{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T16:43:45Z","timestamp":1777481025648,"version":"3.51.4"},"reference-count":29,"publisher":"SAGE Publications","issue":"8","license":[{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancer Biotherapy and Radiopharmaceuticals"],"published-print":{"date-parts":[[2024,10]]},"abstract":"<jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>\n                      The aim of this study was to develop a\n                      <jats:sup>18<\/jats:sup>\n                      F-fluorodeoxyglucose (\n                      <jats:sup>18<\/jats:sup>\n                      F-FDG) positron emission tomography\/computed tomography (PET\/CT) radiomic model for predicting mediastinal lymph node metastasis (LNM) in presurgical patients with lung adenocarcinoma.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>The study enrolled 320 patients with lung adenocarcinoma (288 internal and 32 external cases) and extracted 190 radiomic features using the LIFEx package. Optimal radiomic features to build a radiomic model were selected using the least absolute shrinkage and selection operator algorithm. Logistic regression was used to build the clinical and complex (combined radiomic and clinical variables) models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      Ten radiomic features were selected. In the training group, the area under the receiver operating characteristic curve of the complex model was significantly higher than that of the radiomic and clinical models [0.924 (95% CI: 0.887\u20130.961) vs. 0.863 (95% CI: 0.814\u20130.912;\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      \u2009=\u20090.001) and 0.838 (95% CI: 0.783\u20130.894;\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      \u2009=\u20090.000), respectively]. The sensitivity, specificity, accuracy, and positive and negative predictive values of the radiomic model were 0.857, 0.790, 0.811, and 0.651 and 0.924, respectively, which were better than that of visual evaluation (0.539, 0.724, 0.667, and 0.472 and 0.775, respectively) and PET semiquantitative analyses (0.619, 0.732, 0.697, and 0.513 and 0.808, respectively).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>\n                      <jats:sup>18<\/jats:sup>\n                      F-FDG PET\/CT radiomics showed good predictive performance for LNM and improved the N-stage accuracy of lung adenocarcinoma.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1089\/cbr.2022.0038","type":"journal-article","created":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T12:13:29Z","timestamp":1667823209000},"page":"600-610","source":"Crossref","is-referenced-by-count":6,"title":["Value of Presurgical\n                    <sup>18<\/sup>\n                    F-FDG PET\/CT Radiomics for Predicting Mediastinal Lymph Node Metastasis in Patients with Lung Adenocarcinoma"],"prefix":"10.1177","volume":"39","author":[{"given":"Meng","family":"Dai","sequence":"first","affiliation":[{"name":"Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China."},{"name":"Hebei Provincial Key Laboratory of Tumor Microenvironment and Drug Resistance, Shijiazhuang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Na","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China."},{"name":"Hebei Provincial Key Laboratory of Tumor Microenvironment and Drug Resistance, Shijiazhuang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7060-2643","authenticated-orcid":false,"given":"Xinming","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China."},{"name":"Hebei Provincial Key Laboratory of Tumor Microenvironment and Drug Resistance, Shijiazhuang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianyuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Baoding No. 1 Central Hospital, Baoding, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhaoqi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingmian","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianfang","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujing","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Hebei General Hospital, Shijiazhuang, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 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