{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T11:44:40Z","timestamp":1783338280737,"version":"3.54.6"},"reference-count":95,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2024,5,28]],"date-time":"2024-05-28T00:00:00Z","timestamp":1716854400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,5,28]],"date-time":"2024-05-28T00:00:00Z","timestamp":1716854400000},"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\/s00261-024-04369-7","type":"journal-article","created":{"date-parts":[[2024,5,28]],"date-time":"2024-05-28T03:54:29Z","timestamp":1716868469000},"page":"3615-3636","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Advanced MRI techniques in abdominal imaging"],"prefix":"10.1007","volume":"49","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5266-4322","authenticated-orcid":false,"given":"Yoonhee","family":"Lee","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7030-841X","authenticated-orcid":false,"given":"Sungjin","family":"Yoon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9198-775X","authenticated-orcid":false,"given":"Munyoung","family":"Paek","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1402-5036","authenticated-orcid":false,"given":"Dongyeob","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5962-4772","authenticated-orcid":false,"given":"Moon Hyung","family":"Choi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9935-2863","authenticated-orcid":false,"given":"So Hyun","family":"Park","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,28]]},"reference":[{"key":"4369_CR1","doi-asserted-by":"publisher","first-page":"887","DOI":"10.1002\/jmri.24850","volume":"42","author":"M Zaitsev","year":"2015","unstructured":"Zaitsev M, Maclaren J, Herbst M. (2015) Motion artifacts in MRI: A complex problem with many partial solutions. Journal of magnetic resonance imaging: JMRI 42:887\u2013901. https:\/\/doi.org\/10.1002\/jmri.24850","journal-title":"Journal of magnetic resonance imaging: JMRI"},{"key":"4369_CR2","doi-asserted-by":"publisher","first-page":"1279","DOI":"10.1148\/rg.255045202","volume":"25","author":"JF Glockner","year":"2005","unstructured":"Glockner JF, Hu HH, Stanley DW, Angelos L, King K. (2005) Parallel MR Imaging: A User\u2019s Guide. RadioGraphics 25:1279\u20131297. https:\/\/doi.org\/10.1148\/rg.255045202","journal-title":"RadioGraphics"},{"key":"4369_CR3","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1002\/jmri.23639","volume":"36","author":"A Deshmane","year":"2012","unstructured":"Deshmane A, Gulani V, Griswold MA, Seiberlich N. (2012) Parallel MR imaging. J Magn Reson Imaging 36:55\u201372. https:\/\/doi.org\/10.1002\/jmri.23639","journal-title":"J Magn Reson Imaging"},{"key":"4369_CR4","doi-asserted-by":"publisher","first-page":"898","DOI":"10.1148\/rg.210110","volume":"42","author":"WE Kwok","year":"2022","unstructured":"Kwok WE. (2022) Basic Principles of and Practical Guide to Clinical MRI Radiofrequency Coils. Radiographics: a review publication of the Radiological Society of North America, Inc 42:898\u2013918. https:\/\/doi.org\/10.1148\/rg.210110","journal-title":"Radiographics: a review publication of the Radiological Society of North America, Inc"},{"key":"4369_CR5","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.mri.2008.05.009","volume":"27","author":"L Zhang","year":"2009","unstructured":"Zhang L, Kholmovski EG, Guo J, Choi SE, Morrell GR, Parker DL. (2009) HASTE sequence with parallel acquisition and T2 decay compensation: application to carotid artery imaging. Magnetic resonance imaging 27:13\u201322. https:\/\/doi.org\/10.1016\/j.mri.2008.05.009","journal-title":"Magnetic resonance imaging"},{"key":"4369_CR6","doi-asserted-by":"publisher","first-page":"532","DOI":"10.1148\/rg.342135051","volume":"34","author":"NE Yanasak","year":"2014","unstructured":"Yanasak NE, Kelly MJ. (2014) MR Imaging Artifacts and Parallel Imaging Techniques with Calibration Scanning: A New Twist on Old Problems. RadioGraphics 34:532\u2013548. https:\/\/doi.org\/10.1148\/rg.342135051","journal-title":"RadioGraphics"},{"key":"4369_CR7","doi-asserted-by":"publisher","first-page":"9005","DOI":"10.1038\/s41598-021-88567-z","volume":"11","author":"J Sheng","year":"2021","unstructured":"Sheng J, Shi Y, Zhang Q. (2021) Improved parallel magnetic resonance imaging reconstruction with multiple variable density sampling. Scientific Reports 11:9005. https:\/\/doi.org\/10.1038\/s41598-021-88567-z","journal-title":"Scientific Reports"},{"key":"4369_CR8","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1002\/mrm.21634","volume":"60","author":"WS Hoge","year":"2008","unstructured":"Hoge WS, Brooks DH. (2008) Using GRAPPA to improve autocalibrated coil sensitivity estimation for the SENSE family of parallel imaging reconstruction algorithms. Magnetic Resonance in Medicine 60:462\u2013467. https:\/\/doi.org\/10.1002\/mrm.21634","journal-title":"Magnetic Resonance in Medicine"},{"key":"4369_CR9","doi-asserted-by":"crossref","unstructured":"Cummings E, Macdonald JA, Seiberlich N. (2022) Chap. 6 - Parallel Imaging. In: Ak\u00e7akaya M, Doneva M, Prieto C, (eds) Advances in Magnetic Resonance Technology and Applications. Academic Press, pp 129\u2013157","DOI":"10.1016\/B978-0-12-822726-8.00016-6"},{"key":"4369_CR10","doi-asserted-by":"publisher","first-page":"843","DOI":"10.3174\/ajnr.A1052","volume":"29","author":"P Mukherjee","year":"2008","unstructured":"Mukherjee P, Chung SW, Berman JI, Hess CP, Henry RG. (2008) Diffusion Tensor MR Imaging and Fiber Tractography: Technical Considerations. American Journal of Neuroradiology 29:843. https:\/\/doi.org\/10.3174\/ajnr.A1052","journal-title":"American Journal of