Programmer - Is there an equivalence of "anova" (for lm) to an rpart object ?

Programmer Question

When using R's rpart function, I can easily fit a model with it. for example:

# Classification Tree with rpart
library(rpart)

# grow tree 
fit <- rpart(Kyphosis ~ Age + Number + Start,
     method="class", data=kyphosis)

printcp(fit) # display the results 
plotcp(fit) 
summary(fit) # detailed summary of splits

# plot tree 
plot(fit, uniform=TRUE, 
     main="Classification Tree for Kyphosis")
text(fit, use.n=TRUE, all=TRUE, cex=.8)

My question is -
How can I measure the "importance" of each of my three explanatory variables (Age, Number, Start) to the model?

If this was a regression model, I could have looked at p values from the "anova" F test (between lm models with and without the variable). But what is the equivalence of using "anova" on lm to an rpart object ?

(I hope I managed to make my question clear)

Thanks.

Find the answer here