{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T02:42:22Z","timestamp":1785552142632,"version":"3.56.0"},"reference-count":24,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.mri.2026.110726","type":"journal-article","created":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T23:59:42Z","timestamp":1780963182000},"page":"110726","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["3-dimensional gradient and spin-echo magnetic resonance cholangiopancreatography with deep learning reconstruction at 3T: Achieving superior image quality with reduced acquisition time"],"prefix":"10.1016","volume":"133","author":[{"given":"Kumi","family":"Ozaki","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takafumi","family":"Iyoda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eri","family":"Sugioka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jihun","family":"Kwon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yasutomo","family":"Katsumata","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yukichi","family":"Tanahashi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Satoshi","family":"Goshima","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.mri.2026.110726_bb0005","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/j.mric.2007.06.009","article-title":"MR cholangiopancreatography: 1.5T versus 3T","volume":"15","author":"Schindera","year":"2007","journal-title":"Magn Reson Imaging Clin N Am"},{"key":"10.1016\/j.mri.2026.110726_bb0010","doi-asserted-by":"crossref","first-page":"1781","DOI":"10.1111\/j.1572-0241.2007.01279.x","article-title":"Incidence rates of post-ERCP complications: a systematic survey of prospective studies","volume":"102","author":"Andriulli","year":"2007","journal-title":"Am J Gastroenterol"},{"key":"10.1016\/j.mri.2026.110726_bb0015","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1148\/radiol.2493080389","article-title":"Possible biliary disease: diagnostic performance of high-spatial-resolution isotropic 3D T2-weighted MRCP","volume":"249","author":"Nandalur","year":"2008","journal-title":"Radiology"},{"key":"10.1016\/j.mri.2026.110726_bb0020","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1016\/j.mric.2008.04.005","article-title":"Magnetic resonance cholangiopancreatography: techniques and applications","volume":"16","author":"Anupindi","year":"2008","journal-title":"Magn Reson Imaging Clin N Am"},{"key":"10.1016\/j.mri.2026.110726_bb0025","doi-asserted-by":"crossref","first-page":"1597","DOI":"10.3348\/kjr.2018.0931","article-title":"Rapid imaging: recent advances in abdominal MRI for reducing acquisition time and its clinical applications","volume":"20","author":"Yoon","year":"2019","journal-title":"Korean J Radiol"},{"key":"10.1016\/j.mri.2026.110726_bb0030","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1007\/s00261-019-02342-3","article-title":"Rapid 3D navigator-triggered MR cholangiopancreatography with SPACE sequence at 3T: only one-third acquisition time of conventional 3D SPACE navigator-triggered MRCP","volume":"45","author":"Sun","year":"2020","journal-title":"Abdom Radiol"},{"key":"10.1016\/j.mri.2026.110726_bb0035","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.2214\/AJR.19.21399","article-title":"Three-dimensional breath-hold MRCP using SPACE pulse sequence at 3 T: comparison with conventional navigator-triggered technique","volume":"213","author":"Chen","year":"2019","journal-title":"AJR Am J Roentgenol"},{"key":"10.1016\/j.mri.2026.110726_bb0040","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1148\/radiol.2016151935","article-title":"Three-dimensional MR cholangiopancreatography in a breath hold with sparsity-based reconstruction of highly undersampled data","volume":"280","author":"Chandarana","year":"2016","journal-title":"Radiology"},{"key":"10.1016\/j.mri.2026.110726_bb0045","doi-asserted-by":"crossref","first-page":"966","DOI":"10.1002\/jmri.25547","article-title":"Compressed sensing for body MRI","volume":"45","author":"Feng","year":"2017","journal-title":"J Magn Reson Imaging"},{"key":"10.1016\/j.mri.2026.110726_bb0050","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1097\/RLI.0000000000000380","article-title":"Clinical feasibility of 3-dimensional magnetic resonance cholangiopancreatography using compressed sensing: comparison of image quality and diagnostic performance","volume":"52","author":"Yoon","year":"2017","journal-title":"Investig Radiol"},{"key":"10.1016\/j.mri.2026.110726_bb0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejrad.2021.109873","article-title":"Comparison of respiratory-triggered 3D MR cholangiopancreatography and breath-hold compressed-sensing 3D MR cholangiopancreatography at 1.5 T and 3 T and impact of individual factors on image quality","volume":"142","author":"Blaise","year":"2021","journal-title":"Eur J Radiol"},{"key":"10.1016\/j.mri.2026.110726_bb0060","doi-asserted-by":"crossref","first-page":"6014","DOI":"10.1007\/s00330-020-06996-2","article-title":"Magnetic resonance cholangiopancreatography with compressed sensing at 1.5 T: clinical application