Abstract WMP57: Fully Automated CT-based Quantification Of Microangiopathic Density Reduction In White Matter And Comparison To Gold Standard MRI
Purpose: Severity of white matter (WM) lesion load is difficult to quantify precisely in computed tomography (CT) even though it is the most frequently used imaging modality for brain. This pilot study addressed the need for reliable automated observer-independent quantification of white matter disease in CT. The purpose was to present and evaluate a CT-based automated rater independent method for assessment of microangiopathic WM changes.
Methods and Materials: A probabilistic WM-tissue-map in standad MNI-152 space was obtained from 600 normal MRI scans from two large population studies (published previously). Robust registration of the WM-tissue-map to individual CT space was accomplished by affine linear registration with non-linear refinement (FSL4.1). The tissue- specific density (Hounsfield Unit, HU) within WM-space of the CT image was determined by the mean of all voxel densities weighted by WM content: Σ (HUxyz × Pxyz (WM))/ Σ (Pxyz (WM) ; (HUxyz = density of voxelxyz ; Pxyz = partial WM content at voxelxyz). The reduction of HU over WM-space in 40 CT images with visible WM disease was correlated with gold standard MR-based WM lesion volume measurements.
Results: Automated WM-specific segmentation of brain CT was reliable in 40 cases with varying occurrence of WM-disease. Microangiopathic reduction of density within WM-space showed high correlation with MRI FLAIR-based WM-lesion volume (Pearson correlation coefficient 0.87).
Conclusion: Automated quantification of density reduction within WM-space in CT images is feasible and may be used as a surrogate for gold standard MR based WM lesion load. The presented method needs further validation with larger datasets and different CT scanner protocols.
- © 2012 by American Heart Association, Inc.