Departments of Neurology (SZW, RNK, NM, LH, BJ, AC, JCR, SLG, TMW, AVM, and LJB), Population Health (RNK and LJB), and Ophthalmology (SZW, JCR, SLG, and LJB), New York University Grossman School of Medicine, New York, New York.
J Neuroophthalmol. 2022 Mar 1;42(1):79-87. doi: 10.1097/WNO.0000000000001228. Epub 2021 May 17.
Visual tests in Alzheimer disease (AD) have been examined over the last several decades to identify a sensitive and noninvasive marker of the disease. Rapid automatized naming (RAN) tasks have shown promise for detecting prodromal AD or mild cognitive impairment (MCI). The purpose of this investigation was to determine the capacity for new rapid image and number naming tests and other measures of visual pathway structure and function to distinguish individuals with MCI due to AD from those with normal aging and cognition. The relation of these tests to vision-specific quality of life scores was also examined in this pilot study.
Participants with MCI due to AD and controls from well-characterized NYU research and clinical cohorts performed high and low-contrast letter acuity (LCLA) testing, as well as RAN using the Mobile Universal Lexicon Evaluation System (MULES) and Staggered Uneven Number test, and vision-specific quality of life scales, including the 25-Item National Eye Institute Visual Function Questionnaire (NEI-VFQ-25) and 10-Item Neuro-Ophthalmic Supplement. Individuals also underwent optical coherence tomography scans to assess peripapillary retinal nerve fiber layer and ganglion cell/inner plexiform layer thicknesses. Hippocampal atrophy on brain MRI was also determined from the participants' Alzheimer disease research center or clinical data.
Participants with MCI (n = 14) had worse binocular LCLA at 1.25% contrast compared with controls (P = 0.009) and longer (worse) MULES test times (P = 0.006) with more errors in naming images (P = 0.009) compared with controls (n = 16). These were the only significantly different visual tests between groups. MULES test times (area under the receiver operating characteristic curve [AUC] = 0.79), MULES errors (AUC = 0.78), and binocular 1.25% LCLA (AUC = 0.78) showed good diagnostic accuracy for distinguishing MCI from controls. A combination of the MULES score and 1.25% LCLA demonstrated the greatest capacity to distinguish (AUC = 0.87). These visual measures were better predictors of MCI vs control status than the presence of hippocampal atrophy on brain MRI in this cohort. A greater number of MULES test errors (rs = -0.50, P = 0.005) and worse 1.25% LCLA scores (rs = 0.39, P = 0.03) were associated with lower (worse) NEI-VFQ-25 scores.
Rapid image naming (MULES) and LCLA are able to distinguish MCI due to AD from normal aging and reflect vision-specific quality of life. Larger studies will determine how these easily administered tests may identify patients at risk for AD and serve as measures in disease-modifying therapy clinical trials.
在过去的几十年里，人们一直在研究阿尔茨海默病（AD）的视觉测试，以寻找疾病的敏感且非侵入性标志物。快速自动命名（RAN）任务已显示出在检测前驱性 AD 或轻度认知障碍（MCI）方面的潜力。本研究的目的是确定新的快速图像和数字命名测试以及其他视觉通路结构和功能测量方法，以区分 AD 导致的 MCI 患者与正常衰老和认知的患者。在这项初步研究中，还检查了这些测试与特定于视觉的生活质量评分之间的关系。
来自纽约大学研究和临床队列的 AD 导致的 MCI 患者和对照组参与者进行了高对比度和低对比度字母视力（LCLA）测试，以及使用移动通用词汇评估系统（MULES）和交错不均匀数字测试进行 RAN 测试，以及特定于视觉的生活质量量表，包括 25 项国家眼科研究所视觉功能问卷（NEI-VFQ-25）和 10 项神经眼科补充量表。个体还接受了光相干断层扫描，以评估视盘周围视网膜神经纤维层和节细胞/内丛状层厚度。还根据参与者的阿尔茨海默病研究中心或临床数据确定了脑 MRI 上的海马萎缩。
与对照组相比，MCI 参与者（n=14）在 1.25%对比度下的双眼 LCLA 更差（P=0.009），并且 MULES 测试时间更长（更差）（P=0.006），图像命名错误更多（P=0.009）。这些是组间唯一显著不同的视觉测试。MULES 测试时间（受试者工作特征曲线下面积[AUROC] = 0.79）、MULES 错误（AUROC = 0.78）和双眼 1.25% LCLA（AUROC = 0.78）在区分 MCI 与对照组方面具有良好的诊断准确性。MULES 评分和 1.25% LCLA 的组合表现出最佳的区分能力（AUROC = 0.87）。在该队列中，这些视觉测量方法比脑 MRI 上的海马萎缩更能预测 MCI 与对照组的状态。更多的 MULES 测试错误（rs=-0.50，P=0.005）和更差的 1.25% LCLA 评分（rs=0.39，P=0.03）与更低（更差）的 NEI-VFQ-25 评分相关。
快速图像命名（MULES）和 LCLA 能够区分 AD 导致的 MCI 与正常衰老，并反映特定于视觉的生活质量。更大的研究将确定这些易于管理的测试如何识别 AD 风险患者，并作为疾病修饰治疗临床试验中的措施。
