Abstract
The high spatial resolution of 7T MRI enables us to identify subtle volume changes in brain structures, providing potential biomarkers of mental disorders. Most volumetric approaches require that similar intensity values represent similar tissue types across different persons. By applying colour-coding to T1-weighted MP2RAGE images, we found that the high measurement accuracy achieved by high-resolution imaging may be compromised by inter-individual variations in the image intensity. To address this issue, we analysed the performance of five intensity standardisation techniques in high-resolution T1-weighted MP2RAGE images. Twenty images with extreme intensities in the GM and WM were standardised to a representative reference image. We performed a multi-level evaluation with a focus on the hypothalamic region—analysing the intensity histograms as well as the actual MR images, and requiring that the correlation between the whole-brain tissue volumes and subject age be preserved during standardisation. The results were compared with T1 maps. Linear standardisation using subcortical ROIs of GM and WM provided good results for all evaluation criteria: it improved the histogram alignment within the ROIs and the average image intensity within the ROIs and the whole-brain GM and WM areas. This method reduced the inter-individual intensity variation of the hypothalamic boundary by more than half, outperforming all other methods, and kept the original correlation between the GM volume and subject age intact. Mixed results were obtained for the other four methods, which sometimes came at the expense of unwarranted changes in the age-related pattern of the GM volume. The mapping of the T1 relaxation time with the MP2RAGE sequence is advertised as being especially robust to bias field inhomogeneity. We found little evidence that substantiated the T1 map’s theoretical superiority over the T1-weighted images regarding the inter-individual image intensity homogeneity.
Highlights
BackgroundDr David Kupfer, leading the revision of the world-wide used diagnostic system for mental diseases DSM IV [1], diagnosed “a failure of our neuroscience and biology to give us the level of diagnostic criteria, a level of sensitivity and specificity that we would be able to introduce into the diagnostic manual” [2]
Both techniques that matched the histogram modes improved the homogeneity of the white matter (WM) histograms at the cost of the homogeneity of the grey matter (GM) histograms: piecewise linear histogram matching (PHM) improved the alignment of the target distribution with the reference distribution for the whole-brain WM area as indicated by significant reductions of the average absolute error and the maximum absolute error
In the WM regions of interest (ROIs) it improved the average absolute error alone. These improvements were accompanied by medium to strong increases in both error measures in the whole-brain GM and in the GM ROI, outlining an overall worsening of the GM histogram homogeneity (Table 2)
Summary
BackgroundDr David Kupfer, leading the revision of the world-wide used diagnostic system for mental diseases DSM IV [1], diagnosed “a failure of our neuroscience and biology to give us the level of diagnostic criteria, a level of sensitivity and specificity that we would be able to introduce into the diagnostic manual” [2]. The call for biological markers to replace self-report and exploration could hardly be made clearer To this end, sub-millimetre resolution achieved by 7T magnetic resonance imaging (MRI) holds great potential because it opens the window to small volumes in candidate brain structures of psychiatric patients in vivo. To benefit from the high resolution of 7T MRI, post-processing and subsequent analysis need to be precise In this context we previously established colour-coding as an important tool to ensure high reliability and reasonable time costs of computer-assisted segmentations of the hypothalamus on 7T T1-weighted MR images [3]. Residual interscan intensity variation in the T1-weighted images of the MP2RAGE exists, as we will demonstrate by colour-coding To correct such differences and thereby reduce erroneous variance in the resulting segmentation, the unique intensity scale of each image needs to be standardised
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