{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T12:56:34Z","timestamp":1785761794429,"version":"3.56.0"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T00:00:00Z","timestamp":1742947200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T00:00:00Z","timestamp":1742947200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Funda\u00e7\u00e3o D. Anna de Sommer Champalimaud e Dr. Carlos Montez Champalimaud"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Abdom Radiol"],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Purpose<\/jats:title>\n            <jats:p>This study aims to determine the feasibility, image quality, intra-subject repeatability and inter-reader variability of Diffusion tensor (DTI) and Diffusion kurtosis imaging (DKI) for pancreatic imaging using different protocols and report normative values in healthy individuals.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods<\/jats:title>\n            <jats:p>Single-institution prospective study performed on healthy volunteers in a clinical 3T scanner, using two different protocols (6\/16 diffusion directions). Acquisitions were repeated twice to assess intra-subject repeatability. To assess inter-reader variability, Mean diffusivity (MD), Axial diffusivity (AD), Radial diffusivity (RD), Apparent diffusion coefficient (ADC) and Mean kurtosis (MK) values were extracted from segmented pancreas by two radiologists. A Likert scale was used by both readers to assess subjective image quality.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Twelve healthy volunteers were recruited for each MRI protocol. The 6 diffusion directions protocol was shorter: 7\u00a0min vs. 14\u00a0min (corresponding to 4\u00a0min vs. 7.5\u00a0min for a DTI only reconstruction). No differences in image quality were found between protocols. Only MK maps showed implausible estimates, leading to the exclusion of median 16% and 17.7% pixels for the 6- and 16-direction protocols, respectively. Intra-subject repeatability was determined with negligible coefficients of repeatability for DTI; however, MK presented slightly higher values. Inter-reader agreement was excellent for all maps (ICC\u2009&gt;\u20090.9).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>DTI and DKI of the pancreas are feasible in clinical settings, with excellent inter-observer agreement and good image quality. Intra-subject repeatability is excellent for DTI, but some variability was observed with DKI. A 6-directions protocol may be preferred due to faster acquisition without quantitatively compromising estimates. MK inaccuracies prompt further research for improving artifact correction.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Graphical abstract<\/jats:title>\n          <\/jats:sec>","DOI":"10.1007\/s00261-025-04889-w","type":"journal-article","created":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T23:56:29Z","timestamp":1743206189000},"page":"4563-4574","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Diffusion tensor imaging and diffusion kurtosis imaging of the pancreas - feasibility, robustness and protocol comparison in a healthy population"],"prefix":"10.1007","volume":"50","author":[{"given":"Carlos","family":"Bilreiro","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luisa","family":"Andrade","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rafael","family":"Henriques","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nuno","family":"Lou\u00e7\u00e3o","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Celso","family":"Matos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Noam","family":"Shemesh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,3,26]]},"reference":[{"key":"4889_CR1","doi-asserted-by":"publisher","unstructured":"Altmayer