Magnetic resonance imaging (MRI) and MRI relaxometry were used to investigate disturbed brain myelination in 18q- syndrome, a disorder characterized by mental retardation, dysmorphic features, and growth failure. T1-weighted and dual spin-echo T2-weighted MR images were obtained, and T1 and T2 parametric image maps were created for 20 patients and 12 controls. MRI demonstrated abnormal brain white matter in all patients. White matter T1 and T2 relaxation times were significantly prolonged in patients compared to controls at all ages studied, suggesting incomplete myelination. Chromosome analysis using fluorescence in situ hybridization techniques showed that all patients with abnormal MRI scans and prolonged white matter T1 and T2 relaxation times were missing one copy of the myelin basic protein (MBP) gene. The one patient with normal-appearing white matter and normal white matter T1 and T2 relaxation times possessed two copies of the MBP gene. MRI and molecular genetic data suggest that incomplete cerebral myelination in 18q- is associated with haploinsufficiency of the gene for MBP.

White matter (WM) and gray matter (GM) were accurately measured using a technique based on a single standardized fuzzy classifier (FC) for each tissue. Fuzzy classifier development was based on experts' visual assessments of WM and GM boundaries from a set of T1 parametric MR images. The fuzzy classifier method's accuracy was validated and optimized by a set of T1 phantom images that were based on hand-detailed human brain cryosection images. Nine sets of axial T1 images of varying thickness equally distributed throughout the brain were simulated. All T1 data sets were mapped to the standardized FCs and rapidly segmented into WM and GM voxel fraction images. Resulting volumes revealed that, in most cases, the difference between measured and actual volumes was less than 5%. This was consistent throughout most of the brain, and as expected, the accuracy improved to generally less than 2% for the 1-mm simulated brain slices.

We accurately measured white matter (WM) and gray matter (GM) from three-dimensional (3D) volume studies, using a fuzzy classification technique. The new segmentation method is a modification of a recently published method developed for T1 parametric images. 3D MR images were transformed into pseudo forms of T1 parametric images and segmented into WM and GM voxel fraction images with a set of standardized fuzzy classifiers. This segmentation method was validated with synthesized 3D MR images as phantoms. These phantoms were developed from cryosectioned human brain images located in the superior, middle, and inferior regions of the cerebrum. Phantom volume measurements revealed that, generally, the difference between measured and actual volumes was less than 3% for 1.5-mm simulated brain slices. The average cerebral GM/WM ratio calculated from 3D MR studies in four subjects was 1.77, which compared favorably with the estimate of 1.67 derived from anatomical data. Results indicate that this is an accurate and rapid method for quantifying WM and GM from Tl-weighted 3D volume studies.

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