{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T14:01:25Z","timestamp":1787752885827,"version":"build-2784847793"},"reference-count":33,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2017,4,17]],"date-time":"2017-04-17T00:00:00Z","timestamp":1492387200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81371608"],"award-info":[{"award-number":["81371608"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2017,12]]},"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>To evaluate the diagnostic performance of biphasic contrast\u2010enhanced CT (CECT), volume perfusion CT (VPCT) and 3 Tesla MRI with diffusion\u2010weighted imaging (DWI), in patients with clinically suspected insulinomas.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods<\/jats:title><jats:p>This prospective study was approved by the institutional review board. Sixty\u2010four patients with clinically suspected insulinomas underwent biphasic CECT, VPCT, and 3T MR with DWI. Two radiologists independently determined the presence\/absence of tumor using a 5\u2010scale confidence level. Conspicuity of the lesion and clarity of tumor\u2010to\u2010pancreatic duct distance were graded. Receiver operating characteristic analysis was performed to compare diagnostic performance.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Forty\u2010seven patients were tumor positive, with 51 tumors. The differences between the areas under the curve values for tumor detection were as follows: 0.715 (CECT), 0.903 (VPCT), 0.832 (MRI without DWI) and 0.955 (MRI with DWI) for reader 1, and 0.738 (CECT), 0.895 (VPCT), 0.841 (MRI without DWI), and 0.956 (MRI with DWI) for reader 2. MRI with DWI and VPCT were significantly more accurate than CECT for insulinoma detection (<jats:italic>P<\/jats:italic>\u2009=\u20090.01 and 0.02 for reader 1, and <jats:italic>P<\/jats:italic>\u2009=\u20090.01 and 0.03 for reader 2). Lesion conspicuity was better on MRI compared with VPCT (<jats:italic>P<\/jats:italic>\u2009=\u20090.01), and both were better than CECT (both <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.01). Tumor\u2010to\u2010pancreatic duct distance was better appreciated on MRI, compared with CECT and VPCT (both <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.01). The weighted k values indicate good to excellent agreement between observers for determining tumor presence\/absence (k\u2009=\u20090.64\u20130.84).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The 3T MRI with DWI and VPCT are significantly more accurate than CECT for insulinoma detection. MRI demonstrates higher tumor conspicuity and is superior in depicting the tumor\u2010to\u2010duct distance.<\/jats:p><jats:p><jats:bold>Level of Evidence:<\/jats:bold> 1<\/jats:p><jats:p><jats:bold>Technical Efficacy:<\/jats:bold> Stage 3<\/jats:p><jats:p>J. Magn. Reson. Imaging 2017;46:1648\u20131655.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.25709","type":"journal-article","created":{"date-parts":[[2017,4,17]],"date-time":"2017-04-17T15:22:38Z","timestamp":1492442558000},"page":"1648-1655","source":"Crossref","is-referenced-by-count":38,"title":["Prospective comparison of biphasic contrast\u2010enhanced CT, volume perfusion CT, and 3 Tesla MRI with diffusion\u2010weighted imaging for insulinoma detection"],"prefix":"10.1002","volume":"46","author":[{"given":"Liang","family":"Zhu","sequence":"first","affiliation":[{"name":"Department of Radiology Peking Union Medical College Hospital Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huadan","family":"Xue","sequence":"additional","affiliation":[{"name":"Department of Radiology Peking Union Medical College Hospital Beijing 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