Pertama ialah analisis demografi untuk mendapatkan gambaran keseluruhan jantina, umur, bilangan lesi dan saiz lesi. Seterusnya, kajian tentang kebolehubahan intra dan antara subjek dilakukan bagi mereka yang mempunyai 10 lesi dan ke atas (≥10), (n = 8). Akhirnya, perbandingan FA dan ARC dilakukan untuk menilai keterukan perubahan tisu leukoaraiosis antara subjek dengan lesi yang besar dan sedikit dan mereka yang mempunyai lesi yang sangat kecil dan banyak tetapi dengan jumlah jumlah lesi yang sama.
Didapati bahawa subjek dengan banyak tompok lesi kecil menunjukkan nilai FA yang lebih rendah dan nilai LNR yang lebih tinggi berbanding dengan tompok lesi yang sedikit. Ini menunjukkan bahawa mereka yang mempunyai banyak tompok lesi kecil mempunyai kerosakan tisu yang lebih teruk berbanding mereka yang mempunyai sedikit tompok lesi besar. Pertama ialah analisis demografi untuk mendapatkan gambaran keseluruhan jantina, umur, bilangan bintik lesi dan saiz lesi.
Subsequently, intra- and inter-individual variability was investigated for those with 10 lesion sites and more (≥10), (n = 8). There are variations in FA and LNR values across lesion sizes within subjects with the smallest lesion receiving lower FA and higher LNR values and the largest lesion receiving a small difference between FA and LNR values. Finally, a comparison of FA and LNR values was performed to assess the severity of leukoaraiosis tissue changes between subjects with few major lesions and those with many lesions but with similar total lesion volume.
Subjects with very small lesions were found to show lower FA values and higher ARC values compared to those with few large lesions, indicating that those with very small lesions have more severe tissue damage than those few large lesions.
INTRODUCTION INTRODUCTION
Introduction
2012) analyzed that this method projects 3D trajectories of fiber pathways and connection patterns between different brain systems in vivo.
Research problems
DTI can derive a parameter based on the primary diffusion eigenvector to obtain three-dimensional (3D) fiber bundles that are the white matter pathway. The assessment involves the characterization of leukoaraiosis in a specific region using information obtained from DTI maps. Leukoaraiosis is affected by various risk factors and mechanisms, and it is assumed that the severity of tissue destruction is not similar in different regions, different ages and different sexes.
This research will analyze the correlation between FA and LNR and also, to study the degree of white matter in the brain with few large lesions and many small lesions. DTI index values are measured in leukoaraiosis regions, as well as in normal white matter (NAWM) in different brain regions. 1.3(a) Are there any differences in DTI indices of corpus callosum fiber bundles between subjects with and without leukoaraiosis in frontal and occipital white matter areas.
1.3(b) In subjects who have many leukoaraiosis spots, to what extent there is intra- and inter-individual variability in leukoaraiosis. 1.3(c) Do subjects with many small lesions and those with few large lesions have the same degree of tissue damage.
Justification of study
Objectives
- General objective
- Specific objectives
1.5.2(d) To compare the severity of leukoaraiosis between FA and ARC of the leukoaraiosis between subjects who have few large lesions and those with very small lesions but with similar total lesion volume.
Scope of research
White matter of the brain
Principles of diffusion magnetic resonance imaging
However, the proton spins will not be transformed by the second gradient if the water molecules move in the direction of the gradients during the interval between the two applied gradients. This means that they are out of phase with respect to the hydrogen nuclei of the stationary water molecules. MR signal intensity is generated by proton density (PD), longitudinal relaxation time (T1), transverse relaxation time (T2), physical properties of water molecules and diffusion coefficient (D) (Mori & Zhang, 2006).
The variation of the diffusion sequence to the movement of water molecules can be varied by adjusting the gradient amplitude, the duration of the sensitizing gradients and the time between the gradient pair (de Figueiredo et al., 2011).
