Objective To investigate the feasibility of magnetic resonance diffusion tensor imaging (MRDTI) technique in displaying myocardial fiber architecture. Methods In five ex vivo swine heart, diffusion tensor imaging (DTI) was acquired in 25 directions within 2 hours after excision. The myocardial fiber was reconstructed by using brain white matter tractography algorithm to display its course, distribution and arrangement. Results In the swine heart 1 hour after excision, MRDTI revealed that the arrangement of the myocardial fiber had certain continuity. It spiraled and twisted to form the left and right ventricle. The divection of general myocardial fiber in the left ventricle was vertical below endocardium, horizontal below epicardium and oblique in stratum medium, which is consistent with the theory of ventricular myocardial band. Conclusion MRDTI can reveal the myocardial fiber architecture, showing its integrity and arrangement, and at some level confirming the theory of ventricular myocardial band.
This paper is aimed to analyze the topological properties of structural brain networks in depressive patients with and without anxiety and to explore the neuropath logical mechanisms of depression comorbid with anxiety. Diffusion tensor imaging and deterministic tractography were applied to map the white matter structural networks. We collected 20 depressive patients with anxiety (DPA), 18 depressive patients without anxiety (DP), and 28 normal controls (NC) as comparative groups. The global and nodal properties of the structural brain networks in the three groups were analyzed with graph theoretical methods.The result showed that ① the structural brain networks in three groups showed small-world properties and highly connected global hubs predominately from association cortices; ② DP group showed lower local efficiency and global efficiency compared to NC group, whereas DPA group showed higher local efficiency and global efficiency compared to NC group; ③ significant differences of network properties (clustering coefficient, characteristic path lengths, local efficiency, global efficiency) were found between DPA and DP groups; ④ DP group showed significant changes of nodal efficiency in the brain areas primarily in the temporal lobe and bilateral frontal gyrus, compared to DPA and NC groups. The analysis indicated that the DP and DPA groups showed nodal properties of the structural brain networks, compared to NC group. Moreover, the two diseased groups indicated an opposite trend in the network properties. The results of this study may provide a new imaging index for clinical diagnosis for depression comorbid with anxiety.
ObjectiveChildhood absence epilepsy (CAE) is a common syndrome of idiopathic generalized epilepsy.However, little is known about the brain structural changes in this type of epilepsy, especially in the default mode network (DMN) regions.Diffusion tensor imaging (DTI) is a noninvasive techniques that can be used to quantitatively explore structural characteristics of brain.This study aims at using the DTI technique to quantify structural abnormalities of DMN nodes in CAE patients.MethodDTI data were obtained in 14 CAE patients and 13 age-and gender-matched healthy controls.The data were analyzed using voxel-based analysis (VBA) and statistically compared between patients and controls.For the regions with significant difference in group comparison, their DTI metrics were further analyzed with clinical symptoms using Pearson's correlation.ResultsPatients showed significant increase of apparent diffusion coefficient (ADC) in left medial prefrontal cortex (MPFC) (P=0.042), while fractional anisotropy (FA) value was significantly decreased in left precuneus (P=0.010).In correlation analysis, ADC value from left MPFC was positively associated with duration of epilepsy.Neither the disease duration nor the seizure frequency showed significant correlation with FA values.ConclusionThe findings indicate that structural impairments exist in DMN regions in children suffering from absence epilepsy.This may contribute to understanding the pathological mechanisms and chronic neurological deficits of this disorder.
White matter lesion (WML) of presumed vascular origin is one of the common imaging manifestations of cerebral small vessel diseases, which is the main reason of cognitive impairment and even vascular dementia in the elderly. However, there is a lack of early and effective diagnostic methods currently. In recent years, studies of diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI) have shown that cognitive impairment in patients with WMLs is associated with disrupted white matter microstructural and brain network connectivity. Therefore, it’s speculated that DTI and rs-fMRI can be effective in early imaging diagnosis of WMLs-related cognitive impairment. This article reviews the role and significance of DTI and rs-fMRI in WMLs-related cognitive impairment.
In transcranial magnetic stimulation (TMS), the conductivity of brain tissue is obtained by using diffusion tensor imaging (DTI) data processing. However, the specific impact of different processing methods on the induced electric field in the tissue has not been thoroughly studied. In this paper, we first used magnetic resonance image (MRI) data to create a three-dimensional head model, and then estimated the conductivity of gray matter (GM) and white matter (WM) using four conductivity models, namely scalar (SC), direct mapping (DM), volume normalization (VN) and average conductivity (MC), respectively. Isotropic empirical conductivity values were used for the conductivity of other tissues such as the scalp, skull, and cerebrospinal fluid (CSF), and then the TMS simulations were performed when the coil was parallel and perpendicular to the gyrus of the target. When the coil was perpendicular to the gyrus where the target was located, it was easy to get the maximum electric field in the head model. The maximum electric field in the DM model was 45.66% higher than that in the SC model. The results showed that the conductivity component along the electric field direction of which conductivity model was smaller in TMS, the induced electric field in the corresponding domain corresponding to the conductivity model was larger. This study has guiding significance for TMS precise stimulation.