Neuroradiology"},{"key":"4369_CR11","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.3348\/kjr.2015.16.6.1207","volume":"16","author":"J Huh","year":"2015","unstructured":"Huh J, Kim SY, Yeh BM, Lee SS, Kim KW, Wu EH, et al. (2015) Troubleshooting Arterial-Phase MR Images of Gadoxetate Disodium-Enhanced Liver. Korean J Radiol 16:1207\u20131215. https:\/\/doi.org\/10.3348\/kjr.2015.16.6.1207","journal-title":"Korean J Radiol"},{"key":"4369_CR12","doi-asserted-by":"publisher","first-page":"881","DOI":"10.1002\/mrm.21176","volume":"57","author":"S Skare","year":"2007","unstructured":"Skare S, Newbould RD, Clayton DB, Albers GW, Nagle S, Bammer R. (2007) Clinical multishot DW-EPI through parallel imaging with considerations of susceptibility, motion, and noise. Magn Reson Med 57:881\u2013890. https:\/\/doi.org\/10.1002\/mrm.21176","journal-title":"Magn Reson Med"},{"key":"4369_CR13","doi-asserted-by":"publisher","first-page":"1597","DOI":"10.3348\/kjr.2018.0931","volume":"20","author":"JH Yoon","year":"2019","unstructured":"Yoon JH, Nickel MD, Peeters JM, Lee JM. (2019) Rapid Imaging: Recent Advances in Abdominal MRI for Reducing Acquisition Time and Its Clinical Applications. Korean J Radiol 20:1597\u20131615. https:\/\/doi.org\/10.3348\/kjr.2018.0931","journal-title":"Korean J Radiol"},{"key":"4369_CR14","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1002\/mrm.24980","volume":"72","author":"L Feng","year":"2014","unstructured":"Feng L, Grimm R, Block KT, Chandarana H, Kim S, Xu J, et al. (2014) Golden-angle radial sparse parallel MRI: Combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI. Magnetic Resonance in Medicine 72:707\u2013717. https:\/\/doi.org\/10.1002\/mrm.24980","journal-title":"Magnetic Resonance in Medicine"},{"key":"4369_CR15","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1109\/tmi.2006.885337","volume":"26","author":"S Winkelmann","year":"2007","unstructured":"Winkelmann S, Schaeffter T, Koehler T, Eggers H, Doessel O. (2007) An optimal radial profile order based on the Golden Ratio for time-resolved MRI. IEEE Trans Med Imaging 26:68\u201376. https:\/\/doi.org\/10.1109\/tmi.2006.885337","journal-title":"IEEE Trans Med Imaging"},{"key":"4369_CR16","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1097\/rli.0000000000000409","volume":"53","author":"JH Yoon","year":"2018","unstructured":"Yoon JH, Lee JM, Yu MH, Hur BY, Grimm R, Block KT, et al. (2018) Evaluation of Transient Motion During Gadoxetic Acid-Enhanced Multiphasic Liver Magnetic Resonance Imaging Using Free-Breathing Golden-Angle Radial Sparse Parallel Magnetic Resonance Imaging. Investigative radiology 53:52\u201361. https:\/\/doi.org\/10.1097\/rli.0000000000000409","journal-title":"Investigative radiology"},{"key":"4369_CR17","doi-asserted-by":"publisher","first-page":"320","DOI":"10.1007\/s00330-013-3026-4","volume":"24","author":"H Chandarana","year":"2014","unstructured":"Chandarana H, Block KT, Winfeld MJ, Lala SV, Mazori D, Giuffrida E, et al. (2014) Free-breathing contrast-enhanced T1-weighted gradient-echo imaging with radial k-space sampling for paediatric abdominopelvic MRI. Eur Radiol 24:320\u2013326. https:\/\/doi.org\/10.1007\/s00330-013-3026-4","journal-title":"Eur Radiol"},{"key":"4369_CR18","doi-asserted-by":"publisher","first-page":"1154","DOI":"10.2214\/AJR.07.3657","volume":"191","author":"Y Hirokawa","year":"2008","unstructured":"Hirokawa Y, Isoda H, Maetani YS, Arizono S, Shimada K, Togashi K. (2008) MRI Artifact Reduction and Quality Improvement in the Upper Abdomen with PROPELLER and Prospective Acquisition Correction (PACE) Technique. American Journal of Roentgenology 191:1154\u20131158. https:\/\/doi.org\/10.2214\/AJR.07.3657","journal-title":"American Journal of Roentgenology"},{"key":"4369_CR19","doi-asserted-by":"publisher","first-page":"549","DOI":"10.1002\/mrm.20787","volume":"55","author":"FA Breuer","year":"2006","unstructured":"Breuer FA, Blaimer M, Mueller MF, Seiberlich N, Heidemann RM, Griswold MA, et al. (2006) Controlled aliasing in volumetric parallel imaging (2D CAIPIRINHA). Magnetic Resonance in Medicine 55:549\u2013556. https:\/\/doi.org\/10.1002\/mrm.20787","journal-title":"Magnetic Resonance in Medicine"},{"key":"4369_CR20","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1097\/rli.0000000000000011","volume":"49","author":"YS Park","year":"2014","unstructured":"Park YS, Lee CH, Kim IS, Kiefer B, Woo ST, Kim KA, et al. (2014) Usefulness of controlled aliasing in parallel imaging results in higher acceleration in gadoxetic acid-enhanced liver magnetic resonance imaging to clarify the hepatic arterial phase. Investigative radiology 49:183\u2013188. https:\/\/doi.org\/10.1097\/rli.0000000000000011","journal-title":"Investigative radiology"},{"key":"4369_CR21","doi-asserted-by":"publisher","first-page":"638","DOI":"10.1016\/j.mri.2015.11.011","volume":"34","author":"B Kim","year":"2016","unstructured":"Kim B, Lee CK, Seo N, Lee SS, Kim JK, Choi Y, et al. (2016) Comparison of CAIPIRINHA-VIBE, Radial-VIBE, and conventional VIBE sequences for dynamic contrast-enhanced (DCE) MRI: A validation study using a DCE-MRI phantom. Magnetic resonance imaging 34:638\u2013644. https:\/\/doi.org\/10.1016\/j.mri.2015.11.011","journal-title":"Magnetic resonance imaging"},{"key":"4369_CR22","doi-asserted-by":"publisher","first-page":"20160150","DOI":"10.1259\/bjr.20160150","volume":"89","author":"N Seo","year":"2016","unstructured":"Seo N, Park SJ, Kim B, Lee CK, Huh J, Kim JK, et al. (2016) Feasibility of free-breathing dynamic contrast-enhanced MRI of the abdomen: a comparison between CAIPIRINHA-VIBE, Radial-VIBE with KWIC reconstruction and conventional VIBE. British Journal of Radiology 