Alzheimer's Research & Therapy

Table 3 The prediction results of the development and reversion of MCI based on a structural covariance network

From: Hippocampus-centred grey matter covariance networks predict the development and reversion of mild cognitive impairment

Predictor variable	Normal-to-MCI progression			MCI-to-normal reversion
Predictor variable	AUC	SEN	SPE	AUC	SEN	SPE
BABRI sample
scDN	0.767 (± 0.109)	0.726	0.747	0.722 (± 0.182)	0.500	0.990
scFN	0.692 (± 0.080)	0.960	0.394	0.745 (± 0.128)	0.440	0.990
scHN	0.792 (± 0.087)	0.860	0.707	0.736 (± 0.151)	0.480	0.990
ADNI sample
scDN	0.766 (± 0.090)	0.774	0.667	0.750 (± 0.089)	0.796	0.636
scFN	0.765 (± 0.096)	0.897	0.556	0.701 (± 0.075)	0.751	0.636
scHN	0.785 (± 0.092)	0.827	0.667	0.809 (± 0.093)	0.679	0.818

Abbreviations: AUC area under the curve, SEN sensitivity, SPE specificity, scDN structural covariance of the default network, scFN structural covariance of the frontoparietal control network, scHN structural covariance of the hippocampal network

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ISSN: 1758-9193

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