S, Armelin LM, Pereira JS, et al (2024) MRI with DWI improves detection of liver metastasis and selection of surgical candidates with pancreatic cancer: a systematic review and meta-analysis. Eur Radiol 34:. https:\/\/doi.org\/10.1007\/S00330-023-10069-5","DOI":"10.1007\/S00330-023-10069-5"},{"key":"4889_CR2","doi-asserted-by":"publisher","unstructured":"Brenner R, Metens T, Bali M, et al (2012) Pancreatic neuroendocrine tumor: added value of fusion of T2-weighted imaging and high b-value diffusion-weighted imaging for tumor detection. Eur J Radiol 81:. https:\/\/doi.org\/10.1016\/J.EJRAD.2012.01.032","DOI":"10.1016\/J.EJRAD.2012.01.032"},{"key":"4889_CR3","doi-asserted-by":"publisher","first-page":"109936","DOI":"10.1016\/J.EJRAD.2021.109936","volume":"143","author":"F Donati","year":"2021","unstructured":"Donati F, Casini C, Cervelli R, et al (2021) Diffusion-weighted MRI of solid pancreatic lesions: Comparison between reduced field-of-view and large field-of-view sequences. Eur J Radiol 143:109936. https:\/\/doi.org\/10.1016\/J.EJRAD.2021.109936","journal-title":"Eur J Radiol"},{"key":"4889_CR4","doi-asserted-by":"publisher","first-page":"291","DOI":"10.2214\/AJR.15.14974\/ASSET","volume":"206","author":"SY Choi","year":"2016","unstructured":"Choi SY, Kim SH, Kang TW, et al (2016) Differentiating mass-forming autoimmune pancreatitis from pancreatic ductal adenocarcinoma on the basis of contrast-enhanced MRI and DWI findings. Am J Roentgenol 206:291\u2013300.","journal-title":"Am J Roentgenol"},{"key":"4889_CR5","doi-asserted-by":"publisher","first-page":"6738","DOI":"10.1007\/S00330-024-10720-9\/TABLES\/3","volume":"34","author":"ZH Wang","year":"2024","unstructured":"Wang ZH, Zhu L, Xue HD, Jin ZY (2024) Quantitative MR imaging biomarkers for distinguishing inflammatory pancreatic mass and pancreatic cancer\u2014a systematic review and meta-analysis. Eur Radiol 34:6738\u20136750. https:\/\/doi.org\/10.1007\/S00330-024-10720-9\/TABLES\/3","journal-title":"Eur Radiol"},{"key":"4889_CR6","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1016\/J.PAN.2023.12.009","volume":"24","author":"T Ohtsuka","year":"2024","unstructured":"Ohtsuka T, Fernandez-del Castillo C, Furukawa T, et al (2024) International evidence-based Kyoto guidelines for the management of intraductal papillary mucinous neoplasm of the pancreas. Pancreatology 24:255\u2013270. https:\/\/doi.org\/10.1016\/J.PAN.2023.12.009","journal-title":"Pancreatology"},{"key":"4889_CR7","doi-asserted-by":"publisher","first-page":"772","DOI":"10.1053\/J.GASTRO.2021.10.014","volume":"162","author":"KA Overbeek","year":"2022","unstructured":"Overbeek KA, Goggins MG, Dbouk M, et al (2022) Timeline of Development of Pancreatic Cancer and Implications for Successful Early Detection in High-Risk Individuals. Gastroenterology 162:772\u2013785.e4. https:\/\/doi.org\/10.1053\/J.GASTRO.2021.10.014","journal-title":"Gastroenterology"},{"key":"4889_CR8","doi-asserted-by":"publisher","first-page":"3029","DOI":"10.1007\/S00330-013-2929-4","volume":"23","author":"R Manfredi","year":"2013","unstructured":"Manfredi R, Bonatti M, Mantovani W, et al (2013) Non-hyperfunctioning neuroendocrine tumours of the pancreas: MR imaging appearance and correlation with their biological behaviour. Eur Radiol 23:3029\u20133039. https:\/\/doi.org\/10.1007\/S00330-013-2929-4","journal-title":"Eur Radiol"},{"key":"4889_CR9","doi-asserted-by":"publisher","first-page":"837","DOI":"10.1080\/14737140.2018.1496822","volume":"18","author":"L Lee","year":"2018","unstructured":"Lee L, Ito T, Jensen RT (2018) Imaging of pancreatic neuroendocrine tumors: recent advances, current status, and controversies. Expert Rev Anticancer Ther 18:837\u2013860. https:\/\/doi.org\/10.1080\/14737140.2018.1496822","journal-title":"Expert Rev Anticancer Ther"},{"key":"4889_CR10","doi-asserted-by":"publisher","unstructured":"Bilreiro C, Andrade L, Santiago I, et al (2024) Imaging of pancreatic ductal adenocarcinoma\u2013 An update for all stages of patient management. Eur J Radiol Open 12:. https:\/\/doi.org\/10.1016\/J.EJRO.2024.100553","DOI":"10.1016\/J.EJRO.2024.100553"},{"key":"4889_CR11","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-023-10381-0","author":"C Bilreiro","year":"2023","unstructured":"Bilreiro C, Andrade L, Marques RM, Matos C (2023) Diffusion-weighted imaging for determining response to neoadjuvant therapy in pancreatic cancer: a systematic review and meta-analysis. Eur Radiol. https:\/\/doi.org\/10.1007\/s00330-023-10381-0","journal-title":"Eur Radiol"},{"key":"4889_CR12","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1148\/radiol.14130778","volume":"274","author":"M Barral","year":"2015","unstructured":"Barral M, Taouli B, Guiu B, et al (2015) Diffusion-weighted MR imaging of the pancreas: current status and recommendations. Radiology 274:45\u201363. https:\/\/doi.org\/10.1148\/radiol.14130778","journal-title":"Radiology"},{"key":"4889_CR13","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1053\/J.SULT.2021.07.006","volume":"42","author":"E Martinez-Heras","year":"2021","unstructured":"Martinez-Heras E, Grussu F, Prados F, et al (2021) Diffusion-Weighted Imaging: Recent Advances and Applications. Semin Ultrasound, CT MRI 42:490\u2013506. https:\/\/doi.org\/10.1053\/J.SULT.2021.07.006","journal-title":"Semin Ultrasound, CT MRI"},{"key":"4889_CR14","doi-asserted-by":"publisher","first-page":"1432","DOI":"10.1002\/MRM.20508","volume":"53","author":"JH Jensen","year":"2005","unstructured":"Jensen JH, Helpern JA, Ramani A, et al (2005) Diffusional kurtosis imaging: The quantification of non-gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med 53:1432\u20131440. https:\/\/doi.org\/10.1002\/MRM.20508","journal-title":"Magn Reson Med"},{"key":"4889_CR15","doi-asserted-by":"publisher","first-page":"698","DOI":"10.1002\/NBM.1518","volume":"23","author":"JH Jensen","year":"2010","unstructured":"Jensen JH, Helpern JA (2010) MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed 23:698\u2013710. https:\/\/doi.org\/10.1002\/NBM.1518","journal-title":"NMR Biomed"},{"key":"4889_CR16","doi-asserted-by":"publisher","unstructured":"Nissan N, Golan T, Furman-Haran E, et al (2014) Diffusion tensor magnetic resonance imaging of the pancreas. PLoS One 9:. https:\/\/doi.org\/10.1371\/JOURNAL.PONE.0115783","DOI":"10.1371\/JOURNAL.PONE.0115783"},{"key":"4889_CR17","doi-asserted-by":"publisher","unstructured":"Li X, Zhuang L, Zhang X, et al (2016) Preliminary Study of MR Diffusion Tensor Imaging of Pancreas for the Diagnosis of Acute Pancreatitis. 11:e0160115. https:\/\/doi.org\/10.1371\/JOURNAL.PONE.0160115","DOI":"10.1371\/JOURNAL.PONE.0160115"},{"key":"4889_CR18","doi-asserted-by":"publisher","first-page":"175628481988505","DOI":"10.1177\/1756284819885052","volume":"13","author":"V Granata","year":"2020","unstructured":"Granata V, Fusco R, Sansone M, et al (2020) Magnetic resonance imaging in the assessment of pancreatic cancer with quantitative parameter extraction by means of dynamic contrast-enhanced magnetic resonance imaging, diffusion kurtosis imaging and intravoxel incoherent motion diffusion-weighted imaging. Therap Adv Gastroenterol 13:1756284819885052. https:\/\/doi.org\/10.1177\/1756284819885052","journal-title":"Therap