. Author manuscript; available in PMC: 2014 Dec 1.

Published in final edited form as: Neuroimage. 2013 Jun 21;83:10.1016/j.neuroimage.2013.06.033. doi: 10.1016/j.neuroimage.2013.06.033

Table 5.

Comparison of MRI and clinical measures for prediction of MCI conversion to AD

Method	Measures	Classifier	ACR	AUC	p-value
MRI: whole brain	volume+thickness	LLE+LDA	0.68	0.72	–

MRI: ROI	hippocampus		0.66	0.69	0.19
	hippocampus +entorhinal corex	LDA	0.65	0.69	0.26
	entorhinal cortex		0.61	0.62	0.08

MRI: whole brain	volume+thickness	SVM (Gaussian)	0.61	0.62	< 0.001

neuropsychological scores	ADAS-Cog11+LDEL+CDR+MMSE		0.62	0.69	0.27
	ADAS-Cog11		0.59	0.67	0.14
	LDEL	LDA	0.60	0.61	0.01
	CDR		0.56	0.52	< 0.001
	MMSE		0.57	0.54	< 0.001

MRI: whole brain	volume+thickness	SVM (linear)	0.53	0.58	0.002
MRI: whole brain	volume+thickness	PCA+LDA	0.51	0.53	< 0.001

The results are ranked by accuracy values from high to low.

p-values indicate prediction performance compared with LLE.

All predications used a LDA classifier. ROI = region of interest; PCA = principal component analysis; all other abbreviations are explained in the text.