{"title":"用于疾病评估的深度成像多参数光学相干层析成像系统的设计与构建","authors":"Bruce Vagt, Matthew Foster, Richard L. Blackmon","doi":"10.1109/SIEDS58326.2023.10137789","DOIUrl":null,"url":null,"abstract":"Early cancer detection remains an important problem in healthcare today. Since the mid-1990s, Optical Coherence Tomography (OCT) has been explored as a cancer detection instrument. Previous studies have shown connections between tissue porosity, cell behavior, cell topology, and their relation to cancer and disease progression. Previous researchers have found that in a healthy cell, the pore size of the surrounding extracellular matrix (ECM) is homogenous. However, in a cancerous cell, heterogeneous pores appear. Additionally, as cancer progresses, pore size decreases. Herein, we propose a new method of improving cancer detection using OCT. In a study utilizing an artificial ECM, a connection between pore size and gold nanorod (GNR) diffusion was established such that smaller pores lead to less diffusion, and vice versa. Cell behavior is measured by cell motility, which refers to the rapid, in-place motions of intracellular parts that can be used to assess cell response to therapy, their surrounding environment, and potentially reveal premalignant behavior. Previous investigators have defined two metrics of cell movement, alpha, and motility, which correspond to signal auto-decorrelation and signal amplitude, respectively. Cell topology refers to the 3D structure and shape of cells and cell clusters, which has been shown to mutate in diseases such as cancer. By quantifying cell topology, cellular health can be examined. Techniques using OCT have also been used to monitor the response of diseased tissue to treatment. These studies have been largely independent of each other, and the need for a more holistic measuring system has been called for. This research aims to create a custom OCT system capable of obtaining these metrics simultaneously and with improved imaging depth and comparable resolution. Through an integration of a near-infrared (NIR) laser, interferometer, and LabVIEW control of the system, a new Deep-Imaging, Multi-Parameter OCT (DIMP-OCT) is being created. The system bodes a 4.6µm resolution and 5.4mm imaging depth. This is made possible by a 50-50 fiber optic beam splitter using a 1300nm wavelength laser with 160nm bandwidth, and 2048-pixel spectrometer with a 140kHz linerate. Here, we report the design of the system being built, the techniques used to build and test the hardware, and the approach to developing the graphical user interface. We also will report results from tests to assess DIMP-OCT subsystems.","PeriodicalId":267464,"journal":{"name":"2023 Systems and Information Engineering Design Symposium (SIEDS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Designing and Building a Deep Imaging Multi-Parametric Optical Coherence Tomography System for Disease Assessment\",\"authors\":\"Bruce Vagt, Matthew Foster, Richard L. Blackmon\",\"doi\":\"10.1109/SIEDS58326.2023.10137789\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Early cancer detection remains an important problem in healthcare today. Since the mid-1990s, Optical Coherence Tomography (OCT) has been explored as a cancer detection instrument. Previous studies have shown connections between tissue porosity, cell behavior, cell topology, and their relation to cancer and disease progression. Previous researchers have found that in a healthy cell, the pore size of the surrounding extracellular matrix (ECM) is homogenous. However, in a cancerous cell, heterogeneous pores appear. Additionally, as cancer progresses, pore size decreases. Herein, we propose a new method of improving cancer detection using OCT. In a study utilizing an artificial ECM, a connection between pore size and gold nanorod (GNR) diffusion was established such that smaller pores lead to less diffusion, and vice versa. Cell behavior is measured by cell motility, which refers to the rapid, in-place motions of intracellular parts that can be used to assess cell response to therapy, their surrounding environment, and potentially reveal premalignant behavior. Previous investigators have defined two metrics of cell movement, alpha, and motility, which correspond to signal auto-decorrelation and signal amplitude, respectively. Cell topology refers to the 3D structure and shape of cells and cell clusters, which has been shown to mutate in diseases such as cancer. By quantifying cell topology, cellular health can be examined. Techniques using OCT have also been used to monitor the response of diseased tissue to treatment. These studies have been largely independent of each other, and the need for a more holistic measuring system has been called for. This research aims to create a custom OCT system capable of obtaining these metrics simultaneously and with improved imaging depth and comparable resolution. Through an integration of a near-infrared (NIR) laser, interferometer, and LabVIEW control of the system, a new Deep-Imaging, Multi-Parameter OCT (DIMP-OCT) is being created. The system bodes a 4.6µm resolution and 5.4mm imaging depth. This is made possible by a 50-50 fiber optic beam splitter using a 1300nm wavelength laser with 160nm bandwidth, and 2048-pixel spectrometer with a 140kHz linerate. Here, we report the design of the system being built, the techniques used to build and test the hardware, and the approach to developing the graphical user interface. 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Designing and Building a Deep Imaging Multi-Parametric Optical Coherence Tomography System for Disease Assessment
Early cancer detection remains an important problem in healthcare today. Since the mid-1990s, Optical Coherence Tomography (OCT) has been explored as a cancer detection instrument. Previous studies have shown connections between tissue porosity, cell behavior, cell topology, and their relation to cancer and disease progression. Previous researchers have found that in a healthy cell, the pore size of the surrounding extracellular matrix (ECM) is homogenous. However, in a cancerous cell, heterogeneous pores appear. Additionally, as cancer progresses, pore size decreases. Herein, we propose a new method of improving cancer detection using OCT. In a study utilizing an artificial ECM, a connection between pore size and gold nanorod (GNR) diffusion was established such that smaller pores lead to less diffusion, and vice versa. Cell behavior is measured by cell motility, which refers to the rapid, in-place motions of intracellular parts that can be used to assess cell response to therapy, their surrounding environment, and potentially reveal premalignant behavior. Previous investigators have defined two metrics of cell movement, alpha, and motility, which correspond to signal auto-decorrelation and signal amplitude, respectively. Cell topology refers to the 3D structure and shape of cells and cell clusters, which has been shown to mutate in diseases such as cancer. By quantifying cell topology, cellular health can be examined. Techniques using OCT have also been used to monitor the response of diseased tissue to treatment. These studies have been largely independent of each other, and the need for a more holistic measuring system has been called for. This research aims to create a custom OCT system capable of obtaining these metrics simultaneously and with improved imaging depth and comparable resolution. Through an integration of a near-infrared (NIR) laser, interferometer, and LabVIEW control of the system, a new Deep-Imaging, Multi-Parameter OCT (DIMP-OCT) is being created. The system bodes a 4.6µm resolution and 5.4mm imaging depth. This is made possible by a 50-50 fiber optic beam splitter using a 1300nm wavelength laser with 160nm bandwidth, and 2048-pixel spectrometer with a 140kHz linerate. Here, we report the design of the system being built, the techniques used to build and test the hardware, and the approach to developing the graphical user interface. We also will report results from tests to assess DIMP-OCT subsystems.