Adv Gastroenterol"},{"key":"4889_CR19","doi-asserted-by":"publisher","unstructured":"Bilreiro C, Fernandes FF, Sim\u00f5es R V., et al (2024) Pancreatic Intraepithelial Neoplasia Revealed by Diffusion-Tensor MRI. Invest Radiol. https:\/\/doi.org\/10.1097\/RLI.0000000000001142","DOI":"10.1097\/RLI.0000000000001142"},{"key":"4889_CR20","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1002\/JMRI.24982","volume":"43","author":"Y Noda","year":"2016","unstructured":"Noda Y, Kanematsu M, Goshima S, et al (2016) Diffusion kurtosis imaging of the pancreas for the assessment of HbA1c levels. J Magn Reson Imaging 43:159\u2013165. https:\/\/doi.org\/10.1002\/JMRI.24982","journal-title":"J Magn Reson Imaging"},{"key":"4889_CR21","doi-asserted-by":"publisher","first-page":"1190","DOI":"10.1002\/JMRI.24985","volume":"42","author":"AB Rosenkrantz","year":"2015","unstructured":"Rosenkrantz AB, Padhani AR, Chenevert TL, et al (2015) Body diffusion kurtosis imaging: Basic principles, applications, and considerations for clinical practice. J Magn Reson Imaging 42:1190\u20131202. https:\/\/doi.org\/10.1002\/JMRI.24985","journal-title":"J Magn Reson Imaging"},{"key":"4889_CR22","first-page":"1776","volume":"27","author":"H Ni","year":"2006","unstructured":"Ni H, Kavcic V, Zhu T, et al (2006) Effects of Number of Diffusion Gradient Directions on Derived Diffusion Tensor Imaging Indices in Human Brain. AJNR Am J Neuroradiol 27:1776","journal-title":"AJNR Am J Neuroradiol"},{"key":"4889_CR23","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1002\/MRM.23254","volume":"68","author":"C Lebel","year":"2012","unstructured":"Lebel C, Benner T, Beaulieu C (2012) Six is enough? Comparison of diffusion parameters measured using six or more diffusion-encoding gradient directions with deterministic tractography. Magn Reson Med 68:474\u2013483. https:\/\/doi.org\/10.1002\/MRM.23254","journal-title":"Magn Reson Med"},{"key":"4889_CR24","doi-asserted-by":"publisher","first-page":"394","DOI":"10.1016\/J.NEUROIMAGE.2016.08.016","volume":"142","author":"J Veraart","year":"2016","unstructured":"Veraart J, Novikov DS, Christiaens D, et al (2016) Denoising of diffusion MRI using random matrix theory. Neuroimage 142:394\u2013406. https:\/\/doi.org\/10.1016\/J.NEUROIMAGE.2016.08.016","journal-title":"Neuroimage"},{"key":"4889_CR25","doi-asserted-by":"publisher","first-page":"1574","DOI":"10.1002\/MRM.26054","volume":"76","author":"E Kellner","year":"2016","unstructured":"Kellner E, Dhital B, Kiselev VG, Reisert M (2016) Gibbs-ringing artifact removal based on local subvoxel-shifts. Magn Reson Med 76:1574\u20131581. https:\/\/doi.org\/10.1002\/MRM.26054","journal-title":"Magn Reson Med"},{"key":"4889_CR26","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1016\/j.neuroimage.2013.05.028","volume":"81","author":"J Veraart","year":"2013","unstructured":"Veraart J, Sijbers J, Sunaert S, et al (2013) Weighted linear least squares estimation of diffusion MRI parameters: strengths, limitations, and pitfalls. Neuroimage 81:335\u2013346. https:\/\/doi.org\/10.1016\/j.neuroimage.2013.05.028","journal-title":"Neuroimage"},{"key":"4889_CR27","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1016\/J.NEUROIMAGE.2017.04.023","volume":"156","author":"AS Rydh\u00f6g","year":"2017","unstructured":"Rydh\u00f6g AS, Szczepankiewicz F, Wirestam R, et al (2017) Separating Blood and Water: Perfusion and Free Water Elimination from Diffusion MRI in the Human Brain. Neuroimage 156:423. https:\/\/doi.org\/10.1016\/J.NEUROIMAGE.2017.04.023","journal-title":"Neuroimage"},{"key":"4889_CR28","doi-asserted-by":"publisher","first-page":"534","DOI":"10.1002\/JMRI.1076","volume":"13","author":"D