89:20160150. https:\/\/doi.org\/10.1259\/bjr.20160150","journal-title":"British Journal of Radiology"},{"key":"4369_CR23","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1002\/jmri.24105","volume":"39","author":"KL Wright","year":"2014","unstructured":"Wright KL, Harrell MW, Jesberger JA, Landeras L, Nakamoto DA, Thomas S, et al. (2014) Clinical evaluation of CAIPIRINHA: comparison against a GRAPPA standard. J Magn Reson Imaging 39:189\u2013194. https:\/\/doi.org\/10.1002\/jmri.24105","journal-title":"J Magn Reson Imaging"},{"key":"4369_CR24","doi-asserted-by":"publisher","first-page":"1020","DOI":"10.1002\/jmri.24088","volume":"38","author":"MH Yu","year":"2013","unstructured":"Yu MH, Lee JM, Yoon J-H, Kiefer B, Han JK, Choi B-I. (2013) Clinical application of controlled aliasing in parallel imaging results in a higher acceleration (CAIPIRINHA)-volumetric interpolated breathhold (VIBE) sequence for gadoxetic acid-enhanced liver MR imaging. Journal of Magnetic Resonance Imaging 38:1020\u20131026. https:\/\/doi.org\/10.1002\/jmri.24088","journal-title":"Journal of Magnetic Resonance Imaging"},{"key":"4369_CR25","doi-asserted-by":"publisher","first-page":"1630","DOI":"10.1002\/mrm.22752","volume":"65","author":"SR Yutzy","year":"2011","unstructured":"Yutzy SR, Seiberlich N, Duerk JL, Griswold MA. (2011) Improvements in multislice parallel imaging using radial CAIPIRINHA. Magn Reson Med 65:1630\u20131637. https:\/\/doi.org\/10.1002\/mrm.22752","journal-title":"Magn Reson Med"},{"key":"4369_CR26","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1097\/rct.0000000000000200","volume":"39","author":"AC Morani","year":"2015","unstructured":"Morani AC, Vicens RA, Wei W, Gupta S, Vikram R, Balachandran A, et al. (2015) CAIPIRINHA-VIBE and GRAPPA-VIBE for liver MRI at 1.5 T: a comparative in vivo patient study. J Comput Assist Tomogr 39:263\u2013269. https:\/\/doi.org\/10.1097\/rct.0000000000000200","journal-title":"J Comput Assist Tomogr"},{"key":"4369_CR27","doi-asserted-by":"publisher","first-page":"1289","DOI":"10.1109\/TIT.2006.871582","volume":"52","author":"DL Donoho","year":"2006","unstructured":"Donoho DL. (2006) Compressed sensing. IEEE Transactions on Information Theory 52:1289\u20131306. https:\/\/doi.org\/10.1109\/TIT.2006.871582","journal-title":"IEEE Transactions on Information Theory"},{"key":"4369_CR28","doi-asserted-by":"publisher","first-page":"1293","DOI":"10.3348\/kjr.2023.0743","volume":"24","author":"S Yoon","year":"2023","unstructured":"Yoon S, Park SH, Han D. (2023) Uncover This Tech Term: Compressed Sensing Magnetic Resonance Imaging. Korean J Radiol 24:1293\u20131302. http:\/\/doi.org\/10.3348\/kjr.2023.0743","journal-title":"Korean J Radiol"},{"key":"4369_CR29","doi-asserted-by":"publisher","first-page":"966","DOI":"10.1002\/jmri.25547","volume":"45","author":"L Feng","year":"2017","unstructured":"Feng L, Benkert T, Block KT, Sodickson DK, Otazo R, Chandarana H. (2017) Compressed sensing for body MRI. Journal of Magnetic Resonance Imaging 45:966\u2013987. https:\/\/doi.org\/10.1002\/jmri.25547","journal-title":"Journal of Magnetic Resonance Imaging"},{"key":"4369_CR30","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-023-10226-w","author":"S Yoon","year":"2023","unstructured":"Yoon S, Shim YS, Park SH, Sung J, Nickel MD, Kim YJ, et al. (2023) Hepatobiliary phase imaging in cirrhotic patients using compressed sensing and controlled aliasing in parallel imaging results in higher acceleration. Eur Radiol. https:\/\/doi.org\/10.1007\/s00330-023-10226-w","journal-title":"Eur Radiol"},{"key":"4369_CR31","doi-asserted-by":"publisher","first-page":"438","DOI":"10.3348\/kjr.2018.0310","volume":"20","author":"JG Nam","year":"2019","unstructured":"Nam JG, Lee JM, Lee SM, Kang H-J, Lee ES, Hur BY, et al. (2019) High Acceleration Three-Dimensional T1-Weighted Dual Echo Dixon Hepatobiliary Phase Imaging Using Compressed Sensing-Sensitivity Encoding: Comparison of Image Quality and Solid Lesion Detectability with the Standard T1-Weighted Sequence. Korean J Radiol 20:438\u2013448. https:\/\/doi.org\/10.3348\/kjr.2018.0310","journal-title":"Korean J Radiol"},{"key":"4369_CR32","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s00261-021-03290-7","volume":"47","author":"MH Choi","year":"2022","unstructured":"Choi MH, Kim B, Han D, Lee YJ. (2022) Compressed sensing for breath-hold high-resolution hepatobiliary phase imaging: image noise, artifact, biliary anatomy evaluation, and focal lesion detection in comparison with parallel imaging. Abdominal Radiology 47:133\u2013142. https:\/\/doi.org\/10.1007\/s00261-021-03290-7","journal-title":"Abdominal Radiology"},{"key":"4369_CR33","doi-asserted-by":"publisher","first-page":"20150487","DOI":"10.1259\/bjr.20150487","volume":"88","author":"ON Jaspan","year":"2015","unstructured":"Jaspan ON, Fleysher R, Lipton ML. (2015) Compressed sensing MRI: a review of the clinical literature. The British Journal of Radiology 88:20150487. https:\/\/doi.org\/10.1259\/bjr.20150487","journal-title":"The British Journal of Radiology"},{"key":"4369_CR34","doi-asserted-by":"publisher","first-page":"e0146548","DOI":"10.1371\/journal.pone.0146548","volume":"11","author":"T Akasaka","year":"2016","unstructured":"Akasaka T, Fujimoto K, Yamamoto T, Okada T, Fushumi Y, Yamamoto A, et al. (2016) Optimization of Regularization Parameters in Compressed Sensing of Magnetic Resonance Angiography: Can Statistical Image Metrics Mimic Radiologists\u2019 Perception? PLOS ONE 11:e0146548. https:\/\/doi.org\/10.1371\/journal.pone.0146548","journal-title":"PLOS ONE"},{"key":"4369_CR35","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1109\/msp.2019.2950433","volume":"37","author":"CM