Maria dC Valdes Hernandez, Natalie A Royle, Michael R Jackson, Susana M Maniega, Lars Penke, Mark E Bastin, Ian J Deary, and Joanna M Wardlaw (2012)

Color fusion of magnetic resonance images improves intracranial volume measurement in studies of aging

Open Journal of Radiology, 2:1-9.

Background: Comparison of intracranial volume (ICV) measurements in different subpopulations offers insight into age-related atrophic change and pathological loss of neuronal tissue. For such comparisons to be meaningful the accuracy of ICV measurement is paramount. Color magnetic resonance images (MRI) have been utilised in several research applications and are reported to show promise in the clinical arena. Methods: We selected a sample of 150 older community-dwelling individuals (age 71 to 72 years) representing a wide range of ICV, white matter lesions and atrophy. We compared the extraction of ICV by thresholding on T2*-weighted MR images followed by manual editing (reference standard) done by an analyst trained in brain anatomy, with thresholding plus computational morphological operations followed by manual editing on a framework of a color fusion technique (MCMxxxVI) and two automatic brain segmentation methods widely used, these last three done by two image analysts. Results: The range of ICV was 1074 to 1921 cm3 for the reference standard. The mean difference between the reference standard and the ICV measured using the technique that involved the color fusion was 2.7%, while it was 5.4% compared with any fully automatic technique. However, the 95% confidence interval of the difference between the reference standard and each method was similar: it was 7% for the segmentation aided by the color fusion and was 7% and 8.3% for the two fully automatic methods tested. Conclusion: For studies of aging, the use of color fusion MRI in ICV segmentation in a semi-automatic framework delivered best results compared with a reference standard manual method. Fully automated methods, while fast, all require manual editing to avoid significant errors and, in this post-processing step color fusion MRI is recommended.