Thirty-six subjects with subjective cognitive decline and thirty-three healthy controls without subjective cognitive decline were recruited retrospectively from among the patients who had visited the department of neurology at Inha University Hospital between January 2008 and December 2010. The subjects with subjective cognitive decline were 50 years or older and were diagnosed by the criteria of the Subjective Cognitive Decline Initiative.4 They complained of self-experienced persistent decline in cognitive capacity in comparison with a previously normal status and had scores more than 1.0 standard deviation below age and education-adjusted normative means on all subtests of the Seoul Neuropsychological Screening Battery-Dementia version.12 They had undergone a brain MRI scan including 3D T1-weighted spoiled gradient recalled echo (SPGR) imaging. The normal control subjects without subjective cognitive decline were selected from among the patients who had visited the neurology clinic because of chronic headache or dizziness and had undergone a brain MRI scan including 3D T1-SPGR imaging between January 2008 and December 2010. The control subjects were at least 50-years-old and did not complain of self-experienced persistent decline in cognitive capacity in comparison with a previously normal status and any impairment in activities of daily living. They also did not have any of 28 diseases or a history suggestive of a decrease in cognitive function.13 They included the following: stroke or transient ischemic attack, seizures, Parkinson's disease, multiple sclerosis, cerebral palsy, Huntington's disease, encephalitis, meningitis, brain surgery, surgery to clear arteries to the brain, diabetes that required insulin for control, hypertension that was not well controlled, cancer other than skin cancer diagnosed within the past three years, shortness of breath while sitting still, use of home oxygen, heart attack with changes in memory, walking, or solving problems lasting at least 24 hours, kidney dialysis, liver disease, hospitalization for mental or emotional problems in the past five years, current use of medications for mental or emotional problems, alcohol consumption greater than three drinks each day, abuse of drugs in the past five years, treatment for alcohol abuse in the past five years, unconsciousness for more than one hour other than during surgery, overnight hospitalization because of a head injury, illness causing a permanent decrease in memory or other mental functions, trouble with vision that impairs reading ordinary print even with glasses on, and difficulty understanding conversations because of hearing problems even if wearing a hearing aid. They were matched randomly for age, gender, and education with subjects with subjective cognitive decline.

Patients with the following diseases or conditions were excluded: severe or unstable systemic diseases; abnormal laboratory tests such as vitamin B₁₂ or folate deficiency, positive syphilis serology, and uncontrolled thyroid disease; a major neurological disease such as Parkinson's disease, normal pressure hydrocephalus, seizure, and stroke; alcoholism or drug abuse; the Korean version of Geriatric Depression Scale score above 18,14 major depression, or psychiatric diseases; and severe white matter hyperintensities (Fazekas scale 3),15 any lacunes, cerebral hemorrhages, cortical stroke, or brain tumors on brain MRI. This study was approved by the Institutional Review Board of Inha University Hospital.

SPGR imaging was performed using a 1.5-T GE Signa MRI scanner (signal HDX, General Electric, Milwaukee, WI, USA) with the following imaging parameters: repetition time=11.2 ms, echo time=4.9 ms, field of view=240×240 mm, slice thickness=1.2 mm, no interslice gap, number of excitation=1, and acquisition matrix=250×160.

All images were saved in Digital Imaging and Communications in Medicine format and changed to an appropriate format for voxel based morphometry (VBM) using MRIcro. VBMs were performed using SPM5 software (http://www.fil.ion.ucl.ac.uk/spm/software/spm5/). We used the standard template that was provided by the Montreal Neurological Institute to perform spatial normalization with non-linear transformation. The purpose of performing this step was to correct for global differences in brain shape. Normalized images for each subject were segmented into gray and white matter and CSF using the default SPM brain tissue prior probability maps. After normalization and segmentation, smoothing was performed with a 12-µL full-width at half-maximum Gaussian kernel for preprocessing. After image processing, voxel-based comparisons between the two groups were made using two-sample t-tests. Age, gender, educational levels, and total intracranial volume (TIV), obtained automatically using SPM5, were used as covariates. Only the regions that differed in more than 100 voxels between the two groups were analyzed. Areas with voxel levels of p<0.005, uncorrected, were regarded as significant. The x, y, z coordinates of the areas of significant correlation obtained from the analyses were first converted into Talairach coordinates and then the specific anatomy region and the Brodmann area were identified using the Talairach Daemon Client.

Demographic and clinical characteristics were compared using student t-tests for continuous variables and a chi-square test for categorical variables. The effect of age and subjective cognitive decline on the gray matter volumes was tested by multiple linear regression method. Significance for all tests was set at α=0.05, two-tailed. All statistical analyses were performed using SPSS 19.0 (SPSS Inc., Chicago, IL, USA).