Brain atrophy progression measured from registered serial MRI: validation and application to Alzheimer's disease

In this paper, we validate the brain boundary shift integral (BBSI) as a measure of brain atrophy and demonstrate its application in Alzheimer's disease (AD). Nineteen normal subjects and nine patients with AD underwent serial three-dimensional MRI (6- to 30-month scan intervals). Repeat studies were registered to the baseline studies. The accuracy of the BBSI was assessed by comparison with simulated atrophy and with segmentation; it was also tested for reproducibility, linearity, and its ability to discriminate patients with AD from healthy controls. The BBSI correlated closely with simulated volumes of atrophy (r = 1.000). The mean absolute difference between repeat measures was 1.51 ml or .13% of mean brain volume. Rates of atrophy from all 18 AD scan pairs were widely separated from those of all 31 control pairs. In matched subgroups, the mean (SD) annual rate of brain atrophy in nine controls was .24% (.32%), compared with 2.78% (.92%) in nine patients with AD. We conclude that the BBSI is a linear and highly reproducible measure of atrophy with potential uses in the early diagnosis and measurement of progression in Alzheimer's disease.     

The boundary shift integral: an accurate and robust measure ofcerebral volume changes from registered repeat MRI

We propose the boundary shift integral (BSI) as a measure of cerebral volume changes derived from registered repeat three-dimensional (3-D) magnetic resonance (MR) [3D MR] scans. The BSI determines the total volume through which the boundaries of a given cerebral structure have moved and, hence, the volume change, directly from voxel intensities. We found brain and ventricular BSI's correlated tightly (r=1.000 and r=0.999) with simulated volumes of change. Applied to 21 control scan pairs and 11 scan pairs from Alzheimer's disease (AD) patients (mean interval 386 days) the BSI yielded mean brain volume loss of 1.8 cc (controls) and 34.7 cc (AD); the control group was tightly bunched (SD=3.8 cc) and there was wide group separation, the group means differing by 8.7 control group standard deviations (SDs). A measure based on the same segmentation used by the BSI yielded similar group means, but wide spread in the control group (SD=13.4 cc) and group overlap, the group means differing by 2.8 control group SDs. The BSI yielded mean ventricular volume losses of 0.4 cc (controls) and 10.1 cc (AD). Good linear correlation (r=0.997) was obtained between the ventricular BSI and the difference in their segmented volumes. We conclude the BSI is an accurate and robust measure of regional and global cerebral volume changes     

MR image texture analysis applied to the diagnosis and tracking of Alzheimer''s disease

We assess the value of magnetic resonance (MR) image texture in Alzheimer's disease (AD) both as a diagnostic marker and as a measure of progression. T1-weighted MR scans were acquired from 40 normal controls and 24 AD patients. These were split into a training set (20 controls, 10 AD) and a test set (20 controls, 14 AD). In addition, five control subjects and five AD patients were scanned repeatedly over several years. On each scan a texture feature vector was evaluated over the brain; this consisted of 260 measures derived from the spatial gray-level dependence method. A stepwise discriminant analysis was applied to the training set, to obtain a linear discriminant function. In the test set, this function yielded significantly different values for the control and AD groups (p < 10(-4)) with only small group overlap; a classification rate of 91% was obtained. For the repeatedly scanned control subjects, the median increment in the discriminant function between successive scans of 0.12 was not significantly different from zero (p > 0.05); for the repeatedly scanned AD patients the corresponding median increment of 1.4 was significantly different from zero (p < 0.05). MR image texture may be a useful aid in the diagnosis and tracking of Alzheimer's disease.