Le Bihan","year":"2001","unstructured":"Le Bihan D, Mangin JF, Poupon C, et al (2001) Diffusion tensor imaging: Concepts and applications. J Magn Reson Imaging 13:534\u2013546. https:\/\/doi.org\/10.1002\/JMRI.1076","journal-title":"J Magn Reson Imaging"},{"key":"4889_CR29","doi-asserted-by":"publisher","first-page":"675433","DOI":"10.3389\/FNHUM.2021.675433\/BIBTEX","volume":"15","author":"RN Henriques","year":"2021","unstructured":"Henriques RN, Correia MM, Marrale M, et al (2021) Diffusional Kurtosis Imaging in the Diffusion Imaging in Python Project. Front Hum Neurosci 15:675433. https:\/\/doi.org\/10.3389\/FNHUM.2021.675433\/BIBTEX","journal-title":"Front Hum Neurosci"},{"key":"4889_CR30","doi-asserted-by":"publisher","unstructured":"Henriques RN (2018) Advanced Methods for Diffusion MRI Data Analysis and their Application to the Healthy Ageing Brain. PhD Thesis, Univ Cambridge. https:\/\/doi.org\/10.17863\/CAM.29356","DOI":"10.17863\/CAM.29356"},{"key":"4889_CR31","doi-asserted-by":"publisher","first-page":"3245","DOI":"10.1002\/MRM.27606","volume":"81","author":"RN Henriques","year":"2019","unstructured":"Henriques RN, Jespersen SN, Shemesh N (2019) Microscopic anisotropy misestimation in spherical-mean single diffusion encoding MRI. Magn Reson Med 81:3245\u20133261. https:\/\/doi.org\/10.1002\/MRM.27606","journal-title":"Magn Reson Med"},{"key":"4889_CR32","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/J.MRI.2019.08.001","volume":"63","author":"X Wang","year":"2019","unstructured":"Wang X, Gao W, Li F, et al (2019) Diffusion kurtosis imaging as an imaging biomarker for predicting prognosis of the patients with high-grade gliomas. Magn Reson Imaging 63:131\u2013136. https:\/\/doi.org\/10.1016\/J.MRI.2019.08.001","journal-title":"Magn Reson Imaging"},{"key":"4889_CR33","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1177\/096228029900800204","volume":"8","author":"JM Bland","year":"1999","unstructured":"Bland JM, Altman DG (1999) Measuring agreement in method comparison studies. Stat Methods Med Res 8:135\u2013160. https:\/\/doi.org\/10.1177\/096228029900800204","journal-title":"Stat Methods Med Res"},{"key":"4889_CR34","doi-asserted-by":"publisher","unstructured":"Sorace AG, Wu C, Barnes SL, et al (2018) Repeatability, Reproducibility, and Accuracy of Quantitative MRI of the Breast in the Community Radiology Setting. J Magn Reson Imaging 48:https:\/\/doi.org\/10.1002\/jmri.26011. https:\/\/doi.org\/10.1002\/JMRI.26011","DOI":"10.1002\/jmri.26011"},{"key":"4889_CR35","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/J.JCM.2016.02.012","volume":"15","author":"TK Koo","year":"2016","unstructured":"Koo TK, Li MY (2016) A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. J Chiropr Med 15:155. https:\/\/doi.org\/10.1016\/J.JCM.2016.02.012","journal-title":"J Chiropr Med"},{"key":"4889_CR36","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1037\/H0026256","volume":"70","author":"J Cohen","year":"1968","unstructured":"Cohen J (1968) Weighted kappa: nominal scale agreement with provision for scaled disagreement or partial credit. Psychol Bull 70:213\u2013220. https:\/\/doi.org\/10.1037\/H0026256","journal-title":"Psychol Bull"},{"key":"4889_CR37","doi-asserted-by":"publisher","first-page":"159","DOI":"10.2307\/2529310","volume":"33","author":"JR Landis","year":"1977","unstructured":"Landis JR, Koch GG (1977) The Measurement of Observer Agreement for Categorical Data. Biometrics 33:159. https:\/\/doi.org\/10.2307\/2529310","journal-title":"Biometrics"},{"key":"4889_CR38","doi-asserted-by":"publisher","first-page":"769","DOI":"10.1097\/RLI.0B013E3181B62271","volume":"44","author":"A