Common MRI acquisition non-idealities significantly impact the output of the boundary shift integral method of measuring brain atrophy on serial MRI

Abstract

Measuring rates of brain atrophy from serial magnetic resonance imaging (MRI) studies is an attractive way to assess disease progression in neurodegenerative disorders, particularly Alzheimer's disease (AD). A widely recognized approach is the boundary shift integral (BSI). The objective of this study was to evaluate how several common scan non-idealities affect the output of the BSI algorithm. We created three types of image non-idealities between the image volumes in a serial pair used to measure between-scan change: inconsistent image contrast between serial scans, head motion, and poor signal-to-noise (SNR). In theory the BSI volume difference measured between each pair of images should be zero and any deviation from zero should represent corruption of the BSI measurement by some non-ideality intentionally introduced into the second scan in the pair. Two different BSI measures were evaluated, whole brain and ventricle. As the severity of motion, noise, and non-congruent image contrast increased in the second scan, the calculated BSI values deviated progressively more from the expected value of zero. This study illustrates the magnitude of the error in measures of change in brain and ventricle volume across serial MRI scans that can result from commonly encountered deviations from ideal image quality. The magnitudes of some of the measurement errors seen in this study exceed the disease effect in AD shown in various publications, which range from 1% to 2.78% per year for whole brain atrophy and 5.4% to 13.8% per year for ventricle expansion (Table 1). For example, measurement error may exceed 100% if image contrast properties dramatically differ between the two scans in a measurement pair. Methods to maximize consistency of image quality over time are an essential component of any quantitative serial MRI study.

Figure 1. Standard SPGR Image

Example of a scan used as base in the analyses.

Figure 2. Effects of change in image contrast on BSI calculations

(a) The top row, going from left to right, are the images of the 5 degree flip angle, 12 degree flip angle and fast spin echo SPGR scan. (b) Below each scan mentioned above is its BSI object map overlaid on the base SPGR scan. In each case the BSI object map pictorially illustrates those pixels where volume difference was measured between the base and the second altered scan in the pair. The red and green pixels represent a color map of BSI computed change in volume superimposed on the baseline grey scale MRI scan. Red indicates shrinkage and green expansion of the color annotated pixel

Figure 3. Effects of Motion on BSI calculations

(a) The top row, going from left to right, are SPGR images with increasing motion. (b) Below each respective image is its BSI object map overlaid on the base SPGR scan. In each case the BSI object map pictorially illustrates those pixels where volume difference was measured between the base and the second altered scan in the pair. The red and green pixels represent a color map of BSI computed change in volume superimposed on the baseline grey scale MRI scan. Red indicates shrinkage and green expansion of the color annotated pixel.

Figure 4. Effects of Noise on BSI calculations

(a) The top row, going from left to right, are SPGR images with increasing noise. (b) Below each respective image is its BSI object map overlaid on the SPGR scan where no noise was added. As noise increases, the BSI brain and ventricle values progressively diverge from zero and suggest increased brain atrophy. In each case the BSI object map is calculated by “subtracting” the second altered scans from the base 25 degree FA bas scan. The red and green pixels represent a color map of BSI computed change in volume superimposed on the baseline grey scale MRI scan. Red indicates shrinkage and green expansion of the color annotated pixel.