{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T11:25:21Z","timestamp":1787311521130,"version":"build-2736575974"},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2025,4,17]],"date-time":"2025-04-17T00:00:00Z","timestamp":1744848000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,4,17]],"date-time":"2025-04-17T00:00:00Z","timestamp":1744848000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Abdom Radiol"],"DOI":"10.1007\/s00261-025-04950-8","type":"journal-article","created":{"date-parts":[[2025,4,17]],"date-time":"2025-04-17T00:30:45Z","timestamp":1744849845000},"page":"5079-5089","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["DWI of the rectum with deep learning reconstruction: comparison of PROPELLER, reduced FOV, and conventional DWI."],"prefix":"10.1007","volume":"50","author":[{"given":"Shohei","family":"Matsumoto","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takahiro","family":"Tsuboyama","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hiromitsu","family":"Onishi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Koki","family":"Kaketaka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tetsuya","family":"Wakayama","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinzeng","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Atsushi","family":"Nakamoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takashi","family":"Ota","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hideyuki","family":"Fukui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Toru","family":"Honda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kengo","family":"Kiso","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Koji","family":"Oba","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Noriyuki","family":"Tomiyama","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,4,17]]},"reference":[{"key":"4950_CR1","doi-asserted-by":"publisher","first-page":"2893","DOI":"10.1007\/s00261-018-1642-9","volume":"43","author":"MJ Gollub","year":"2018","unstructured":"Gollub MJ, Arya S, Beets-Tan RG, et al (2018) Use of magnetic resonance imaging in rectal cancer patients: Society of Abdominal Radiology (SAR) rectal cancer disease-focused panel (DFP) recommendations 2017. Abdominal Radiology 43:2893\u20132902. https:\/\/doi.org\/10.1007\/s00261-018-1642-9","journal-title":"Abdominal Radiology"},{"key":"4950_CR2","doi-asserted-by":"publisher","first-page":"1003","DOI":"10.3348\/kjr.2018.0611","volume":"20","author":"N Seo","year":"2019","unstructured":"Seo N, Kim H, Cho MS, Lim JS (2019) Response Assessment with MRI after Chemoradiotherapy in Rectal Cancer: Current Evidences. Korean J Radiol 20:1003\u20131018. https:\/\/doi.org\/10.3348\/kjr.2018.0611.","journal-title":"Korean J Radiol"},{"key":"4950_CR3","doi-asserted-by":"publisher","first-page":"3674","DOI":"10.1007\/s00261-019-02139-4","volume":"44","author":"R Fornell-Perez","year":"2019","unstructured":"Fornell-Perez R, Perez-Alonso E, Porcel-de-Peralta G, et al (2019) Primary and post-chemoradiotherapy staging using MRI in rectal cancer: the role of diffusion imaging in the assessment of perirectal infiltration. Abdominal Radiology 44:3674\u20133682. https:\/\/doi.org\/10.1007\/s00261-019-02139-4.","journal-title":"Abdominal Radiology"},{"key":"4950_CR4","doi-asserted-by":"publisher","first-page":"e230079","DOI":"10.1148\/RADIOL.230079","volume":"308","author":"TH Kim","year":"2023","unstructured":"Kim TH, Firat C, Thompson HM, et al (2023) Extramural Venous Invasion and Tumor Deposit at Diffusion-weighted MRI in Patients after Neoadjuvant Treatment for Rectal Cancer. Radiology 308:e230079. https:\/\/doi.org\/10.1148\/RADIOL.230079.","journal-title":"Radiology"},{"key":"4950_CR5","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/j.ejrad.2017.12.020","volume":"99","author":"JJM van Griethuysen","year":"2018","unstructured":"van Griethuysen JJM, Bus EM, Hauptmann M, Lahaye MJ, Maas M, ter Beek LC, Beets GL, Bakers FCH, Beets-Tan RGH, Lambregts DMJ (2018) Gas-induced susceptibility artefacts on diffusion-weighted MRI of the rectum at 1.5 T - Effect of applying a micro-enema to improve image quality. Eur J Radiol 99:131\u2013137. https:\/\/doi.org\/10.1016\/j.ejrad.2017.12.020.","journal-title":"Eur J Radiol"},{"key":"4950_CR6","doi-asserted-by":"publisher","first-page":"1192","DOI":"10.1007\/s11547-023-01699-2","volume":"128","author":"A Inoue","year":"2023","unstructured":"Inoue A, Tanabe M, Ihara K, et al (2023) Evaluation of diffusion-weighted magnetic resonance imaging of the rectal cancers: comparison between modified reduced