for the evaluation of branch duct IPMN of the pancreas","volume":"30","author":"Henninger","year":"2020","journal-title":"Eur Radiol"},{"key":"10.1016\/j.mri.2026.110726_bb0065","doi-asserted-by":"crossref","first-page":"2436","DOI":"10.1007\/s00330-017-5240-y","article-title":"Magnetic resonance cholangiopancreatography with GRASE sequence at 3.0T: does it improve image quality and acquisition time as compared with 3D TSE?","volume":"28","author":"Yoshida","year":"2018","journal-title":"Eur Radiol"},{"key":"10.1016\/j.mri.2026.110726_bb0070","doi-asserted-by":"crossref","first-page":"3721","DOI":"10.1007\/s00330-017-5275-0","article-title":"GRASE revisited: breath-hold three-dimensional (3D) magnetic resonance cholangiopancreatography using a gradient and spin Echo (GRASE) technique at 3T","volume":"28","author":"Nam","year":"2018","journal-title":"Eur Radiol"},{"key":"10.1016\/j.mri.2026.110726_bb0075","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.21037\/qims.2020.04.14","article-title":"Magnetic resonance cholangiopancreatography at 3T in a single breath-hold: comparative effectiveness between three-dimensional (3D) gradient- and spin-echo and two-dimensional (2D) thick-slab fast spin-echo acquisitions","volume":"10","author":"Chien","year":"2020","journal-title":"Quant Imag Med Surg"},{"key":"10.1016\/j.mri.2026.110726_bb0080","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejrad.2021.109994","article-title":"Breath-hold 3D magnetic resonance cholangiopancreatography at 1.5 T using a deep learning-based noise-reduction approach: comparison with the conventional respiratory-triggered technique","volume":"144","author":"Tajima","year":"2021","journal-title":"Eur J Radiol"},{"key":"10.1016\/j.mri.2026.110726_bb0085","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejrad.2021.109833","article-title":"Comparing compressed sensing breath-hold 3D MR cholangiopancreatography with two parallel imaging MRCP strategies in main pancreatic duct and common bile duct","volume":"142","author":"Chen","year":"2021","journal-title":"Eur J Radiol"},{"key":"10.1016\/j.mri.2026.110726_bb0090","doi-asserted-by":"crossref","first-page":"2500","DOI":"10.1007\/s00330-022-09227-y","article-title":"Rapid 3D breath-hold MR cholangiopancreatography using deep learning-constrained compressed sensing reconstruction","volume":"33","author":"Zhang","year":"2023","journal-title":"Eur Radiol"},{"key":"10.1016\/j.mri.2026.110726_bb0095","doi-asserted-by":"crossref","first-page":"204825","DOI":"10.1109\/ACCESS.2020.3034287","article-title":"An adaptive intelligence algorithm for undersampled knee MRI reconstruction: application to the 2019 fastMRI Challenge","volume":"8","author":"Pezzotti","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.mri.2026.110726_bb0100","series-title":"Adaptive-CS-Net: FastMRI with Adaptive Intelligence","author":"Pezzotti","year":"2019"},{"key":"10.1016\/j.mri.2026.110726_bb0105","series-title":"Medical image computing and computer-assisted intervention \u2013 MICCAI 2015","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.mri.2026.110726_bb0110","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1109\/MSP.2019.2950640","article-title":"Deep-learning methods for parallel magnetic resonance imaging reconstruction: a survey of the current approaches, trends, and issues","volume":"37","author":"Knoll","year":"2020","journal-title":"IEEE Signal Process Mag"},{"key":"10.1016\/j.mri.2026.110726_bb0115","doi-asserted-by":"crossref","first-page":"1014","DOI":"10.1002\/jmri.24033","article-title":"Usefulness of the SPACE pulse sequence at 1.5T MR cholangiography: comparison of image quality and image acquisition time with conventional 3D-TSE sequence","volume":"38","author":"Nakaura","year":"2013","journal-title":"J Magn Reson Imaging"},{"key":"10.1016\/j.mri.2026.110726_bb0120","doi-asserted-by":"crossref","first-page":"159","DOI":"10.2307\/2529310","article-title":"The measurement of observer agreement for categorical data","volume":"33","author":"Landis","year":"1977","journal-title":"Biometrics"}],"container-title":["Magnetic Resonance Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0730725X26001190?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0730725X26001190?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T11:25:33Z","timestamp":1785497133000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0730725X26001190"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":24,"alternative-id":["S0730725X26001190"],"URL":"https:\/\/doi.org\/10.1016\/j.mri.2026.110726","relation":{},"ISSN":["0730-725X"],"issn-type":[{"value":"0730-725X","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"3-dimensional gradient and spin-echo magnetic resonance cholangiopancreatography with deep learning reconstruction at 3T: Achieving superior image quality with reduced acquisition time","name":"articletitle","label":"Article Title"},{"value":"Magnetic Resonance Imaging","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.mri.2026.110726","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"110726"}}