Lemke","year":"2009","unstructured":"Lemke A, Laun FB, Klau M, et al (2009) Differentiation of pancreas carcinoma from healthy pancreatic tissue using multiple b-values: Comparison of apparent diffusion coefficient and intravoxel incoherent motion derived parameters. Invest Radiol 44:769\u2013775. https:\/\/doi.org\/10.1097\/RLI.0B013E3181B62271","journal-title":"Invest Radiol"},{"key":"4889_CR39","doi-asserted-by":"publisher","unstructured":"Herrmann J, Schoennagel BP, Roesch M, et al (2013) Diffusion-weighted imaging of the healthy pancreas: ADC values are age and gender dependent. 37:886\u2013891. https:\/\/doi.org\/10.1002\/JMRI.23871","DOI":"10.1002\/JMRI.23871"},{"key":"4889_CR40","doi-asserted-by":"publisher","first-page":"4843","DOI":"10.1111\/EJN.15785","volume":"56","author":"V Kumpulainen","year":"2022","unstructured":"Kumpulainen V, Merisaari H, Copeland A, et al (2022) Effect of number of diffusion-encoding directions in diffusion metrics of 5\u2010year\u2010olds using tract\u2010based spatial statistical analysis. Eur J Neurosci 56:4843. https:\/\/doi.org\/10.1111\/EJN.15785","journal-title":"Eur J Neurosci"},{"key":"4889_CR41","doi-asserted-by":"publisher","unstructured":"Barrio-Arranz G, De Luis-Garc\u00eda R, Trist\u00e1n-Vega A, et al (2015) Impact of MR Acquisition Parameters on DTI Scalar Indexes: A Tractography Based Approach. PLoS One 10:. https:\/\/doi.org\/10.1371\/JOURNAL.PONE.0137905","DOI":"10.1371\/JOURNAL.PONE.0137905"},{"key":"4889_CR42","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1016\/J.NEUROIMAGE.2015.01.010","volume":"109","author":"Y Chen","year":"2015","unstructured":"Chen Y, Tymofiyeva O, Hess CP, Xu D (2015) Effects of rejecting diffusion directions on tensor-derived parameters. Neuroimage 109:160\u2013170. https:\/\/doi.org\/10.1016\/J.NEUROIMAGE.2015.01.010","journal-title":"Neuroimage"},{"key":"4889_CR43","doi-asserted-by":"publisher","first-page":"756","DOI":"10.1002\/JMRI.21053","volume":"26","author":"JAD Farrell","year":"2007","unstructured":"Farrell JAD, Landman BA, Jones CK, et al (2007) Effects of signal-to-noise ratio on the accuracy and reproducibility of diffusion tensor imaging-derived fractional anisotropy, mean diffusivity, and principal eigenvector measurements at 1.5 T. J Magn Reson Imaging 26:756\u2013767. https:\/\/doi.org\/10.1002\/JMRI.21053","journal-title":"J Magn Reson Imaging"},{"key":"4889_CR44","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-022-15511-0","volume":"121 12","author":"A Cromb\u00e9","year":"2022","unstructured":"Cromb\u00e9 A, Nicolas R, Richard N, et al (2022) High B-value diffusion tensor imaging for early detection of hippocampal microstructural alteration in a mouse model of multiple sclerosis. Sci Reports 2022 121 12:1\u201315. https:\/\/doi.org\/10.1038\/s41598-022-15511-0","journal-title":"Sci Reports 2022"},{"key":"4889_CR45","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 Artefacts in MRI: a Complex Problem with Many Partial Solutions. J Magn Reson Imaging 42:887. https:\/\/doi.org\/10.1002\/JMRI.24850","journal-title":"J Magn Reson Imaging"},{"key":"4889_CR46","doi-asserted-by":"publisher","first-page":"214","DOI":"10.2214\/AJR.17.18267\/ASSET","volume":"210","author":"BE Dogan","year":"2018","unstructured":"Dogan BE, Scoggins ME, Son JB, et al (2018) American College of Radiology\u2013Compliant Short Protocol Breast MRI for High-Risk Breast Cancer Screening: A Prospective Feasibility Study. Am J Roentgenol 210:214\u2013221.","journal-title":"Am J Roentgenol"},{"key":"4889_CR47","doi-asserted-by":"publisher","first-page":"1600","DOI":"10.1002\/MRM.28730","volume":"86","author":"RN