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To reduce the scan time, one can collect fewer T<jats:sub>1<\/jats:sub>w images, albeit at the cost of precision or\/and accuracy. Recently, the feasibility of using a neural network instead of conventional two\u2010 or three\u2010parameter fit modeling has been demonstrated. However, prior studies used data from a single vendor and field strength; therefore, the generalizability of the models has not been established.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>To develop and evaluate an accelerated cardiac T<jats:sub>1<\/jats:sub> mapping approach based on MyoMapNet, a convolution neural network T<jats:sub>1<\/jats:sub> estimator that can be used across different vendors and field strengths by incorporating the relevant scanner information as additional inputs to the model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Study Type<\/jats:title><jats:p>Retrospective, multicenter.<\/jats:p><\/jats:sec><jats:sec><jats:title>Population<\/jats:title><jats:p>A total of 1423 patients with known or suspected cardiac disease (808 male, 57\u2009\u00b1\u200916\u2009years), from three centers, two vendors (Siemens, Philips), and two field strengths (1.5\u2009T, 3\u2009T). The data were randomly split into 60% training, 20% validation, and 20% testing.<\/jats:p><\/jats:sec><jats:sec><jats:title>Field Strength\/Sequence<\/jats:title><jats:p>A 1.5\u2009T and 3\u2009T, Modified Look\u2010Locker inversion recovery (MOLLI) for native and postcontrast T<jats:sub>1<\/jats:sub>.<\/jats:p><\/jats:sec><jats:sec><jats:title>Assessment<\/jats:title><jats:p>Scanner\u2010independent MyoMapNet (SI\u2010MyoMapNet) was developed by altering the deep learning (DL) architecture of MyoMapNet to incorporate scanner vendor and field strength as inputs. Epicardial and endocardial contours and blood pool (by manually drawing a large region of interest in the blood pool) of the left ventricle were manually delineated by three readers, with 2, 8, and 9\u2009years of experience, and SI\u2010MyoMapNet myocardial and blood pool T<jats:sub>1<\/jats:sub> values (calculated from four T<jats:sub>1<\/jats:sub>w images) were compared with conventional MOLLI T<jats:sub>1<\/jats:sub> values (calculated from 8 to 11 T<jats:sub>1<\/jats:sub>w images).<\/jats:p><\/jats:sec><jats:sec><jats:title>Statistical Tests<\/jats:title><jats:p>Equivalency test with 95% confidence interval (CI), linear regression slope, Pearson correlation coefficient (<jats:italic>r<\/jats:italic>), Bland\u2013Altman analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The proposed SI\u2010MyoMapNet successfully created T<jats:sub>1<\/jats:sub> maps. Native and postcontrast T<jats:sub>1<\/jats:sub> values measured from SI\u2010MyoMapNet were strongly correlated with MOLLI, despite using only four T<jats:sub>1<\/jats:sub>w images, at both field\u2010strengths and vendors (all <jats:italic>r<\/jats:italic>\u2009&gt;\u20090.86). For native T<jats:sub>1<\/jats:sub>, SI\u2010MyoMapNet and MOLLI were in good agreement for myocardial and blood T<jats:sub>1<\/jats:sub> values in institution 1 (myocardium: 5\u2009msec, 95% CI [3, 8]; blood: \u221210\u2009msec, 95%CI [\u221216, \u22124]), in institution 2 (myocardium: 6\u2009msec, 95% CI [0, 11]; blood: 0\u2009msec, [\u221218, 17]), and in institution 3 (myocardium: 7\u2009msec, 95% CI [\u22128, 22]; blood: 8\u2009msec, [\u221214, 30]). Similar results were observed for postcontrast T<jats:sub>1<\/jats:sub>.<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Conclusion<\/jats:title><jats:p>Inclusion of field strength and vendor as additional inputs to the DL architecture allows generalizability of MyoMapNet across different vendors or field strength.<\/jats:p><\/jats:sec><jats:sec><jats:title>Evidence Level<\/jats:title><jats:p>2.<\/jats:p><\/jats:sec><jats:sec><jats:title>Technical Efficacy<\/jats:title><jats:p>Stage 2.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.28739","type":"journal-article","created":{"date-parts":[[2023,4,13]],"date-time":"2023-04-13T15:18:12Z","timestamp":1681399092000},"page":"179-189","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Scanner\u2010Independent <scp>MyoMapNet<\/scp> for Accelerated Cardiac <scp>MRI T<sub>1<\/sub><\/scp> Mapping Across Vendors and Field 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