Benefits and Pitfalls

It has been well reported in recent years that the accuracy of VFA T1 estimates is very sensitive to pulse sequence implementations (Stikov et al. 2015; Lutti & Weiskopf 2013; Baudrexel et al. 2018), and as such is less robust than the gold standard inversion recovery technique. In particular, the signal bias resulting from insufficient spoiling can result in inaccurate T1 estimates of up to 30% relative to inversion recovery estimated values (Stikov et al. 2015). VFA T1 map accuracy and precision is also strongly dependent on the quality of the measured B1 map (Lee et al. 2017), which can vary substantially between implementations (Boudreau et al. 2017). Modern rapid B1 mapping pulse sequences are not as widely available as VFA, resulting in some groups attempting alternative ways of removing the bias from the T1 maps like generating an artificial B1 map through the use of image processing techniques (Liberman et al. 2014) or omitting B1 correction altogether (Yuan et al. 2012). The latter is not recommended, because most MRI scanners have default pulse sequences that, with careful protocol settings, can provide B1 maps of sufficient quality very rapidly (Boudreau et al. 2017; Wang et al. 2005; Samson et al. 2006).

Despite some drawbacks, VFA is still one of the most widely used T1 mapping methods in research. Its rapid acquisition time, rapid image processing time, and widespread availability makes it a great candidate for use in other quantitative imaging acquisition protocols like quantitative magnetization transfer imaging (Yarnykh 2002; Cercignani et al. 2005) and dynamic contrast enhanced imaging (Sung et al. 2013; Li et al. 2018).

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