{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T00:15:28Z","timestamp":1783556128094,"version":"3.55.0"},"reference-count":35,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T00:00:00Z","timestamp":1769558400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Can Assoc Radiol J"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Reduced field-of-view (rFOV) T2WI improves in-plane spatial resolution. Deep learning-based reconstruction (DLR) has emerged as enhancing image quality. We compared examination time, image quality, and lesion detection rates between pancreaticobiliary rFOV T2WI with and without DLR.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>\n                      198 patients who underwent pancreaticobiliary rFOV T2WI were included. The protocol included rFOV T2WI with 2 NEX (rFOV T2WI\n                      <jats:sub>N2<\/jats:sub>\n                      ) and 1 NEX (rFOV T2WI\n                      <jats:sub>N1<\/jats:sub>\n                      ). DLR was applied to generate corresponding datasets: rFOV T2WI\n                      <jats:sub>N2-DLR<\/jats:sub>\n                      and rFOV T2WI\n                      <jats:sub>N1-DLR<\/jats:sub>\n                      datasets. Three observers evaluated the noise, respiratory motion artifacts (RMA), overall image quality (OIQ), and diagnostic confidence (DC). Two observers measured the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Image quality metrics were compared using either ANOVA or Friedman test. Lesion detection rates were tested using the Cochran\u2019s Q test and McNemar test.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      The noise, RMA, OIQ, and DC scores of rFOV T2WI\n                      <jats:sub>N1-DLR<\/jats:sub>\n                      were notably higher than those of rFOV T2WI\n                      <jats:sub>N1<\/jats:sub>\n                      . The noise, OIQ, and DC scores of rFOV T2WI\n                      <jats:sub>N2<\/jats:sub>\n                      were notably higher than those of rFOV T2WI\n                      <jats:sub>N1<\/jats:sub>\n                      (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      \u2009&lt;\u2009.001). The SNR and CNR of rFOV T2WI with DLR were notably higher than those of rFOV T2WI without DLR (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      \u2009&lt;\u2009.05). The rFOV T2WI\n                      <jats:sub>N1-DLR<\/jats:sub>\n                      sequence yielded a higher lesion detection rate (92.5%; 491\/531) compared to rFOV T2WI\n                      <jats:sub>N1<\/jats:sub>\n                      (76.5%; 406\/531).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>Pancreaticobiliary rFOV T2WI with DLR is feasible and yields superior image quality compared to rFOV T2WI without DLR. A 37.1% to 74.4% reduction in acquisition time is achievable without increasing image noise or compromising overall image quality and lesion detection rate.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Relevance Statement:<\/jats:title>\n                    <jats:p>The perfect balance of image quality, scanning time, and lesion detection rate can be achieved by using DLR in pancreaticobiliary rFOV T2WI.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/08465371251407889","type":"journal-article","created":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T11:08:44Z","timestamp":1769598524000},"page":"478-489","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Accelerated Reduced Field of View T2-Weighted Imaging of Pancreaticobiliary Disorders Using Deep Learning-Based Reconstruction: Reduction of Acquisition Time and Improvement of Image Quality"],"prefix":"10.1177","volume":"77","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-0225-2436","authenticated-orcid":false,"given":"Nan","family":"Wang","sequence":"first","affiliation":[{"name":"The First Affiliated Hospital of Dalian Medical University, Liaoning, China"},{"name":"Technology Innovation Center of Hyperpolarized MRI, Dalian, Liaoning, China"},{"name":"Technology Innovation Center of Artificial Intelligence in Medical Imaging, Dalian, Liaoning, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miaotong","family":"Liu","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Dalian Medical University, Liaoning, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenhui","family":"Wang","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Dalian Medical University, Liaoning, China"},{"name":"Technology Innovation Center of Hyperpolarized MRI, Dalian, Liaoning, China"},{"name":"Technology Innovation Center of Artificial Intelligence in Medical Imaging, Dalian, Liaoning, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Zhao","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Dalian Medical University, Liaoning, China"},{"name":"Technology Innovation Center of Hyperpolarized MRI, Dalian, Liaoning, China"},{"name":"Technology Innovation Center of Artificial Intelligence in Medical Imaging, Dalian, Liaoning, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Li","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Dalian Medical University, Liaoning, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xue","family":"Ren","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Dalian