Probably the most straightforward way to do this would be to apply PCA to each of the imputed data sets and then use those in whatever analysis models you want. As an alternative, you could use the stacked dataset of all imputation (see my earlier email) and run PCA giving each of the rows of the stacked data (1/m) weight where m is the number of imputed datasets. This would ensure that all of the imputed data sets use the same factor loadings. 

Cheers,
Matt