Henriques","year":"2021","unstructured":"Henriques RN, Jespersen SN, Jones DK, Veraart J (2021) Toward more robust and reproducible diffusion kurtosis imaging. Magn Reson Med 86:1600.","journal-title":"Magn Reson Med"},{"key":"4889_CR48","doi-asserted-by":"publisher","first-page":"823","DOI":"10.1002\/MRM.22655","volume":"65","author":"A Tabesh","year":"2011","unstructured":"Tabesh A, Jensen JH, Ardekani BA, Helpern JA (2011) Estimation of tensors and tensor-derived measures in diffusional kurtosis imaging. Magn Reson Med 65:823\u2013836. https:\/\/doi.org\/10.1002\/MRM.22655","journal-title":"Magn Reson Med"},{"key":"4889_CR49","doi-asserted-by":"publisher","first-page":"1956","DOI":"10.1002\/MRM.28846","volume":"86","author":"R Geng","year":"2021","unstructured":"Geng R, Zhang Y, Starekova J, et al (2021) Characterization and Correction of Cardiovascular Motion Artifacts in Diffusion-Weighted Imaging of the Pancreas. Magn Reson Med 86:1956. https:\/\/doi.org\/10.1002\/MRM.28846","journal-title":"Magn Reson Med"},{"key":"4889_CR50","doi-asserted-by":"publisher","first-page":"2146","DOI":"10.1002\/MRM.28824","volume":"86","author":"C Bilreiro","year":"2021","unstructured":"Bilreiro C, Fernandes FF, Andrade L, et al (2021) Effective bowel motion reduction in mouse abdominal MRI using hyoscine butylbromide. Magn Reson Med 86:2146\u20132155. https:\/\/doi.org\/10.1002\/MRM.28824","journal-title":"Magn Reson Med"},{"key":"4889_CR51","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, et al (2018) Gas-induced susceptibility artefacts on diffusion-weighted MRI of the rectum at 1.5 T\u2013 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":"4889_CR52","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":"4889_CR53","doi-asserted-by":"publisher","first-page":"604","DOI":"10.1002\/MRM.1910030413","volume":"3","author":"WA Edelstein","year":"1986","unstructured":"Edelstein WA, Glover GH, Hardy CJ, Redington RW (1986) The intrinsic signal-to-noise ratio in NMR imaging. Magn Reson Med 3:604\u2013618. https:\/\/doi.org\/10.1002\/MRM.1910030413","journal-title":"Magn Reson Med"},{"key":"4889_CR54","doi-asserted-by":"publisher","first-page":"263","DOI":"10.6028\/jres.070c.025","volume":"70C","author":"HH Ku","year":"1966","unstructured":"Ku HH (1966) Notes on the use of propagation of error formulas. J Res Natl Bur Stand Sect C Eng Instrum 70\u00a0C:263. https:\/\/doi.org\/10.6028\/jres.070c.025","journal-title":"J Res Natl Bur Stand Sect C Eng Instrum"}],"container-title":["Abdominal Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00261-025-04889-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00261-025-04889-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00261-025-04889-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T12:03:58Z","timestamp":1758715438000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00261-025-04889-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,26]]},"references-count":54,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2025,10]]}},"alternative-id":["4889"],"URL":"https:\/\/doi.org\/10.1007\/s00261-025-04889-w","relation":{},"ISSN":["2366-0058"],"issn-type":[{"value":"2366-0058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,26]]},"assertion":[{"value":"29 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 March 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 March 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 March 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":"Noam Shemesh serves on the Scientific Advisory Board of Bruker Biospin. No other potential competing interests are reported.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}