Research On Cell Viability Evaluation Method And Application Based On Lensfree Diffraction Imaging

In vitro cell experiments are widely used in the area of agriculture,like animal delivery,disease detection and epidemic prevention,analysis of the efficacy of natural active ingredients of animals and plants.Cell viability,which is assumed as an indicator to effectively evaluate the state of cell growth under different culture conditions,is the key basis for researchers to draw correct conclusions.In cell viability detection field,the widely used staining and colorimetric methods at present need to deal with reagents every time,which is difficult to automate.The reaction time of reagent combination is long,resulting in the time-consuming and laborious detection process;the reagents are harmful to cells.Thus,a group of samples cannot be detected continuously,causing to hardly improvement of evaluation accuracy,large consumption of reagents and the obvious disadvantages.The novel label-free and non-terminal detection methods,such as impedance method and electrochemical method,effectively improve the degree of automation.However,due to the harsh requirements of special materials and processing technology of cell culture equipment,the research cost is high;Based on the overall electrical parameters,the detection limit is high and the resolution is difficult to be improved;while it can only evaluate the overall performance and not be competent for the situation of multi sample coexistence.Optical microscopic imaging technology can effectively overcome those drawbacks.However,the index of cell viability can only be evaluated accurately based on the statistics of a large number of cell populations,which requires the optical microscopic imaging technology to have both the characteristics of large field of view and the ability to effectively extract micro information which can reflect cell viability.Obviously,the traditional microscopic imaging methods are difficult to deal with this contradiction effectively.In this paper,a new method of cell viability detection based on lensfree diffraction imaging and cell morphology is proposed.The lensfree diffraction imaging technology has the characteristics of large field of view.On the basis of this advantage,theoretical analysis and practical exploration were made on how to extract the information that can effectively reflect the state of cell activity on the micro scale of cell,and on how to realize the accurate evaluation of cell viability.A numerical simulation method of lensless diffraction imaging of cell samples under partially coherent light irradiation is established,based on the analysis of the principle of lensfree diffraction imaging and the optical modulation of cell samples.Aiming at the specific target scale of cells,this paper analyzes the influence of system elements on imaging performance from the aspects of coherent characteristics of system light source,spectral characteristics and geometric parameters of system by using the established numerical simulation method and the combination of simulation calculation and experimental data.Then the appropriate parameters are selected and the system implementation is carried out to provide the foundation of effective extraction of information from the perspective of the high-quality imaging.According to the principle of cell morphology combined with simulation calculation and experimental imaging,the lensfree diffracted fingerprints corresponding to cell morphology in different active states are studied.Meanwhile the characteristics closely related to cell morphology in fingerprints are analyzed,and the method of extracting effective features from the original lensless diffracted fingerprints to realize living cell identification is established to measure cell viability based on the number of living cells.Comparative studies in the cytotoxicity experiments show that the correlation coefficient is 0.9837 and 0.9760,and relative standard deviations are lower and more stable concentrating at 6.1%-7.4%,which validate the proposed method.In order to solve the problem that the original diffractive fingerprint is not able to recognize the details of cell morphology,this paper further explores the reconstruction method of lensfree diffractive imaging of cell samples.Aiming at the problem that the important parameter of reconstruction distance is difficult to obtain directly according to the geometric relationship of the system,a self-focusing algorithm for the optimal reconstruction distance is established.Aiming at the problem of strong twin image interference in the reconstruction process,a reconstruction method based on four-step diffraction transmission numerical calculation is established,which effectively suppresses the twin image and realizes the fast and high-quality reconstruction of cell lensless diffraction image.The reconstruction results reflect the details of cell morphology,and are suitable for the occasions with high requirements for large field of view,high throughput and imaging details.In the applied research,the established method is used in the field of agriculture based on mammalian cell experiments in vitro,as a means to evaluate cell viability.;The results show that compared with the MTT method,the proposed method can significantly reduce the consumption of reagent consumables.The total testing time reduces from dozens of hours to tens of minutes with high efficiency,high degree of automation and the testing workload is significantly reduced;the proposed method can achieve the viability evaluation of cell classification under the multi cell hybrid system.In this application,it can improve the accuracy of the evaluation.And it has incomparable advantages compared with the existing methods.This method is also used in the rapid detection of cell viability and living cell concentration of Saccharomyces cerevisiae.The whole process is completed in 3 minutes.The standard PI counting method can effectively reduce the false positive and counting error caused by the subjectivity of the tester.The application research fully shows the advantages of the proposed method in high throughput,high precision,automation,wide application range and so on.