左背外侧前额皮质萎缩的脑卒中老年女性语言流畅性差

doi:10.3969/j.issn.1673-5374.2013.04.007

中国神经再生研究(英文版) ›› 2013, Vol. 8 ›› Issue (4): 346-356.doi: 10.3969/j.issn.1673-5374.2013.04.007

• 原著:脑损伤修复保护与再生 • 上一篇下一篇

左背外侧前额皮质萎缩的脑卒中老年女性语言流畅性差

收稿日期:2012-11-12 修回日期:2013-01-10 出版日期:2013-02-05 发布日期:2013-02-05

Atrophy of the left dorsolateral prefrontal cortex is associated with poor performance in verbal fluency in elderly poststroke women

Yang-Kun Chen¹, Wei-Min Xiao¹, Defeng Wang², Lin Shi², Winnie CW Chu², Vincent CT Mok³, Ka Sing Wong³, Gabor S Ungvari⁴, Wai Kwong Tang⁵

1 Department of Neurology, Dongguan People’s Hospital, Dongguan 523059, Guangdong Province, China
2 Department of Diagnostic Radiology and Organ Imaging, the Chinese University of Hong Kong, Hong Kong SAR 999077, China

3 Department of Medicine and Therapeutics, the Chinese University of Hong Kong, Hong Kong SAR 999077, China

4 Graylands Hospital, School of Psychiatry & Clinical Neurosciences, University of Western Australia, Perth 6005, Australia
5 Department of Psychiatry, the Chinese University of Hong Kong, Hong Kong SAR 999077, China

Received:2012-11-12 Revised:2013-01-10 Online:2013-02-05 Published:2013-02-05
Contact: Wai Kwong Tang, M.D., Professor, Department of Psychiatry, Shatin Hospital, Shatin, N.T., Hong Kong, China, tangwk@cuhk.edu.hk.
About author:Yang-Kun Chen☆, M.D., Ph.D
Supported by:
This study was supported by the Research Grants Council of the Hong Kong SAR, No. 452906.

摘要/Abstract

摘要：

为探讨老年脑卒中患者的执行功能有关前额皮质萎缩与语言表述能力的关系。纳入30例老年非失语缺血性脑卒中患者和30例年龄匹配的非失语男性缺血性脑卒中患者。应用自动MRI序列评估前额叶皮质及其亚区前扣带回皮质、眶-额皮质和背外侧的前额皮质的容积。脑卒中后3和15个月进行语义语言表述流畅试验。脑卒中后3个月，在控制年龄、教育、糖尿病、神经缺损、白质缺损体积、以及梗死部位和体积情况下，女性患者左背外侧的前额皮质容积与语义语言表述流畅试验评分呈明显正相关(partial coefficient=0.453, P=0.045)。脑卒中后15个月，女性患者左背外侧的前额皮质和左侧前额皮质容积仍与语义语言表述流畅试验评分呈正相关(partial coefficient=0.661, P=0.001；partial coefficient=0.573, P=0.004)。说明左背外侧的前额皮质萎缩可能致老年女性脑卒中患者语言表述能力下降。

关键词: 神经再生, 神经影像, 脑萎缩, 语言流畅, 神经精神测验, 认知缺损, 执行功能, 脑卒中, 性别差异, 前额皮质, 背外侧的前额皮质, MRI, 临床实践, 基金资助文章, 图片文章

Abstract:

This study aimed to investigate the association between atrophy in the prefrontal cortex with executive function and verbal fluency in elderly male and female patients poststroke. Thirty elderly female patients with non-aphasic ischemic stroke aged ≥ 60 years and 30 age-matched non-aphasic male patients with ischemic stroke were recruited. Automatic magnetic resonance imaging segmentation was used to assess the volume of the whole prefrontal cortex, along with its subdivisions: anterior cingulate cortex, orbitofrontal cortex and dorsolateral prefrontal cortex. The Semantic Verbal Fluency Test was administered at 3 and 15 months poststroke. At 3 months poststroke, left dorsolateral prefrontal cortex volume was significantly correlated with Verbal Fluency Test score in female patients only (partial coefficient = 0.453, P = 0.045), after controlling for age, education, diabetes, neurological deficit, white matter lesions volume, as well as the location and volume of infarcts. At 15 months poststroke, there remained a significant association between the left dorsolateral prefrontal cortex volume and Verbal Fluency Test (partial coefficient = 0.661, P = 0.001) and between the left prefrontal cortex volume and Verbal Fluency Test (partial coefficient = 0.573, P = 0.004) in female patients after the same adjustments. These findings indicate that atrophy of the left dorsolateral prefrontal cortex contributes to the impairment of verbal fluency in elderly female patients with stroke. Sex differences may be present in the neuropsychological mechanisms of verbal fluency impairment in patients with stroke.

Key words: neural regeneration, neuroimaging, brain atrophy, verbal fluency, executive function, stroke, sex differences, prefrontal cortex, dorsolateral prefrontal cortex, magnetic resonance imaging, grants-supported paper, photographs-containing paper, neuroregeneration

. 左背外侧前额皮质萎缩的脑卒中老年女性语言流畅性差[J]. 中国神经再生研究(英文版), 2013, 8(4): 346-356.

