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The cohort included 34 unique subjects with postmenstrual age range between 33 and 52\u2009weeks and contained a mix of healthy individuals and those with clinical concerns. Single\u2010slice T<jats:sub>1<\/jats:sub> and T<jats:sub>2<\/jats:sub> mapping protocols were used to provide measurements in white matter, cortex, cerebellum, and deep gray matter. Automatic image segmentation of a separate T<jats:sub>2<\/jats:sub>\u2010weighted brain volume was used to define regions of interest for analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Linear regression was used to estimate relaxation times at term equivalent age (40\u2009weeks postmenstrual age).  with 95% confidence intervals was measured to be 2933 [2893, 2972] ms in white matter; 2653 [2604, 2701] ms in cerebellum; and 2486 [2439, 2532] ms in basal ganglia.  was estimated as 119 [116, 121] ms in white matter, 99 [96, 102] ms in cerebellum, and 90 [89, 92] ms in basal ganglia. Most tissue\u2010relaxation times showed a significant negative correlation with postmenstrual age, with the strongest correlation seen in cerebellum.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>We describe neonatal brain tissue and age\u2010specific T<jats:sub>1<\/jats:sub> and T<jats:sub>2<\/jats:sub> relaxation values at 7\u2009T. The presented values differ substantially from both adult values at 7\u2009T and neonate values measured at lower field strengths, and will be essential for pulse\u2010sequence optimization for neonatal studies.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mrm.30403","type":"journal-article","created":{"date-parts":[[2024,12,14]],"date-time":"2024-12-14T06:11:33Z","timestamp":1734156693000},"page":"2153-2162","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["<scp>T<sub>1<\/sub><\/scp> and <scp>T<sub>2<\/sub><\/scp> measurements of the neonatal brain at <scp>7 T<\/scp>"],"prefix":"10.1002","volume":"93","author":[{"given":"Aiman","family":"Mahmoud","sequence":"first","affiliation":[{"name":"Imaging Physics and Engineering Research Department, School of Biomedical Engineering and Imaging Sciences King's College London   London 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