Principles of diffusion tensor imaging
- Anisotropic and isotropic diffusion
- DTI Scalars
- Fiber tractography
For example, the CSF spaces in the human brain have a high degree of isotropy due to their microarchitecture. The eigenvalues are the values corresponding to the apparent diffusion coefficient (ADC) of the water molecules in each voxel along the direction of the eigenvectors. The eigenvectors represent the diffusivity along the principal direction and two perpendicular to each image voxel (Wheeler-Kingshott et al. 2012).
The simplest scalar derivation from DTI is the average of the three eigenvalues λ1, λ2, and λ3, called mean diffusivity (MD) (Le Bihan et al., 2012). MD measures the average magnitude of molecular displacement by diffusion for a tensor, while the sum of tensor eigenvalues is represented as Trace (D) (Basser et al., . 2002). Meanwhile, O'Donnel & Westin (2012) argued that this average refers to the apparent diffusion coefficient (ADC) map. The FA parameter measures the fraction of diffusion that is anisotropic and has a range from 0 to 1.
This parameter shows the amount of tissue organization and location contained within a single white matter tract within voxel. FA can thus be regarded as a parameter of white matter level (O'Donnel & Westin, 2012). FA is also able to form color maps that indicate the direction of water diffusion (Pajevic & Pierpaoli, 2000).
AD is the longest eigenvector representing the rate of water diffusion parallel to the white matter tract (Chanraud et al. 2010). Both parameters are specific markers for assessing the state of the axon and myelin of neuronal fibers (Aung et al., 2013). The most commonly used scalar indices for the general assessment of white matter level are MD and FA (Rokem et al., 2017; Soares et al., 2013).
Fiber tractography is a method to assess the location of white matter tracts integrated into the navigation system (Ciccarelli et al., 2008). The local diffusion characteristic within is described by a second-order tensor for obtaining the diffusion properties within a voxel, which is calculated with the Stejskal-Tanner equation (Kuhnt et al., 2013). A single predominant fiber orientation and part with those local orientations that characterize each imaging voxel in the fiber tractography (Jeurissen et al., 2017).
Clinical significance of DTI in brain imaging
- Leukoaraiosis
Leukoaraiosis (LA) is a white matter pathology in the brain that appears as hyperintense white matter on T2-weighted MRI brain scans or CT scans. As can be seen in Figure 2.5, the term "leukoaraiosis" is originally from Greek, as "leuko" referred to white and "araiosis" referred to rarity (O'Sllivan, 2008). In general, the terms were often used synonymously to describe LA, such as white matter lesion (WML), white matter hyperintensity (WMH), and white matter changes (WMC).
All these terms are categorized as cerebral small vessel disease (CSVD) which refers to the presence of white matter patches in the brain (Wardlaw et al., 2013). Other few terms that were also used in previous studies are white matter disease (WMD), white matter injury, and ischemic white matter disease. LA is often seen in the elderly and white matter changes associated with increased age.
It is also commonly associated with vascular risk factors such as hypertension, cognitive decline (Zhao et al., 2019) and diabetes mellitus (Zupan, 2016). Smith (2010) revealed that LA may be a marker of stroke as it is commonly seen in stroke patients. Furthermore, the neuropathological studies revealed that LA was associated with demyelination, gliosis, axonal loss and perivascular spaces (Zupan, 2016).
Data acquisition
- Inclusion criteria
- Exclusion criteria
The sample size was calculated using the sample size calculator software (https://wnarifin.github.io/ssc_web.html), based on the comparison of two means for study power of 80% and confidence interval of 95%. Subjects were reported to have been recruited based on the following inclusion and exclusion criteria.
Data analysis
Placement of ROI
Introduction
Method of analysis
Results and discussion
- Gender and number of lesions
- Gender and lesion sizes
However, for the youngest subject it was 39 years old and the only subject coming from 30 to 39 years old. In Figure 4.1, for both groups of male and female subjects, most subjects had 1 to 10 lesion spots compared to subjects with a number of lesion spots above 10. The number of lesion spots from 1 to 9 is more in subjects female because the number of female subjects is more than that of male subjects.
In addition, independent T-test was used to determine the association between gender and number of lesions. Thus, there was no significant difference in the average number of lesions between men and women. A previous study found no gender differences in the incidence of leukoaraiosis (Grueter and Schulz revealed that women have a higher incidence of leukoaraiosis.