field-of-view single-shot echo-planar imaging with tilted two-dimensional radiofrequency excitation pulses and conventional full field-of-view readout-segmented echo-planar imaging. Radiologia Medica 128:1192\u20131198. https:\/\/doi.org\/10.1007\/s11547-023-01699-2.","journal-title":"Radiologia Medica"},{"key":"4950_CR7","doi-asserted-by":"publisher","first-page":"5225","DOI":"10.1007\/s00330-017-4922-9","volume":"27","author":"T Ota","year":"2017","unstructured":"Ota T, Hori M, Onishi H, Sakane M, Tsuboyama T, Tatsumi M, Nakamoto A, Kimura T, Narumi Y, Tomiyama N (2017) Preoperative staging of endometrial cancer using reduced field-of-view diffusion-weighted imaging: a preliminary study. Eur Radiol 27:5225\u20135235. https:\/\/doi.org\/10.1007\/s00330-017-4922-9.","journal-title":"Eur Radiol"},{"key":"4950_CR8","doi-asserted-by":"publisher","first-page":"656","DOI":"10.1097\/RLI.0b013e3181af3f0e","volume":"44","author":"UI Attenberger","year":"2009","unstructured":"Attenberger UI, Runge VM, Stemmer A, Williams KD, Naul LG, Michaely HJ, Schoenberg SO, Reiser MF, Wintersperger BJ (2009) Diffusion weighted imaging: a comprehensive evaluation of a fast spin echo DWI sequence with BLADE (PROPELLER) k-space sampling at 3 T, using a 32-channel head coil in acute brain ischemia. Invest Radiol 44:656\u201361. https:\/\/doi.org\/10.1097\/RLI.0b013e3181af3f0e.","journal-title":"Invest Radiol"},{"key":"4950_CR9","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1097\/RLI.0000000000000248","volume":"51","author":"I Kida","year":"2016","unstructured":"Kida I, Ueguchi T, Matsuoka Y, Zhou K, Stemmer A, Porter D (2016) Comparison of Diffusion-Weighted Imaging in the Human Brain Using Readout-Segmented EPI and PROPELLER Turbo Spin Echo With Single-Shot EPI at 7 T MRI. Invest Radiol 51:435\u20139. https:\/\/doi.org\/10.1097\/RLI.0000000000000248.","journal-title":"Invest Radiol"},{"key":"4950_CR10","doi-asserted-by":"publisher","first-page":"1352","DOI":"10.2214\/AJR.17.18796","volume":"210","author":"TH Kim","year":"2018","unstructured":"Kim TH, Baek MY, Park JE, Ryu YJ, Cheon JE, Kim IO, Choi YH (2018) Comparison of DWI Methods in the Pediatric Brain: PROPELLER Turbo Spin-Echo Imaging Versus Readout-Segmented Echo-Planar Imaging Versus Single-Shot Echo-Planar Imaging. American Journal of Roentgenology 210:1352\u20131358. https:\/\/doi.org\/10.2214\/AJR.17.18796.","journal-title":"American Journal of Roentgenology"},{"key":"4950_CR11","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1016\/j.ejrad.2018.03.021","volume":"102","author":"M Czarniecki","year":"2018","unstructured":"Czarniecki M, Caglic I, Grist JT, Gill AB, Lorenc K, Slough RA, Priest AN, Barrett T (2018) Role of PROPELLER-DWI of the prostate in reducing distortion and artefact from total hip replacement metalwork. Eur J Radiol 102:213\u2013219. https:\/\/doi.org\/10.1016\/j.ejrad.2018.03.021.","journal-title":"Eur J Radiol"},{"key":"4950_CR12","doi-asserted-by":"publisher","first-page":"1275","DOI":"10.1007\/s11547-024-01861-4","volume":"129","author":"T Tsuboyama","year":"2024","unstructured":"Tsuboyama T, Yanagawa M, Fujioka T, et al (2024) Recent trends in AI applications for pelvic MRI: a comprehensive review. Radiologia Medica 129:1275\u20131287. https:\/\/doi.org\/10.1007\/s11547-024-01861-4.","journal-title":"Radiologia Medica"},{"key":"4950_CR13","doi-asserted-by":"publisher","first-page":"479","DOI":"10.1097\/rli.0000000000001047","volume":"59","author":"S Matsumoto","year":"2024","unstructured":"Matsumoto S, Tsuboyama T, Onishi H, et al (2024) Ultra-High-Resolution T2-Weighted PROPELLER MRI of the Rectum With Deep Learning Reconstruction: Assessment of Image Quality and Diagnostic Performance. Invest Radiol 59:479\u2013488. https:\/\/doi.org\/10.1097\/rli.0000000000001047.","journal-title":"Invest Radiol"},{"key":"4950_CR14","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1007\/s00261-022-03701-3","volume":"48","author":"B Kim","year":"2023","unstructured":"Kim B, Lee C min, Jang JK, Kim J, Lim SB, Kim AY (2023) Deep learning-based imaging reconstruction for MRI after neoadjuvant chemoradiotherapy for rectal cancer: effects on image quality and assessment of treatment response. Abdominal Radiology 48:201\u2013210. https:\/\/doi.org\/10.1007\/s00261-022-03701-3.","journal-title":"Abdominal Radiology"},{"key":"4950_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2024.111802","author":"I Petkovska","year":"2024","unstructured":"Petkovska I, Alus O, Rodriguez L, El Homsi M, Golia Pernicka JS, Fernandes MC, Zheng J, Capanu M, Otazo R (2024) Clinical evaluation