Current Knowledge and Clinical Application of Brain Imaging in Alzheimer's Disease / 신경정신의학

Alzheimer's disease (AD) is a debilitating syndrome with cognitive decline and impairment in daily activities. Although clinical assessment forms the basis for diagnosing AD, structural and functional brain imaging tools have been known to enhance accuracy of differential diagnosis and prognosis prediction by presenting structural and functional signatures for AD. Associated with the important role of brain imaging in diagnosing and treating AD, brain imaging has been recommended in the current diagnostic guidelines of AD. Visual rating scales, a cost-effective diagnostic tool, have been known to assess atrophy and functional changes in patients with cognitive impairment as accurate as quantitative assessment. In this regard, visual rating scales for brain imaging interpretation could be useful in clinical settings. In this review, we interpret structural and functional brain imaging results with standardized visual rating scales, and review recent findings concerning brain imaging tools for differential diagnosing and predicting prognosis of AD.

The relationship of white matter lesions location and cognitive function in leukoaraisosis patients / 中华行为医学与脑科学杂志

Objective To study the effect of white matter lesions location on cognitive function by comparing the correlation between the anatomical location of white matter lesions and cognitive function in leukoaraisosis(LA)patients. Methods A total of 75 LA patients with different degrees of white matter le-sion were randomly recruited.The modified Scheltens scale,Manolio scale and Fazekas scale were utilized to assess the severity of white matter lesions(WMLs)by two physicians.Montreal cognitive assessment (MoCA)was used to evaluate the cognitive function.The correlation between WMLs location and cognitive function was analyzed by spearman rank correlation analysis.The t-test was used to test the differences of periventricular white matter lesions with cognitive impairment(PWMLs-CI)and periventricular white matter lesions with cognitive normal(PWMLs-CN)in each goup. Results For Fazekas scale,PWMLs were signifi-cantly correlated with the decrease scores of MoCA score(r=-0.388,P=0.007),visuospatial and executive (r=-0.466,P=0.000),delayed recall(r=-0.461,P=0.001),abstraction(r=-0.355,P=0.011)and ori-entation(r=-0.337,P=0.016)(P<0.05).For Scheltens scale,PWMLs was negatively correlated with MoCA score(r=-0.390,P=0.003),visuospatial and executive(r=-0.464,P=0.000),delayed recall(r=0.484, P=0.000),attention(r=-0.375,P=0.008)and orientation(r=-0.342,P=0.013)(P<0.05),but not in deep white matter lesions(DWMLs)(P>0.05).Compared with PWMLs-CN,executive function(42.13 ± 0.89),attention(16.36±1.24)and visuospatial(2.25±0.31)in PWMLs-CI had statistical significance(P<0.05). Conclusion White matter lesions location affect cognitive function,PWMLs are more closely related to cognitive impairement,characterized by executive function,attention and visuospatial aspects.

Age-Specific Cutoff Scores on a T1-Weighted Axial Medial Temporal-Lobe Atrophy Visual Rating Scale in Alzheimer's Disease Using Clinical Research Center for Dementia of South Korea Data

BACKGROUND AND PURPOSE: Visual assessment of medial temporal-lobe atrophy (MTA) has been quick, reliable, and easy to apply in routine clinical practice. However, one of the limitations in visual assessments of MTA is the lack of widely accepted age-adjusted norms and cutoff scores for MTA for a diagnosis of Alzheimer's disease (AD). This study aimed to determine the optimal cutoff score on a T1-weighted axial MTA Visual Rating Scale (VRS) for differentiating patients with AD from cognitively normal elderly people. METHODS: The 3,430 recruited subjects comprising 1,427 with no cognitive impairment (NC) and 2003 AD patients were divided into age ranges of 50–59, 60–69, 70–79, and 80–89 years. Of these, 446 participants (218 in the NC group and 228 in the AD group) were chosen by random sampling for inclusion in this study. Each decade age group included 57 individuals, with the exception of 47 subjects being included in the 80- to 89-year NC group. The scores on the T1-weighted axial MTA VRS were graded by two neurologists. The cutoff values were evaluated from the area under the receiver operating characteristic curve. RESULTS: The optimal axial MTA VRS cutoff score from discriminating AD from NC increased with age: it was ≥as ≥1, ≥2, and ≥3 in subjects aged 50–59, 60–69, 70–79, and 80–89 years, respectively (all p < 0.001). CONCLUSIONS: These results show that the optimal cutoff score on the axial MTA VRS for diagnosing of AD differed according to the decade age group. This information could be of practical usefulness in the clinical setting.