Sandino","year":"2020","unstructured":"Sandino CM, Cheng JY, Chen F, Mardani M, Pauly JM, Vasanawala SS. (2020) Compressed Sensing: From Research to Clinical Practice with Deep Neural Networks. IEEE Signal Process Mag 37:111\u2013127. https:\/\/doi.org\/10.1109\/msp.2019.2950433","journal-title":"IEEE Signal Process Mag"},{"key":"4369_CR36","doi-asserted-by":"publisher","first-page":"376","DOI":"10.3390\/diagnostics10060376","volume":"10","author":"JS Song","year":"2020","unstructured":"Song JS, Kim SH, Kuehn B, Paek MY. (2020) Optimized Breath-Hold Compressed-Sensing 3D MR Cholangiopancreatography at 3T: Image Quality Analysis and Clinical Feasibility Assessment. Diagnostics 10:376. https:\/\/doi.org\/10.3390\/diagnostics10060376","journal-title":"Diagnostics"},{"key":"4369_CR37","doi-asserted-by":"publisher","first-page":"1389","DOI":"10.1002\/jmri.26049","volume":"48","author":"L Zhu","year":"2018","unstructured":"Zhu L, Xue H, Sun Z, Qian T, Weiland E, Kuehn B, et al. (2018) Modified breath-hold compressed-sensing 3D MR cholangiopancreatography with a small field-of-view and high resolution acquisition: Clinical feasibility in biliary and pancreatic disorders. Journal of Magnetic Resonance Imaging 48:1389\u20131399. https:\/\/doi.org\/10.1002\/jmri.26049","journal-title":"Journal of Magnetic Resonance Imaging"},{"key":"4369_CR38","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1097\/rli.0000000000000380","volume":"52","author":"JH Yoon","year":"2017","unstructured":"Yoon JH, Lee SM, Kang H-J, Weiland E, Raithel E, Son Y, et al. (2017) Clinical Feasibility of 3-Dimensional Magnetic Resonance Cholangiopancreatography Using Compressed Sensing: Comparison of Image Quality and Diagnostic Performance. Investigative radiology 52:612\u2013619. https:\/\/doi.org\/10.1097\/rli.0000000000000380","journal-title":"Investigative radiology"},{"key":"4369_CR39","doi-asserted-by":"publisher","first-page":"1828","DOI":"10.1007\/s00261-022-03418-3","volume":"47","author":"W Wang","year":"2022","unstructured":"Wang W, Yang J, Liu J, Li W, Zhao K, Xue K, et al. (2022) Three-dimensional static-fluid MR urography with gradient- and spin-echo (GRASE) at 3.0T: comparison of image quality and diagnostic performance with respiratory-triggered fast spin-echo (FSE). Abdominal Radiology 47:1828\u20131839. https:\/\/doi.org\/10.1007\/s00261-022-03418-3","journal-title":"Abdominal Radiology"},{"key":"4369_CR40","doi-asserted-by":"publisher","first-page":"4378","DOI":"10.1007\/s00330-022-09336-8","volume":"33","author":"SH Park","year":"2023","unstructured":"Park SH, Yoon JH, Park JY, Shim YS, Lee SM, Choi SJ, et al. (2023) Performance of free-breathing dynamic T1-weighted sequences in patients at risk of developing motion artifacts undergoing gadoxetic acid-enhanced liver MRI. Eur Radiol 33:4378\u20134388. https:\/\/doi.org\/10.1007\/s00330-022-09336-8","journal-title":"Eur Radiol"},{"key":"4369_CR41","doi-asserted-by":"crossref","unstructured":"Gassenmaier S, K\u00fcstner T, Nickel D, Herrmann J, Hoffmann R, Almansour H, et al. (2021) Deep Learning Applications in Magnetic Resonance Imaging: Has the Future Become Present? 11:2181.","DOI":"10.3390\/diagnostics11122181"},{"key":"4369_CR42","doi-asserted-by":"publisher","first-page":"1483","DOI":"10.1016\/j.acra.2014.07.004","volume":"21","author":"NA Obuchowski","year":"2014","unstructured":"Obuchowski NA, Subhas N, Schoenhagen P. (2014) Testing for interchangeability of imaging tests. Academic radiology 21:1483\u20131489. https:\/\/doi.org\/10.1016\/j.acra.2014.07.004","journal-title":"Academic radiology"},{"key":"4369_CR43","doi-asserted-by":"publisher","first-page":"e220425","DOI":"10.1148\/radiol.220425","volume":"307","author":"PM Johnson","year":"2023","unstructured":"Johnson PM, Lin DJ, Zbontar J, Zitnick CL, Sriram A, Muckley M, et al. (2023) Deep Learning Reconstruction Enables Prospectively Accelerated Clinical Knee MRI. Radiology 307:e220425. https:\/\/doi.org\/10.1148\/radiol.220425","journal-title":"Radiology"},{"key":"4369_CR44","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1097\/rli.0000000000000743","volume":"56","author":"J Herrmann","year":"2021","unstructured":"Herrmann J, Gassenmaier S, Nickel D, Arberet S, Afat S, Lingg A, et al. (2021) Diagnostic Confidence and Feasibility of a Deep Learning Accelerated HASTE Sequence of the Abdomen in a Single Breath-Hold. Investigative radiology 56:313\u2013319. https:\/\/doi.org\/10.1097\/rli.0000000000000743","journal-title":"Investigative radiology"},{"key":"4369_CR45","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.acra.2022.03.018","volume":"30","author":"J Herrmann","year":"2023","unstructured":"Herrmann J, Wessling D, Nickel D, Arberet S, Almansour H, Afat C, et al. (2023) Comprehensive Clinical Evaluation of a Deep Learning-Accelerated, Single-Breath-Hold Abdominal HASTE at 1.5 T and 3 T. Academic radiology 30:93\u2013102. https:\/\/doi.org\/10.1016\/j.acra.2022.03.018","journal-title":"Academic radiology"},{"key":"4369_CR46","doi-asserted-by":"publisher","first-page":"6817","DOI":"10.1007\/s00330-023-09693-y","volume":"33","author":"P Wary","year":"2023","unstructured":"Wary P, Hossu G, Ambarki K, Nickel D, Arberet S, Oster J, et al. (2023) Deep learning HASTE sequence compared with T2-weighted BLADE sequence for liver MRI at 3 Tesla: a qualitative and quantitative prospective study. European Radiology 33:6817\u20136827. https:\/\/doi.org\/10.1007\/s00330-023-09693-y","journal-title":"European Radiology"},{"key":"4369_CR47","doi-asserted-by":"publisher","first-page":"8447","DOI":"10.1007\/s00330-021-08008-3","volume":"31","author":"K Shanbhogue","year":"2021","unstructured":"Shanbhogue K, Tong A, Smereka