Yang-Kun Chen, Wei-Min Xiao, Defeng Wang, Lin Shi, Winnie CW Chu, Vincent CT Mok, Ka Sing Wong, Gabor S Ungvari, Wai Kwong Tang. Atrophy of the left dorsolateral prefrontal cortex is associated with poor performance in verbal fluency in elderly poststroke women[J]. Neural Regeneration Research, 2013, 8(4): 346-356.

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引言

材料方法

Design

A cross-sectional observational study.

Time and setting

Assessments were performed at a psychiatric clinic in Prince of Wales Hospital in Hong Kong between June 2006 and June 2007.

Subjects

Eighty-three elderly patients with acute ischemic stroke, aged ≥ 60 years old, were admitted to the Acute Stroke Unit of the Prince of Wales Hospital in Hong Kong between June 2006 and June 2007 and were consecutively recruited in a longitudinal study on poststroke cognitive impairment. All participants were right-handed, of Chinese descent and fluent in the Cantonese dialect. Each participant underwent an MRI examination. To exclude the aphasic patients, all participants were required to have a score of zero in the best language item of National Institutes of Health Stroke Scale^[41]. Scores on the best language item of National Institutes of Health Stroke Scale range from 0–3, with a higher score indicating worse language disturbance. Participants did not have dementia or depression or any other central nervous system disease other than stroke, and they were free of significant dysarthria and visual and hearing impairment. Among them, 33 elderly female patients with ischemic stroke participated in the neuropsychological testing 3 months poststroke, but three of these patients dropped out within 1 year following the baseline assessment. Eventually, 30 elderly poststroke female patients were included in the study. Simultaneously, a group of 30 age-matched male patients with ischemic stroke who completed the follow-up assessment were selected from the same cohort; these participants comprised the sex-matched group. Each female case was age-matched (≤ 3 years) to a male patient with the closest admission date. Thus, in this cohort of 83 subjects initially, 20 elderly stroke male patients were excluded. All participants signed a consent form.

Basic sociodemographic and clinical data including age, sex, education (years), hypertension, diabetes mellitus, previous stroke history, and National Institutes of Health Stroke Scale score on hospital admission were retrieved from the Stroke Registry at the Acute Stroke Unit of the Prince of Wales Hospital. Hypertension was defined as repeated blood pressure measures of ≥ 140/90 mmHg (1 mmHg = 0.133 kPa) or the need for chronic antihypertensive medication. Diabetes mellitus was defined as a fasting blood glucose ≥ 7.0 mM, postprandial blood glucose ≥ 11.1 mM, or on glucose- lowering treatment.

Methods

Neuropsychological tests

All subjects completed a series of neuropsychological tests both 3 and 15 months after the index stroke. We chose the time point of 3 months poststroke, as stroke survivors can have a relatively quick natural recovery within 3 months after the stroke has occurred. These two time points were often adopted by studies on poststroke cognitive impairment^[42-44]. Global cognitive function was assessed using the Cantonese version of the Mini-Mental Status Examination^[45]. It contains assessments covering 5 cognitive domains, which are orientation, memory, attention and calculation, recall and language, and its score can range from 0–30 points. The Mini-Mental Status Examination is a quick and easy measure of cognitive functioning that has been widely used in clinical evaluation and research involving patients with dementia, as well as in poststroke patients^[43]. The Chinese-version of Frontal Assessment Battery^[46-47] was used to evaluate executive function. A high Frontal Assessment Battery score indicates good performance. The Chinese Frontal Assessment Battery contains six items, which assess conceptualization, lexical fluency, motor programming, sensitivity-to- interference, go/no-go, and environmental autonomy. A maximum of 3 is scored for each item and the total test score is 18. The Frontal Assessment Battery takes about 10–15 minutes to administer depending on the patient’s level of impairment. It has been widely used in the evaluation of executive function in elderly stroke and degenerative dementia patients^[48-49]. In the Semantic Verbal Fluency Test^[50], patients were asked to retrieve words belonging to the categories of ‘food’ and ‘animal’. The time limit was 60 seconds for both tasks. The Verbal Fluency Test score was the sum of both category tests. The severity of depressive symptoms was also evaluated with a short form of the Geriatric Depression Scale, Chinese version^[51], with scores that ranged 0–15, where a higher indicates more depressive symptoms.

