One of the important characteristics of Alzheimer’s disease(AD) is the iron accumulations in the brain¹.A quantitative susceptibility map(QSM) technique can be used to quantify the iron contents. Therefore, QSM may be useful to evaluate the AD brain. The objective of this study, therefore, was to systematically investigate the brain changes in the subjects with cognitive normal(CN), mild cognitive impairment(MCI) and AD by using both voxel-by-voxel based and ROI-based analysis for both QSM and gray matter volume(GMV) data.Nineteen CN(mean age = 65.74, 14 females and 5 males), 19 MCI(mean age = 71.84, 14 females and 5 males), and 19 AD subjects(mean age = 72.84, 17 females and 2 males) were participated after informed consent. For the QSM data, a 3D gradient-echo(FFE) sequence was run with seven echoes(first TE/△TE/final TE=3.4/5.9/39 ms). For an image registration, for generating anatomical templates, and for evaluating GMV, sagittal structural 3D T1-weighted(3DT1W) images were acquired with the magnetization-prepared rapid acquisition of gradient echo (MPRAGE) sequence(1mm isotropic voxel). QSM data were obtained with the morphology enabled dipole inversion (MEDI) software². For the QSM data, the susceptibility value in each voxel was subtracted by the reference values which were estimated by the average of the susceptibility values in the bilateral posterior ventricular region for each subject. The Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra(DARTEL) toolbox and Statistical Parametric Mapping Version 8(SPM8) were used to post-processing. A voxel-based statistical group analysis was performed for QSM data and GMV using a one-way analysis of variance(ANOVA) test with the gender and age as covariates. ROIs(eight well-known iron accumulation regions; hippocampus, amygdala, globus pallibus, precuneu, pulvinar, putamen, red nucleus and thalamus³/ five well-known amyloid β accumulation regions; neocortex, allocortex, entorhinal cortex, anterior cingulate cortex and posterior cingulate cortex⁴)-based statistical group analysis was also performed for QSM data and GMV. Finally, the receiver operating characteristic(ROC) curve analysis was performed to demonstrate sensitivity and specificity of GMVs and QSM to differentiate among the subject groups for each ROI.Fig.1 demonstrates the differences of voxel-based statistical analysis of GMV (A) and QSM (B) values between the CN and AD groups as well as the mean values of percentage changes of GMV (C) and QSM (D) using ROIs-based statistical analysis on the MCI and AD against the CN group. For the voxel-based analyses, decreased GMV in AD compared with CN was found at some areas, but no differences between other groups. Increased QSM values in AD compared with CN were found several brain areas, included in the right parahippocampal gyrus, but no differences between other groups. For the ROI-based analyses, GMV was decreased in MCI and AD at several areas compared to the CN group. However, GMV was increased in the MCI and AD groups at pulvinar, red nucleus, thalamus and allocortex regions compared to the CN group. QSM values were increased in the MCI and AD groups compared to the CN group for all ROIs. Results of ROC curves analysis showed that QSM values were significantly differentiated among the three groups. QSM values were differentiated between CN and MCI groups in the in the neocortex(AUC=0.722, p=0.0091), allocortex(AUC=0.772, p=0.0005), entorhinal cortex(AUC=0.681, p=0.0453), anterior cingulate cortex(AUC=0.739, p=0.0037), posterior cingulate cortex(AUC=0.742, p=0.0033) regions. However, GMV values were only differentiated between CN and MCI/AD group as well as between MCI and AD, but not differentiated between CN and MCI groups.Quantification of iron concentrations in vivo is instrumental for understanding the role of irons in many neurological diseases. From the comparison between the QSM values and GMVs, we found higher sensitivity of QSM data than GMV data. For the QSM data, the susceptibility values increased in eight iron accumulation and five amyloid β accumulation regions from CN to MCI and to AD. Iron is a paramagnetic substance and contributes to dephasing of the signals so AD is expected to have the most iron plaques⁵. In particular, the QSM values are more effective to evaluate in the precuneus and neocortex regions than the GMVs between the CN and MCI groups. The QSM technique offers more efficiency information of the susceptibility effects for early diagnosis for AD than the GMV estimation.The susceptibility effects of the QSM data in the precuneus and neocortex region was attribute to the iron accumulation in patients. The QSM data proved to be more effective to evaluate the early stage for AD than GMVs. Therefore, the susceptibility effects in the QSM can be used to an early diagnosis for AD. Furthermore, the QSM technique can be used as an imaging biomarker to evaluate AD.