Can sklearn Decisiontreeregressor handle np.nan values for independent features?

If yes, how does node splitting takes place?
If no, and we impute using an outlier value, would the splits obtained be inaccurate?

I had tried created Decision tree with np.nan and the same imputed with an outlier -999999 and got different split points and variables on which split happened.