P, Nickel D, Arberet S, Anthopolos R, et al. (2021) Accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning-based image reconstruction: qualitative and quantitative comparison of image quality with conventional T2-weighted FS sequence. Eur Radiol 31:8447\u20138457. https:\/\/doi.org\/10.1007\/s00330-021-08008-3","journal-title":"Eur Radiol"},{"key":"4369_CR48","doi-asserted-by":"publisher","unstructured":"Matsumoto S, Tsuboyama T, Onishi H, Fukui H, Honda T, Wakayama T, et al. (2023) Ultra-High-Resolution T2-Weighted PROPELLER MRI of the Rectum With Deep Learning Reconstruction: Assessment of Image Quality and Diagnostic Performance. Investigative radiology. https:\/\/doi.org\/10.1097\/rli.0000000000001047","DOI":"10.1097\/rli.0000000000001047"},{"key":"4369_CR49","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 CM, 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 (New York) 48:201\u2013210. https:\/\/doi.org\/10.1007\/s00261-022-03701-3","journal-title":"Abdominal radiology (New York)"},{"key":"4369_CR50","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1016\/j.diii.2022.11.002","volume":"104","author":"S Afat","year":"2023","unstructured":"Afat S, Herrmann J, Almansour H, Benkert T, Weiland E, H\u00f6lldobler T, et al. (2023) Acquisition time reduction of diffusion-weighted liver imaging using deep learning image reconstruction. Diagnostic and interventional imaging 104:178\u2013184. https:\/\/doi.org\/10.1016\/j.diii.2022.11.002","journal-title":"Diagnostic and interventional imaging"},{"key":"4369_CR51","doi-asserted-by":"publisher","first-page":"1098","DOI":"10.1007\/s11547-022-01539-9","volume":"127","author":"M Zerunian","year":"2022","unstructured":"Zerunian M, Pucciarelli F, Caruso D, Polici M, Masci B, Guido G, et al. (2022) Artificial intelligence based image quality enhancement in liver MRI: a quantitative and qualitative evaluation. La Radiologia medica 127:1098\u20131105. https:\/\/doi.org\/10.1007\/s11547-022-01539-9","journal-title":"La Radiologia medica"},{"key":"4369_CR52","doi-asserted-by":"publisher","first-page":"111149","DOI":"10.1016\/j.ejrad.2023.111149","volume":"168","author":"Q Chen","year":"2023","unstructured":"Chen Q, Fang S, Yuchen Y, Li R, Deng R, Chen Y, et al. (2023) Clinical feasibility of deep learning reconstruction in liver diffusion-weighted imaging: Improvement of image quality and impact on apparent diffusion coefficient value. European journal of radiology 168:111149. https:\/\/doi.org\/10.1016\/j.ejrad.2023.111149","journal-title":"European journal of radiology"},{"key":"4369_CR53","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1097\/rli.0000000000000988","volume":"58","author":"DH Kim","year":"2023","unstructured":"Kim DH, Kim B, Lee HS, Benkert T, Kim H, Choi JI, et al. (2023) Deep Learning-Accelerated Liver Diffusion-Weighted Imaging: Intraindividual Comparison and Additional Phantom Study of Free-Breathing and Respiratory-Triggering Acquisitions. Investigative radiology 58:782\u2013790. https:\/\/doi.org\/10.1097\/rli.0000000000000988","journal-title":"Investigative radiology"},{"key":"4369_CR54","doi-asserted-by":"publisher","first-page":"110428","DOI":"10.1016\/j.ejrad.2022.110428","volume":"154","author":"SH Bae","year":"2022","unstructured":"Bae SH, Hwang J, Hong SS, Lee EJ, Jeong J, Benkert T, et al. (2022) Clinical feasibility of accelerated diffusion weighted imaging of the abdomen with deep learning reconstruction: Comparison with conventional diffusion weighted imaging. European journal of radiology 154:110428. https:\/\/doi.org\/10.1016\/j.ejrad.2022.110428","journal-title":"European journal of radiology"},{"key":"4369_CR55","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1097\/rli.0000000000000769","volume":"56","author":"H Almansour","year":"2021","unstructured":"Almansour H, Gassenmaier S, Nickel D, Kannengiesser S, Afat S, Weiss J, et al. (2021) Deep Learning-Based Superresolution Reconstruction for Upper Abdominal Magnetic Resonance Imaging: An Analysis of Image Quality, Diagnostic Confidence, and Lesion Conspicuity. Investigative radiology 56:509\u2013516. https:\/\/doi.org\/10.1097\/rli.0000000000000769","journal-title":"Investigative radiology"},{"key":"4369_CR56","doi-asserted-by":"publisher","unstructured":"Wessling D, Herrmann J, Afat S, Nickel D, Almansour H, Keller G, et al. (2022) Application of a Deep Learning Algorithm for Combined Super-Resolution and Partial Fourier Reconstruction Including Time Reduction in T1-Weighted Precontrast and Postcontrast Gradient Echo Imaging of Abdominopelvic MR Imaging. Diagnostics (Basel, Switzerland) 12. https:\/\/doi.org\/10.3390\/diagnostics12102370","DOI":"10.3390\/diagnostics12102370"},{"key":"4369_CR57","doi-asserted-by":"publisher","first-page":"863","DOI":"10.1016\/j.acra.2022.06.003","volume":"30","author":"H Almansour","year":"2023","unstructured":"Almansour H, Herrmann J, Gassenmaier S, Lingg A, Nickel MD, Kannengiesser S, et al. (2023) Combined Deep Learning-based Super-Resolution and Partial Fourier Reconstruction for Gradient Echo Sequences in Abdominal MRI at 3 Tesla: Shortening Breath-Hold Time and Improving Image Sharpness and Lesion Conspicuity. Academic radiology 30:863\u2013872. https:\/\/doi.org\/10.1016\/j.acra.2022.06.003","journal-title":"Academic radiology"},{"key":"4369_CR58","doi-asserted-by":"publisher","first-page":"2500","DOI":"10.1007\/s00330-022-09227-y","volume":"33","author":"Y Zhang","year":"2023","unstructured":"Zhang Y, Peng W, Xiao Y, Ming Y, Ma K, Hu S, et al. (2023) Rapid 3D breath-hold MR cholangiopancreatography using deep learning\u2013constrained compressed sensing reconstruction. European Radiology 