Abstract
Brain atrophy measured using structural magnetic resonance imaging (MRI) has been widely used as an imaging biomarker for disease diagnosis and tracking of pathologic progression in neurodegenerative diseases. In this work, we present a generalized and extended formulation of the boundary shift integral (gBSI) using probabilistic segmentations to estimate anatomic changes between 2 time points. This method adaptively estimates a non-binary exclusive OR region of interest from probabilistic brain segmentations of the baseline and repeat scans to better localize and capture the brain atrophy. We evaluate the proposed method by comparing the sample size requirements for a hypothetical clinical trial of Alzheimer's disease to that needed for the current implementation of BSI as well as a fuzzy implementation of BSI. The gBSI method results in a modest but reduced sample size, providing increased sensitivity to disease changes through the use of the probabilistic exclusive OR region.
Highlights
Imaging biomarkers have become a key tool for early detection, differential diagnosis, and disease progression in neurodegenerative diseases in the last decade (Gustaw-Rothenberg et al, 2010)
The mean Percentage Brain Volume Change (PBVC) in controls were quite similar in manualKN-Boundary Shift Integral (BSI), STEPS-KN-BSI, and gBSI for 1.5 T and 3 T scans, some of these differences, less than 0.1% absolute atrophy, were significant using a paired t test
This work presents a generalized BSI method for measuring brain atrophy rates, and we show that it produces a modest but significant reduction in sample sizes needed in clinical trials in comparison with binarised implementation of the BSI
Summary
Imaging biomarkers have become a key tool for early detection, differential diagnosis, and disease progression in neurodegenerative diseases in the last decade (Gustaw-Rothenberg et al, 2010). Using these biomarkers as outcome measures in trials would have the potential to show a disease modifying effect on fewer subjects than standard cognitive tests, with proper enrichment strategies making these useful for predementia trials. FS is based on performing independent tissue segmentation at each time point and build subject-specific average from the time points These analyses can be limited to specific ROIs, such as the entorhinal cortex or the hippocampus, to better localize where atrophy is occurring
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