Abstract
The aim of this study was to present a model that uses multi-parametric quantitative MRI to estimate the presence of myelin and edema in the brain. The model relates simultaneous measurement of R1 and R2 relaxation rates and proton density to four partial volume compartments, consisting of myelin partial volume, cellular partial volume, free water partial volume, and excess parenchymal water partial volume. The model parameters were obtained using spatially normalized brain images of a group of 20 healthy controls. The pathological brain was modeled in terms of the reduction of myelin content and presence of excess parenchymal water, which indicates the degree of edema. The method was tested on spatially normalized brain images of a group of 20 age-matched multiple sclerosis (MS) patients. Clear differences were observed with respect to the healthy controls: the MS group had a 79 mL smaller brain volume (1069 vs. 1148 mL), a 38 mL smaller myelin volume (119 vs. 157 mL), and a 21 mL larger excess parenchymal water volume (78 vs. 57 mL). Template regions of interest of various brain structures indicated that the myelin partial volume in the MS group was 1.6 ± 1.5% lower for gray matter (GM) structures and 2.8 ± 1.0% lower for white matter (WM) structures. The excess parenchymal water partial volume was 9 ± 10% larger for GM and 5 ± 2% larger for WM. Manually placed ROIs indicated that the results using the template ROIs may have suffered from loss of anatomical detail due to the spatial normalization process. Examples of the application of the method on high-resolution images are provided for three individual subjects: a 45-year-old healthy subject, a 72-year-old healthy subject, and a 45-year-old MS patient. The observed results agreed with the expected behavior considering both age and disease. In conclusion, the proposed model may provide clinically important parameters, such as the total brain volume, degree of myelination, and degree of edema, based on a single qMRI acquisition with a clinically acceptable scan time.
Highlights
Myelin is crucial for efficient signal transmission over long ranges in the nervous system because it increases the speed at which the impulses propagate along the axons
The proposed model for the observed R1, R2, and PDmax σ (PD) values of the brain is visualized in Figure 1: each MRI acquisition voxel is composed of four partial volume compartments: the myelin partial volume VMY, cellular partial volume VCL, free water partial volume VFW, and excess parenchymal water partial volume VEPW
The black dots are placed at the maximum values of the histograms in each direction, generating the 600 maxima defining the structure in the R1–R2–PD space
Summary
Myelin is crucial for efficient signal transmission over long ranges in the nervous system because it increases the speed at which the impulses propagate along the axons. Degradation of myelin impairs the signal transmission, and the nerve may eventually wither, leading to brain atrophy and brain dysfunction. Knowledge of myelin content supports the investigation of early brain development [1, 2]. Accurate myelin measurements are valuable in studies of neurodegenerative diseases, such as multiple sclerosis (MS) [3, 4] and dementia [5,6,7]. Measurements and monitoring of myelin content would provide important information for the diagnosis and prognosis in patients with suspected myelin degradation
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