33:2500\u20132509. https:\/\/doi.org\/10.1007\/s00330-022-09227-y","journal-title":"European Radiology"},{"key":"4369_CR59","doi-asserted-by":"publisher","first-page":"729","DOI":"10.1002\/jmri.22580","volume":"34","author":"SB Reeder","year":"2011","unstructured":"Reeder SB, Cruite I, Hamilton G, Sirlin CB. (2011) Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy. Journal of Magnetic Resonance Imaging 34:729\u2013749. https:\/\/doi.org\/10.1002\/jmri.22580","journal-title":"Journal of Magnetic Resonance Imaging"},{"key":"4369_CR60","doi-asserted-by":"publisher","first-page":"486","DOI":"10.1148\/radiol.2017170550","volume":"286","author":"T Yokoo","year":"2018","unstructured":"Yokoo T, Serai SD, Pirasteh A, Bashir MR, Hamilton G, Hernando D, et al. (2018) Linearity, Bias, and Precision of Hepatic Proton Density Fat Fraction Measurements by Using MR Imaging: A Meta-Analysis. Radiology 286:486\u2013498. https:\/\/doi.org\/10.1148\/radiol.2017170550","journal-title":"Radiology"},{"key":"4369_CR61","doi-asserted-by":"publisher","unstructured":"Reeder SB, Sirlin CB. (2010) Quantification of liver fat with magnetic resonance imaging. Magnetic resonance imaging clinics of North America 18:337\u2013357, ix. https:\/\/doi.org\/10.1016\/j.mric.2010.08.013","DOI":"10.1016\/j.mric.2010.08.013"},{"key":"4369_CR62","doi-asserted-by":"publisher","first-page":"1260","DOI":"10.3348\/kjr.2022.0334","volume":"23","author":"S Park","year":"2022","unstructured":"Park S, Kwon JH, Kim SY, Kang JH, Chung JI, Jang JK, et al. (2022) Cutoff Values for Diagnosing Hepatic Steatosis Using Contemporary MRI-Proton Density Fat Fraction Measuring Methods. Korean J Radiol 23:1260\u20131268. https:\/\/doi.org\/10.3348\/kjr.2022.0334","journal-title":"Korean J Radiol"},{"key":"4369_CR63","doi-asserted-by":"publisher","unstructured":"Szczepaniak LS, Nurenberg P, Leonard D, Browning JD, Reingold JS, Grundy S, et al. (2005) Magnetic resonance spectroscopy to measure hepatic triglyceride content: prevalence of hepatic steatosis in the general population. 288:E462-E468. https:\/\/doi.org\/10.1152\/ajpendo.00064.2004","DOI":"10.1152\/ajpendo.00064.2004"},{"key":"4369_CR64","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1148\/radiol.12112520","volume":"265","author":"JP K\u00fchn","year":"2012","unstructured":"K\u00fchn JP, Hernando D, Mu\u00f1oz del Rio A, Evert M, Kannengiesser S, V\u00f6lzke H, et al. (2012) Effect of multipeak spectral modeling of fat for liver iron and fat quantification: correlation of biopsy with MR imaging results. Radiology 265:133\u2013142. https:\/\/doi.org\/10.1148\/radiol.12112520","journal-title":"Radiology"},{"key":"4369_CR65","doi-asserted-by":"publisher","first-page":"22","DOI":"10.52668\/kjar.2022.00143","volume":"6","author":"H Kim","year":"2022","unstructured":"Kim H, Choi J-I, Lee H-S. (2022) Friend or Foe: How to Suppress and Measure Fat During Abdominal Resonance Imaging? Korean J Abdom Radiol 6:22\u201336. https:\/\/doi.org\/10.52668\/kjar.2022.00143","journal-title":"Korean J Abdom Radiol"},{"key":"4369_CR66","doi-asserted-by":"publisher","first-page":"13","DOI":"10.3348\/kjr.2021.0112","volume":"23","author":"J Park","year":"2022","unstructured":"Park J, Lee JM, Lee G, Jeon SK, Joo I. (2022) Quantitative Evaluation of Hepatic Steatosis Using Advanced Imaging Techniques: Focusing on New Quantitative Ultrasound Techniques. Korean J Radiol 23:13\u201329. https:\/\/doi.org\/10.3348\/kjr.2021.0112","journal-title":"Korean J Radiol"},{"key":"4369_CR67","unstructured":"Sellers R. (2016) MR LiverLab. MAGNETOM Flash 66: 39\u201343. https:\/\/cdn0.scrvt.com\/39b415fb07de4d9656c7b516d8e2d907\/1800000003537376\/b2961f8cb1ea\/Magnetom-Flash-66_How-I-do-it-MR-LiverLab_Sellers_1800000003537376.pdf. Accessed 28 Feb 2024"},{"key":"4369_CR68","doi-asserted-by":"publisher","DOI":"10.1007\/s00261-023-04009-6","author":"S Song","year":"2023","unstructured":"Song S, Kim H, Choi J-I, Kim DH, Kim B, Lee H, et al. (2023) Validity of an automated screening Dixon technique for quantifying hepatic steatosis in living liver donors. Abdominal Radiology. https:\/\/doi.org\/10.1007\/s00261-023-04009-6","journal-title":"Abdominal Radiology"},{"key":"4369_CR69","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1002\/mrm.21561","volume":"59","author":"H Kim","year":"2008","unstructured":"Kim H, Taksali SE, Dufour S, Befroy D, Goodman TR, Petersen KF, et al. (2008) Comparative MR study of hepatic fat quantification using single-voxel proton spectroscopy, two-point dixon and three-point IDEAL. Magnetic Resonance in Medicine 59:521\u2013527. https:\/\/doi.org\/10.1002\/mrm.21561","journal-title":"Magnetic Resonance in Medicine"},{"key":"4369_CR70","doi-asserted-by":"publisher","first-page":"1353","DOI":"10.1002\/mrm.25054","volume":"72","author":"X Zhong","year":"2014","unstructured":"Zhong X, Nickel MD, Kannengiesser SA, Dale BM, Kiefer B, Bashir MR. (2014) Liver fat quantification using a multi-step adaptive fitting approach with multi-echo GRE imaging. Magn Reson Med 72:1353\u20131365. https:\/\/doi.org\/10.1002\/mrm.25054","journal-title":"Magn Reson Med"},{"key":"4369_CR71","doi-asserted-by":"publisher","unstructured":"Labranche R, Gilbert G, Cerny M, Vu K-N, Souli\u00e8res D, Olivi\u00e9 D, et al. (2018) Liver Iron Quantification with MR Imaging: A Primer for Radiologists. 38:392\u2013412. https:\/\/doi.org\/10.1148\/rg.2018170079","DOI":"10.1148\/rg.2018170079"},{"key":"4369_CR72","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1055\/s-2005-923315","volume":"25","author":"GA Ramm","year":"2005","unstructured":"Ramm GA, Ruddell RG. (2005) Hepatotoxicity of Iron Overload: Mechanisms of Iron-Induced Hepatic Fibrogenesis. Semin Liver Dis 25:433\u2013449. https:\/\/doi.org\/10.1055\/s-2005-923315","journal-title":"Semin Liver Dis"},{"key":"4369_CR73","doi-asserted-by":"publisher","unstructured":"Pietrangelo A. (2016) Iron and the liver. 