{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T05:32:19Z","timestamp":1762061539003,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,15]],"date-time":"2022-08-15T00:00:00Z","timestamp":1660521600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Joint Research Project by Southeast University and Nanjing Medical University","award":["3207027381"],"award-info":[{"award-number":["3207027381"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>The distinguishable absorption contrast among healthy gastric tissues, carcinoma in situ and cancer tissues in the THz frequency range is one of the keys to realizing gastric cancer diagnosis by THz imaging. Based on microwave devices and a sub-wavelength fiber, we developed a fast-scanning THz imaging system combined with the principle of surface plasmon resonance enhancement. This imaging system has a near-field \u03bb\/17 spatial resolution and imaging S\/N ratio as high as 108:1, and the image results are directly displayed within 1 min. We also successfully demonstrated the image diagnostic capability on sliced tissues from eight patients with gastric cancer. The results indicate that THz absorption images can not only clearly distinguish cancer tissue from healthy tissues but also accurately define the margins of cancer. Through a medical statistical study of 40 sliced tissues from 40 patients, we prove that THz imaging can be used as a standalone method to diagnose gastric cancer tissues with a diagnostic specificity and sensitivity of 100%. Compared with the H&amp;E staining method, THz imaging diagnosis makes the automation of tissue-sampling pre-screening procedure possible and assists in quickly determining the boundary between cancerous and healthy tissues.<\/jats:p>","DOI":"10.3390\/cancers14163932","type":"journal-article","created":{"date-parts":[[2022,8,15]],"date-time":"2022-08-15T20:58:08Z","timestamp":1660597088000},"page":"3932","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Clinical Diagnosis of Gastric Cancer by High-Sensitivity THz Fiber-Based Fast-Scanning Near-Field Imaging"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7308-6683","authenticated-orcid":false,"given":"Hua","family":"Chen","sequence":"first","affiliation":[{"name":"School of Physics, Southeast University, Nanjing 211189, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Han","sequence":"additional","affiliation":[{"name":"School of Physics, Southeast University, Nanjing 211189, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shihua","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Physics, Southeast University, Nanjing 211189, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianzhu","family":"Qiu","sequence":"additional","affiliation":[{"name":"Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaofeng","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China"},{"name":"Department of Oncology, Pukou Branch Hospital of Jiangsu Province Hospital, Nanjing 211800, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7","DOI":"10.3322\/caac.21708","article-title":"Cancer statistics, 2022","volume":"72","author":"Siegel","year":"2022","journal-title":"CA Cancer J. 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