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Although a pilot national live-donor kidney exchange program was recently launched in the US, the kidney shortage is increasing faster than ever. A new solution paradigm is able to incorporate compatible pairs in exchange. In this paper, we consider an exchange framework that has both compatible and incompatible pairs, and patients are indifferent over compatible pairs. Only two-way exchanges are permitted because of institutional constraints. We explore the structure of Pareto-efficient matchings in this framework. We show that under Pareto-efficient matchings, the same number of patients receive transplants, and it is possible to construct Pareto-efficient matchings that match the same incompatible pairs while matching the least number of compatible pairs. We extend the celebrated Gallai–Edmonds Decomposition in the combinatorial optimization literature to our new framework. We also conduct comparative static exercises on how this decomposition changes as new compatible pairs join the pool.