blood vessels are increased in comparison with the control group. These changes confirm the presence of a pathological process caused by peritonitis. OCT images demonstrate clear differences between the control group and the group with model peritonitis, which indicates high information content of this method for assessing inflammatory changes in small intestinal tissue. The revealed structural changes correspond to the expected manifestations of inflammation and can be used for further quantitative and qualitative assessment of the effectiveness of therapeutic interventions.
References:
[1] Chromik AM, Meiser A, Holling J, Sülberg D, Daigeler A, Meurer K, Vogelsang H, Seelig MH, Uhl W. Identification of patients at risk for development of tertiary peritonitis on a surgical intensive care unit. J Gastrointest Surg. 2009 Jul;13(7):1358-67. doi: 10.1007/s11605-009-0882-y. Epub 2009 Apr 8. PMID: 19352781.
[2] Koperna T, Schulz F. Prognosis and treatment of peritonitis. Do we need new scoring systems? Arch Surg. 1996 Feb;131(2):180-6. doi: 10.1001/archsurg.1996.01430140070019. PMID: 8611076.
[3] Briers D, Duncan DD, Hirst E, et al. Laser speckle contrast imaging: theoretical and practical limitations. JBiomed Opt. 2013;18(6):066018.
[4] Sang X, Chen B, Li D, Pan D, Sang X. Transient Thermal Response of Blood Vessels during Laser Irradiation Monitored by Laser Speckle Contrast Imaging. Photonics. 2022; 9(8):520.
[5] Yu CY, Chammas M, Gurden H, Lin HH, Pain F. Design and validation of a convolutional neural network for fast, model-free blood flow imaging with multiple exposure speckle imaging. Biomed Opt Express. 2023;14(9):4439-4454.
[6] Patel DD, Lipinski DM. Validating a low-cost laser speckle contrast imaging system as a quantitative tool for assessing retinal vascular function. Sci Rep. 2020;10(1):7177.
[7] Arias-Cruz JA, Chiu R, Peregrina-Barreto H, Ramos-Garcia R, Spezzia-Mazzocco T, Ramirez-San-Juan JC. Visualization of in vitro deep blood vessels using principal component analysis based laser speckle imaging. Biomed Opt Express. 2019;10(4):2020-2031.
[8] Sdobnov A, Piavchenko GA, Bykov AV, Meglinski I. Advances in Dynamic Light Scattering Imaging of Blood Flow. Laser & Photonics Rev.. 2024;18(2):2300494.
[9] González Olmos A, Zilpelwar S, Sunil S, Boas DA, Postnov DD. Optimizing the precision of laser speckle contrast imaging. Sci Rep. 2023;13(1):17970.
[10] Postnikov EB, Tsoy MO, Timoshina PA, Postnov DE. Gaussian sliding window for robust processing laser speckle contrast images. Int JNumer Method Biomed Eng. 2019;35(4):e3186.
[11] Liu X, Yang H, Li R.. Improving contrast accuracy and resolution of laser speckle contrast imaging using two-dimensional entropy algorithm. IEEE Access. 2021; 9: 148925-148932.
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[12] Khaksari K, Kirkpatrick SJ. Laser speckle contrast imaging is sensitive to advective flux. J Biomed Opt. 2016;21(7):76001.
[13] Khaksari K, Kirkpatrick SJ. Combined effects of scattering and absorption on laser speckle contrast imaging. J Biomed Opt. 2016;21(7):76002.
