<i>In vivo</i> tomographically diagnosing technique of early cancer using 2-color optical coherence dosigraphy
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- NAKAMICHI Yu
- RIKEN Brain Science Institute
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- SAEKI Souichi
- Graduate School of Engineering Mechanical and Physical Engineering, Osaka City University
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- HIRO Takafumi
- Division of Cardiology, Department of Medicine, Nihon University School of Medicine
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- MATSUZAKI Masunori
- Saint Hill hospital
抄録
<p>The endoscopic optical coherence tomography (OCT) has been developed for early detection of digestive system cancer. However, it is difficult to detect cancerous tissue due to complicated speckle patterns contributed by optical properties of scattering and absorption in the morphological images of OCT. In our previous papers, 2-color optical coherence dosigraphy (2C-OCD) was proposed, which quantified OCT signal as scattering and absorption coefficients and could provide drug distribution at the micro-scale spatial resolution. In this study, an in vivo tomographically diagnosing technique of early cancer is presented, in which 2C-OCD is applied to cancerous tissue with selective uptake of photosensitizer. The feasibility study was demonstrated and investigated, based on 2C-OCD visualization of the subcutaneous tumor-implanted nude mice with photosensitizer AlPcS administered. Consequently, it was confirmed that drug absorption coefficient obtained by 2C-OCD was correlated with fluorescence intensity from accumulated AlPcS (r = 0.918), comparing with their histological images. Additionally, 2C-OCD could diagnose tumor tissue significantly with sensitivity of 82.5% and specificity of 78.3%, respectively. Therefore, 2C-OCD can detect photosensitizer infiltration into cancerous tissue, and thus has a promising modality for in vivo tomographically diagnosing technique of early cancer.</p>
収録刊行物
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- Journal of Biomechanical Science and Engineering
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Journal of Biomechanical Science and Engineering 12 (2), 16-00591-16-00591, 2017
一般社団法人 日本機械学会
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詳細情報 詳細情報について
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- CRID
- 1390282680239042944
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- NII論文ID
- 130005695213
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- ISSN
- 18809863
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可