Detecting frontotemporal dementia syndromes using MRI biomarkers
Detecting frontotemporal dementia syndromes using MRI biomarkers
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DOI：
10.1016/j.nicl.2019.101711
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发表时间：
2019-01-01
影响因子：
4.2
通讯作者：
Frederiksen, Kristian S.
中科院分区：
文献类型：
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作者：
Bruun, Marie;Koikkalainen, Juha;Frederiksen, Kristian S.
背景：额颞叶痴呆的诊断可能具有挑战性。磁共振成像（MRI）上分析局部脑萎缩模式的新方法可以增加诊断评估。因此，我们的目标是开发自动成像生物标志物，用于区分额颞叶痴呆亚型与其他诊断组，以及彼此。（年龄67 +/- 9，48%女性）来自两个记忆诊所队列：116例额颞叶痴呆，341例阿尔茨海默病，66例路易体痴呆，40例血管性痴呆，104例其他痴呆，229例轻度认知障碍，317例主观认知下降。从自动分割的皮质区域的标准化体积中推导出三种MRI萎缩生物标志物：1）前部与后部指数，2）不对称指数，以及3）颞极左侧指数。我们使用了以下性能指标：受试者工作特征曲线下面积（AUC）、灵敏度和特异性。为了解释额颞叶痴呆的低患病率，我们追求95%的高特异性。交叉验证用于评估性能。在一个独立的队列（n = 200）的概括性进行了评估。结果：前与后的指数进行的AUC为83%的额颞叶痴呆从所有其他诊断组（敏感性= 59%，特异性= 95%，阳性似然比= 11.8，阴性似然比= 0.4）的分化。不对称指数在区分原发性进行性失语和行为变异型额颞叶痴呆方面表现最好（AUC = 85%，灵敏度= 79%，特异性= 92%，阳性似然比= 9.9，阴性似然比= 0.2），而颞极左指数对于检测语义变异型原发性进行性失语具有特异性（AUC = 85%，灵敏度= 82%，特异性= 80%，阳性似然比= 4.1，阴性似然比= 0.2）。验证队列提供了相应的结果为前与后的指数和颞极左index.Conclusion：这项研究提出了三个定量的MRI生物标志物，这可以提供额外的信息，诊断评估，并协助临床医生诊断额颞叶痴呆。
Background: Diagnosing frontotemporal dementia may be challenging. New methods for analysis of regional brain atrophy patterns on magnetic resonance imaging (MRI) could add to the diagnostic assessment. Therefore, we aimed to develop automated imaging biomarkers for differentiating frontotemporal dementia subtypes from other diagnostic groups, and from one another.Methods: In this retrospective multicenter cohort study, we included 1213 patients (age 67 +/- 9, 48% females) from two memory clinic cohorts: 116 frontotemporal dementia, 341 Alzheimer's disease, 66 Dementia with Lewy bodies, 40 vascular dementia, 104 other dementias, 229 mild cognitive impairment, and 317 subjective cognitive decline. Three MRI atrophy biomarkers were derived from the normalized volumes of automatically segmented cortical regions: 1) the anterior vs. posterior index, 2) the asymmetry index, and 3) the temporal pole left index. We used the following performance metrics: area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. To account for the low prevalence of frontotemporal dementia we pursued a high specificity of 95%. Cross-validation was used in assessing the performance. The generalizability was assessed in an independent cohort (n = 200).Results: The anterior vs. posterior index performed with an AUC of 83% for differentiation of frontotemporal dementia from all other diagnostic groups (Sensitivity = 59%, Specificity = 95%, positive likelihood ratio = 11.8, negative likelihood ratio = 0.4). The asymmetry index showed highest performance for separation of primary progressive aphasia and behavioral variant frontotemporal dementia (AUC = 85%, Sensitivity = 79%, Specificity = 92%, positive likelihood ratio = 9.9, negative likelihood ratio = 0.2), whereas the temporal pole left index was specific for detection of semantic variant primary progressive aphasia (AUC = 85%, Sensitivity = 82%, Specificity = 80%, positive likelihood ratio = 4.1, negative likelihood ratio = 0.2). The validation cohort provided corresponding results for the anterior vs. posterior index and temporal pole left index.Conclusion: This study presents three quantitative MRI biomarkers, which could provide additional information to the diagnostic assessment and assist clinicians in diagnosing frontotemporal dementia.