Medical University, Liaoning, China"},{"name":"Technology Innovation Center of Hyperpolarized MRI, Dalian, Liaoning, China"},{"name":"Technology Innovation Center of Artificial Intelligence in Medical Imaging, Dalian, Liaoning, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Yu","sequence":"additional","affiliation":[{"name":"United Imaging Research Institute of Intelligent Imaging, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ailian","family":"Liu","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Dalian Medical University, Liaoning, China"},{"name":"Technology Innovation Center of Hyperpolarized MRI, Dalian, Liaoning, China"},{"name":"Technology Innovation Center of Artificial Intelligence in Medical Imaging, Dalian, Liaoning, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiukun","family":"Hou","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Dalian Medical University, Liaoning, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7035-7211","authenticated-orcid":false,"given":"Qingwei","family":"Song","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Dalian Medical University, Liaoning, China"},{"name":"Technology Innovation Center of Hyperpolarized MRI, Dalian, Liaoning, China"},{"name":"Technology Innovation Center of Artificial Intelligence in Medical Imaging, Dalian, Liaoning, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,1,28]]},"reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11604-020-00940-6"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.mric.2015.11.010"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.mric.2022.04.009"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.25250"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.2463\/mrms.mp.2024-0017"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2022.04.005"},{"key":"e_1_3_4_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2024.111737"},{"key":"e_1_3_4_9_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-023-09470-x"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.3389\/fvets.2023.1251535"},{"key":"e_1_3_4_11_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-023-09693-y"},{"key":"e_1_3_4_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.diii.2022.05.001"},{"key":"e_1_3_4_13_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13244-025-02022-5"},{"key":"e_1_3_4_14_2","doi-asserted-by":"publisher","DOI":"10.1097\/RLI.0000000000001110"},{"key":"e_1_3_4_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.diii.2024.09.008"},{"key":"e_1_3_4_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.diii.2022.06.006"},{"key":"e_1_3_4_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2022.06.003"},{"key":"e_1_3_4_18_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-022-09227-y"},{"key":"e_1_3_4_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2021.109994"},{"key":"e_1_3_4_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.diii.2022.11.002"},{"key":"e_1_3_4_21_2","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.29380"},{"key":"e_1_3_4_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2022.110428"},{"key":"e_1_3_4_23_2","doi-asserted-by":"publisher","DOI":"10.4329\/wjr.v15.i12.338"},{"key":"e_1_3_4_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.dld.2024.03.005"},{"key":"e_1_3_4_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.crad.2017.07.009"},{"key":"e_1_3_4_26_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinimag.2018.12.001"},{"key":"e_1_3_4_27_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12880-021-00679-0"},{"key":"e_1_3_4_28_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.diii.2024.12.003"},{"key":"e_1_3_4_29_2","doi-asserted-by":"publisher","DOI":"10.1097\/RCT.0000000000001451"},{"key":"e_1_3_4_30_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2022.08.012"},{"key":"e_1_3_4_31_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00261-021-03290-7"},{"key":"e_1_3_4_32_2","doi-asserted-by":"publisher","DOI":"10.3390\/cancers13143593"},{"key":"e_1_3_4_33_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2021.109600"},{"key":"e_1_3_4_34_2","doi-asserted-by":"publisher","DOI":"10.1186\/s41747-024-00506-5"},{"key":"e_1_3_4_35_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-021-08008-3"},{"key":"e_1_3_4_36_2","doi-asserted-by":"publisher","DOI":"10.1186\/s41747-023-00377-2"}],"container-title":["Canadian Association of Radiologists Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/08465371251407889","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/08465371251407889","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/08465371251407889","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T23:21:51Z","timestamp":1783552911000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/08465371251407889"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,28]]},"references-count":35,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["10.1177\/08465371251407889"],"URL":"https:\/\/doi.org\/10.1177\/08465371251407889","relation":{},"ISSN":["0846-5371","1488-2361"],"issn-type":[{"value":"0846-5371","type":"print"},{"value":"1488-2361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,28]]}}}