36:116\u2013123. https:\/\/doi.org\/10.1111\/liv.13020","DOI":"10.1111\/liv.13020"},{"key":"4369_CR74","doi-asserted-by":"publisher","unstructured":"Reeder SB, Yokoo T, Fran\u00e7a M, Hernando D, Alberich-Bayarri \u00c1, Al\u00fastiza JM, et al. (2023) Quantification of Liver Iron Overload with MRI: Review and Guidelines from the ESGAR and SAR. 307:e221856. https:\/\/doi.org\/10.1148\/radiol.221856","DOI":"10.1148\/radiol.221856"},{"key":"4369_CR75","doi-asserted-by":"publisher","first-page":"1460","DOI":"10.1182\/blood-2004-10-3982","volume":"106","author":"JC Wood","year":"2005","unstructured":"Wood JC, Enriquez C, Ghugre N, Tyzka JM, Carson S, Nelson MD, et al. (2005) MRI R2 and R2* mapping accurately estimates hepatic iron concentration in transfusion-dependent thalassemia and sickle cell disease patients. Blood 106:1460\u20131465. https:\/\/doi.org\/10.1182\/blood-2004-10-3982","journal-title":"Blood"},{"key":"4369_CR76","doi-asserted-by":"publisher","first-page":"4853","DOI":"10.1182\/blood-2008-12-191643","volume":"113","author":"JS Hankins","year":"2009","unstructured":"Hankins JS, McCarville MB, Loeffler RB, Smeltzer MP, Onciu M, Hoffer FA, et al. (2009) R2* magnetic resonance imaging of the liver in patients with iron overload. Blood 113:4853\u20134855. https:\/\/doi.org\/10.1182\/blood-2008-12-191643","journal-title":"Blood"},{"key":"4369_CR77","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1186\/1532-429X-16-40","volume":"16","author":"MW Garbowski","year":"2014","unstructured":"Garbowski MW, Carpenter J-P, Smith G, Roughton M, Alam MH, He T, et al. (2014) Biopsy-based calibration of T2* magnetic resonance for estimation of liver iron concentration and comparison with R2 Ferriscan. Journal of Cardiovascular Magnetic Resonance 16:40. https:\/\/doi.org\/10.1186\/1532-429X-16-40","journal-title":"Journal of Cardiovascular Magnetic Resonance"},{"key":"4369_CR78","doi-asserted-by":"publisher","first-page":"472","DOI":"10.1055\/s-0034-1399318","volume":"187","author":"B Henninger","year":"2015","unstructured":"Henninger B, Zoller H, Rauch S, Finkenstedt A, Schocke M, Jaschke W, et al. (2015) R2* relaxometry for the quantification of hepatic iron overload: biopsy-based calibration and comparison with the literature. RoFo: Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin 187:472\u2013479. https:\/\/doi.org\/10.1055\/s-0034-1399318","journal-title":"RoFo: Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin"},{"key":"4369_CR79","unstructured":"Kannengiesser S. (2016) Iron quantification with LiverLab. MAGNETOM Flash 66:44\u201346. https:\/\/cdn0.scrvt.com\/39b415fb07de4d9656c7b516d8e2d907\/1800000003537375\/763f370f9ee4\/Magnetom-Flash-66_Iron-quantification-with-LiverLab_Kannengiesser_1800000003537375.pdf. Accessed 28 Feb 2024."},{"key":"4369_CR80","doi-asserted-by":"publisher","unstructured":"Trout AT, Serai S, Mahley AD, Wang H, Zhang Y, Zhang B, et al. (2016) Liver Stiffness Measurements with MR Elastography: Agreement and Repeatability across Imaging Systems, Field Strengths, and Pulse Sequences. 281:793\u2013804. https:\/\/doi.org\/10.1148\/radiol.2016160209","DOI":"10.1148\/radiol.2016160209"},{"key":"4369_CR81","doi-asserted-by":"publisher","first-page":"2419","DOI":"10.1016\/j.ultrasmedbio.2018.07.008","volume":"44","author":"G Ferraioli","year":"2018","unstructured":"Ferraioli G, Wong VW, Castera L, Berzigotti A, Sporea I, Dietrich CF, et al. (2018) Liver Ultrasound Elastography: An Update to the World Federation for Ultrasound in Medicine and Biology Guidelines and Recommendations. Ultrasound in medicine & biology 44:2419\u20132440. https:\/\/doi.org\/10.1016\/j.ultrasmedbio.2018.07.008","journal-title":"Ultrasound in medicine & biology"},{"key":"4369_CR82","first-page":"605","volume":"8","author":"NH Afdhal","year":"2012","unstructured":"Afdhal NH. (2012) Fibroscan (transient elastography) for the measurement of liver fibrosis. Gastroenterology & hepatology 8:605\u2013607.","journal-title":"Gastroenterology & hepatology"},{"key":"4369_CR83","doi-asserted-by":"publisher","unstructured":"Guglielmo FF, Venkatesh SK, Mitchell DG. (2019) Liver MR Elastography Technique and Image Interpretation: Pearls and Pitfalls. 39:1983\u20132002. https:\/\/doi.org\/10.1148\/rg.2019190034","DOI":"10.1148\/rg.2019190034"},{"key":"4369_CR84","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1097\/rli.0000000000000269","volume":"51","author":"M Wagner","year":"2016","unstructured":"Wagner M, Besa C, Bou Ayache J, Yasar TK, Bane O, Fung M, et al. (2016) Magnetic Resonance Elastography of the Liver: Qualitative and Quantitative Comparison of Gradient Echo and Spin Echo Echoplanar Imaging Sequences. Investigative radiology 51:575\u2013581. https:\/\/doi.org\/10.1097\/rli.0000000000000269","journal-title":"Investigative radiology"},{"key":"4369_CR85","doi-asserted-by":"publisher","first-page":"1086","DOI":"10.1002\/jmri.26918","volume":"51","author":"DW Kim","year":"2020","unstructured":"Kim DW, Kim SY, Yoon HM, Kim KW, Byun JH. (2020) Comparison of technical failure of MR elastography for measuring liver stiffness between gradient-recalled echo and spin-echo echo-planar imaging: A systematic review and meta-analysis. Journal of magnetic resonance imaging: JMRI 51:1086\u20131102. https:\/\/doi.org\/10.1002\/jmri.26918","journal-title":"Journal of magnetic resonance imaging: JMRI"},{"key":"4369_CR86","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1016\/j.cgh.2014.09.046","volume":"13","author":"S