{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T04:11:59Z","timestamp":1773029519320,"version":"3.50.1"},"reference-count":35,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T00:00:00Z","timestamp":1768780800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T00:00:00Z","timestamp":1768780800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000070","name":"National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","award":["P41EB027061"],"award-info":[{"award-number":["P41EB027061"]}],"id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000070","name":"National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","award":["R01EB031787"],"award-info":[{"award-number":["R01EB031787"]}],"id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance in Med"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>\n                      Brain MR imaging at 10.5\u2009T ultra\u2010high field offers significant improvements in signal\u2010to\u2010noise ratio (SNR), but faces challenges with B\n                      <jats:sub>1<\/jats:sub>\n                      <jats:sup>+<\/jats:sup>\n                      inhomogeneity. Parallel\u2010transmission (pTx) can be used to achieve a more uniform RF field distribution, but necessitates the use of B\n                      <jats:sub>1<\/jats:sub>\n                      <jats:sup>+<\/jats:sup>\n                      calibration in the region of interest. This study explores a universal B\n                      <jats:sub>1<\/jats:sub>\n                      <jats:sup>+<\/jats:sup>\n                      shim solution on 10.5\u2009T that could eliminate the need for time\u2010consuming subject\u2010specific B\n                      <jats:sub>1<\/jats:sub>\n                      <jats:sup>+<\/jats:sup>\n                      calibration.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      B\n                      <jats:sub>1<\/jats:sub>\n                      <jats:sup>+<\/jats:sup>\n                      data from 7 participants (19 sessions) were used to develop the universal B\n                      <jats:sub>1<\/jats:sub>\n                      <jats:sup>+<\/jats:sup>\n                      shim, which was then validated against traditional subject\u2010specific approaches using T\n                      <jats:sub>1<\/jats:sub>\n                      \u2010weighted MP2RAGE structural images in 5 participants (6 sessions). Statistical comparisons of tissue and subcortical segmentations were conducted using popular neuroimaging tools SPM and FreeSurfer, respectively.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The universal shim rapidly converged with a small training dataset, likely due to consistent positioning and the simplicity of B\n                      <jats:sub>1<\/jats:sub>\n                      <jats:sup>+<\/jats:sup>\n                      shimming used for head imaging. Whole\u2010brain tissue segmentation showed no statistically significant differences between universal and subject\u2010specific solutions, with only minor variations near the ventricles and inferior brain regions in the detailed subcortical segmentation. The proposed universal B\n                      <jats:sub>1<\/jats:sub>\n                      <jats:sup>+<\/jats:sup>\n                      shim reduces examination time by removing the need for separate data acquisition and optimization.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      These findings suggest that the universal B\n                      <jats:sub>1<\/jats:sub>\n                      <jats:sup>+<\/jats:sup>\n                      shim is a viable substitute for subject\u2010specific approaches, offering a more efficient solution for neuroimaging applications. Additionally, it confirms that 10.5\u2009T MRI can produce reliable structural brain imaging data, paving the way for broader adoption of ultra\u2010high field MRI in neuroimaging research.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mrm.70262","type":"journal-article","created":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T05:19:47Z","timestamp":1768886387000},"page":"2776-2785","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["10.5\u2009T In Vivo Head Imaging With Universal\n                    <scp>RF<\/scp>\n                    Shimming"],"prefix":"10.1002","volume":"95","author":[{"given":"Young Woo","family":"Park","sequence":"first","affiliation":[{"name":"Center for Magnetic Resonance Research, Department of Radiology University of Minnesota  Minneapolis Minnesota USA"},{"name":"Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc  Bethesda Maryland USA"},{"name":"Department of Radiology Uniformed Services University of the Health Sciences  Bethesda Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon","family":"Schmidt","sequence":"additional","affiliation":[{"name":"Center for Magnetic Resonance Research, Department of Radiology University of Minnesota  Minneapolis Minnesota USA"},{"name":"Medical Physics in Radiology German Cancer Research Center (DKFZ)  Heidelberg Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wolfgang","family":"Bogner","sequence":"additional","affiliation":[{"name":"High Field MR Center, Department of Biomedical Imaging and Image\u2010Guided Therapy Medical University of Vienna  Vienna Austria"},{"name":"Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK)  Vienna Austria"},{"name":"Comprehensive Center for AI in Medicine (CAIM) Medical University of Vienna  Vienna Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3187-6529","authenticated-orcid":false,"given":"Gregory J.","family":"Metzger","sequence":"additional","affiliation":[{"name":"Center for Magnetic Resonance Research, Department of Radiology University of Minnesota  Minneapolis Minnesota USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4727-2447","authenticated-orcid":false,"given":"Ma\u0142gorzata","family":"Marja\u0144ska","sequence":"additional","affiliation":[{"name":"Center for Magnetic Resonance Research, Department of Radiology University of Minnesota  Minneapolis Minnesota USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,1,19]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.07.007"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.30108"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.30315"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.30476"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.117349"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2022.119200"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2025.121015"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.20321"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.26148"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.30617"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.30305"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28749"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.30185"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.30137"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICEAA.2019.8879180"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.29866"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2020.08.004"},{"key":"e_1_2_10_19_1","volume-title":"Proceedings of the 17th Annual Meeting of ISMRM","author":"Moortele P. 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