The　small-world　architecture　has　gained　considerable　attention　in　anatomical　brain　connectivity　studies.　However,　how　to　adequately　quantify　small-worldness　in　diffusion　networks　has　remained　a　problem.　We　addressed　the　limits　of　small-world　measures　and　defined　new　metric　indices:　the　small-world　efficiency　(SWE)　and　the　small-world　angle　(SWA),　both　based　on　the　tradeoff　between　high　global　and　local　efficiency.　To　confirm　the　validity　of　the　new　indices,　we　examined　the　behavior　of　SWE　and　SWA　of　networks　based　on　the　Watts-Strogatz　model　as　well　as　the　diffusion　tensor　imaging　(DTI)　data　from　75　healthy　old　subjects　(aged　50-70).　We　found　that　SWE　could　classify　the　subjects　into　different　age　groups,　and　was　correlated　with　individual　performance　on　the　WAIS-IV　test.　Moreover,　to　evaluate　the　sensitivity　of　the　proposed　measures　to　network,　two　network　attack　strategies　were　applied.　Our　results　indicate　that　the　new　indices　outperform　their　predecessors　in　the　analysis　of　DTI　data.