{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T14:44:16Z","timestamp":1776696256555,"version":"3.51.2"},"reference-count":50,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2019,6,30]],"date-time":"2019-06-30T00:00:00Z","timestamp":1561852800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"name":"CEA's Programme Transversal, Technologies pour la Sant\u00e9"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance in Med"],"published-print":{"date-parts":[[2019,12]]},"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>A calibration\u2010free pulse design method is introduced to alleviate <jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/mrm27870-math-0002.png\" xlink:title=\"urn:x-wiley:07403194:media:mrm27870:mrm27870-math-0002\"\/> artifacts in clinical routine with parallel transmission at high field, dealing with significant inter\u2010subject variability, found for instance in the abdomen.<\/jats:p><\/jats:sec><jats:sec><jats:title>Theory and Methods<\/jats:title><jats:p>From a dual\u2010transmit 3T scanner, a database of <jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/mrm27870-math-0003.png\" xlink:title=\"urn:x-wiley:07403194:media:mrm27870:mrm27870-math-0003\"\/> and off\u2010resonance abdominal maps from 50 subjects was first divided into 3 clusters based on mutual affinity between their respective tailored k<jats:sub>T<\/jats:sub>\u2010points pulses. For each cluster, a k<jats:sub>T<\/jats:sub>\u2010points pulse was computed, minimizing normalized root\u2010mean\u2010square flip angle deviations simultaneously for all subjects comprised in it. Using 30 additional subjects' field distributions, a machine learning classifier was trained on this 80\u2010labeled\u2010subject database to recognize the best pulse from the 3 ones available, relying only on patient features accessible from the preliminary localizer sequence present in all protocols. This so\u2010called <jats:italic>SmartPulse<\/jats:italic> process was experimentally tested on an additional 53\u2010subject set and compared with other pulse types: vendor's hard calibration\u2010free dual excitation, tailored static radiofrequency shimming, universal and tailored k<jats:sub>T<\/jats:sub>\u2010points pulses.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>S<jats:italic>martPulse<\/jats:italic> outperformed both calibration\u2010free approaches. Tailored static radiofrequency shimming yielded similar flip angle homogeneity for most patients but broke down for some while <jats:italic>SmartPulse<\/jats:italic> remained robust. Although flip angle homogeneity was systematically better with tailored k<jats:sub>T<\/jats:sub>\u2010points, the difference was barely noticeable on in vivo images.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The proposed method paves the way toward an efficient trade\u2010off between tailored and universal pulse design approaches for large inter\u2010subject variability. With no need for on\u2010line field mapping or pulse design, it can fit seamlessly into a clinical protocol.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mrm.27870","type":"journal-article","created":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T05:07:15Z","timestamp":1561957635000},"page":"2016-2031","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["SmartPulse, a machine learning approach for calibration\u2010free dynamic RF shimming: Preliminary study in a clinical environment"],"prefix":"10.1002","volume":"82","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6149-9154","authenticated-orcid":false,"given":"Rapha\u00ebl","family":"Tomi\u2010Tricot","sequence":"first","affiliation":[{"name":"NeuroSpin, CEA, Universit\u00e9 Paris\u2010Saclay Gif\u2010sur\u2010Yvette France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vincent","family":"Gras","sequence":"additional","affiliation":[{"name":"NeuroSpin, CEA, Universit\u00e9 Paris\u2010Saclay Gif\u2010sur\u2010Yvette France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bertrand","family":"Thirion","sequence":"additional","affiliation":[{"name":"Parietal, Inria Universit\u00e9 Paris\u2010Saclay Gif\u2010sur\u2010Yvette France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Franck","family":"Mauconduit","sequence":"additional","affiliation":[{"name":"Siemens Healthcare SAS Saint\u2010Denis France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicolas","family":"Boulant","sequence":"additional","affiliation":[{"name":"NeuroSpin, CEA, Universit\u00e9 Paris\u2010Saclay Gif\u2010sur\u2010Yvette France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamza","family":"Cherkaoui","sequence":"additional","affiliation":[{"name":"Parietal, Inria Universit\u00e9 Paris\u2010Saclay Gif\u2010sur\u2010Yvette France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pierre","family":"Zerbib","sequence":"additional","affiliation":[{"name":"Department of Radiology AP\u2010HP, CHU Henri Mondor Cr\u00e9teil France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexandre","family":"Vignaud","sequence":"additional","affiliation":[{"name":"NeuroSpin, CEA, Universit\u00e9 Paris\u2010Saclay Gif\u2010sur\u2010Yvette France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alain","family":"Luciani","sequence":"additional","affiliation":[{"name":"Department of Radiology AP\u2010HP, CHU Henri Mondor Cr\u00e9teil France"},{"name":"Universit\u00e9 Paris\u2010Est Cr\u00e9teil Val de Marne Cr\u00e9teil France"},{"name":"INSERM U955, Team 18, Molecular Virology and Immunology \u2013 Physiopathology and Therapeutic of Chronic Viral Hepatitis Cr\u00e9teil France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexis","family":"Amadon","sequence":"additional","affiliation":[{"name":"NeuroSpin, CEA, Universit\u00e9 Paris\u2010Saclay Gif\u2010sur\u2010Yvette France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2019,6,30]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2007.11.006"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.20698"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.3313"},{"key":"e_1_2_8_5_1","unstructured":"KukukGM GiesekeJ NellesM et al.Clinical liver MRI at 3.0 Tesla using parallel RF transmission with patient\u2010adaptive B1 shimming. 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