Singh","year":"2015","unstructured":"Singh S, Venkatesh SK, Wang Z, Miller FH, Motosugi U, Low RN, et al. (2015) Diagnostic performance of magnetic resonance elastography in staging liver fibrosis: a systematic review and meta-analysis of individual participant data. Clinical gastroenterology and hepatology: the official clinical practice journal of the American Gastroenterological Association 13:440\u2013451.e446. https:\/\/doi.org\/10.1016\/j.cgh.2014.09.046","journal-title":"Clinical gastroenterology and hepatology: the official clinical practice journal of the American Gastroenterological Association"},{"key":"4369_CR87","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1038\/nature11971","volume":"495","author":"D Ma","year":"2013","unstructured":"Ma D, Gulani V, Seiberlich N, Liu K, Sunshine JL, Duerk JL, et al. (2013) Magnetic resonance fingerprinting. Nature 495:187\u2013192. https:\/\/doi.org\/10.1038\/nature11971","journal-title":"Nature"},{"key":"4369_CR88","doi-asserted-by":"publisher","first-page":"675","DOI":"10.1002\/jmri.26836","volume":"51","author":"ME Poorman","year":"2020","unstructured":"Poorman ME, Martin MN, Ma D, McGivney DF, Gulani V, Griswold MA, et al. (2020) Magnetic resonance fingerprinting Part 1: Potential uses, current challenges, and recommendations. Journal of Magnetic Resonance Imaging 51:675\u2013692. https:\/\/doi.org\/10.1002\/jmri.26836","journal-title":"Journal of Magnetic Resonance Imaging"},{"key":"4369_CR89","doi-asserted-by":"publisher","first-page":"2614","DOI":"10.1002\/mrm.27556","volume":"81","author":"T Hong","year":"2019","unstructured":"Hong T, Han D, Kim DH. (2019) Simultaneous estimation of PD, T(1), T(2), T(2)(*), and \u2206B(0) using magnetic resonance fingerprinting with background gradient compensation. Magn Reson Med 81:2614\u20132623. https:\/\/doi.org\/10.1002\/mrm.27556","journal-title":"Magn Reson Med"},{"key":"4369_CR90","doi-asserted-by":"publisher","first-page":"2303","DOI":"10.1002\/mrm.25818","volume":"75","author":"D Ma","year":"2016","unstructured":"Ma D, Pierre EY, Jiang Y, Schluchter MD, Setsompop K, Gulani V, et al. (2016) Music-based magnetic resonance fingerprinting to improve patient comfort during MRI examinations. Magn Reson Med 75:2303\u20132314. https:\/\/doi.org\/10.1002\/mrm.25818","journal-title":"Magn Reson Med"},{"key":"4369_CR91","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1097\/rli.0000000000000975","volume":"58","author":"S Gaur","year":"2023","unstructured":"Gaur S, Panda A, Fajardo JE, Hamilton J, Jiang Y, Gulani V. (2023) Magnetic Resonance Fingerprinting: A Review of Clinical Applications. Investigative radiology 58:561\u2013577. https:\/\/doi.org\/10.1097\/rli.0000000000000975","journal-title":"Investigative radiology"},{"key":"4369_CR92","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1148\/radiol.2016152037","volume":"279","author":"Y Chen","year":"2016","unstructured":"Chen Y, Jiang Y, Pahwa S, Ma D, Lu L, Twieg MD, et al. (2016) MR Fingerprinting for Rapid Quantitative Abdominal Imaging. Radiology 279:278\u2013286. https:\/\/doi.org\/10.1148\/radiol.2016152037","journal-title":"Radiology"},{"key":"4369_CR93","doi-asserted-by":"publisher","first-page":"2625","DOI":"10.1002\/mrm.28311","volume":"84","author":"O Jaubert","year":"2020","unstructured":"Jaubert O, Arrieta C, Cruz G, Bustin A, Schneider T, Georgiopoulos G, et al. (2020) Multi-parametric liver tissue characterization using MR fingerprinting: Simultaneous T(1), T(2), T(2) *, and fat fraction mapping. Magn Reson Med 84:2625\u20132635. https:\/\/doi.org\/10.1002\/mrm.28311","journal-title":"Magn Reson Med"},{"key":"4369_CR94","doi-asserted-by":"publisher","first-page":"1332","DOI":"10.3348\/kjr.2020.1362","volume":"22","author":"D Han","year":"2021","unstructured":"Han D, Choi MH, Lee YJ, Kim DH. (2021) Feasibility of Novel Three-Dimensional Magnetic Resonance Fingerprinting of the Prostate Gland: Phantom and Clinical Studies. Korean J Radiol 22:1332\u20131340. https:\/\/doi.org\/10.3348\/kjr.2020.1362","journal-title":"Korean J Radiol"},{"key":"4369_CR95","doi-asserted-by":"publisher","first-page":"729","DOI":"10.1148\/radiol.2017161599","volume":"283","author":"AC Yu","year":"2017","unstructured":"Yu AC, Badve C, Ponsky LE, Pahwa S, Dastmalchian S, Rogers M, et al. (2017) Development of a Combined MR Fingerprinting and Diffusion Examination for Prostate Cancer. Radiology 283:729\u2013738. https:\/\/doi.org\/10.1148\/radiol.2017161599","journal-title":"Radiology"}],"container-title":["Abdominal Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00261-024-04369-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00261-024-04369-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00261-024-04369-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T03:46:36Z","timestamp":1726112796000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00261-024-04369-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,28]]},"references-count":95,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2024,10]]}},"alternative-id":["4369"],"URL":"https:\/\/doi.org\/10.1007\/s00261-024-04369-7","relation":{},"ISSN":["2366-0058"],"issn-type":[{"value":"2366-0058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,28]]},"assertion":[{"value":"19 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 April 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 May 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 May 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Munyoung Paek and Dongyeob Han are employees of Siemens Healthineers Ltd. Other authors have no potential conflicts of interest to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}