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“正常”认知功能的评估及其与MRI容积测定的相关性:迈向血管性认知障碍的定义

Evaluation of 'Normal' Cognitive Functions and Correlation With MRI Volumetry: Towards a Definition of Vascular Cognitive Impairment.

作者信息

Sundar Uma, Mukhopadhyay Amita, Raghavan Sheelakumari, Debata Ipsita, Menon Ramshekhar N, Kesavadas Chandrasekharan, Shah Nilesh, Adsul Balkrishna B, Joshi Anagha R, Tejas Janardhan

机构信息

Department of Medicine, Lokmanya Tilak Municipal Medical College and General Hospital, Mumbai, IND.

Department of Hospital and Health Management, Institute of Health Management Research Bangalore, Bengaluru, IND.

出版信息

Cureus. 2023 Nov 26;15(11):e49461. doi: 10.7759/cureus.49461. eCollection 2023 Nov.

DOI:10.7759/cureus.49461
PMID:38152804
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10751464/
Abstract

Introduction It is important to establish criteria to define vascular cognitive impairment (VCI) in India as VCI is an image-based diagnosis and magnetic resonance imaging (MRI) changes resulting from age with prevalent vascular risk factors may confound MRI interpretation. The objective of this study was to establish normative community data for MRI volumetry including white matter hyperintensity volume (WMHV), correlated with age-stratified cognitive scores and vascular risk factors (VRFs), in adults aged 40 years and above.  Methods We screened 2651 individuals without known neurological morbidity, living in Mumbai and nearby rural areas, using validated Marathi translations of Kolkata Cognitive Battery (KCB) and geriatric depression score (GDS). We stratified 1961 persons with GDS ≤9 by age and cognitive score, and randomly selected 10% from each subgroup for MRI brain volumetry. Crude volumes were standardized to reflect percentage of intracranial volume.  Results MRI volumetry studies were done in 199 individuals (F/M = 90/109; 73 with body mass index (BMI) ≥25; 44 hypertensives; 29 diabetics; mean cognitive score 76.3). Both grey and white matter volumes decreased with increasing age. WMHV increased with age and hypertension. Grey matter volume (GMV) decreased with increasing WMHV. Positive predictors of cognition included standardized hippocampal volume (HCV), urban living, education, and BMI, while WMHV and age were negative predictors. Urban dwellers had higher cognitive scores than rural, and, paradoxically, smaller HCV.  Conclusion In this study of MRI volumetry correlated with age, cognitive scores and VRFs, increasing age and WMHV predicted lower cognitive scores, whereas urban living and hippocampal volume predicted higher scores. Age and WMHV also correlated with decreasing GMV. Further study is warranted into sociodemographic and biological factors that mutually influence cognition and brain volumes, including nutritional and endocrine factors, especially at lower cognitive score bands. In this study, at the lower KCB score bins, the lack of laboratory data pertaining to nutritional and endocrine deficiencies is a drawback that reflects the logistical limitations of screening large populations at the community level. Our volumetric data which is age and cognition stratified, and takes into account the vascular risk factors associated, nevertheless constitutes important baseline data for the Indian population. Our findings could possibly contribute to the formulation of baseline criteria for defining VCI in India and could help in early diagnosis and control of cognitive decline and its key risk factors.

摘要

引言

在印度,确立血管性认知障碍(VCI)的定义标准非常重要,因为VCI是一种基于影像的诊断,而随着年龄增长以及普遍存在的血管危险因素导致的磁共振成像(MRI)变化可能会混淆MRI的解读。本研究的目的是为40岁及以上成年人建立MRI容积测定的社区标准数据,包括白质高信号容积(WMHV),并将其与按年龄分层的认知得分及血管危险因素(VRF)相关联。

方法

我们使用经过验证的加尔各答认知量表(KCB)和老年抑郁量表(GDS)的马拉地语翻译版本,对居住在孟买及其周边农村地区的2651名无已知神经疾病的个体进行了筛查。我们根据年龄和认知得分对1961名GDS≤9的个体进行分层,并从每个亚组中随机抽取10%进行脑部MRI容积测定。将原始容积标准化以反映颅内容积的百分比。

结果

对199名个体进行了MRI容积测定研究(男/女 = 90/109;73人体重指数(BMI)≥25;44人患有高血压;29人患有糖尿病;平均认知得分为76.3)。灰质和白质容积均随年龄增长而减少。WMHV随年龄和高血压的增加而增加。灰质容积(GMV)随WMHV的增加而减少。认知的正向预测因素包括标准化海马体容积(HCV)、城市居住、教育程度和BMI,而WMHV和年龄则为负向预测因素。城市居民的认知得分高于农村居民,且矛盾的是,其HCV较小。

结论

在这项将MRI容积测定与年龄、认知得分和VRF相关联的研究中,年龄增长和WMHV预示着较低的认知得分,而城市居住和海马体容积则预示着较高的得分。年龄和WMHV也与GMV的减少相关。有必要进一步研究相互影响认知和脑容积的社会人口学和生物学因素,包括营养和内分泌因素,尤其是在较低认知得分区间。在本研究中,在较低的KCB得分区间,缺乏与营养和内分泌缺乏相关的实验室数据是一个缺陷,这反映了在社区层面筛查大量人群的后勤限制。我们按年龄和认知分层并考虑了相关血管危险因素的容积数据,仍然构成了印度人群重要的基线数据。我们的研究结果可能有助于制定印度VCI定义的基线标准,并有助于早期诊断和控制认知衰退及其关键危险因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c706/10751464/1b72cbd79c20/cureus-0015-00000049461-i04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c706/10751464/862310bc010b/cureus-0015-00000049461-i01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c706/10751464/a0e247097cc2/cureus-0015-00000049461-i02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c706/10751464/6341e43134d1/cureus-0015-00000049461-i03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c706/10751464/1b72cbd79c20/cureus-0015-00000049461-i04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c706/10751464/862310bc010b/cureus-0015-00000049461-i01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c706/10751464/a0e247097cc2/cureus-0015-00000049461-i02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c706/10751464/6341e43134d1/cureus-0015-00000049461-i03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c706/10751464/1b72cbd79c20/cureus-0015-00000049461-i04.jpg

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