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I think referees might not like it, if you do the right thing and are honest in your submission. That being said, if you have only one patient population, it's not clear to me why it's a problem. That is, if you're trying to show an effect is statistically significant, you're just averaging the results of the two scanners. There is of course the implicit assumption in the way SPM does things that error variance is fairly constant across subjects (I think FSL for example gets around this), but I don't think that assumption is that big a deal (meaning, the relevant stats are often fairly robust to violations of it). The problem would be if you're comparing two populations, and you don't have a good balance of both populations on the two scanners. The extreme case, which would make the results useless, would be if all the subjects of group A were on one scanner, and all the ones in group B on the other. More generally, one could check for a group-by-scanner interaction and claim that it's not statistically significant (though often the cells are small enough that that's weak evidence).