# Image Registration and Analysis within quantitative MRI to improve estimation of brain parenchymal fraction

University essay from Linköpings universitet/Institutionen för medicinsk teknik

Keywords: Image Registration; quantitative MRI;

Abstract: In certain neuro-degenerative diseases likemultiple sclerosis (MS), the rate of brain atrophy can be measured by monitoring the brain parenchymal fraction (BPF) in such patients. The BPF is defined as the ratio of brain parenchymal volume (BPV, defined as the total volume of gray matter tissue, white matter tissue and other unidentified tissue) and intracranial volume (ICV, the total volume of the skull). It can be represented by the formula in equation 1: $\small BPF = \frac {PBV}{ICV} \; \; \; \; (1)$ A complication with this measure is that the BPF is affected by the presence of edema in the brain, which leads to swelling and hence may obscure the true rate of brain atrophy. This leads to uncertainty when establishing “normal values” of BPF when analyzing different magnetic resonance imaging (MRI) scans of the same patient. Another problem is that different MRI scans of the same patient cannot be compared directly, due to the fact that the head of the patient will be in a different position for every scan. The SyMRI software used in this master thesis has the functionality to perform brain tissue characterization and measurement of brain volume, given a number of MR images of a patient. Using tissue properties such as longitudinal relaxation time (T1), transverse relaxation time (T2) and proton density (PD), each voxel in a volume can be classified to belong to a certain tissue type. From these measurements, the intracranial volume, brain volume, white matter, gray matter and cerebrospinal fluid volumes can easily be estimated. In this master thesis, the BPF of several patients were analyzed based on quantitative MRI (qMRI) images, in order to identify the change of BPF due to the presence of edema over time. Volumes obtained from the same patients at different time points were aligned (registered), such that the BPF can be easily compared between years. A correlation analysis between the BPF and R1, R2 and PD was performed (R1 is the longitudinal relaxation rate defined as 1/T1 relaxation time and R2 Is transverse relaxation rate defined as 1/T2 relaxation time) to investigate if any of these variables can explain the change in BPF. The results show that due to image registration, and removing some of the slices from the top and bottom of the head, the BPF of the patients was corrected to a certain extent. The change in the mean BPF of each patient over four years was less than 1% post registration and slice removal. However, the decrease in standard deviation was between 6.9% to 52% after registration and removing of slices. The BPF of the follow-up years also came closer to the initial BPF value measured in the first year. The statistical analysis of the BPF and R1, R2 and PD, showed a very low correlation (0.1) between BPF and PD, and intermediate correlations between BPF and R1, R2 (0.385 and -0.51, respectively). Future work will focus on understanding how these results relate to edema.