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).