{"title":"自动毛细管流分割和映射的甲襞视频毛细管镜","authors":"Tomoya Niizawa, Kota Yokemura, Tomoya Kusaka, Takuma Sugashi, Ichiro Miura, Keiji Kawagoe, Kazuto Masamoto","doi":"10.1111/micc.12753","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Objective</h3>\n \n <p>This study aimed to develop an automated image analysis method for segmentation and mapping of capillary flow dynamics captured using nailfold video capillaroscopy (NVC). Methods were applied to compare capillary flow structures and dynamics between young and middle-aged healthy controls.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>NVC images were obtained in a resting state, and a region of the vessel in the image was extracted using a conventional U-Net neural network. The approximate length, diameter, and radius of the curvature were calculated automatically. Flow speed and its fluctuation over time were mapped using the Radon transform and frequency spectrum analysis from the kymograph image created along the vessel's centerline.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The diameter of the curve segment (14.4 μm and 13.0 μm) and the interval of two straight segments (13.7 μm and 32.1 μm) of young and middle-aged subjects, respectively, were significantly different. Faster flow was observed in older subjects (0.48 mm/s) than in younger subjects (0.26 mm/s). The power spectral analysis revealed a significant correlation between the high-frequency power spectrum and the flow speed.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>The present method allows a spatiotemporal characterization of capillary morphology and flow dynamics with NVC, allowing a wide application such as large-scale health assessment.</p>\n </section>\n </div>","PeriodicalId":18459,"journal":{"name":"Microcirculation","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Automated capillary flow segmentation and mapping for nailfold video capillaroscopy\",\"authors\":\"Tomoya Niizawa, Kota Yokemura, Tomoya Kusaka, Takuma Sugashi, Ichiro Miura, Keiji Kawagoe, Kazuto Masamoto\",\"doi\":\"10.1111/micc.12753\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Objective</h3>\\n \\n <p>This study aimed to develop an automated image analysis method for segmentation and mapping of capillary flow dynamics captured using nailfold video capillaroscopy (NVC). Methods were applied to compare capillary flow structures and dynamics between young and middle-aged healthy controls.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>NVC images were obtained in a resting state, and a region of the vessel in the image was extracted using a conventional U-Net neural network. The approximate length, diameter, and radius of the curvature were calculated automatically. Flow speed and its fluctuation over time were mapped using the Radon transform and frequency spectrum analysis from the kymograph image created along the vessel's centerline.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>The diameter of the curve segment (14.4 μm and 13.0 μm) and the interval of two straight segments (13.7 μm and 32.1 μm) of young and middle-aged subjects, respectively, were significantly different. Faster flow was observed in older subjects (0.48 mm/s) than in younger subjects (0.26 mm/s). The power spectral analysis revealed a significant correlation between the high-frequency power spectrum and the flow speed.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>The present method allows a spatiotemporal characterization of capillary morphology and flow dynamics with NVC, allowing a wide application such as large-scale health assessment.</p>\\n </section>\\n </div>\",\"PeriodicalId\":18459,\"journal\":{\"name\":\"Microcirculation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2022-02-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Microcirculation\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/micc.12753\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"HEMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microcirculation","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/micc.12753","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEMATOLOGY","Score":null,"Total":0}
Automated capillary flow segmentation and mapping for nailfold video capillaroscopy
Objective
This study aimed to develop an automated image analysis method for segmentation and mapping of capillary flow dynamics captured using nailfold video capillaroscopy (NVC). Methods were applied to compare capillary flow structures and dynamics between young and middle-aged healthy controls.
Methods
NVC images were obtained in a resting state, and a region of the vessel in the image was extracted using a conventional U-Net neural network. The approximate length, diameter, and radius of the curvature were calculated automatically. Flow speed and its fluctuation over time were mapped using the Radon transform and frequency spectrum analysis from the kymograph image created along the vessel's centerline.
Results
The diameter of the curve segment (14.4 μm and 13.0 μm) and the interval of two straight segments (13.7 μm and 32.1 μm) of young and middle-aged subjects, respectively, were significantly different. Faster flow was observed in older subjects (0.48 mm/s) than in younger subjects (0.26 mm/s). The power spectral analysis revealed a significant correlation between the high-frequency power spectrum and the flow speed.
Conclusions
The present method allows a spatiotemporal characterization of capillary morphology and flow dynamics with NVC, allowing a wide application such as large-scale health assessment.
期刊介绍：
The journal features original contributions that are the result of investigations contributing significant new information relating to the vascular and lymphatic microcirculation addressed at the intact animal, organ, cellular, or molecular level. Papers describe applications of the methods of physiology, biophysics, bioengineering, genetics, cell biology, biochemistry, and molecular biology to problems in microcirculation.
Microcirculation also publishes state-of-the-art reviews that address frontier areas or new advances in technology in the fields of microcirculatory disease and function. Specific areas of interest include: Angiogenesis, growth and remodeling; Transport and exchange of gasses and solutes; Rheology and biorheology; Endothelial cell biology and metabolism; Interactions between endothelium, smooth muscle, parenchymal cells, leukocytes and platelets; Regulation of vasomotor tone; and Microvascular structures, imaging and morphometry. Papers also describe innovations in experimental techniques and instrumentation for studying all aspects of microcirculatory structure and function.
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