The Correlation of the White Matter Lesions and Lacunar Infarcts in Patients with Vascular Cognitive Impairment

BACKGROUND: Cerebral white matter lesions (WMLs) and lacunar infarcts (LIs) are mostly caused by small vessel disease (SVD). Whereas the main pathomechanism behind LIs is SVD, a variety of mechanisms could be responsible for WMLs. We tried to investigate the relationship between WMLs and LIs and the impact of subtypes of WMLs on its relationship. METHODS: We assessed 128 subjects with vascular cognitive impairment with subcortical vascular lesion (VCI-S). LI number and WML volume were determined on T1-, T2-weighted images and fluid-attenuated inversion recovery images using a semiquantitative visual scale. Cognitive function and daily functional impairment were assessed with Mini-Mental State Examination (MMSE) and the Seoul-Instrumental Activities of Daily Living (S-IADL). RESULTS: Of the 128 patients, 106 (82.8%) had Alzheimer's disease with WML and 22 (17.2%) had subcortical vascular dementia. Seventy patients (54.7%) had at least one lacune. A univariate Poisson model showed that history of hypertension, history of stroke and WML volume (periventricular and deep subcortical) were associated with LIs. A multivariate Poisson model showed that increased WML volume of both types and history of hypertension were associated with LIs. Neither S-IADL score nor MMSE was significantly associated with WML volume of both types. CONCLUSIONS: We found that LIs were associated with WMLs regardless of their types in patients with VCI-S. These findings may suggest that periventricular and deep subcortical WMLs share the same vascular pathomechanism of SVD as LIs.

Development of the Multi-Parametric Mapping Software Based on Functional Maps to Determine the Clinical Target Volumes / 의학물리

To determine the clinical target volumes considering vascularity and cellularity of tumors, the software was developed for mapping of the analyzed biological clinical target volumes on anatomical images using regional cerebral blood volume (rCBV) maps and apparent diffusion coefficient (ADC) maps. The program provides the functions for integrated registrations using mutual information, affine transform and non-rigid registration. The registration accuracy is evaluated by the calculation of the overlapped ratio of segmented bone regions and average distance difference of contours between reference and registered images. The performance of the developed software was tested using multimodal images of a patient who has the residual tumor of high grade gliomas. Registration accuracy of about 74% and average 2.3 mm distance difference were calculated by the evaluation method of bone segmentation and contour extraction. The registration accuracy can be improved as higher as 4% by the manual adjustment functions. Advanced MR images are analyzed using color maps for rCBV maps and quantitative calculation based on region of interest (ROI) for ADC maps. Then, multi-parameters on the same voxels are plotted on plane and constitute the multi-functional parametric maps of which x and y axis representing rCBV and ADC values. According to the distributions of functional parameters, tumor regions showing the higher vascularity and cellularity are categorized according to the criteria corresponding malignant gliomas. Determined volumes reflecting pathological and physiological characteristics of tumors are marked on anatomical images. By applying the multi-functional images, errors arising from using one type of image would be reduced and local regions representing higher probability as tumor cells would be determined for radiation treatment plan. Biological tumor characteristics can be expressed using image registration and multi-functional parametric maps in the developed software. The software can be considered to delineate clinical target volumes using advanced MR images with anatomical images.

Working Memory Mapping Analysis using fMRI / 의학물리

Impaired processing of facial information is one of the broad ranges of cognitive deficits seen in patients with schizophrenia. The purpose of this study was to elucidate the differences in brain activities involved in the process of facial working memory between schizophrenic patients and healthy comparison subjects. Ten patients with schizophrenia were recruited along with matched healthy volunteers as a comparison group. Functional magnetic resonance imaging (fMRI) was used to assess cortical activities during the performance of a 1-back working memory paradigm using images of neutral faces as mnemonic content. The patient group performed the tasks with reduced accuracy. Group analysis revealed that left fusiform gyrus, right superior frontal gyrus, bilateral middle frontal gyri/insula, left middle temporal gyrus, precuneus and vermis of cerebellum and showed decreased cortical activities in the patient group. On the other hand, an increased level of activation in lateral prefrontal cortex and parietal lobule was observed from the patient group, all in the right hemisphere. A decreased level of activity in the left fusiform gyrus among the patient group implicates inefficient processing of facial information. An increased level of activation in prefrontal and parietal neural networks from the patient group confirms earlier findings on the impaired working memory of patients with schizophrenia.