of accelerated diffusion-weighted imaging of rectal cancer using a denoising neural network. Eur J Radiol. https:\/\/doi.org\/10.1016\/j.ejrad.2024.111802","journal-title":"Eur J Radiol"},{"key":"4950_CR16","doi-asserted-by":"publisher","first-page":"1615","DOI":"10.1007\/s00261-024-04280-1","volume":"49","author":"X Zhang","year":"2024","unstructured":"Zhang X, Wang Y, Xu X, Zhang J, Sun Y, Hu M, Wang S, Li Y, Chen Y, Zhao X (2024) Bladder MRI with deep learning-based reconstruction: a prospective evaluation of muscle invasiveness using VI-RADS. Abdominal Radiology 49:1615\u20131625. https:\/\/doi.org\/10.1007\/s00261-024-04280-1.","journal-title":"Abdominal Radiology"},{"key":"4950_CR17","doi-asserted-by":"publisher","first-page":"2921","DOI":"10.1007\/s00261-024-04256-1","volume":"49","author":"SJ Riederer","year":"2024","unstructured":"Riederer SJ, Borisch EA, Froemming AT, Kawashima A, Takahashi N (2024) Comparison of model-based versus deep learning-based image reconstruction for thin-slice T2-weighted spin-echo prostate MRI. Abdominal Radiology 49:2921\u20132931. https:\/\/doi.org\/10.1007\/s00261-024-04256-1.","journal-title":"Abdominal Radiology"},{"key":"4950_CR18","unstructured":"Lebel RM (2020) Performance characterization of a novel deep learning-based MR image reconstruction pipeline. https:\/\/arxiv.org\/pdf\/2008.06559 (accessed February 17, 2025)."},{"key":"4950_CR19","unstructured":"Wang X, Peters RD, Steve Lawson, Yuko Snow (2022) AIR\u2122 Recon DL PROPELLER for motion-insensitive and distortion-free imaging. https:\/\/signapulse.gehealthcare.com\/autumn-2022\/ge-air-recon-dl-imaging-technology-benefits (accessed February 17, 2025)."},{"issue":"3","key":"4950_CR20","doi-asserted-by":"publisher","first-page":"638","DOI":"10.1148\/radiol.2453062151","volume":"245","author":"JT Heverhagen","year":"2007","unstructured":"Heverhagen JT (2007) Noise measurement and estimation in MR imaging experiments. Radiology 245(3):638\u2013639. doi: https:\/\/doi.org\/10.1148\/radiol.2453062151.","journal-title":"Radiology"},{"key":"4950_CR21","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1186\/s12885-015-1632-z","volume":"15","author":"JJ Smith","year":"2015","unstructured":"Smith JJ, Chow OS, Gollub MJ, Nash GM, Temple LK, Weiser MR, Guillem JG, Paty PB, Avila K, Garcia-Aguilar J (2015) Organ Preservation in Rectal Adenocarcinoma: a phase II randomized controlled trial evaluating 3-year disease-free survival in patients with locally advanced rectal cancer treated with chemoradiation plus induction or consolidation chemotherapy, and total mesorectal excision or nonoperative management. BMC Cancer 15:767. https:\/\/doi.org\/10.1186\/s12885-015-1632-z.","journal-title":"BMC Cancer"},{"key":"4950_CR22","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1159\/000515631","volume":"40","author":"A Surov","year":"2022","unstructured":"Surov A, Pech M, Powerski M, Woidacki K, Wienke A (2022) Pretreatment Apparent Diffusion Coefficient Cannot Predict Histopathological Features and Response to Neoadjuvant Radiochemotherapy in Rectal Cancer: A Meta-Analysis. Digestive Diseases 40:33\u201349. https:\/\/doi.org\/10.1159\/000515631.","journal-title":"Digestive Diseases"}],"container-title":["Abdominal Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00261-025-04950-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00261-025-04950-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00261-025-04950-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T18:11:03Z","timestamp":1761847863000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00261-025-04950-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,17]]},"references-count":22,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2025,11]]}},"alternative-id":["4950"],"URL":"https:\/\/doi.org\/10.1007\/s00261-025-04950-8","relation":{},"ISSN":["2366-0058"],"issn-type":[{"value":"2366-0058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,17]]},"assertion":[{"value":"18 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 April 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 April 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 April 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Institution (Department of Radiology, Osaka University graduate school of medicine and Osaka University hospital) received support from GE Healthcare for equipment related to this study, and payment for travel to meetings or other activities not related to this study. Two of the authors are employees of GE Healthcare.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}