MRI measurements

MRI assessments were performed in a 1.5T MR scanner (Sonata, Siemens Medical, Erlangen, Germany) for each subject within 7 days of the initial stroke. Imaging sequences included diffusion weighted imaging, T1 weighted imaging, T2 weighted imaging, fluid attenuation inversion recovery, and T2* weighted gradient echo. Whole brain volume was acquired using a T1-weighted FLASH sequence. Diffusion weighted imaging spin echo echo planar imaging (repetition time/echo time/ excitation = 180/122/4, matrix = 128 × 128, field of view = 230 mm, slice thickness/gap = 5 mm/1 mm, echo planar imaging factor = 90, acquisition time = 55 seconds) with three orthogonally applied gradients were used with a b value of 1 000 and 500. Axial gradient echo images were acquired as the second sequence with imaging parameters of repetition time/echo time/excitation = 350/30/2, flip angle of 30°, slice thickness/gap = 5 mm/0.5 mm, field of view = 230 mm, matrix = 256 × 256 and acquisition time = 5 minutes 4 seconds. Axial SE T1 (repetition time/echo time/excitation = 425/14/2, field of view = 230 mm, slice thickness/gap = 5 mm/0.5 mm, matrix = 256 × 256 and acquisition time = 4 minutes 28 seconds) and TSE T2 (repetition time/echo time/excitation = 2 500/120/1, turbo factor of 15, field of view = 230 mm, slice thickness/gap = 5 mm/0.5 mm, matrix of 256 × 256 and acquisition time = 1 minute 39 seconds) images were also acquired.

Identification of brain infarcts

Brain infarctions were identified on T1 weighted images and confirmed on the corresponding T2-weighted images, with the volumetric measurements being carried out on T1-weighted images^[48]. They included acute and old infarcts on the MRI images in the acute phase of stroke. Brain infarcts that affected the frontal, temporal, parietal and occipital lobes, corona radiata, centrum semiovale, internal capsule, basal ganglia, thalamus, brainstem and cerebellum were recorded. Multiple infarcts or infarct(s) involving more than one location were counted in all locations they occurred. The area of infarcts in each visible slice was measured with manual outlines. The total volume of infarcts was calculated by multiplying the total area by the sum of the slice thickness and gap^[48].

Determination of volumetry of brain regions

Volumetric analysis of brain regions was performed using an automatic image analysis program, Insight Segmentation and Registration Toolkit (http://www.itk.org). The N3 algorithm^[52]was employed to automatically correct the non-uniform image intensity for the volume data. The brain extraction tool^[53] was used to segment the brain from the MRI data. Tissue classification was performed using the supervised k-nearest neighbor classifier for classifying the entire 3-D image^[54]. The volumes of the white matter and gray matter were calculated as the number of voxels multiplied by the size of each voxel. A fully automated clustering-based quantitative white matter lesion volume detection technique was adopted to analyze fluid attenuation inversion recovery intensities on the white matter mask, which is generated from the segmentation result from T1 images co-aligned with fluid attenuation inversion recovery data. The whole-brain segmentation was achieved using an atlas-based approach that automatically adjusts the prior atlas intensity model to new input data and has good robustness^[55]. The brain atlas (i.e., Talairach atlas^[56]) was constructed by manually delineating the deep brain structures and intracranial region on a single subject. The intracranial volume was calculated by automatically adjusting the prior atlas intensity model to new input data. The label of the intracranial region was transformed to the input data non-rigidly (using demon registration)^[57].

Parcellation of the cerebral cortex into different cortical regions was made by non-rigid registration to a cortical surface atlas^[58]. The registration to the spherical atlas was performed using the cortical folding patterns to match the cortical geometry between each subject and the surface atlas. This registration algorithm modeled the warping of gray scale in the images as the flow of fluid using the partial differential equations of the Navier- Stokes equations^[59]. The labels of the anterior cingulate cortex and orbitofrontal cortex were given by the atlas^[57], whereas the labels of the dorsolateral prefrontal cortex and prefrontal cortex were defined manually according to a previous reference^[60]. All brain region volumes were standardized by the intracranial volume (1 000 × raw volume/intracranial volume). The volumes described below refer to the standardized volumes. The gray matter ratio was defined as the gray matter volume divided by the whole brain volume. Examples of parcellation of the cerebral cortex of a woman are shown in Figure 2.

Statistical analysis

The difference in proportions between the groups was analyzed with the chi-square test or the Fisher’s exact test. The continuous data were compared using t-tests (parametric data) or Mann-Whitney U tests (non- parametric data), as appropriate. The one-sample Kolmogorov-Smirnov test determined age, gray matter ratio and all standard volume of the brain regions as parametric data. Education years, National Institutes of Health Stroke Scale score, Mini-Mental Status Examination score, Frontal Assessment Battery and Geriatric Depression Scale scores, volume of infarcts and volume of white matter lesions were determined as non-parametric data.

Spearman’s correlations were performed between the standardized volumes of brain regions and white matter lesions and Mini-Mental Status Examination and Frontal Assessment Battery scores separately for female and male patients. Pearson’s correlations were performed for the MRI volumetric variables and Verbal Fluency Test. For these univariate correlation analyses, the significance level was set at P < 0.01 (two-tailed) because of multiple comparisons. Then, significant correlations were retested by partial correlation after controlling for possible confounders. The level of significance in partial correlations was set at P < 0.05 (two-sided). The statistical analyses were performed using SPSS (version 16.0; SPSS, Chicago, IL, USA).

左背外侧前额皮质萎缩的脑卒中老年女性语言流畅性差

Atrophy of the left dorsolateral prefrontal cortex is associated with poor performance in verbal fluency in elderly poststroke women

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