Recruitment and Characterization of Subjects
Forty-eight subjects are included in this report—24 AD patients and 24 controls who were individually matched with the patients for gender and age (± 4 years) (). Controls and cases ranged in age from 70 to 89 years. Patients with AD and the cognitively normal control subjects for this study were recruited from the Mayo Alzheimer's Disease Center /Alzheimer's Disease Patient Registry. Informed consent was obtained for participation from the subjects or an appropriate proxy.
Characterization of Subjects
Control subjects were recruited from the pool of patients coming to Mayo primary care physicians for a general medical examination. The criteria for cognitively normal controls were 1) no active neurologic or psychiatric disorders and 2) some had ongoing medical problems, however the illnesses or their treatments did not interfere with cognitive function. A control subject was identified for each AD patient and matched by gender, and age ±4 years.
The diagnosis of AD was made according to the NINCDS/ADRDA criteria [14
]. The severity of AD was classified on the basis of the clinical dementia rating (CDR) score [16
]. Eleven patients had very mild disease (CDR = 0.5); 11 patients had mild disease (CDR = 1); and 2 patients had moderate disease severity (CDR = 2). Cases and controls were well matched on education, and by virtue of the study design on age and gender as well(). The number of men in both the case and control groups was 8.
APOE genotyping was performed in all subjects. DNA was extracted from peripheral leukocytes and amplified by polymerase chain reaction [17
]. Polymerase chain reaction products were digested with Hhal
and the fragments were separated by electrophoresis on an 8% polyacrylamide non-denaturing gel. The gel was then treated with ethidium bromide for 30 minutes, and DNA fragments were visualized by UV illumination.
The presence or absence of three vascular risk factors—hypertension, ischemic cardiac disease, diabetes—was assessed by review of the medical records. Subjects were recorded as positive for hypertension, if hypertension or its treatment was identified at any point in time in the medical record. The same criteria were applied to the diagnosis of diabetes. Subjects were considered to have coronary ischemic disease if any of the following diagnoses were identified: angina pectorus, myocardial infarction, coronary bypass surgery, or coronary angioplasty.
The presence or absence of estrogen replacement therapy was documented in all female subjects. The age of menopause was established in each subject and subsequent estrogen replacement therapy was recorded as either present or absent through review of the medical records.
All subjects underwent a MRI examination protocol of the brain within 4 months of their initial clinical assessment. An identical MRI study was repeated 12 or more months after the initial MRI in all subjects, and this was linked with a second clinical assessment. Potential subjects were excluded if either of the MRI studies were of unacceptable diagnostic quality, demonstrated a focal structural abnormality, or if their clinical status changed between the serial MRI examinations (e.g. a control who developed cognitive impairment).
All subjects were imaged at 1.5T (G.E. Signa, Milwaukee, WI) using a standardized imaging protocol. A T1-weighted sagittal set of spin echo images was used to measure total intracranial volume. A 3D volumetric spoiled gradient echo sequence with TR = 27 msec, TE = 9 msec, 124 contiguous partitions, 1.6 mm slice thickness, a 22 × 16.5 cm field of view, 192 views, and 45° flip angle was used to measure the volumes of the hippocampus and temporal horn.
All image processing steps (including boundary tracing) in every subject were performed by the same trained research assistant who was blinded to all clinical information (age, gender and clinical status). The date of each MRI scan was also masked in the image file so that the image processing was done without knowledge of the chronologic ordering of the scans in each pair. This ensured rigorous quality control, completely unbiased data generation, and uniformity in the subjective aspects of image processing across all the subjects in this study.
The 3D MRI data for both MRI scans were interpolated in the slice select dimension to give cubic voxels [18
]. An automated image registration program was employed to coregister the 3D image data set of the first scan to that of the second scan. This program was developed in-house and was based on the principle of minimization of inter scan signal intensity differences across all voxels. The image data of both scan 1 and scan 2 were then interpolated in plane to the equivalent of a 512 × 512 matrix and magnified times two. The voxel size of the fully processed image data was 0.316mm3
. The images of the whole brain were then subvolumed to include the temporal lobes. An intensity inhomogeneity correction algorithm developed in-house was then applied to both MRI scans. After the boundaries of the hippocampi and temporal horns had been delineated on each anatomic slice, the number of voxels in each structure was calculated automatically with a summing region of interest function. These were multiplied by voxel volume to give a numeric value in mm3
The borders of the right and left hippocampi were manually traced with a mouse driven cursor for each slice sequentially from posterior to anterior [18
]. Inplane hippocampal anatomic boundaries were defined to include the CA1-CA4 sectors of the hippocampus proper, the dentate gyrus, and subiculum(). The posterior boundary of the hippocampus was determined by the oblique coronal anatomic section on which the crura of the fornices were identified in full profile. Thus, essentially the entire hippocampus from tail through head was included in these measurements. The entire hippocampal tracing process takes approximately 2 hours per patient. Subdivision of the hippocampus along its antero-posterior axis into three segments labeled head, body, and tail was accomplished as follows: the hippocampal head was defined to encompass those imaging slices extending from the intralimbic gyrus forward to the anterior termination of the hippocampal formation. The posterior margin of the hippocampal head was labeled imaging slice x, and the volume of the hippocampal tail was determined by summing the area of the hippocampus on successive slices beginning from the forniceal crura to slice
. The volume of the body consisted of the sum of areas on successive slices beginning with slice
and extending to slice x-1. This method allowed for assignment of fractional slice areas in the event of an odd number of slices posterior to the hippocampal head.
A region growing autotrace algorithm was employed to define the boundaries of the temporal horns bilaterally(). The signal intensities of temporal lobe white matter adjacent to the temporal horn, as well as CSF in the temporal horn were sampled in multiple places. The signal intensity threshold employed to define the temporal horn boundary was half of the maximum temporal lobe parenchymal signal intensity above background, where background was defined as CSF signal intensity[19
]. The posterior extent of the temporal horn was defined as the same imaging slice used to demarcate the posterior boundary of the hippocampal formation. The anterior boundary of the temporal horn was determined by its full anterior anatomic extent.
The primary endpoint in these analyses was the annualized percent change in hippocampal and temporal horn volume. This was computed as the volume in mm3 of scan 2 minus that of scan 1 divided by structure volume on the scan 1, divided by the duration between the two scans (in years). To compare the annualized percent change between AD cases and controls, the rank sum test was employed. Stepwise regression (stepping up) was employed to identify explanatory variables which might be associated with the volumetric endpoints. The regression analyses were performed separately for each group and also with the groups combined using group as a variable. After identifying significant main effects we looked for two-way interactions. The variables included in the regression analysis were age, gender, presence of hypertension, cardiac ischemic disease, diabetes, estrogen replacement, apolipoprotein E genotype, and duration of clinical followup. Differences in the annualized rate of change between sides (right vs left) and between hippocampal segments (head, body, tail) were assessed with paired t-tests.
In order to assess the reproducibility of the method, 10 young adult volunteers underwent the MRI imaging protocol described above on two separate occasions, separated by 2–4 weeks. The volumes of the hippocampi and temporal horns in both scans of each of the volunteers were then measured as described above. Test-retest measurement reproducibility in 10 young adult volunteers was defined in terms of the coefficient of variation.