{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,28]],"date-time":"2026-06-28T06:45:02Z","timestamp":1782629102407,"version":"3.54.5"},"reference-count":33,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T00:00:00Z","timestamp":1775520000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"crossref","award":["RS-2023-00241409"],"award-info":[{"award-number":["RS-2023-00241409"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Thyroid\u00ae"],"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Hybrid single-photon emission computed tomography (SPECT)\/computed tomography (CT) is used for the differential diagnosis of thyrotoxicosis, but its dependence on CT and complex analysis remains debated. This study evaluated whether CT-free thyroid SPECT using artificial intelligence (AI) could substitute for conventional SPECT\/CT.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>This prospective multicenter noninferiority clinical trial (KCT0008387) included 152 patients with thyrotoxicosis from three tertiary referral hospitals. A pretrained AI model generated technetium thyroid uptake (TcTU) values using SPECT images without CT. These values were compared with TcTU derived from conventional SPECT\/CT. The primary endpoint was diagnostic accuracy for Graves\u2019 disease. Noninferiority was defined as a lower confidence interval (CI) limit greater than \u221210%. Secondary endpoints included diagnostic accuracy for destructive thyroiditis and prediction of antithyroid drug (ATD) prescription within one month.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Among 152 patients, 84 had Graves\u2019 disease, 45 had indeterminate disease, and 23 had thyroiditis. For Graves\u2019 disease, CT-free SPECT demonstrated 86.2% accuracy compared with 85.5% for conventional SPECT\/CT. The lower bound of the CI of the accuracy difference was \u22123.0%, meeting the prespecified noninferiority margin. For thyroiditis and ATD prescription, the lower bounds were \u22127.4% and \u22123.2%, respectively. Omission of CT resulted in a 33.5% reduction of radiation exposure from 3.34 mSv to 2.22 mSv, and CT-free SPECT automatically generated TcTU values more quickly than SPECT\/CT (40 minutes vs. 4 minutes).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>CT-free SPECT using AI demonstrated noninferior diagnostic performance for thyrotoxicosis compared with conventional hybrid imaging while reducing radiation exposure and analysis time.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial Registration:<\/jats:title>\n                    <jats:p>\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/cris.nih.go.kr\">https:\/\/cris.nih.go.kr<\/jats:ext-link>\n                      (KCT0008387).\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/10507256261440401","type":"journal-article","created":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T09:36:18Z","timestamp":1775554578000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["CT-Free Quantitative Thyroid SPECT Based on Artificial Intelligence: A Prospective Multicenter Noninferiority Clinical Trial"],"prefix":"10.1177","author":[{"given":"Hyun Woo","family":"Chung","sequence":"first","affiliation":[{"name":"Department of Nuclear Medicine, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Republic of Korea."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sang-Geon","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Chonnam National University Hospital and Medical School, Gwangju, Republic of 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of Korea."},{"name":"Institute of Radiation Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea."},{"name":"Department of Health Science and Technology, The Graduate School of Convergence Science and Technology, Seoul National University, Suwon, Republic of Korea."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"on behalf of K-SPECT 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