Table 4.

Performance of the CT attenuation of each bone to predict osteoporosis and osteopenia/osteoporosis in the training/validation dataset.

Osteoporosis	CT attenuation threshold	Sensitivity	Specificity	AUC	Accuracy	Positive Predictive Value (PPV)	Negative Predictive Value (NPV)
Calcaneus	143.243	0.815	0.526	0.702	0.602	0.379	0.889
Talus	283.996	0.556	0.789	0.698	0.728	0.484	0.833
Navicular	298.246	0.741	0.697	0.700	0.709	0.465	0.883
Cuboid	127.220	0.667	0.605	0.634	0.621	0.375	0.836
Lateral cuneiform	264.602	0.852	0.513	0.686	0.602	0.383	0.907
Intermediate cuneiform	344.202	0.593	0.724	0.682	0.689	0.432	0.833
Medial cuneiform	260.755	0.667	0.605	0.644	0.621	0.375	0.836
SVM with linear kernel	–	0.778	0.750	0.819	0.757	0.525	0.905
SVM with RBF kernel	–	0.926	0.934	0.942	0.932	0.833	0.973
SVM with sigmoid kernel	–	0.630	0.539	0.568	0.563	0.327	0.804
PCA	–	0.444	0.934	0.689	0.748	0.510	0.963
Osteopenia/osteoporosis	CT attenuation threshold	Sensitivity	Specificity	AUC	Accuracy	Positive Predictive Value (PPV)	Negative Predictive Value (NPV)
Calcaneus	141.054	0.646	0.857	0.795	0.689	0.946	0.383
Talus	362.224	0.805	0.762	0.810	0.796	0.930	0.500
Navicular	372.465	0.829	0.667	0.767	0.796	0.907	0.500
Cuboid	139.161	0.659	0.714	0.708	0.670	0.900	0.349
Lateral cuneiform	311.144	0.854	0.667	0.808	0.816	0.909	0.538
Intermediate cuneiform	380.160	0.585	0.810	0.756	0.631	0.923	0.333
Medial cuneiform	327.331	0.890	0.571	0.740	0.825	0.890	0.571
SVM with linear kernel	–	0.878	0.857	0.888	0.874	0.960	0.643
SVM with RBF kernel	–	0.878	1.00	0.968	0.903	1.00	0.677
SVM with sigmoid kernel	–	0.695	0.524	0.570	0.660	0.851	0.306
PCA	–	0.951	0.524	0.738	0.864	0.886	0.733
Femoral neck BMD T-score ≤ -2.5	CT attenuation threshold	Sensitivity	Specificity	AUC	Accuracy	Positive Predictive Value (PPV)	Negative Predictive Value (NPV)
Calcaneus	116.188	0.692	0.722	0.705	0.718	0.264	0.942
Talus	281.738	0.538	0.744	0.631	0.718	0.233	0.918
Navicular	298.246	0.769	0.633	0.682	0.650	0.233	0.950
Cuboid	124.764	0.692	0.578	0.595	0.592	0.191	0.929
Lateral cuneiform	201.863	0.538	0.822	0.666	0.786	0.304	0.925
Intermediate cuneiform	424.880	0.923	0.378	0.631	0.447	0.176	0.971
Medial cuneiform	257.709	0.692	0.611	0.626	0.621	0.205	0.932
SVM with linear kernel	–	0.615	0.933	0.821	0.893	0.571	0.944
SVM with RBF kernel	–	0.923	0.989	0.964	0.981	0.923	0.989
SVM with sigmoid kernel	–	0.923	0.378	0.568	0.447	0.176	0.971
PCA	–	0.308	0.978	0.643	0.893	0.667	0.907
Femoral neck BMD T-score < -1	CT attenuation threshold	Sensitivity	Specificity	AUC	Accuracy	Positive Predictive Value (PPV)	Negative Predictive Value (NPV)
Calcaneus	122.043	0.543	0.970	0.775	0.680	0.974	0.500
Talus	349.638	0.786	0.636	0.750	0.738	0.821	0.583
Navicular	313.437	0.629	0.788	0.752	0.680	0.863	0.500
Cuboid	115.516	0.443	0.939	0.702	0.612	0.939	0.443
Lateral cuneiform	249.764	0.629	0.818	0.760	0.689	0.880	0.509
Intermediate cuneiform	380.160	0.643	0.788	0.748	0.689	0.865	0.510
Medial cuneiform	245.128	0.500	0.848	0.713	0.612	0.875	0.444
SVM with linear kernel	–	0.757	0.879	0.857	0.796	0.930	0.630
SVM with RBF kernel	–	0.786	0.970	0.923	0.845	0.982	0.681
SVM with sigmoid kernel	–	0.614	0.667	0.628	0.631	0.796	0.449
PCA	–	0.843	0.636	0.740	0.777	0.831	0.656

BMD, bone mineral density; SVM, support vector machine; RBF, radial basis function; PCA, principal components analysis.