bootstraping sensitivity and specificity

Dear all, I have a standard method and two alternatives to perform a test, 
called method A and method B.

I have calculated the sensitivity and specificity for
standard method vs. method A and standard method vs. method B.
Hence, I have two sensitivity values an two specificity values.

To be clear, sensitivity and specificity was calculated from:

		     Disease(A) No Disease(Ac) Total
Positive Screen(T)        a 		b 	a+b
Negative Screen(Tc) 	  c 		d 	c+d
Total			 a+c 	       b+d    a+b+c+d

where  	sensitivity:   P(T | A)=a/(a+c) and
specificity: P(Tc | Ac)=d/(b+d).

My questions:

How can I compare this quantities? That is, how method have high sensitivity 
or specificity?
Could I get the empirical distributions for sensitivity and specificity from 
Bootstrap?

If yes, Could I sampling from the set of "all" contingency tables
with given marginals, and works only if the marginals are positive?
It is the technique used by chisq.test when simulate.p.value is TRUE.

Best Regards.

LB.